{} found!\\\".format(min_sequence_length)\\n self._logger.error(msg)\\n raise IOError(msg)\\n return file_path_output\",\n \"def scan_id(barcode):\\n return scanner.scan(barcode)\",\n \"def generate_filename(\\r\\n filepath,\\r\\n filestartwith,\\r\\n fileendwith,\\r\\n run_date,\\r\\n filemask):\\r\\n\\r\\n filedate = generate_dateformat(run_date, filemask)\\r\\n if not filedate:\\r\\n filename = filestartwith\\r\\n else:\\r\\n filename = filestartwith + filedate\\r\\n\\r\\n if fileendwith:\\r\\n filename = filename + fileendwith\\r\\n\\r\\n if filepath and len(filepath.strip()) > 0:\\r\\n filename = filepath.strip() + '/' + filename\\r\\n\\r\\n return filename\",\n \"def test_ascii_increment(self):\\r\\n self.assertRaises(ValueError, convert_fastaqual, self.fasta_file_path,\\r\\n ascii_increment=140, output_directory=self.output_dir)\",\n \"def validate(code):\\n if not code.isdigit():\\n raise IllegalCharacterError('[0-9]{%d}' % UPCA.digits)\\n\\n if len(code) != UPCA.digits:\\n raise ValueError('Bar code %s requires %d digits' % (code, UPCA.digits))\\n\\n checksum = UPCA.calculate_checksum(code)\\n if checksum != int(code[-1]):\\n raise ValueError('Checksum character mismatch %s != %s' % (checksum, code[-1]))\",\n \"def test_decode_barcode_8_ok(self):\\r\\n self.assertEqual(decode_barcode_8(self.valid_bc_1),\\r\\n (self.valid_bc_1, 0))\\r\\n self.assertEqual(decode_barcode_8(self.valid_bc_2),\\r\\n (self.valid_bc_2, 0))\\r\\n self.assertEqual(decode_barcode_8(self.valid_bc_3),\\r\\n (self.valid_bc_3, 0))\\r\\n self.assertEqual(decode_barcode_8(self.valid_bc_4),\\r\\n (self.valid_bc_4, 0))\\r\\n self.assertEqual(decode_barcode_8(self.valid_bc_5),\\r\\n (self.valid_bc_5, 0))\",\n \"def print_bar_code(zip_code):\\r\\n zip_sum = 0\\r\\n check_digit = 0\\r\\n\\r\\n print(\\\"|\\\", end=\\\"\\\")\\r\\n\\r\\n for i in zip_code:\\r\\n i = int(i)\\r\\n print_digit(i)\\r\\n zip_sum += i\\r\\n\\r\\n while zip_sum % 10 != 0:\\r\\n check_digit += 1\\r\\n zip_sum += 1\\r\\n\\r\\n print_digit(check_digit)\\r\\n print(\\\"|\\\")\",\n \"def get_required_samplesheet_format(bcl2fastq_version):\\n version = utils.parse_version(bcl2fastq_version)\\n major,minor = version[0:2]\\n if (major,minor) == utils.parse_version('1.8')[0:2]:\\n # Version 1.8.*\\n return 'CASAVA'\\n elif major == utils.parse_version('2')[0]:\\n # Version 2.*\\n return 'IEM'\\n else:\\n # Not a known version\\n raise NotImplementedError('unknown version: %s' %\\n bcl2fastq_version)\",\n \"def create_filenames(date):\\n \\n filelist = list()\\n for t in [\\\"0000\\\", \\\"0600\\\", \\\"1200\\\", \\\"1800\\\"]:\\n for t2 in [\\\"000\\\", \\\"003\\\"]:\\n filelist.append(\\\"gfsanl_4_\\\"+d.strftime('%Y%m%d')+\\\"_\\\"+t+\\\"_\\\"+t2+\\\".grb2\\\")\\n return filelist\",\n \"def barcode_is_10xgenomics(s):\\n return bool(re.match(r'^SI\\\\-[A-Z0-9]+\\\\-[A-Z0-9]+$',s))\",\n \"def print_barcode39_doc( ):\\n\\t\\n\\tprint( 'Print the Barcode39 ZPL document' )\\n\\tprint( '--------------------------------' )\\n\\tmedium = PrinterCupsAdapter( printer_queue_name = PRINTER_QUEUE_NAME )\\n\\td = ZplDocument( target_encoding = PRINTER_ENCODING, printer_adapter = medium, title = 'Barcode doc' )\\n\\t\\n\\t# Start a Print format\\n\\td.format_start()\\n\\n\\t# Origin Y is set to 80. 80 = 50 (Y position here upper) + 30 (font height here upper).\\n\\t#d.field( origin=(100,80), font=d.font('C'), data=u'Fun electronic hacking' ) \\n\\t\\n\\t# Write a BarCode field\\n\\td.field( origin=(120,11), font=d.font('E'), data=u'RASPBERRY.' )\\n\\td.field( origin=(120,42), font=d.font('E'), data=u'Pi.2......' )\\n\\td.barcode39( origin=(110,80), data=u'P0576', height_dots = 50 )\\n\\t\\n\\td.field( origin=(140,160), font=d.font('C'), data=u'MC Hobby sprl' )\\n\\td.field( origin=(130,180), font=d.font('C'), data=u'shop.mchobby.be' )\\n\\t# End Print format\\n\\td.format_end()\\n\\n\\t\\n\\tmedium.open() # Open the media for transmission. \\n\\t\\t\\t\\t # With CUPS medium this open a temporary file\\n\\ttry:\\n\\t\\td.send() # With CUPS medium this send the data to the temporary file\\n\\t\\tmedium.flush() # With CUPS medium this close the temporary file and\\n\\t\\t # sends to file to the print queue \\n\\tfinally:\\n\\t\\tmedium.close() \\n\\t\\t \\n\\t\\n\\tdel( medium )\",\n \"def process_barcode_in_label(read1_data,\\r\\n read2_data,\\r\\n output_bc_fastq,\\r\\n bc1_len=6,\\r\\n bc2_len=6,\\r\\n rev_comp_bc1=False,\\r\\n rev_comp_bc2=False,\\r\\n char_delineator=\\\":\\\"):\\r\\n header_index = 0\\r\\n\\r\\n # Check for char_delineator in sequence\\r\\n try:\\r\\n bc1_read = read1_data[header_index].split(\\r\\n char_delineator)[-1][0:bc1_len]\\r\\n # If there is an index error, it means the char_delineator wasn't found\\r\\n except IndexError:\\r\\n raise IndexError(\\\"Found sequence lacking character delineator. \\\"\\r\\n \\\"Sequence header %s, character delineator %s\\\" %\\r\\n (read1_data[header_index], char_delineator))\\r\\n\\r\\n # Create fake quality scores, using 6 here to match the existing qual fake\\r\\n # qual scores that were all F.\\r\\n bc1_qual = np.ones(len(bc1_read), dtype=np.int8) * 6\\r\\n if rev_comp_bc1:\\r\\n bc1_read = str(DNA(bc1_read).rc())\\r\\n\\r\\n if read2_data:\\r\\n bc2_read =\\\\\\r\\n read2_data[header_index].strip().split(\\r\\n char_delineator)[-1][0:bc2_len]\\r\\n bc2_qual = np.ones(len(bc2_read), dtype=np.int8) * 6\\r\\n if rev_comp_bc2:\\r\\n bc2_read = str(DNA(bc2_read).rc())\\r\\n else:\\r\\n bc2_read = \\\"\\\"\\r\\n bc2_qual = np.array([], dtype=np.int8)\\r\\n\\r\\n if not bc1_read and not bc2_read:\\r\\n raise ValueError(\\\"Came up with empty barcode sequence, please check \\\"\\r\\n \\\"character delineator with -s, and fastq label \\\"\\r\\n \\\"%s\\\" % read1_data[header_index])\\r\\n\\r\\n bc_lines = format_fastq_record(read1_data[header_index],\\r\\n bc1_read + bc2_read,\\r\\n np.hstack([bc1_qual, bc2_qual]))\\r\\n\\r\\n output_bc_fastq.write(bc_lines)\\r\\n\\r\\n return\",\n \"def formatRead(raw_barcode, corrected_barcode, title, sequence, quality):\\n \\n # for bowtie, anything after space in name will go to SAM\\n # remove existing comments as they may not be properly formatted\\n mod_title = title.split(\\\" \\\")[0]\\n \\n mod_title += \\\" CB:Z:\\\" + corrected_barcode + \\\"\\\\tCR:Z:\\\" + raw_barcode\\n\\n return(\\\"@%s\\\\n%s\\\\n+\\\\n%s\\\\n\\\" % (mod_title, sequence, quality))\",\n \"def test_process_barcode_in_label(self):\\r\\n\\r\\n fastq1_data = [\\r\\n \\\"HWI-ST830:ATCG\\\",\\r\\n \\\"AAAATTTTCCCCGGGG\\\",\\r\\n np.arange(3, 19, dtype=np.int8)]\\r\\n fastq2_data = [\\\"HWI-ST830:GGGG\\\", \\\"TCCCCGGGG\\\",\\r\\n np.arange(3, 12, dtype=np.int8)]\\r\\n bcs_out = FakeOutFile()\\r\\n\\r\\n process_barcode_in_label(fastq1_data, fastq2_data, bcs_out,\\r\\n bc1_len=4, bc2_len=3, rev_comp_bc1=True, rev_comp_bc2=True)\\r\\n\\r\\n actual_bcs = bcs_out.data.split('\\\\n')\\r\\n expected_bcs = ['@HWI-ST830:ATCG', 'CGATCCC', '+', \\\"'''''''\\\", '']\\r\\n self.assertEqual(actual_bcs, expected_bcs)\",\n \"def lastDigit(barcode):\\r\\n lastnumber = int(barcode[-1])\\r\\n return lastnumber\",\n \"def test_short_string_out_of_upper_range(self):\\n self.failUnlessRaises(Exception, self.codec.encode_shortstr, 'x'*256)\",\n \"def get_prefix() :\\n \\n import glob\\n filenames = glob.glob(picture_folder+'*.jpg')\\n max_prefix = 0\\n for filename in filenames :\\n parts = filenames.split('_')\\n if len(parts) > 1 :\\n possible_prefix = parse_int(parts[0])\\n if possible_prefix > max_prefix :\\n max_prefix = possible_prefix\\n \\n max_prefix += 1\\n return '%04d' % max_prefix\",\n \"def extract_barcodes(fastq1,\\r\\n fastq2=None,\\r\\n output_dir=\\\".\\\",\\r\\n input_type=\\\"barcode_single_end\\\",\\r\\n bc1_len=6,\\r\\n bc2_len=6,\\r\\n rev_comp_bc1=False,\\r\\n rev_comp_bc2=False,\\r\\n char_delineator=\\\":\\\",\\r\\n switch_bc_order=False,\\r\\n map_fp=None,\\r\\n attempt_read_orientation=False,\\r\\n disable_header_match=False):\\r\\n\\r\\n # Turn off extra file creation for single read.\\r\\n if input_type == \\\"barcode_single_end\\\" and attempt_read_orientation:\\r\\n attempt_read_orientation = False\\r\\n if attempt_read_orientation:\\r\\n header, mapping_data, run_description, errors, warnings =\\\\\\r\\n process_id_map(map_fp)\\r\\n forward_primers, reverse_primers = get_primers(header, mapping_data)\\r\\n output_bc_not_oriented = open(join(output_dir,\\r\\n \\\"barcodes_not_oriented.fastq.incomplete\\\"), \\\"w\\\")\\r\\n fastq1_out_not_oriented = open(join(output_dir,\\r\\n \\\"reads1_not_oriented.fastq.incomplete\\\"), \\\"w\\\")\\r\\n fastq2_out_not_oriented = open(join(output_dir,\\r\\n \\\"reads2_not_oriented.fastq.incomplete\\\"), \\\"w\\\")\\r\\n else:\\r\\n forward_primers = None\\r\\n reverse_primers = None\\r\\n output_bc_not_oriented = None\\r\\n fastq1_out_not_oriented = None\\r\\n fastq2_out_not_oriented = None\\r\\n\\r\\n output_bc_fastq = open(join(output_dir, \\\"barcodes.fastq.incomplete\\\"), \\\"w\\\")\\r\\n if input_type in [\\\"barcode_single_end\\\", \\\"barcode_paired_stitched\\\"]:\\r\\n output_fastq1 = open(join(output_dir, \\\"reads.fastq.incomplete\\\"), \\\"w\\\")\\r\\n output_fastq2 = None\\r\\n final_fastq1_name = join(output_dir, \\\"reads.fastq\\\")\\r\\n elif input_type in [\\\"barcode_paired_end\\\"]:\\r\\n output_fastq1 = open(join(output_dir, \\\"reads1.fastq.incomplete\\\"), \\\"w\\\")\\r\\n output_fastq2 = open(join(output_dir, \\\"reads2.fastq.incomplete\\\"), \\\"w\\\")\\r\\n final_fastq1_name = join(output_dir, \\\"reads1.fastq\\\")\\r\\n else:\\r\\n output_fastq1 = None\\r\\n output_fastq2 = None\\r\\n\\r\\n if not fastq2:\\r\\n fastq2 = cycle([\\\"@\\\", \\\"AAAAAAAAAAAA\\\", \\\"+\\\", \\\"AAAAAAAAAAAA\\\"])\\r\\n not_paired = True\\r\\n else:\\r\\n not_paired = False\\r\\n\\r\\n check_header_match_f = get_casava_version(fastq1)\\r\\n\\r\\n header_index = 0\\r\\n\\r\\n for read1_data, read2_data in izip(\\r\\n parse_fastq(fastq1, strict=False),\\r\\n parse_fastq(fastq2, strict=False)):\\r\\n if not disable_header_match:\\r\\n if not check_header_match_f(read1_data[header_index],\\r\\n read2_data[header_index]):\\r\\n raise FastqParseError(\\\"Headers of read1 and read2 do not match. Can't continue. \\\"\\r\\n \\\"Confirm that the fastq sequences that you are \\\"\\r\\n \\\"passing match one another. --disable_header_match can be \\\"\\r\\n \\\"used to suppress header checks.\\\")\\r\\n\\r\\n if input_type == \\\"barcode_single_end\\\":\\r\\n process_barcode_single_end_data(read1_data, output_bc_fastq,\\r\\n output_fastq1, bc1_len, rev_comp_bc1)\\r\\n\\r\\n elif input_type == \\\"barcode_paired_end\\\":\\r\\n process_barcode_paired_end_data(read1_data, read2_data,\\r\\n output_bc_fastq, output_fastq1, output_fastq2, bc1_len, bc2_len,\\r\\n rev_comp_bc1, rev_comp_bc2, attempt_read_orientation,\\r\\n forward_primers, reverse_primers, output_bc_not_oriented,\\r\\n fastq1_out_not_oriented, fastq2_out_not_oriented)\\r\\n\\r\\n elif input_type == \\\"barcode_paired_stitched\\\":\\r\\n process_barcode_paired_stitched(read1_data,\\r\\n output_bc_fastq, output_fastq1, bc1_len, bc2_len,\\r\\n rev_comp_bc1, rev_comp_bc2, attempt_read_orientation,\\r\\n forward_primers, reverse_primers, output_bc_not_oriented,\\r\\n fastq1_out_not_oriented, switch_bc_order)\\r\\n\\r\\n elif input_type == \\\"barcode_in_label\\\":\\r\\n if not_paired:\\r\\n curr_read2_data = False\\r\\n else:\\r\\n curr_read2_data = read2_data\\r\\n process_barcode_in_label(read1_data, curr_read2_data,\\r\\n output_bc_fastq, bc1_len, bc2_len,\\r\\n rev_comp_bc1, rev_comp_bc2, char_delineator)\\r\\n\\r\\n output_bc_fastq.close()\\r\\n rename(output_bc_fastq.name, join(output_dir, \\\"barcodes.fastq\\\"))\\r\\n if output_fastq1:\\r\\n output_fastq1.close()\\r\\n rename(output_fastq1.name, final_fastq1_name)\\r\\n if output_fastq2:\\r\\n output_fastq2.close()\\r\\n rename(output_fastq2.name, join(output_dir, \\\"reads2.fastq\\\"))\\r\\n if output_bc_not_oriented:\\r\\n rename(output_bc_not_oriented.name,\\r\\n join(output_dir, \\\"barcodes_not_oriented.fastq\\\"))\\r\\n if fastq1_out_not_oriented:\\r\\n rename(fastq1_out_not_oriented.name,\\r\\n join(output_dir, \\\"reads1_not_oriented.fastq\\\"))\\r\\n if fastq2_out_not_oriented:\\r\\n rename(fastq2_out_not_oriented.name,\\r\\n join(output_dir, \\\"reads2_not_oriented.fastq\\\"))\",\n \"def is_reserved(code):\\n return 1000 <= code <= 2999\",\n \"def _build_range(self) -> str:\\n return build_sequence(filter(None, (self.uids, self.sequence)))\",\n \"def generate_valid_keys():\\n valid_keys = []\\n for minimum, maximum in RANGES:\\n for i in range(ord(minimum), ord(maximum) + 1):\\n valid_keys.append(chr(i))\\n return valid_keys\",\n \"def process_fastq_single_end_read_file(fastq_read_f,\\r\\n fastq_barcode_f,\\r\\n barcode_to_sample_id,\\r\\n store_unassigned=False,\\r\\n max_bad_run_length=0,\\r\\n phred_quality_threshold=2,\\r\\n min_per_read_length_fraction=0.75,\\r\\n rev_comp=False,\\r\\n rev_comp_barcode=False,\\r\\n seq_max_N=0,\\r\\n start_seq_id=0,\\r\\n filter_bad_illumina_qual_digit=False,\\r\\n log_f=None,\\r\\n histogram_f=None,\\r\\n barcode_correction_fn=None,\\r\\n max_barcode_errors=1.5,\\r\\n strict_header_match=True,\\r\\n phred_to_ascii_f=None):\\r\\n header_index = 0\\r\\n sequence_index = 1\\r\\n quality_index = 2\\r\\n\\r\\n seq_id = start_seq_id\\r\\n # grab the first lines and then seek back to the beginning of the file\\r\\n try:\\r\\n fastq_read_f_line1 = fastq_read_f.readline()\\r\\n fastq_read_f_line2 = fastq_read_f.readline()\\r\\n fastq_read_f.seek(0)\\r\\n except AttributeError:\\r\\n fastq_read_f_line1 = fastq_read_f[0]\\r\\n fastq_read_f_line2 = fastq_read_f[1]\\r\\n\\r\\n post_casava_v180 = is_casava_v180_or_later(fastq_read_f_line1)\\r\\n if post_casava_v180:\\r\\n offset = 33\\r\\n check_header_match_f = check_header_match_180_or_later\\r\\n else:\\r\\n offset = 64\\r\\n check_header_match_f = check_header_match_pre180\\r\\n\\r\\n # compute the barcode length, if they are all the same.\\r\\n # this is useful for selecting a subset of the barcode read\\r\\n # if it's too long (e.g., for technical reasons on the sequencer)\\r\\n barcode_lengths = set([len(bc)\\r\\n for bc, sid in barcode_to_sample_id.items()])\\r\\n if len(barcode_lengths) == 1:\\r\\n barcode_length = barcode_lengths.pop()\\r\\n else:\\r\\n barcode_length = None\\r\\n\\r\\n # compute the minimum read length as a fraction of the length of the input\\r\\n # read\\r\\n min_per_read_length = min_per_read_length_fraction * \\\\\\r\\n len(fastq_read_f_line2)\\r\\n\\r\\n # prep data for logging\\r\\n input_sequence_count = 0\\r\\n count_barcode_not_in_map = 0\\r\\n count_too_short = 0\\r\\n count_too_many_N = 0\\r\\n count_bad_illumina_qual_digit = 0\\r\\n count_barcode_errors_exceed_max = 0\\r\\n sequence_lengths = []\\r\\n seqs_per_sample_counts = {}\\r\\n for bc_data, read_data in izip(\\r\\n parse_fastq(fastq_barcode_f, strict=False, phred_offset=offset),\\r\\n parse_fastq(fastq_read_f, strict=False, phred_offset=offset)):\\r\\n input_sequence_count += 1\\r\\n # Confirm match between barcode and read headers\\r\\n if strict_header_match and \\\\\\r\\n (not check_header_match_f(bc_data[header_index], read_data[header_index])):\\r\\n raise FastqParseError(\\\"Headers of barcode and read do not match. Can't continue. \\\"\\r\\n \\\"Confirm that the barcode fastq and read fastq that you are \\\"\\r\\n \\\"passing match one another.\\\")\\r\\n else:\\r\\n header = read_data[header_index]\\r\\n\\r\\n # Grab the barcode sequence\\r\\n if barcode_length:\\r\\n # because thirteen cycles are sometimes used for\\r\\n # techical reasons, this step looks only at the\\r\\n # first tweleve bases. note that the barcode is\\r\\n # rev-comp'ed after this step if requested since\\r\\n # the thirteen base is a technical artefact, not\\r\\n # barcode sequence.\\r\\n barcode = bc_data[sequence_index][:barcode_length]\\r\\n else:\\r\\n barcode = bc_data[sequence_index]\\r\\n if rev_comp_barcode:\\r\\n barcode = str(DNA(barcode).rc())\\r\\n # Grab the read sequence\\r\\n sequence = read_data[1]\\r\\n # Grab the read quality\\r\\n quality = read_data[2]\\r\\n\\r\\n # correct the barcode (if applicable) and map to sample id\\r\\n num_barcode_errors, corrected_barcode, correction_attempted, sample_id = \\\\\\r\\n correct_barcode(\\r\\n barcode,\\r\\n barcode_to_sample_id,\\r\\n barcode_correction_fn)\\r\\n # skip samples with too many errors\\r\\n if (num_barcode_errors > max_barcode_errors):\\r\\n count_barcode_errors_exceed_max += 1\\r\\n continue\\r\\n\\r\\n # skip unassignable samples unless otherwise requested\\r\\n if sample_id is None:\\r\\n if not store_unassigned:\\r\\n count_barcode_not_in_map += 1\\r\\n continue\\r\\n else:\\r\\n sample_id = 'Unassigned'\\r\\n\\r\\n quality_filter_result, sequence, quality =\\\\\\r\\n quality_filter_sequence(header,\\r\\n sequence,\\r\\n quality,\\r\\n max_bad_run_length,\\r\\n phred_quality_threshold,\\r\\n min_per_read_length,\\r\\n seq_max_N,\\r\\n filter_bad_illumina_qual_digit)\\r\\n\\r\\n # process quality result\\r\\n if quality_filter_result != 0:\\r\\n # if the quality filter didn't pass record why and\\r\\n # move on to the next record\\r\\n if quality_filter_result == 1:\\r\\n count_too_short += 1\\r\\n elif quality_filter_result == 2:\\r\\n count_too_many_N += 1\\r\\n elif quality_filter_result == 3:\\r\\n count_bad_illumina_qual_digit += 1\\r\\n else:\\r\\n raise ValueError(\\r\\n \\\"Unknown quality filter result: %d\\\" %\\r\\n quality_filter_result)\\r\\n continue\\r\\n\\r\\n sequence_lengths.append(len(sequence))\\r\\n\\r\\n try:\\r\\n seqs_per_sample_counts[sample_id] += 1\\r\\n except KeyError:\\r\\n seqs_per_sample_counts[sample_id] = 1\\r\\n\\r\\n if rev_comp:\\r\\n sequence = str(DNA(sequence).rc())\\r\\n quality = quality[::-1]\\r\\n\\r\\n fasta_header = '%s_%s %s orig_bc=%s new_bc=%s bc_diffs=%d' %\\\\\\r\\n (sample_id, seq_id, header, barcode,\\r\\n corrected_barcode, num_barcode_errors)\\r\\n yield fasta_header, sequence, quality, seq_id\\r\\n seq_id += 1\\r\\n\\r\\n # Add sample IDs with zero counts to dictionary for logging\\r\\n for curr_sample_id in barcode_to_sample_id.values():\\r\\n if curr_sample_id not in seqs_per_sample_counts.keys():\\r\\n seqs_per_sample_counts[curr_sample_id] = 0\\r\\n\\r\\n if log_f is not None:\\r\\n log_str = format_split_libraries_fastq_log(count_barcode_not_in_map,\\r\\n count_too_short,\\r\\n count_too_many_N,\\r\\n count_bad_illumina_qual_digit,\\r\\n count_barcode_errors_exceed_max,\\r\\n input_sequence_count,\\r\\n sequence_lengths,\\r\\n seqs_per_sample_counts)\\r\\n log_f.write(log_str)\\r\\n\\r\\n if len(sequence_lengths) and histogram_f is not None:\\r\\n counts, bin_edges = make_histograms(sequence_lengths)\\r\\n histogram_str = format_histogram_one_count(counts, bin_edges)\\r\\n histogram_f.write(histogram_str)\\r\\n histogram_f.write('\\\\n--\\\\n\\\\n')\",\n \"def validate_filename(\\n filename: PathType,\\n platform: Optional[PlatformType] = None,\\n min_len: int = DEFAULT_MIN_LEN,\\n max_len: int = _DEFAULT_MAX_FILENAME_LEN,\\n fs_encoding: Optional[str] = None,\\n check_reserved: bool = True,\\n) -> None:\\n\\n FileNameValidator(\\n platform=platform,\\n min_len=min_len,\\n max_len=max_len,\\n fs_encoding=fs_encoding,\\n check_reserved=check_reserved,\\n ).validate(filename)\",\n \"def __return_new_file_name(self, file_name: str, file_path: str):\\n\\n fastq_runid = re.split('[_.]', file_name) # split on `_` or `.`\\n barcode_number = file_path.split(\\\"/\\\")[-1] # get the barcode number\\n fastq_or_fasta = fastq_runid[-1] # get the .fastq/.fasta file extension\\n\\n # create the new file name\\n new_file_name = \\\"_\\\".join(fastq_runid[:3]) # join first three elements\\n new_file_name += \\\"_%s.%s\\\" % (barcode_number, fastq_or_fasta) # append the barcode number and file extension\\n\\n return new_file_name\",\n \"def test_standard_seq_week(self):\\n date = datetime(2016, 11, 15)\\n prices = [2] * 7\\n expected_sequence = 22\\n expected_week = 46\\n self.assertEqual(\\n star_barcode.date_to_sequence_and_week(\\n date=date, price_codes=prices),\\n (expected_sequence, expected_week)\\n )\",\n \"def test_uoctet_out_of_lower_range(self):\\n self.failUnlessRaises(Exception, self.codec.encode_octet, -1)\",\n \"def test_ascii_increment(self):\\r\\n self.assertRaises(ValueError, convert_fastq, self.fasta_file_path,\\r\\n self.qual_file_path, ascii_increment=140, output_directory=self.output_dir)\\r\\n self.assertRaises(ValueError, convert_fastq, self.fasta_file_path,\\r\\n self.qual_file_path, ascii_increment=10, output_directory=\\r\\n self.output_dir)\",\n \"def test_SequenceFrameRangeString(self):\\n\\n data = [1, 5, 7] + list(range(9, 15))\\n\\n self.assertEqual(path_core._core.Sequence._figureOutFrameRange(data), '1 5 7 9-14')\\n data.append(17)\\n self.assertEqual(path_core._core.Sequence._figureOutFrameRange(data), '1 5 7 9-14 17')\",\n \"def y2k_coding(n):\\n if n < 60:\\n return 2000 + n\\n else:\\n return 1900 + n\",\n \"def _format_id(self, index):\\n if index in self.VALID_ID_RANGE:\\n return '!ID {}\\\\n'.format(str(index).zfill(self.MAX_DIGITS_QTD))\\n raise IndexError(\\\"IDFile._format_id: {} is out of range\\\".format(index))\",\n \"def test_script_to_fs_script_too_long():\\n script = (b'shouldfit' * 3023)[:-1]\\n _ = uflash.script_to_fs(script, uflash._MICROBIT_ID_V1)\\n\\n script += b'1'\\n with pytest.raises(ValueError) as ex:\\n _ = uflash.script_to_fs(script, uflash._MICROBIT_ID_V1)\\n assert 'Python script must be less than' in ex.value.args[0]\",\n \"def test_octet_out_of_upper_range(self):\\n self.failUnlessRaises(Exception, self.codec.encode_octet, 256)\",\n \"def __file_from_int_to_str(file: int) -> str:\\n # Warning, my own, not very well tested implementation of base26 converter\\n output_chars = 1\\n while (len(ascii_lowercase)) ** output_chars <= file:\\n output_chars += 1\\n values = []\\n for i in range(output_chars):\\n val = (file // len(ascii_lowercase) ** i) % (len(ascii_lowercase))\\n values.append(val)\\n\\n return \\\"\\\".join(ascii_lowercase[x] for x in reversed(values))\",\n \"def test_typical(self):\\n with tempfile.TemporaryDirectory() as tempdir:\\n filename = 'test-barcode.pdf'\\n file_path = Path(tempdir, filename)\\n\\n # Make sure it's not there by accident\\n self.assertFalse(file_path.exists())\\n\\n star_barcode.create_barcode(\\n postscript=self.postscript,\\n output_file=file_path)\\n\\n self.assertTrue(file_path.exists())\",\n \"def test_compress_max_seq_len(self):\\n a_int = ord('a')\\n seq = ''.join(map(chr, range(a_int, a_int + LZ77.max_seq)))\\n text = '123' + seq + '345' + seq\\n actual = LZ77.compress(text)\\n expected = bytearray([0]) + bytearray(text[:8], 'utf-8')\\\\\\n + bytearray([0]) + bytearray(text[8: 16], 'utf-8')\\\\\\n + bytearray([1]) + bytearray(text[16: 23], 'utf-8')\\\\\\n + bytearray([1, 63])\\n self.assertEqual(actual, expected)\",\n \"def _get_aso_id_from_file_name(self, filename: str) -> str:\\n id_parts = filename.split('/')\\n prefix = id_parts[1]\\n suffix = id_parts[-1].split('.')[0].zfill(3)\\n if len(suffix) == 5:\\n return suffix\\n else:\\n return prefix + suffix\",\n \"def generate_raw_filename(self, source_name, table_name, environment, seq_number, upload_time, load_type,\\n file_format):\\n file_date = upload_time.strftime(\\n \\\"%Y-%m-%d-%H-%M-%S-%f\\\")[:-3] # [:-3] => Removing the 3 last characters as %f is for millis.\\n res = f'{source_name}/{source_name}_{table_name}/' \\\\\\n f'{source_name}_{environment}_{table_name}_{str(seq_number).zfill(3)}_' \\\\\\n f'{file_date}_utc_{load_type}.{file_format}'\\n res = res.lower()\\n\\n # Check if no illegal chars were passed\\n #test = FileNameStandardConvention(res)\\n #test.check_naming_convention()\\n return res\",\n \"def _clean_code(self) -> str:\\n if len(self.code) >= self.BARCODE_LENGTH:\\n code = self.code[:self.BARCODE_LENGTH]\\n\\n # Calculate the checksum digit\\n check_digit = self.calculate_checksum(code)\\n return code + str(check_digit)\",\n \"def prefix_from_filename(input_file):\\n prefix = \\\"\\\"\\n \\n if str(input_file).find(\\\"medication_bner_\\\") != -1:\\n prefix = \\\"drugbank\\\"\\n elif str(input_file).find(\\\"_bc5cdr\\\") != -1:\\n prefix = \\\"bc5cdr\\\"\\n elif str(input_file).find(\\\"_bionlp13cg\\\") != -1:\\n prefix = \\\"bionlp13cg\\\"\\n \\n return prefix\",\n \"def test_week_wrong(self):\\n weeks = [0, 54]\\n for week in weeks:\\n with self.subTest(week=week):\\n with self.assertRaisesRegex(ValueError, str(week)):\\n star_barcode.construct_postscript(\\n week=week,\\n bwipp_location=self.bwipp,\\n issn=self.issn,\\n sequence=21,\\n header_line=''\\n )\",\n \"def filename_decode(path):\\n path = re.sub(r'--[0-9A-Fa-f]{32}', u'\\\\u2026', path)\\n path = re.sub(r'-([0-9a-f]{4})', lambda match: unichr(int(match.group(1), 16)), path)\\n return path\",\n \"def barcode(self, uuid):\\n\\n barcode = code128.Code128(str(uuid), barWidth=1, barHeight=20)\\n barcode.drawOn(self.canvas, self.lastx, self.lasty)\\n self.lasty = self.lasty - 20\\n self.y = self.lasty\",\n \"def _compress_name(name):\\n n = 0\\n for c in name:\\n n = (n * _P1 + ord(c)) % _P2 \\n return '%09d' % n\",\n \"def convert_name_to_barcode_id(multiplex, fc_name, fq):\\n fqout = list([None, None])\\n name2bcid = dict([(mp['name'], mp['barcode_id']) for mp in multiplex])\\n for name in name2bcid.keys():\\n mstr = \\\"%s_%s_\\\" % (fc_name, name) \\n if fq[0].find(mstr) != -1:\\n from_str = \\\"%s_%s_\\\" %(fc_name, name)\\n to_str = \\\"%s_%s_\\\" %(fc_name, name2bcid[name])\\n fqout[0] = fq[0].replace(from_str, to_str)\\n if not fq[1] == None:\\n fqout[1] = fq[1].replace(from_str, to_str)\\n fqout[0] = fqout[0].replace(\\\".fastq\\\", \\\"_fastq.txt\\\")\\n if not fqout[1] == None:\\n fqout[1] = fqout[1].replace(\\\".fastq\\\", \\\"_fastq.txt\\\")\\n return os.path.basename(fqout[0]), (os.path.basename(fqout[1]) if len(fqout) > 1 else None)\",\n \"def inject_filename_counter(fname, counterval, maxextlen=6):\\n cvstr = '%05d' % counterval\\n parts = fname.split('.')\\n def isext(part):\\n return (len(part) <= maxextlen) or (part.startswith('container-'))\\n if (len(parts) == 1) or (not isext(parts[-1])):\\n return '%s-%s' % (fname, cvstr)\\n else:\\n return '%s-%s.%s' % ('.'.join(parts[:-1]), cvstr, parts[-1])\",\n \"def valid_serial_key(serial_key):\\n parts = serial_key.split('-')\\n if len(parts) != 5:\\n return False\\n\\n for part in parts:\\n if not re.match('[A-Z0-9]{5}$', part):\\n return False\\n\\n return True\",\n \"def test_get_barcode_kit(self):\\n run_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2'\\n sample_sheet_104 = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2/SQK-LSK109_sample_sheet.csv'\\n run_104 = MinIONqc(run_dir, sample_sheet_104, None)\\n got_kit_104 = run_104._get_barcode_kit()\\n \\n sample_sheet_114 = 'data/nanopore_data/run8/demux_failed/20200108_1412_MN19414_AAU648_68125dc2/SQK-LSK109_sample_sheet.csv'\\n run_114 = MinIONqc(run_dir, sample_sheet_114, None)\\n got_kit_114 = run_114._get_barcode_kit()\\n self.assertEqual(got_kit_104, 'EXP-NBD104')\\n self.assertEqual(got_kit_114, 'EXP-NBD114')\",\n \"def validate_isbn_format(isbn_code: str):\\n format_valid = False\\n isbn = list(isbn_code)\\n msj = ''\\n\\n if len(isbn) == 13:\\n\\n isbn_numbers = []\\n isbn_separator = []\\n index = 0\\n isbn_characters = []\\n\\n for character in isbn:\\n\\n if character in '0123456789':\\n isbn_numbers.append(character)\\n\\n elif character not in '0123456789':\\n isbn_characters.append(character)\\n\\n if character == '-':\\n isbn_separator.append(character)\\n\\n if index > 0:\\n if isbn[index - 1] not in '0123456789':\\n msj = 'Se ingresaron dos separadores juntos'\\n break\\n else:\\n msj = 'Se ingresó un caracter inválido'\\n break\\n\\n index += 1\\n\\n if len(isbn_numbers) < 10:\\n msj = 'Faltan dígitos'\\n\\n if len(isbn_separator) != 3:\\n msj = 'No son 4 grupos de números.'\\n\\n if len(isbn_separator) < 3:\\n diff = 3 - len(isbn_separator)\\n msj += ' Faltan ' + str(diff) + ' separadores'\\n else:\\n diff = len(isbn_separator) - 3\\n msj += ' Hay ' + str(diff) + ' separador sobrante'\\n\\n if msj == '':\\n format_valid = True\\n\\n elif len(isbn) < 13:\\n msj = 'Faltan caracteres'\\n\\n else:\\n msj = 'Se excede la cantidad de carácteres'\\n\\n return format_valid, msj\",\n \"def readdata(self,filename_):\\n if isinstance(filename_,unicode):\\n filename_ = filename_.encode(\\\"utf-8\\\",errors=\\\"replace\\\")\\n res = __library__.MSK_XX_readdataautoformat(self.__nativep,filename_)\\n if res != 0:\\n _,msg = self.__getlasterror(res)\\n raise Error(rescode(res),msg)\",\n \"def main(fileToCheck, minLength=-1, maxLength=-1):\\n\\n # Initialise variables.\\n lineCount = 1 # The number of the line being examined. Used for displaying error messages.\\n protDescription = True # Whether or not we are currently expecting a line starting with >.\\n firstLine = True # Whether or not we are currently examining the first line of the file.\\n proteinsInFile = {} # A dictionary indexed by the protein description line of the FASTA file.\\n # The value of each entry is the correctly formatted protein sequence corresponding to the index.\\n\\n # Strip off all excess whitespace, and split the string into the individual lines of the file.\\n checking = fileToCheck.rstrip()\\n checking = checking.lstrip()\\n checking = checking.split('\\\\n')\\n for line in checking:\\n line = line.rstrip()\\n if firstLine:\\n # True if we have just started parsing the file string, and haven;t yet examined any lines.\\n if line[0] == '>':\\n currentProt = line # Record the description line of the protein which is about to have its sequence inspected.\\n currentSeq = '' # Initialise the sequence of the protein.\\n protDescription = False # We are now expecting a protein sequence, not a protein description.\\n firstLine = False\\n else:\\n # The first line of the file MUST be a protein description line (i.e. start with '>'). If the line was not\\n # the beginning of a protein record, terminate the program.\\n errorMessage = \\\"Expected line \\\" + str(lineCount) + \\\" to start with a >, but instead got: \\\" + line\\n return 1, errorMessage\\n elif protDescription:\\n # This is true only if a line beginning with a '>' is expected.\\n if line[0] == '>':\\n # Expected a protein description line, and found a protein description line. This means that the entire sequence\\n # of the currentProt protein has been found (i.e. we have finished inspecting the sequence of a protein, and\\n # have found the protein to be valid). Now determine if the length of the sequence is within the user\\n # specified bounds.\\n if minLength == -1:\\n if maxLength == -1:\\n # If there are no restrictions on the protein sequence length, then record the protein and its sequence.\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) <= maxLength:\\n # If there is no minimum length restriction, and the protein sequence is not longer than the maximum\\n # sequence length permitted, then record the protein and its sequence.\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) >= minLength:\\n if maxLength == -1:\\n # If there is no maximum length restriction, and the protein sequence is not shorter than the minimum\\n # sequence length permitted, then record the protein and its sequence.\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) <= maxLength:\\n # If the protein sequence is not shorter than the minimum sequence length permitted and not longer\\n # than the maximum length permitted, then record the protein and its sequence.\\n proteinsInFile[currentProt] = currentSeq\\n currentProt = line # Record the description line of the protein which is about to have its sequence inspected.\\n currentSeq = '' # Initialise the sequence of the protein.\\n protDescription = False # We are now expecting a protein sequence, not a protein description.\\n else:\\n # If the line does not begin with a '>', and it is expected to, it is possible that the amino acid sequence\\n # is split over multiple lines.\\n if line.isalpha():\\n # If every character on the line is a letter, then the line contains a valid portion of the sequence.\\n # Add the uppercase version of the sequence portion to the sequence currently being recorded.\\n currentSeq += line.upper()\\n else:\\n # If the line did not contain only letters, terminate the program.\\n errorMessage = \\\"Expected line \\\" + str(lineCount) + \\\" to start with a >, but instead got: \\\" + line\\n return 1, errorMessage\\n else:\\n # If an amino acid sequence is expected.\\n if line.isalpha():\\n # If the line is all alphabetic characters, write the line out and indicate that we are expecting a\\n # protein description line next (i.e. one beginning with a '>').\\n currentSeq += line.upper()\\n protDescription = True\\n else:\\n # If the line did not contain only letters, terminate the program.\\n errorMessage = \\\"Expected line \\\" + str(lineCount) + \\\" to contain only letters, but instead got: \\\" + line\\n return 2, errorMessage\\n\\n lineCount += 1\\n\\n # Catch the final protein from the file, and determine whether it should be recorded.\\n if minLength == -1:\\n if maxLength == -1:\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) <= maxLength:\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) >= minLength:\\n if maxLength == -1:\\n proteinsInFile[currentProt] = currentSeq\\n elif len(currentSeq) <= maxLength:\\n proteinsInFile[currentProt] = currentSeq\\n\\n if len(proteinsInFile.keys()) < 2:\\n # There are too few protein sequences entered\\n errorMessage = (\\\"Not enough unique protein sequences have been entered.\\\" +\\n \\\" This is possibly caused by not enough sequences of the required minimum and maximum length being provided.\\\"\\n )\\n return 3, errorMessage\\n elif protDescription:\\n # Return an indication that the FASTA file is correctly formatted.\\n outputString = ''\\n for i in proteinsInFile.keys():\\n outputString += i + '\\\\n' + proteinsInFile[i] + '\\\\n'\\n return 0, outputString[:-1]\\n else:\\n # The file did not end with a protein sequence.\\n errorMessage = \\\"Reached the end of the file, but no protein sequence found for the final protein.\\\"\\n return 3, errorMessage\",\n \"def generate_barcode(self):\\n self.disable_generate_button()\\n try:\\n barcode_type, frame_type, color_metric, sampled_frame_rate, skip_over, total_frames, video_filename = \\\\\\n self.acquire_generation_param()\\n except FileNotFoundError:\\n self.enable_generate_button()\\n return\\n except:\\n showerror(\\\"Acquisition Parameters\\\", \\\"An unknown Error occurred when reading\\\\n\\\"\\n \\\"the acquisition parameters.\\\\n\\\\n\\\"\\n \\\"Please make sure all parameters are positive\\\\n\\\"\\n \\\"Frames units must all be integers\\\\n\\\"\\n \\\"In Time unit, mins:secs in Start and End at must be integers\\\\n\\\"\\n \\\"Sample every (secs) can be decimals but not fraction.\\\")\\n self.enable_generate_button()\\n return\\n\\n # Update all the parameters to the barcode generator\\n self.barcode_generator.barcode_type = barcode_type\\n self.barcode_generator.frame_type = frame_type\\n self.barcode_generator.color_metric = color_metric\\n self.barcode_generator.sampled_frame_rate = sampled_frame_rate\\n self.barcode_generator.skip_over = skip_over\\n self.barcode_generator.total_frames = total_frames\\n\\n # Check if user choose the multi-thread or not\\n if self.var_multi_thread.get() == 0:\\n multi_thread = None\\n elif self.var_multi_thread.get() == 1:\\n # If user choose to use the multi-thread, then get the number of threads that will be used\\n try:\\n multi_thread = int(self.thread_entry.get())\\n if multi_thread < 1:\\n showwarning(\\\"Non Positive Thread Number\\\", \\\"Number of threads has been adjusted to 1.\\\\n\\\"\\n \\\"Degenerated to single thread generation.\\\")\\n multi_thread = 1\\n except:\\n showerror(\\\"Invalid Thread Number\\\", \\\"Invalid number of threads.\\\\n\\\"\\n \\\"Number of threads must be an integer\\\")\\n self.enable_generate_button()\\n return\\n\\n # Check if user choose to save the frames or not\\n if self.var_saved_frame.get() == 1:\\n save_frames = True\\n try:\\n save_frames_rate = int(self.save_frame_entry.get())\\n except:\\n showerror(\\\"Invalid Save Frame Rate\\\", \\\"Invalid Save frame rate.\\\\n\\\"\\n \\\"Save frame rate must be a positive Integer.\\\")\\n self.enable_generate_button()\\n else:\\n save_frames_rate = -1\\n save_frames = False\\n\\n # Check if user choose to rescale the frames or not\\n if self.var_rescale_frame.get() == 1:\\n try:\\n rescale_factor = float(self.rescale_factor_entry.get())\\n except:\\n showerror(\\\"Invalid Rescale Factor\\\", \\\"Invalid frame rescale factor.\\\\n\\\"\\n \\\"Must be a positive number.\\\\n\\\"\\n \\\"It can be a decimal number but not fractions\\\")\\n self.enable_generate_button()\\n return\\n else:\\n rescale_factor = -1\\n\\n # Check if user choose to define the letter box region manually\\n if self.letterbox_option.get() == \\\"Manual\\\":\\n try:\\n # Update the letter box parameters, if user choose Manual\\n high_ver = int(self.high_ver_entry.get())\\n low_ver = int(self.low_ver_entry.get())\\n left_hor = int(self.left_hor_entry.get())\\n right_hor = int(self.right_hor_entry.get())\\n # Start the generation\\n self.barcode_generator.generate_barcode(video_filename, user_defined_letterbox=True,\\n low_ver=low_ver, high_ver=high_ver,\\n left_hor=left_hor, right_hor=right_hor,\\n num_thread=multi_thread, save_frames=save_frames,\\n rescale_frames_factor=rescale_factor,\\n save_frames_rate=save_frames_rate)\\n except:\\n showwarning(\\\"Error Occurred in Barcode Generation\\\", \\\"An unknown Error occurred in the barcode \\\"\\n \\\"generation.\\\\nPlease check the letterbox set up\\\"\\n \\\" and the other parameters' specification.\\\")\\n self.enable_generate_button()\\n return\\n elif self.letterbox_option.get() == \\\"Auto\\\":\\n # try:\\n # If not, start the generation.\\n # The letter box will be automatically found during the generation process\\n self.barcode_generator.generate_barcode(video_filename, num_thread=multi_thread,\\n save_frames=save_frames,\\n rescale_frames_factor=rescale_factor,\\n save_frames_rate=save_frames_rate)\\n # except:\\n # showwarning(\\\"Error Occurred in Barcode Generation\\\", \\\"An unknown Error occurred in the barcode \\\"\\n # \\\"generation.\\\\nPlease check the parameters' \\\"\\n # \\\"specification.\\\")\\n # self.enable_generate_button()\\n # return\\n\\n # Correct the total frames\\n total_frames = self.barcode_generator.get_barcode().total_frames\\n\\n # Get the key of the barcode, which will be later stored in the memory stack (dictionary)\\n start_pos = video_filename.rfind(\\\"/\\\") + 1\\n if start_pos < 0:\\n start_pos = 0\\n end_pos = video_filename.rfind(\\\".\\\")\\n videoname = video_filename[start_pos:end_pos] + \\\"_\\\" + barcode_type + \\\"_\\\" + frame_type + \\\"_\\\" + color_metric \\\\\\n + \\\"_\\\" + str(skip_over) + \\\"_\\\" + str(sampled_frame_rate) + \\\"_\\\" + str(total_frames)\\n\\n # Get the barcode from the barcode generator\\n barcode = self.barcode_generator.get_barcode()\\n\\n # Clear the cv2 captured video object\\n barcode.video = None\\n\\n # Update the user pre-defined meta data to the computed barcode\\n barcode.meta_data = copy.deepcopy(self.meta_data_dict)\\n\\n # Add the generated barcode to the memory stack (dictionary)\\n self.barcode_stack[videoname] = copy.deepcopy(barcode)\\n\\n # Enable the generate button for the next barcode generation request\\n self.enable_generate_button()\\n\\n # Reset the meta data to the initial state\\n self.meta_data_dict = {}\\n\\n # Show barcode generation success message\\n showinfo(\\\"Finished Successfully\\\", \\\"{:s} {:s} {:s} Barcode of the input video:\\\\n\\\"\\n \\\"{:20s}\\\\n\\\"\\n \\\"has been successfully generated!\\\\n\\\\n\\\"\\n \\\"Barcode is saved in the memory with name: {:20s}\\\".format(color_metric,\\n frame_type,\\n barcode_type,\\n video_filename,\\n videoname))\",\n \"def _create_unique_filename_with_integer_suffix(fullpath):\\n # create an unique filename\\n suffix = None\\n suffix_cnt=1\\n while os.path.exists(fullpath):\\n if suffix: fullpath = fullpath[0:-len(suffix)]\\n suffix = \\\".%s\\\" % suffix_cnt\\n suffix_cnt+=1\\n fullpath = fullpath + suffix\\n return fullpath\",\n \"def make_file_format(filename, format_extension):\\r\\n \\r\\n if filename[len(filename)-len(format_extension):len(filename)] != format_extension:\\r\\n filename += format_extension\\r\\n \\r\\n return(filename)\",\n \"def _generate_barcode_ids(info_iter):\\n bc_type = \\\"SampleSheet\\\"\\n barcodes = list(set([x[-1] for x in info_iter]))\\n barcodes.sort()\\n barcode_ids = {}\\n for i, bc in enumerate(barcodes):\\n barcode_ids[bc] = (bc_type, i+1)\\n return barcode_ids\",\n \"def write( self, ucode ):\\n\\t\\tassert isinstance( ucode, unicode ), \\\"the code to compute in barcode must be a unicode string\\\" \\n\\t\\t\\n\\t\\t# code barre message must starts and finish with *\\n\\t\\tucode = u'*%s*' % ucode.strip()\\n\\t\\t\\n\\t\\tself.owner.write_bytes( self._bc_start )\\n\\t\\t# Transfert every computed esc sequence into the document \\n\\t\\tfor bytes_seq in self.code_to_sequences( ucode ):\\n\\t\\t\\tself.owner.write_bytes( bytes_seq )\\n\\t\\t\\tself.owner.write_bytes( eval( '_ns', globals(), self.__dict__ ) ) # add a ns after each caracter sequence\\n\\t\\tself.owner.write_bytes( self._bc_end )\",\n \"def test_typical(self):\\n seq = 21\\n week = 46\\n header = 'MSTAR 2016-11-14 MON 1.0'\\n issn_args = ' '.join([self.issn, str(seq), str(week)])\\n result = star_barcode.construct_postscript(\\n bwipp_location=self.bwipp,\\n issn=self.issn,\\n sequence=seq,\\n week=week,\\n header_line=header\\n )\\n self.assertGreater(result.find(str(self.bwipp)), -1)\\n self.assertGreater(result.find(issn_args), -1)\\n self.assertGreater(result.find(header), -1)\",\n \"def validate_b2_file_name(name):\\n if not isinstance(name, str):\\n raise ValueError('file name must be a string, not bytes')\\n name_utf8 = name.encode('utf-8')\\n if len(name_utf8) < 1:\\n raise ValueError('file name too short (0 utf-8 bytes)')\\n if 1000 < len(name_utf8):\\n raise ValueError('file name too long (more than 1000 utf-8 bytes)')\\n if name[0] == '/':\\n raise ValueError(\\\"file names must not start with '/'\\\")\\n if name[-1] == '/':\\n raise ValueError(\\\"file names must not end with '/'\\\")\\n if '\\\\\\\\' in name:\\n raise ValueError(\\\"file names must not contain '\\\\\\\\'\\\")\\n if '//' in name:\\n raise ValueError(\\\"file names must not contain '//'\\\")\\n if chr(127) in name:\\n raise ValueError(\\\"file names must not contain DEL\\\")\\n if any(250 < len(segment) for segment in name_utf8.split(b'/')):\\n raise ValueError(\\\"file names segments (between '/') can be at most 250 utf-8 bytes\\\")\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6251834","0.6211295","0.6178404","0.61356765","0.6012833","0.5837435","0.5756376","0.5724416","0.56670076","0.56564724","0.5565162","0.55428994","0.5510424","0.5450344","0.52778983","0.5277632","0.51578164","0.51521355","0.5145388","0.5137915","0.5113716","0.5082711","0.50473666","0.5041459","0.5028049","0.5025804","0.5011257","0.49898285","0.4961907","0.4919932","0.48942006","0.4887376","0.48776433","0.48732814","0.4869922","0.48672953","0.48438674","0.483688","0.48337096","0.4831683","0.48291826","0.48234642","0.48139057","0.48103523","0.47864303","0.4777521","0.4742606","0.47303328","0.4725174","0.471784","0.47011873","0.46928528","0.46864215","0.46743265","0.4665144","0.4662369","0.46613595","0.46501288","0.46386474","0.46328753","0.46326527","0.46189126","0.4607404","0.46037567","0.45880055","0.45727557","0.45701146","0.45589307","0.4558351","0.45550445","0.45518798","0.45508507","0.45413148","0.45397842","0.45324206","0.45312548","0.45305604","0.45264047","0.45239648","0.45023313","0.4500906","0.44994298","0.44953665","0.44916663","0.4485901","0.44854146","0.4484359","0.44798753","0.44790363","0.44757673","0.44648993","0.4457266","0.44472462","0.4442862","0.4440199","0.4439887","0.4439202","0.44378632","0.4436811","0.44278485"],"string":"[\n \"0.6251834\",\n \"0.6211295\",\n \"0.6178404\",\n \"0.61356765\",\n \"0.6012833\",\n \"0.5837435\",\n \"0.5756376\",\n \"0.5724416\",\n \"0.56670076\",\n \"0.56564724\",\n \"0.5565162\",\n \"0.55428994\",\n \"0.5510424\",\n \"0.5450344\",\n \"0.52778983\",\n \"0.5277632\",\n \"0.51578164\",\n \"0.51521355\",\n \"0.5145388\",\n \"0.5137915\",\n \"0.5113716\",\n \"0.5082711\",\n \"0.50473666\",\n \"0.5041459\",\n \"0.5028049\",\n \"0.5025804\",\n \"0.5011257\",\n \"0.49898285\",\n \"0.4961907\",\n \"0.4919932\",\n \"0.48942006\",\n \"0.4887376\",\n \"0.48776433\",\n \"0.48732814\",\n \"0.4869922\",\n \"0.48672953\",\n \"0.48438674\",\n \"0.483688\",\n \"0.48337096\",\n \"0.4831683\",\n \"0.48291826\",\n \"0.48234642\",\n \"0.48139057\",\n \"0.48103523\",\n \"0.47864303\",\n \"0.4777521\",\n \"0.4742606\",\n \"0.47303328\",\n \"0.4725174\",\n \"0.471784\",\n \"0.47011873\",\n \"0.46928528\",\n \"0.46864215\",\n \"0.46743265\",\n \"0.4665144\",\n \"0.4662369\",\n \"0.46613595\",\n \"0.46501288\",\n \"0.46386474\",\n \"0.46328753\",\n \"0.46326527\",\n \"0.46189126\",\n \"0.4607404\",\n \"0.46037567\",\n \"0.45880055\",\n \"0.45727557\",\n \"0.45701146\",\n \"0.45589307\",\n \"0.4558351\",\n \"0.45550445\",\n \"0.45518798\",\n \"0.45508507\",\n \"0.45413148\",\n \"0.45397842\",\n \"0.45324206\",\n \"0.45312548\",\n \"0.45305604\",\n \"0.45264047\",\n \"0.45239648\",\n \"0.45023313\",\n \"0.4500906\",\n \"0.44994298\",\n \"0.44953665\",\n \"0.44916663\",\n \"0.4485901\",\n \"0.44854146\",\n \"0.4484359\",\n \"0.44798753\",\n \"0.44790363\",\n \"0.44757673\",\n \"0.44648993\",\n \"0.4457266\",\n \"0.44472462\",\n \"0.4442862\",\n \"0.4440199\",\n \"0.4439887\",\n \"0.4439202\",\n \"0.44378632\",\n \"0.4436811\",\n \"0.44278485\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.54502195"},"document_rank":{"kind":"string","value":"14"}}},{"rowIdx":3987,"cells":{"query":{"kind":"string","value":"Test the __init__ method when parameter 'ip' is None. Since the field is optional, it should pass."},"document":{"kind":"string","value":"def test_init_no_ip(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n ap = APInfo(port_id=1, ip=None, mac=\"bb:bb:bb:bb:bb:bb\", radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\n self.assertEqual(ap.ip, None)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_init_no_ip(self):\n client = ClientInfo(\"cc:cc:cc:cc:cc:cc\", ip=None, ap_info=self.ap)\n self.assertEqual(client.ip, None)\n self.assertEqual(client.ip_bytes, None)","def __init__(__self__, *,\n ip: Optional[pulumi.Input['IPAccessControlArgs']] = None):\n if ip is not None:\n pulumi.set(__self__, \"ip\", ip)","def __init__(__self__, *,\n ip: Optional[pulumi.Input['IPAccessControlArgs']] = None):\n if ip is not None:\n pulumi.set(__self__, \"ip\", ip)","def __init__(self) -> None:\n self.ip_address: str | None = None","def __init__(__self__, *,\n host_ip: Optional[pulumi.Input[str]] = None,\n port: Optional[pulumi.Input[str]] = None):\n if host_ip is not None:\n pulumi.set(__self__, \"host_ip\", host_ip)\n if port is not None:\n pulumi.set(__self__, \"port\", port)","def __init__(\n self, name: str = \"\", protocol: int | None = None, **kwargs: Any\n ) -> None:\n\n super().__init__(name=name, **kwargs)\n if not ipaddress:\n raise SoftDependencyError(\"ipaddress\")\n if protocol not in [None, 4, 6]:\n raise ValueError(\"IpAddress protocol needs to be either 4, 6 or None\")\n self.protocol = protocol","def __init__(\n self, name: str = \"\", protocol: int | None = None, **kwargs: Any\n ) -> None:\n\n super().__init__(name=name, **kwargs)\n\n if protocol not in [None, 4, 6]:\n raise ValueError(\"IpAddress protocol needs to be either 4, 6 or None\")\n self.protocol = protocol","def test_validate_ip_ok():\n ip = '1.1.1.1'\n assert howisresolved.validate_ip(ip) is None","def test_field_none_nullable(self):\n node_dict = {\n 'host_name': 'abc'\n }\n try:\n Node(**node_dict)\n except Exception as e:\n self.assertEqual(type(e), ValueError)","def __init__(__self__, *,\n ip_tag_type: Optional[pulumi.Input[str]] = None,\n tag: Optional[pulumi.Input[str]] = None):\n if ip_tag_type is not None:\n pulumi.set(__self__, \"ip_tag_type\", ip_tag_type)\n if tag is not None:\n pulumi.set(__self__, \"tag\", tag)","def __init__(self, allow_none=False):\n if allow_none:\n self.validate = self.validate_none\n self.info = self.info_none\n self.fast_validate = (2, None)\n else:\n self.fast_validate = (2,)","def __init__(__self__, *,\n destination_pool_name: Optional[pulumi.Input[str]] = None,\n ip: Optional[pulumi.Input[str]] = None):\n if destination_pool_name is not None:\n pulumi.set(__self__, \"destination_pool_name\", destination_pool_name)\n if ip is not None:\n pulumi.set(__self__, \"ip\", ip)","def test_init_no_mac(self):\n with self.assertRaises(ValueError):\n client = ClientInfo(None, ip=\"3.3.3.3\", ap_info=self.ap)","def __init__(self, ip, mask):\n self.vip = ip\n self.mask = mask","def __init__(__self__, *,\n end_ip: pulumi.Input[str],\n start_ip: pulumi.Input[str]):\n pulumi.set(__self__, \"end_ip\", end_ip)\n pulumi.set(__self__, \"start_ip\", start_ip)","def __init__(__self__, *,\n host: Optional[pulumi.Input[str]] = None,\n port: Optional[pulumi.Input[int]] = None):\n if host is not None:\n pulumi.set(__self__, \"host\", host)\n if port is not None:\n pulumi.set(__self__, \"port\", port)","def __init__(self, ip: str):\n self.api = API(f\"http://{ip}\")\n self.ip = ip\n self.board_data = None","def test_no_ip_address_passed(self, api_client):\n runner = CliRunner()\n\n with patch(\"greynoise.cli.helper.sys\") as sys:\n sys.stdin.isatty.return_value = True\n result = runner.invoke(\n subcommand.ip, parent=Context(main, info_name=\"greynoise\")\n )\n assert result.exit_code == -1\n assert \"Usage: greynoise ip\" in result.output\n api_client.ip.assert_not_called()","def __init__(__self__, *,\n ignore_missing_v_net_service_endpoint: Optional[pulumi.Input[bool]] = None,\n subnet_id: Optional[pulumi.Input[str]] = None):\n if ignore_missing_v_net_service_endpoint is not None:\n pulumi.set(__self__, \"ignore_missing_v_net_service_endpoint\", ignore_missing_v_net_service_endpoint)\n if subnet_id is not None:\n pulumi.set(__self__, \"subnet_id\", subnet_id)","def test_optional_arg(self):\n obj = Base()\n self.assertEqual(obj.id, 1)","def __init__(__self__, *,\n droplet_id: Optional[pulumi.Input[int]] = None,\n ip_address: Optional[pulumi.Input[str]] = None,\n region: Optional[pulumi.Input[str]] = None,\n urn: Optional[pulumi.Input[str]] = None):\n if droplet_id is not None:\n pulumi.set(__self__, \"droplet_id\", droplet_id)\n if ip_address is not None:\n pulumi.set(__self__, \"ip_address\", ip_address)\n if region is not None:\n pulumi.set(__self__, \"region\", region)\n if urn is not None:\n pulumi.set(__self__, \"urn\", urn)","def __init__(__self__, *,\n allow: Optional[pulumi.Input[Sequence[pulumi.Input['IPRangeArgs']]]] = None):\n if allow is not None:\n pulumi.set(__self__, \"allow\", allow)","def __init__(__self__, *,\n region: pulumi.Input[str],\n droplet_id: Optional[pulumi.Input[int]] = None,\n ip_address: Optional[pulumi.Input[str]] = None):\n pulumi.set(__self__, \"region\", region)\n if droplet_id is not None:\n pulumi.set(__self__, \"droplet_id\", droplet_id)\n if ip_address is not None:\n pulumi.set(__self__, \"ip_address\", ip_address)","def __init__(self):\n self.clean_optional()","def __init__(__self__, *,\n resourcegroup: pulumi.Input[str],\n server: pulumi.Input[str],\n endipaddress: Optional[pulumi.Input[str]] = None,\n startipaddress: Optional[pulumi.Input[str]] = None):\n pulumi.set(__self__, \"resourcegroup\", resourcegroup)\n pulumi.set(__self__, \"server\", server)\n if endipaddress is not None:\n pulumi.set(__self__, \"endipaddress\", endipaddress)\n if startipaddress is not None:\n pulumi.set(__self__, \"startipaddress\", startipaddress)","def __init__(self, ip=None, header=None, hostname=None, aliases=None):\n self.id = header or \"\"\n self.hostname = hostname or \"\"\n self.aliases = aliases or []\n self.ip = \"\"\n if ip:\n try:\n self.ip=ipaddress.ip_address(ip)\n except ipaddress.AddressValueError as e:\n print(\"Error parsing ip address from hosts.conf file\")\n raise e\n self.stored_state = None","def __init__(self, **kwargs):\n self.swagger_types = {\n 'assign_public_ip': 'bool',\n 'defined_tags': 'dict(str, dict(str, object))',\n 'display_name': 'str',\n 'freeform_tags': 'dict(str, str)',\n 'hostname_label': 'str',\n 'nsg_ids': 'list[str]',\n 'private_ip': 'str',\n 'skip_source_dest_check': 'bool',\n 'subnet_id': 'str'\n }\n\n self.attribute_map = {\n 'assign_public_ip': 'assignPublicIp',\n 'defined_tags': 'definedTags',\n 'display_name': 'displayName',\n 'freeform_tags': 'freeformTags',\n 'hostname_label': 'hostnameLabel',\n 'nsg_ids': 'nsgIds',\n 'private_ip': 'privateIp',\n 'skip_source_dest_check': 'skipSourceDestCheck',\n 'subnet_id': 'subnetId'\n }\n\n self._assign_public_ip = None\n self._defined_tags = None\n self._display_name = None\n self._freeform_tags = None\n self._hostname_label = None\n self._nsg_ids = None\n self._private_ip = None\n self._skip_source_dest_check = None\n self._subnet_id = None","def __init__(__self__,\n resource_name: str,\n args: ReservedIpArgs,\n opts: Optional[pulumi.ResourceOptions] = None):\n ...","def __init__(self, **kwargs):\n members = ('ip', 'mac', 'port', 'timeout', 'flags',\n 'index', 'tag', 'hostname')\n\n # copy the given value or default to None\n for member in members:\n self.__dict__[member] = kwargs.setdefault (member, None)","def test_init_without_kwargs(self):\n c = City()\n self.assertTrue('id' in c.__dict__)\n self.assertTrue('created_at' in c.__dict__)\n self.assertTrue('updated_at' in c.__dict__)\n self.assertIsInstance(c, BaseModel)","def validate_ip(argname, param, safe, optional = False):\n _validate_one(argname, param, safe, _check_ip, optional)","def test_init_wrong_ap_type(self):\n ap_wrong = object()\n with self.assertRaises(ValueError):\n client = ClientInfo(\"cc:cc:cc:cc:cc:cc\",\n ip=\"3.3.3.3\", ap_info=ap_wrong)","def __init__(__self__, *,\n protocol: Optional[pulumi.Input[str]] = None,\n url: Optional[pulumi.Input[str]] = None):\n if protocol is not None:\n pulumi.set(__self__, \"protocol\", protocol)\n if url is not None:\n pulumi.set(__self__, \"url\", url)","def __init__(__self__, *,\n public_ips: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceReferenceArgs']]]] = None):\n if public_ips is not None:\n pulumi.set(__self__, \"public_ips\", public_ips)","def __init__(__self__, *,\n cidr: pulumi.Input[str],\n resource_group_name: pulumi.Input[str],\n commissioning_enabled: Optional[pulumi.Input[bool]] = None,\n internet_advertising_disabled: Optional[pulumi.Input[bool]] = None,\n location: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None,\n parent_custom_ip_prefix_id: Optional[pulumi.Input[str]] = None,\n roa_validity_end_date: Optional[pulumi.Input[str]] = None,\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n wan_validation_signed_message: Optional[pulumi.Input[str]] = None,\n zones: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\n pulumi.set(__self__, \"cidr\", cidr)\n pulumi.set(__self__, \"resource_group_name\", resource_group_name)\n if commissioning_enabled is not None:\n pulumi.set(__self__, \"commissioning_enabled\", commissioning_enabled)\n if internet_advertising_disabled is not None:\n pulumi.set(__self__, \"internet_advertising_disabled\", internet_advertising_disabled)\n if location is not None:\n pulumi.set(__self__, \"location\", location)\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if parent_custom_ip_prefix_id is not None:\n pulumi.set(__self__, \"parent_custom_ip_prefix_id\", parent_custom_ip_prefix_id)\n if roa_validity_end_date is not None:\n pulumi.set(__self__, \"roa_validity_end_date\", roa_validity_end_date)\n if tags is not None:\n pulumi.set(__self__, \"tags\", tags)\n if wan_validation_signed_message is not None:\n pulumi.set(__self__, \"wan_validation_signed_message\", wan_validation_signed_message)\n if zones is not None:\n pulumi.set(__self__, \"zones\", zones)","def test_control_create_with_empty_field(self, field):\n request = self.prepare_control_request_body()\n request[field] = None\n\n response = self.api.post(all_models.Control, data=request)\n\n self.assert400(response)","def test_init_correct(self):\n client = ClientInfo(\"cc:cc:cc:cc:cc:cc\", ip=\"3.3.3.3\", ap_info=self.ap)\n self.assertEqual(client.ip, \"3.3.3.3\")\n self.assertEqual(client.ip_bytes, b'\\x03\\x03\\x03\\x03')","def __init__(__self__, *,\n id: str,\n private_ip_address: Optional[str] = None):\n pulumi.set(__self__, \"id\", id)\n if private_ip_address is not None:\n pulumi.set(__self__, \"private_ip_address\", private_ip_address)","def test_creation_notallow_none():\n with pytest.raises(ValueError) as __:\n value = None\n __ = param.Integer(value=value, allow_None=False)","def validate_ip(self, ip):\n if not ip:\n raise ValidationError(\"Please provide an actual IP or web address. You gave me: \" + ip)","def __init__(__self__, *,\n destination_pool_name: pulumi.Input[str],\n ip: pulumi.Input[str]):\n pulumi.set(__self__, \"destination_pool_name\", destination_pool_name)\n pulumi.set(__self__, \"ip\", ip)","def test_field_nullable(self):\n node_dict = {\n 'host_name': 'abc',\n 'local_router_id': '1.1.1.1',\n 'as_num': 100,\n 'bgpls_id': '0.0.0.0',\n 'igp_id': '0.0.0.0'\n }\n node = Node(**node_dict)\n for name, field in node_dict.items():\n self.assertEqual(field, node.__dict__[name])","def __init__(__self__, *,\n cidr: Optional[pulumi.Input[str]] = None,\n commissioning_enabled: Optional[pulumi.Input[bool]] = None,\n internet_advertising_disabled: Optional[pulumi.Input[bool]] = None,\n location: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None,\n parent_custom_ip_prefix_id: Optional[pulumi.Input[str]] = None,\n resource_group_name: Optional[pulumi.Input[str]] = None,\n roa_validity_end_date: Optional[pulumi.Input[str]] = None,\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n wan_validation_signed_message: Optional[pulumi.Input[str]] = None,\n zones: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\n if cidr is not None:\n pulumi.set(__self__, \"cidr\", cidr)\n if commissioning_enabled is not None:\n pulumi.set(__self__, \"commissioning_enabled\", commissioning_enabled)\n if internet_advertising_disabled is not None:\n pulumi.set(__self__, \"internet_advertising_disabled\", internet_advertising_disabled)\n if location is not None:\n pulumi.set(__self__, \"location\", location)\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if parent_custom_ip_prefix_id is not None:\n pulumi.set(__self__, \"parent_custom_ip_prefix_id\", parent_custom_ip_prefix_id)\n if resource_group_name is not None:\n pulumi.set(__self__, \"resource_group_name\", resource_group_name)\n if roa_validity_end_date is not None:\n pulumi.set(__self__, \"roa_validity_end_date\", roa_validity_end_date)\n if tags is not None:\n pulumi.set(__self__, \"tags\", tags)\n if wan_validation_signed_message is not None:\n pulumi.set(__self__, \"wan_validation_signed_message\", wan_validation_signed_message)\n if zones is not None:\n pulumi.set(__self__, \"zones\", zones)","def __init__(__self__, *,\n allowed_host_ports: Optional[pulumi.Input[Sequence[pulumi.Input['PortRangeArgs']]]] = None,\n application_security_groups: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n node_public_ip_tags: Optional[pulumi.Input[Sequence[pulumi.Input['IPTagArgs']]]] = None):\n if allowed_host_ports is not None:\n pulumi.set(__self__, \"allowed_host_ports\", allowed_host_ports)\n if application_security_groups is not None:\n pulumi.set(__self__, \"application_security_groups\", application_security_groups)\n if node_public_ip_tags is not None:\n pulumi.set(__self__, \"node_public_ip_tags\", node_public_ip_tags)","def validate_input(self, IP, Port):\n exception = ServerInitError\n try:\n if IP != None:\n if re.match(IPRegex, IP):\n self.IP = IP\n else:\n exception = InavlidIPError\n raise\n\n if Port != None:\n if int(Port) in range(0,65535):\n self.Port = Port\n else:\n exception = InvalidPortError\n raise\n except:\n traceback_print_exc()","def __init__(__self__, *,\n address: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None,\n subnet_prefix_length: Optional[pulumi.Input[int]] = None):\n if address is not None:\n pulumi.set(__self__, \"address\", address)\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if subnet_prefix_length is not None:\n pulumi.set(__self__, \"subnet_prefix_length\", subnet_prefix_length)","def test_same_ip(self):\n self.create_ptr(\n ip_str='128.193.0.2', ip_type='4', fqdn='foo1.oregonstate.edu')\n\n with self.assertRaises(ValidationError):\n self.create_ptr(\n ip_str='128.193.0.2', ip_type='4', fqdn='foo2.oregonstate.edu')","def __init__(self,\r\n name=None,\r\n lan_ip=None,\r\n uplink=None,\r\n public_port=None,\r\n local_port=None,\r\n allowed_ips=None,\r\n protocol=None):\r\n\r\n # Initialize members of the class\r\n self.name = name\r\n self.lan_ip = lan_ip\r\n self.uplink = uplink\r\n self.public_port = public_port\r\n self.local_port = local_port\r\n self.allowed_ips = allowed_ips\r\n self.protocol = protocol","def __init__(__self__, *,\n dns_servers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n gateway: Optional[pulumi.Input[str]] = None,\n infra_vnet_profile: Optional[pulumi.Input['VirtualNetworksPropertiesInfraVnetProfileArgs']] = None,\n ip_address_prefix: Optional[pulumi.Input[str]] = None,\n vip_pool: Optional[pulumi.Input[Sequence[pulumi.Input['VirtualNetworksPropertiesVipPoolArgs']]]] = None,\n vmip_pool: Optional[pulumi.Input[Sequence[pulumi.Input['VirtualNetworksPropertiesVmipPoolArgs']]]] = None):\n if dns_servers is not None:\n pulumi.set(__self__, \"dns_servers\", dns_servers)\n if gateway is not None:\n pulumi.set(__self__, \"gateway\", gateway)\n if infra_vnet_profile is not None:\n pulumi.set(__self__, \"infra_vnet_profile\", infra_vnet_profile)\n if ip_address_prefix is not None:\n pulumi.set(__self__, \"ip_address_prefix\", ip_address_prefix)\n if vip_pool is not None:\n pulumi.set(__self__, \"vip_pool\", vip_pool)\n if vmip_pool is not None:\n pulumi.set(__self__, \"vmip_pool\", vmip_pool)","def test_init_correct(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n ap = APInfo(port_id=1, ip=\"2.2.2.2\", mac=\"bb:bb:bb:bb:bb:bb\", radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\n\n self.assertEqual(ap.ip, '2.2.2.2')","def test_noop(self):\n self.assertFalse(helpers.getBcastAddrforIPv4())\n self.assertIsNone(helpers.no_op())","def test_get_source_ip(self):\n pass","def __init__(__self__, *,\n idle_timeout_in_minutes: pulumi.Input[int],\n location: pulumi.Input[str],\n public_ip_address_version: pulumi.Input[str],\n public_ip_allocation_method: pulumi.Input[str],\n resource_group: pulumi.Input[str],\n sku_name: pulumi.Input[str],\n ip_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\n pulumi.set(__self__, \"idle_timeout_in_minutes\", idle_timeout_in_minutes)\n pulumi.set(__self__, \"location\", location)\n pulumi.set(__self__, \"public_ip_address_version\", public_ip_address_version)\n pulumi.set(__self__, \"public_ip_allocation_method\", public_ip_allocation_method)\n pulumi.set(__self__, \"resource_group\", resource_group)\n pulumi.set(__self__, \"sku_name\", sku_name)\n if ip_tags is not None:\n pulumi.set(__self__, \"ip_tags\", ip_tags)","def test_constructor_fill_fields(self):\r\n builder = IndicatorBuilder(\"url\")\r\n\r\n self.assertEqual(builder.url, \"url\")\r\n self.assertEqual(builder.data, {})","def __init__(__self__,\n resource_name: str,\n opts: Optional[pulumi.ResourceOptions] = None,\n destination_pool_name: Optional[pulumi.Input[str]] = None,\n ip: Optional[pulumi.Input[str]] = None,\n __props__=None):\n ...","def test_hostport_or_network(self):\n # If providing host or port, must provide both\n with self.assertRaises(AssertionError):\n a = LedgerApi(host='host')\n with self.assertRaises(AssertionError):\n a = LedgerApi(port=1234)\n # If providing network, may not provide host or port\n with self.assertRaises(AssertionError):\n a = LedgerApi(host='host', network='alpha')\n with self.assertRaises(AssertionError):\n a = LedgerApi(port=1234, network='alpha')\n with self.assertRaises(AssertionError):\n a = LedgerApi(host='host', port=1234, network='alpha')","def __init__(\n self,\n host: str,\n database: str,\n user: str,\n password: str\n ) -> None:\n self.host: str = host\n self.database: str = database\n self.user: str = user\n self.password: str = password\n\n # all these values are needed\n for attr in ('host', 'database', 'user', 'password'):\n if not getattr(self, attr):\n raise ValueError(f\"{attr} must not be None!\")","def __init__(__self__, *,\n location: pulumi.Input[str],\n public_ip_address_name: pulumi.Input[str],\n resource_group: pulumi.Input[str],\n subnet_name: pulumi.Input[str],\n vnet_name: pulumi.Input[str]):\n pulumi.set(__self__, \"location\", location)\n pulumi.set(__self__, \"public_ip_address_name\", public_ip_address_name)\n pulumi.set(__self__, \"resource_group\", resource_group)\n pulumi.set(__self__, \"subnet_name\", subnet_name)\n pulumi.set(__self__, \"vnet_name\", vnet_name)","def test_exclude_ip_ban(self):\n pass","def test_basemodel_basic_instance_none(self):\n with self.assertRaises(TypeError):\n BaseModel(None)","def __init__(self, ip):\r\n\t\tself.ip = str(ip)\r\n\t\tself.ice = IceParser(self.ip)\r\n\t\tself.versions_list = []\r\n\t\tself.alarm_list = []\r\n\t\tself.status_list = []","def test_required_city_missing(self):\r\n self.url_params['city'] = ''\r\n response = self.client.post(self.url, self.url_params)\r\n self.assertEqual(response.status_code, 400)\r\n obj = json.loads(response.content)\r\n self.assertEqual(\r\n obj['value'],\r\n u'A city is required',\r\n )","def __init__(__self__, *,\n endpoint_id: pulumi.Input[str],\n client_ip_preservation_enabled: Optional[pulumi.Input[bool]] = None,\n weight: Optional[pulumi.Input[int]] = None):\n pulumi.set(__self__, \"endpoint_id\", endpoint_id)\n if client_ip_preservation_enabled is not None:\n pulumi.set(__self__, \"client_ip_preservation_enabled\", client_ip_preservation_enabled)\n if weight is not None:\n pulumi.set(__self__, \"weight\", weight)","def __init__(__self__, *,\n http_proxy: Optional[pulumi.Input[str]] = None,\n https_proxy: Optional[pulumi.Input[str]] = None,\n no_proxy: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n trusted_ca: Optional[pulumi.Input[str]] = None):\n if http_proxy is not None:\n pulumi.set(__self__, \"http_proxy\", http_proxy)\n if https_proxy is not None:\n pulumi.set(__self__, \"https_proxy\", https_proxy)\n if no_proxy is not None:\n pulumi.set(__self__, \"no_proxy\", no_proxy)\n if trusted_ca is not None:\n pulumi.set(__self__, \"trusted_ca\", trusted_ca)","def test_init(self):\n with self.assertRaises(ValueError):\n TraxionPay(api_key=self.api_key)","def __init__(__self__, *,\n group_id: pulumi.Input[str],\n ip_protocol: pulumi.Input[str],\n cidr_ip: Optional[pulumi.Input[str]] = None,\n cidr_ipv6: Optional[pulumi.Input[str]] = None,\n description: Optional[pulumi.Input[str]] = None,\n destination_prefix_list_id: Optional[pulumi.Input[str]] = None,\n destination_security_group_id: Optional[pulumi.Input[str]] = None,\n from_port: Optional[pulumi.Input[int]] = None,\n to_port: Optional[pulumi.Input[int]] = None):\n pulumi.set(__self__, \"group_id\", group_id)\n pulumi.set(__self__, \"ip_protocol\", ip_protocol)\n if cidr_ip is not None:\n pulumi.set(__self__, \"cidr_ip\", cidr_ip)\n if cidr_ipv6 is not None:\n pulumi.set(__self__, \"cidr_ipv6\", cidr_ipv6)\n if description is not None:\n pulumi.set(__self__, \"description\", description)\n if destination_prefix_list_id is not None:\n pulumi.set(__self__, \"destination_prefix_list_id\", destination_prefix_list_id)\n if destination_security_group_id is not None:\n pulumi.set(__self__, \"destination_security_group_id\", destination_security_group_id)\n if from_port is not None:\n pulumi.set(__self__, \"from_port\", from_port)\n if to_port is not None:\n pulumi.set(__self__, \"to_port\", to_port)","def __init__(__self__,\n resource_name: str,\n opts: Optional[pulumi.ResourceOptions] = None,\n droplet_id: Optional[pulumi.Input[int]] = None,\n ip_address: Optional[pulumi.Input[str]] = None,\n region: Optional[pulumi.Input[str]] = None,\n __props__=None):\n ...","def test_allow_none():\n value = None\n num_a = param.Integer(value=value, allow_None=True)\n assert num_a.value == value","def test_init_attributes(self):\n t = self.Test({'id': 1, 'poop': 'abc'})\n\n self.assertEqual(t.id, 1)\n self.assertEqual(t.name, None)\n self.assertRaises(AttributeError, t.__getattribute__, 'poop')","def test_default_country_by_ip_no_settings(self):\n\n response = self.client.get(\n reverse(\"billing_info\"), HTTP_X_FORWARDED_FOR=\"85.214.132.117\"\n )\n self.assertEqual(response.status_code, 200)\n self.assertContains(\n response, '<option value=\"\" selected>---------</option>', html=True\n )","def test_State_none_kwargs(self):\n with self.assertRaises(TypeError):\n State(id=None, created_at=None, updated_at=None)","def __init__(self, IP=None, Port=None):\n\n self.validate_input(IP, Port)\n self.url = ('http://{}:{}/v2/'.format(self.IP, self.Port))\n self.get_templates()\n self.get_data()\n self.telnet_threads = []","def test_init_no_mac(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n with self.assertRaises(ValueError):\n ap = APInfo(port_id=1, ip=\"2.2.2.2\", mac=None, radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)","def test_basemodel_none_kwargs(self):\n with self.assertRaises(TypeError):\n BaseModel(id=None, created_at=None, updated_at=None)","def __init__(self,address = None):\n\t\t# I really should do some validation around here\n\t\n\t\tif address != None:\n\t\t\tself.connect(address)","def test_invalid_ip_address_as_argument(self, api_client):\n runner = CliRunner()\n\n expected = 'Error: Invalid value for \"[IP_ADDRESS]...\": not-an-ip\\n'\n\n result = runner.invoke(subcommand.quick, [\"not-an-ip\"])\n assert result.exit_code == 2\n assert expected in result.output\n api_client.quick.assert_not_called()","def is_valid_ip(ip):\n ...","def __init__(__self__, *,\n ip_address: str,\n time_to_retire: str,\n type: str):\n pulumi.set(__self__, \"ip_address\", ip_address)\n pulumi.set(__self__, \"time_to_retire\", time_to_retire)\n pulumi.set(__self__, \"type\", type)","def __init__(self, *args, **kwargs):\n super(IPDetector, self).__init__()\n\n self.opts_family = kwargs.get(\"family\")\n # ensure address family is understood:\n af_ok = {None: AF_UNSPEC, \"INET\": AF_INET, \"INET6\": AF_INET6,\n AF_UNSPEC: AF_UNSPEC, AF_INET: AF_INET, AF_INET6: AF_INET6}\n if self.opts_family not in af_ok:\n raise ValueError(\"IPDetector(): Unsupported address family '%s' specified, please use one of %r\" %\n (self.opts_family, af_ok.keys()))\n else:\n self.opts_family = af_ok[self.opts_family]","def validate_ip(ip):\n try:\n ipobj = IPy.IP(ip)\n if ipobj.iptype() == 'PRIVATE':\n print(\"IP addresses {} will be ignored as it is in a private network range.\".format(ip))\n ip = None\n except ValueError as ve:\n print(\"Invalid IP: {}\".format(ve.args))\n ip = None\n finally:\n return ip","def __init__(__self__, *,\n acl_id: pulumi.Input[str],\n dest_cidr: pulumi.Input[str],\n dest_port_range: pulumi.Input[str],\n direction: pulumi.Input[str],\n ip_protocol: pulumi.Input[str],\n policy: pulumi.Input[str],\n source_cidr: pulumi.Input[str],\n source_port_range: pulumi.Input[str],\n description: Optional[pulumi.Input[str]] = None,\n priority: Optional[pulumi.Input[int]] = None):\n pulumi.set(__self__, \"acl_id\", acl_id)\n pulumi.set(__self__, \"dest_cidr\", dest_cidr)\n pulumi.set(__self__, \"dest_port_range\", dest_port_range)\n pulumi.set(__self__, \"direction\", direction)\n pulumi.set(__self__, \"ip_protocol\", ip_protocol)\n pulumi.set(__self__, \"policy\", policy)\n pulumi.set(__self__, \"source_cidr\", source_cidr)\n pulumi.set(__self__, \"source_port_range\", source_port_range)\n if description is not None:\n pulumi.set(__self__, \"description\", description)\n if priority is not None:\n pulumi.set(__self__, \"priority\", priority)","def __init__(self, uuid, secret, url_base, sha=\"SHA512\") -> None:\n self.uuid = uuid\n self.secret = secret\n self.url_base = url_base\n self.sha = sha\n self.ip = requests.get(\"https://jsonip.com\").json()[\"ip\"]\n self.fake = Faker()\n \"\"\"str: current ip from which Remindo is accessed.\n It needs to be authorized.\n \"\"\"","def test_empty(self):\n self.assertFalse(isIPv6Address(\"\"))","def test_init_kwarg(self):\n b1 = BaseModel(name=\"Red\")\n self.assertEqual(type(b1).__name__, \"BaseModel\")\n self.assertTrue(hasattr(b1, \"name\"))\n self.assertTrue(hasattr(b1, \"__class__\"))\n self.assertFalse(hasattr(b1, \"id\"))\n self.assertFalse(hasattr(b1, \"created_at\"))\n self.assertFalse(hasattr(b1, \"updated_at\"))","def __init__(self):\n self._zipcode = None\n self._city = None","def __init__(__self__,\n resource_name: str,\n opts: Optional[pulumi.ResourceOptions] = None,\n cidr: Optional[pulumi.Input[str]] = None,\n description: Optional[pulumi.Input[str]] = None,\n publish_cidr_route: Optional[pulumi.Input[bool]] = None,\n transit_router_cidr_name: Optional[pulumi.Input[str]] = None,\n transit_router_id: Optional[pulumi.Input[str]] = None,\n __props__=None):\n ...","def __init__(__self__, *,\n arp: Optional[pulumi.Input[bool]] = None,\n control_node_id: Optional[pulumi.Input[str]] = None,\n display_name: Optional[pulumi.Input[str]] = None,\n honeypot_bind_lists: Optional[pulumi.Input[Sequence[pulumi.Input['HoneypotProbeHoneypotBindListArgs']]]] = None,\n honeypot_probe_id: Optional[pulumi.Input[str]] = None,\n ping: Optional[pulumi.Input[bool]] = None,\n probe_type: Optional[pulumi.Input[str]] = None,\n probe_version: Optional[pulumi.Input[str]] = None,\n proxy_ip: Optional[pulumi.Input[str]] = None,\n service_ip_lists: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n status: Optional[pulumi.Input[str]] = None,\n uuid: Optional[pulumi.Input[str]] = None,\n vpc_id: Optional[pulumi.Input[str]] = None):\n if arp is not None:\n pulumi.set(__self__, \"arp\", arp)\n if control_node_id is not None:\n pulumi.set(__self__, \"control_node_id\", control_node_id)\n if display_name is not None:\n pulumi.set(__self__, \"display_name\", display_name)\n if honeypot_bind_lists is not None:\n pulumi.set(__self__, \"honeypot_bind_lists\", honeypot_bind_lists)\n if honeypot_probe_id is not None:\n pulumi.set(__self__, \"honeypot_probe_id\", honeypot_probe_id)\n if ping is not None:\n pulumi.set(__self__, \"ping\", ping)\n if probe_type is not None:\n pulumi.set(__self__, \"probe_type\", probe_type)\n if probe_version is not None:\n pulumi.set(__self__, \"probe_version\", probe_version)\n if proxy_ip is not None:\n pulumi.set(__self__, \"proxy_ip\", proxy_ip)\n if service_ip_lists is not None:\n pulumi.set(__self__, \"service_ip_lists\", service_ip_lists)\n if status is not None:\n pulumi.set(__self__, \"status\", status)\n if uuid is not None:\n pulumi.set(__self__, \"uuid\", uuid)\n if vpc_id is not None:\n pulumi.set(__self__, \"vpc_id\", vpc_id)","def __init__(__self__, *,\n address_family: pulumi.Input[str],\n ipam_scope_id: pulumi.Input[str],\n allocation_default_netmask_length: Optional[pulumi.Input[int]] = None,\n allocation_max_netmask_length: Optional[pulumi.Input[int]] = None,\n allocation_min_netmask_length: Optional[pulumi.Input[int]] = None,\n allocation_resource_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n auto_import: Optional[pulumi.Input[bool]] = None,\n aws_service: Optional[pulumi.Input[str]] = None,\n description: Optional[pulumi.Input[str]] = None,\n locale: Optional[pulumi.Input[str]] = None,\n public_ip_source: Optional[pulumi.Input[str]] = None,\n publicly_advertisable: Optional[pulumi.Input[bool]] = None,\n source_ipam_pool_id: Optional[pulumi.Input[str]] = None,\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\n pulumi.set(__self__, \"address_family\", address_family)\n pulumi.set(__self__, \"ipam_scope_id\", ipam_scope_id)\n if allocation_default_netmask_length is not None:\n pulumi.set(__self__, \"allocation_default_netmask_length\", allocation_default_netmask_length)\n if allocation_max_netmask_length is not None:\n pulumi.set(__self__, \"allocation_max_netmask_length\", allocation_max_netmask_length)\n if allocation_min_netmask_length is not None:\n pulumi.set(__self__, \"allocation_min_netmask_length\", allocation_min_netmask_length)\n if allocation_resource_tags is not None:\n pulumi.set(__self__, \"allocation_resource_tags\", allocation_resource_tags)\n if auto_import is not None:\n pulumi.set(__self__, \"auto_import\", auto_import)\n if aws_service is not None:\n pulumi.set(__self__, \"aws_service\", aws_service)\n if description is not None:\n pulumi.set(__self__, \"description\", description)\n if locale is not None:\n pulumi.set(__self__, \"locale\", locale)\n if public_ip_source is not None:\n pulumi.set(__self__, \"public_ip_source\", public_ip_source)\n if publicly_advertisable is not None:\n pulumi.set(__self__, \"publicly_advertisable\", publicly_advertisable)\n if source_ipam_pool_id is not None:\n pulumi.set(__self__, \"source_ipam_pool_id\", source_ipam_pool_id)\n if tags is not None:\n pulumi.set(__self__, \"tags\", tags)","def __init__(__self__, *,\n control_node_id: pulumi.Input[str],\n display_name: pulumi.Input[str],\n probe_type: pulumi.Input[str],\n arp: Optional[pulumi.Input[bool]] = None,\n honeypot_bind_lists: Optional[pulumi.Input[Sequence[pulumi.Input['HoneypotProbeHoneypotBindListArgs']]]] = None,\n ping: Optional[pulumi.Input[bool]] = None,\n probe_version: Optional[pulumi.Input[str]] = None,\n proxy_ip: Optional[pulumi.Input[str]] = None,\n service_ip_lists: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n uuid: Optional[pulumi.Input[str]] = None,\n vpc_id: Optional[pulumi.Input[str]] = None):\n pulumi.set(__self__, \"control_node_id\", control_node_id)\n pulumi.set(__self__, \"display_name\", display_name)\n pulumi.set(__self__, \"probe_type\", probe_type)\n if arp is not None:\n pulumi.set(__self__, \"arp\", arp)\n if honeypot_bind_lists is not None:\n pulumi.set(__self__, \"honeypot_bind_lists\", honeypot_bind_lists)\n if ping is not None:\n pulumi.set(__self__, \"ping\", ping)\n if probe_version is not None:\n pulumi.set(__self__, \"probe_version\", probe_version)\n if proxy_ip is not None:\n pulumi.set(__self__, \"proxy_ip\", proxy_ip)\n if service_ip_lists is not None:\n pulumi.set(__self__, \"service_ip_lists\", service_ip_lists)\n if uuid is not None:\n pulumi.set(__self__, \"uuid\", uuid)\n if vpc_id is not None:\n pulumi.set(__self__, \"vpc_id\", vpc_id)","def test_no_ip_address_passed(self, api_client):\n runner = CliRunner()\n\n with patch(\"greynoise.cli.helper.sys\") as sys:\n sys.stdin.isatty.return_value = True\n result = runner.invoke(\n subcommand.quick, parent=Context(main, info_name=\"greynoise\")\n )\n assert result.exit_code == -1\n assert \"Usage: greynoise quick\" in result.output\n api_client.quick.assert_not_called()","def __init__(__self__, *,\n acl_id: Optional[pulumi.Input[str]] = None,\n description: Optional[pulumi.Input[str]] = None,\n dest_cidr: Optional[pulumi.Input[str]] = None,\n dest_port_range: Optional[pulumi.Input[str]] = None,\n direction: Optional[pulumi.Input[str]] = None,\n ip_protocol: Optional[pulumi.Input[str]] = None,\n policy: Optional[pulumi.Input[str]] = None,\n priority: Optional[pulumi.Input[int]] = None,\n source_cidr: Optional[pulumi.Input[str]] = None,\n source_port_range: Optional[pulumi.Input[str]] = None):\n if acl_id is not None:\n pulumi.set(__self__, \"acl_id\", acl_id)\n if description is not None:\n pulumi.set(__self__, \"description\", description)\n if dest_cidr is not None:\n pulumi.set(__self__, \"dest_cidr\", dest_cidr)\n if dest_port_range is not None:\n pulumi.set(__self__, \"dest_port_range\", dest_port_range)\n if direction is not None:\n pulumi.set(__self__, \"direction\", direction)\n if ip_protocol is not None:\n pulumi.set(__self__, \"ip_protocol\", ip_protocol)\n if policy is not None:\n pulumi.set(__self__, \"policy\", policy)\n if priority is not None:\n pulumi.set(__self__, \"priority\", priority)\n if source_cidr is not None:\n pulumi.set(__self__, \"source_cidr\", source_cidr)\n if source_port_range is not None:\n pulumi.set(__self__, \"source_port_range\", source_port_range)","def test_invalid_ip_address_as_argument(self, api_client):\n runner = CliRunner()\n\n expected = 'Error: Invalid value for \"[IP_ADDRESS]...\": not-an-ip\\n'\n\n result = runner.invoke(subcommand.ip, [\"not-an-ip\"])\n assert result.exit_code == 2\n assert expected in result.output\n api_client.ip.assert_not_called()","def __init__(__self__, *,\n activation_key: Optional[pulumi.Input[str]] = None,\n ip_address: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None,\n private_link_endpoint: Optional[pulumi.Input[str]] = None,\n security_group_arns: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n subnet_arns: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n vpc_endpoint_id: Optional[pulumi.Input[str]] = None):\n if activation_key is not None:\n pulumi.set(__self__, \"activation_key\", activation_key)\n if ip_address is not None:\n pulumi.set(__self__, \"ip_address\", ip_address)\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if private_link_endpoint is not None:\n pulumi.set(__self__, \"private_link_endpoint\", private_link_endpoint)\n if security_group_arns is not None:\n pulumi.set(__self__, \"security_group_arns\", security_group_arns)\n if subnet_arns is not None:\n pulumi.set(__self__, \"subnet_arns\", subnet_arns)\n if tags is not None:\n pulumi.set(__self__, \"tags\", tags)\n if vpc_endpoint_id is not None:\n pulumi.set(__self__, \"vpc_endpoint_id\", vpc_endpoint_id)","def test_ip(response):\n \n # from comeon_core import update\n ip = getIP()\n print(ip)\n #init_db(engine)\n #update()\n assert True","def test_accepts_init_with_strict_subset_of_args(self):\n\n class API(platform.PlatformAPI):\n def __init__(self, base_url):\n pass\n\n api = API(\"some-url\")\n assert isinstance(api, platform.PlatformAPI)","def __init__(__self__, *,\n dry_run: Optional[pulumi.Input[bool]] = None,\n load_balancer_id: Optional[pulumi.Input[str]] = None,\n security_group_id: Optional[pulumi.Input[str]] = None):\n if dry_run is not None:\n pulumi.set(__self__, \"dry_run\", dry_run)\n if load_balancer_id is not None:\n pulumi.set(__self__, \"load_balancer_id\", load_balancer_id)\n if security_group_id is not None:\n pulumi.set(__self__, \"security_group_id\", security_group_id)","def __init__(__self__, *,\n resource_group: pulumi.Input[str],\n server: pulumi.Input[str],\n subnet_name: pulumi.Input[str],\n v_net_name: pulumi.Input[str],\n v_net_resource_group: pulumi.Input[str],\n ignore_missing_service_endpoint: Optional[pulumi.Input[bool]] = None):\n pulumi.set(__self__, \"resource_group\", resource_group)\n pulumi.set(__self__, \"server\", server)\n pulumi.set(__self__, \"subnet_name\", subnet_name)\n pulumi.set(__self__, \"v_net_name\", v_net_name)\n pulumi.set(__self__, \"v_net_resource_group\", v_net_resource_group)\n if ignore_missing_service_endpoint is not None:\n pulumi.set(__self__, \"ignore_missing_service_endpoint\", ignore_missing_service_endpoint)","def __init__(__self__, *,\n resource_group: pulumi.Input[str],\n server: pulumi.Input[str],\n subnet_name: pulumi.Input[str],\n v_net_name: pulumi.Input[str],\n v_net_resource_group: pulumi.Input[str],\n ignore_missing_service_endpoint: Optional[pulumi.Input[bool]] = None):\n pulumi.set(__self__, \"resource_group\", resource_group)\n pulumi.set(__self__, \"server\", server)\n pulumi.set(__self__, \"subnet_name\", subnet_name)\n pulumi.set(__self__, \"v_net_name\", v_net_name)\n pulumi.set(__self__, \"v_net_resource_group\", v_net_resource_group)\n if ignore_missing_service_endpoint is not None:\n pulumi.set(__self__, \"ignore_missing_service_endpoint\", ignore_missing_service_endpoint)","def __init__(self):\n # assert(self.validate('61882613000194'))\n # assert(self.validate('061882613000190'))\n # assert(not self.validate('61882613000195'))\n pass","def __init__(__self__, *,\n end_ip_address: pulumi.Input[str],\n resource_group: pulumi.Input[str],\n server: pulumi.Input[str],\n start_ip_address: pulumi.Input[str]):\n pulumi.set(__self__, \"end_ip_address\", end_ip_address)\n pulumi.set(__self__, \"resource_group\", resource_group)\n pulumi.set(__self__, \"server\", server)\n pulumi.set(__self__, \"start_ip_address\", start_ip_address)"],"string":"[\n \"def test_init_no_ip(self):\\n client = ClientInfo(\\\"cc:cc:cc:cc:cc:cc\\\", ip=None, ap_info=self.ap)\\n self.assertEqual(client.ip, None)\\n self.assertEqual(client.ip_bytes, None)\",\n \"def __init__(__self__, *,\\n ip: Optional[pulumi.Input['IPAccessControlArgs']] = None):\\n if ip is not None:\\n pulumi.set(__self__, \\\"ip\\\", ip)\",\n \"def __init__(__self__, *,\\n ip: Optional[pulumi.Input['IPAccessControlArgs']] = None):\\n if ip is not None:\\n pulumi.set(__self__, \\\"ip\\\", ip)\",\n \"def __init__(self) -> None:\\n self.ip_address: str | None = None\",\n \"def __init__(__self__, *,\\n host_ip: Optional[pulumi.Input[str]] = None,\\n port: Optional[pulumi.Input[str]] = None):\\n if host_ip is not None:\\n pulumi.set(__self__, \\\"host_ip\\\", host_ip)\\n if port is not None:\\n pulumi.set(__self__, \\\"port\\\", port)\",\n \"def __init__(\\n self, name: str = \\\"\\\", protocol: int | None = None, **kwargs: Any\\n ) -> None:\\n\\n super().__init__(name=name, **kwargs)\\n if not ipaddress:\\n raise SoftDependencyError(\\\"ipaddress\\\")\\n if protocol not in [None, 4, 6]:\\n raise ValueError(\\\"IpAddress protocol needs to be either 4, 6 or None\\\")\\n self.protocol = protocol\",\n \"def __init__(\\n self, name: str = \\\"\\\", protocol: int | None = None, **kwargs: Any\\n ) -> None:\\n\\n super().__init__(name=name, **kwargs)\\n\\n if protocol not in [None, 4, 6]:\\n raise ValueError(\\\"IpAddress protocol needs to be either 4, 6 or None\\\")\\n self.protocol = protocol\",\n \"def test_validate_ip_ok():\\n ip = '1.1.1.1'\\n assert howisresolved.validate_ip(ip) is None\",\n \"def test_field_none_nullable(self):\\n node_dict = {\\n 'host_name': 'abc'\\n }\\n try:\\n Node(**node_dict)\\n except Exception as e:\\n self.assertEqual(type(e), ValueError)\",\n \"def __init__(__self__, *,\\n ip_tag_type: Optional[pulumi.Input[str]] = None,\\n tag: Optional[pulumi.Input[str]] = None):\\n if ip_tag_type is not None:\\n pulumi.set(__self__, \\\"ip_tag_type\\\", ip_tag_type)\\n if tag is not None:\\n pulumi.set(__self__, \\\"tag\\\", tag)\",\n \"def __init__(self, allow_none=False):\\n if allow_none:\\n self.validate = self.validate_none\\n self.info = self.info_none\\n self.fast_validate = (2, None)\\n else:\\n self.fast_validate = (2,)\",\n \"def __init__(__self__, *,\\n destination_pool_name: Optional[pulumi.Input[str]] = None,\\n ip: Optional[pulumi.Input[str]] = None):\\n if destination_pool_name is not None:\\n pulumi.set(__self__, \\\"destination_pool_name\\\", destination_pool_name)\\n if ip is not None:\\n pulumi.set(__self__, \\\"ip\\\", ip)\",\n \"def test_init_no_mac(self):\\n with self.assertRaises(ValueError):\\n client = ClientInfo(None, ip=\\\"3.3.3.3\\\", ap_info=self.ap)\",\n \"def __init__(self, ip, mask):\\n self.vip = ip\\n self.mask = mask\",\n \"def __init__(__self__, *,\\n end_ip: pulumi.Input[str],\\n start_ip: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"end_ip\\\", end_ip)\\n pulumi.set(__self__, \\\"start_ip\\\", start_ip)\",\n \"def __init__(__self__, *,\\n host: Optional[pulumi.Input[str]] = None,\\n port: Optional[pulumi.Input[int]] = None):\\n if host is not None:\\n pulumi.set(__self__, \\\"host\\\", host)\\n if port is not None:\\n pulumi.set(__self__, \\\"port\\\", port)\",\n \"def __init__(self, ip: str):\\n self.api = API(f\\\"http://{ip}\\\")\\n self.ip = ip\\n self.board_data = None\",\n \"def test_no_ip_address_passed(self, api_client):\\n runner = CliRunner()\\n\\n with patch(\\\"greynoise.cli.helper.sys\\\") as sys:\\n sys.stdin.isatty.return_value = True\\n result = runner.invoke(\\n subcommand.ip, parent=Context(main, info_name=\\\"greynoise\\\")\\n )\\n assert result.exit_code == -1\\n assert \\\"Usage: greynoise ip\\\" in result.output\\n api_client.ip.assert_not_called()\",\n \"def __init__(__self__, *,\\n ignore_missing_v_net_service_endpoint: Optional[pulumi.Input[bool]] = None,\\n subnet_id: Optional[pulumi.Input[str]] = None):\\n if ignore_missing_v_net_service_endpoint is not None:\\n pulumi.set(__self__, \\\"ignore_missing_v_net_service_endpoint\\\", ignore_missing_v_net_service_endpoint)\\n if subnet_id is not None:\\n pulumi.set(__self__, \\\"subnet_id\\\", subnet_id)\",\n \"def test_optional_arg(self):\\n obj = Base()\\n self.assertEqual(obj.id, 1)\",\n \"def __init__(__self__, *,\\n droplet_id: Optional[pulumi.Input[int]] = None,\\n ip_address: Optional[pulumi.Input[str]] = None,\\n region: Optional[pulumi.Input[str]] = None,\\n urn: Optional[pulumi.Input[str]] = None):\\n if droplet_id is not None:\\n pulumi.set(__self__, \\\"droplet_id\\\", droplet_id)\\n if ip_address is not None:\\n pulumi.set(__self__, \\\"ip_address\\\", ip_address)\\n if region is not None:\\n pulumi.set(__self__, \\\"region\\\", region)\\n if urn is not None:\\n pulumi.set(__self__, \\\"urn\\\", urn)\",\n \"def __init__(__self__, *,\\n allow: Optional[pulumi.Input[Sequence[pulumi.Input['IPRangeArgs']]]] = None):\\n if allow is not None:\\n pulumi.set(__self__, \\\"allow\\\", allow)\",\n \"def __init__(__self__, *,\\n region: pulumi.Input[str],\\n droplet_id: Optional[pulumi.Input[int]] = None,\\n ip_address: Optional[pulumi.Input[str]] = None):\\n pulumi.set(__self__, \\\"region\\\", region)\\n if droplet_id is not None:\\n pulumi.set(__self__, \\\"droplet_id\\\", droplet_id)\\n if ip_address is not None:\\n pulumi.set(__self__, \\\"ip_address\\\", ip_address)\",\n \"def __init__(self):\\n self.clean_optional()\",\n \"def __init__(__self__, *,\\n resourcegroup: pulumi.Input[str],\\n server: pulumi.Input[str],\\n endipaddress: Optional[pulumi.Input[str]] = None,\\n startipaddress: Optional[pulumi.Input[str]] = None):\\n pulumi.set(__self__, \\\"resourcegroup\\\", resourcegroup)\\n pulumi.set(__self__, \\\"server\\\", server)\\n if endipaddress is not None:\\n pulumi.set(__self__, \\\"endipaddress\\\", endipaddress)\\n if startipaddress is not None:\\n pulumi.set(__self__, \\\"startipaddress\\\", startipaddress)\",\n \"def __init__(self, ip=None, header=None, hostname=None, aliases=None):\\n self.id = header or \\\"\\\"\\n self.hostname = hostname or \\\"\\\"\\n self.aliases = aliases or []\\n self.ip = \\\"\\\"\\n if ip:\\n try:\\n self.ip=ipaddress.ip_address(ip)\\n except ipaddress.AddressValueError as e:\\n print(\\\"Error parsing ip address from hosts.conf file\\\")\\n raise e\\n self.stored_state = None\",\n \"def __init__(self, **kwargs):\\n self.swagger_types = {\\n 'assign_public_ip': 'bool',\\n 'defined_tags': 'dict(str, dict(str, object))',\\n 'display_name': 'str',\\n 'freeform_tags': 'dict(str, str)',\\n 'hostname_label': 'str',\\n 'nsg_ids': 'list[str]',\\n 'private_ip': 'str',\\n 'skip_source_dest_check': 'bool',\\n 'subnet_id': 'str'\\n }\\n\\n self.attribute_map = {\\n 'assign_public_ip': 'assignPublicIp',\\n 'defined_tags': 'definedTags',\\n 'display_name': 'displayName',\\n 'freeform_tags': 'freeformTags',\\n 'hostname_label': 'hostnameLabel',\\n 'nsg_ids': 'nsgIds',\\n 'private_ip': 'privateIp',\\n 'skip_source_dest_check': 'skipSourceDestCheck',\\n 'subnet_id': 'subnetId'\\n }\\n\\n self._assign_public_ip = None\\n self._defined_tags = None\\n self._display_name = None\\n self._freeform_tags = None\\n self._hostname_label = None\\n self._nsg_ids = None\\n self._private_ip = None\\n self._skip_source_dest_check = None\\n self._subnet_id = None\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: ReservedIpArgs,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\",\n \"def __init__(self, **kwargs):\\n members = ('ip', 'mac', 'port', 'timeout', 'flags',\\n 'index', 'tag', 'hostname')\\n\\n # copy the given value or default to None\\n for member in members:\\n self.__dict__[member] = kwargs.setdefault (member, None)\",\n \"def test_init_without_kwargs(self):\\n c = City()\\n self.assertTrue('id' in c.__dict__)\\n self.assertTrue('created_at' in c.__dict__)\\n self.assertTrue('updated_at' in c.__dict__)\\n self.assertIsInstance(c, BaseModel)\",\n \"def validate_ip(argname, param, safe, optional = False):\\n _validate_one(argname, param, safe, _check_ip, optional)\",\n \"def test_init_wrong_ap_type(self):\\n ap_wrong = object()\\n with self.assertRaises(ValueError):\\n client = ClientInfo(\\\"cc:cc:cc:cc:cc:cc\\\",\\n ip=\\\"3.3.3.3\\\", ap_info=ap_wrong)\",\n \"def __init__(__self__, *,\\n protocol: Optional[pulumi.Input[str]] = None,\\n url: Optional[pulumi.Input[str]] = None):\\n if protocol is not None:\\n pulumi.set(__self__, \\\"protocol\\\", protocol)\\n if url is not None:\\n pulumi.set(__self__, \\\"url\\\", url)\",\n \"def __init__(__self__, *,\\n public_ips: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceReferenceArgs']]]] = None):\\n if public_ips is not None:\\n pulumi.set(__self__, \\\"public_ips\\\", public_ips)\",\n \"def __init__(__self__, *,\\n cidr: pulumi.Input[str],\\n resource_group_name: pulumi.Input[str],\\n commissioning_enabled: Optional[pulumi.Input[bool]] = None,\\n internet_advertising_disabled: Optional[pulumi.Input[bool]] = None,\\n location: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None,\\n parent_custom_ip_prefix_id: Optional[pulumi.Input[str]] = None,\\n roa_validity_end_date: Optional[pulumi.Input[str]] = None,\\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n wan_validation_signed_message: Optional[pulumi.Input[str]] = None,\\n zones: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\\n pulumi.set(__self__, \\\"cidr\\\", cidr)\\n pulumi.set(__self__, \\\"resource_group_name\\\", resource_group_name)\\n if commissioning_enabled is not None:\\n pulumi.set(__self__, \\\"commissioning_enabled\\\", commissioning_enabled)\\n if internet_advertising_disabled is not None:\\n pulumi.set(__self__, \\\"internet_advertising_disabled\\\", internet_advertising_disabled)\\n if location is not None:\\n pulumi.set(__self__, \\\"location\\\", location)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if parent_custom_ip_prefix_id is not None:\\n pulumi.set(__self__, \\\"parent_custom_ip_prefix_id\\\", parent_custom_ip_prefix_id)\\n if roa_validity_end_date is not None:\\n pulumi.set(__self__, \\\"roa_validity_end_date\\\", roa_validity_end_date)\\n if tags is not None:\\n pulumi.set(__self__, \\\"tags\\\", tags)\\n if wan_validation_signed_message is not None:\\n pulumi.set(__self__, \\\"wan_validation_signed_message\\\", wan_validation_signed_message)\\n if zones is not None:\\n pulumi.set(__self__, \\\"zones\\\", zones)\",\n \"def test_control_create_with_empty_field(self, field):\\n request = self.prepare_control_request_body()\\n request[field] = None\\n\\n response = self.api.post(all_models.Control, data=request)\\n\\n self.assert400(response)\",\n \"def test_init_correct(self):\\n client = ClientInfo(\\\"cc:cc:cc:cc:cc:cc\\\", ip=\\\"3.3.3.3\\\", ap_info=self.ap)\\n self.assertEqual(client.ip, \\\"3.3.3.3\\\")\\n self.assertEqual(client.ip_bytes, b'\\\\x03\\\\x03\\\\x03\\\\x03')\",\n \"def __init__(__self__, *,\\n id: str,\\n private_ip_address: Optional[str] = None):\\n pulumi.set(__self__, \\\"id\\\", id)\\n if private_ip_address is not None:\\n pulumi.set(__self__, \\\"private_ip_address\\\", private_ip_address)\",\n \"def test_creation_notallow_none():\\n with pytest.raises(ValueError) as __:\\n value = None\\n __ = param.Integer(value=value, allow_None=False)\",\n \"def validate_ip(self, ip):\\n if not ip:\\n raise ValidationError(\\\"Please provide an actual IP or web address. You gave me: \\\" + ip)\",\n \"def __init__(__self__, *,\\n destination_pool_name: pulumi.Input[str],\\n ip: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"destination_pool_name\\\", destination_pool_name)\\n pulumi.set(__self__, \\\"ip\\\", ip)\",\n \"def test_field_nullable(self):\\n node_dict = {\\n 'host_name': 'abc',\\n 'local_router_id': '1.1.1.1',\\n 'as_num': 100,\\n 'bgpls_id': '0.0.0.0',\\n 'igp_id': '0.0.0.0'\\n }\\n node = Node(**node_dict)\\n for name, field in node_dict.items():\\n self.assertEqual(field, node.__dict__[name])\",\n \"def __init__(__self__, *,\\n cidr: Optional[pulumi.Input[str]] = None,\\n commissioning_enabled: Optional[pulumi.Input[bool]] = None,\\n internet_advertising_disabled: Optional[pulumi.Input[bool]] = None,\\n location: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None,\\n parent_custom_ip_prefix_id: Optional[pulumi.Input[str]] = None,\\n resource_group_name: Optional[pulumi.Input[str]] = None,\\n roa_validity_end_date: Optional[pulumi.Input[str]] = None,\\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n wan_validation_signed_message: Optional[pulumi.Input[str]] = None,\\n zones: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\\n if cidr is not None:\\n pulumi.set(__self__, \\\"cidr\\\", cidr)\\n if commissioning_enabled is not None:\\n pulumi.set(__self__, \\\"commissioning_enabled\\\", commissioning_enabled)\\n if internet_advertising_disabled is not None:\\n pulumi.set(__self__, \\\"internet_advertising_disabled\\\", internet_advertising_disabled)\\n if location is not None:\\n pulumi.set(__self__, \\\"location\\\", location)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if parent_custom_ip_prefix_id is not None:\\n pulumi.set(__self__, \\\"parent_custom_ip_prefix_id\\\", parent_custom_ip_prefix_id)\\n if resource_group_name is not None:\\n pulumi.set(__self__, \\\"resource_group_name\\\", resource_group_name)\\n if roa_validity_end_date is not None:\\n pulumi.set(__self__, \\\"roa_validity_end_date\\\", roa_validity_end_date)\\n if tags is not None:\\n pulumi.set(__self__, \\\"tags\\\", tags)\\n if wan_validation_signed_message is not None:\\n pulumi.set(__self__, \\\"wan_validation_signed_message\\\", wan_validation_signed_message)\\n if zones is not None:\\n pulumi.set(__self__, \\\"zones\\\", zones)\",\n \"def __init__(__self__, *,\\n allowed_host_ports: Optional[pulumi.Input[Sequence[pulumi.Input['PortRangeArgs']]]] = None,\\n application_security_groups: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n node_public_ip_tags: Optional[pulumi.Input[Sequence[pulumi.Input['IPTagArgs']]]] = None):\\n if allowed_host_ports is not None:\\n pulumi.set(__self__, \\\"allowed_host_ports\\\", allowed_host_ports)\\n if application_security_groups is not None:\\n pulumi.set(__self__, \\\"application_security_groups\\\", application_security_groups)\\n if node_public_ip_tags is not None:\\n pulumi.set(__self__, \\\"node_public_ip_tags\\\", node_public_ip_tags)\",\n \"def validate_input(self, IP, Port):\\n exception = ServerInitError\\n try:\\n if IP != None:\\n if re.match(IPRegex, IP):\\n self.IP = IP\\n else:\\n exception = InavlidIPError\\n raise\\n\\n if Port != None:\\n if int(Port) in range(0,65535):\\n self.Port = Port\\n else:\\n exception = InvalidPortError\\n raise\\n except:\\n traceback_print_exc()\",\n \"def __init__(__self__, *,\\n address: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None,\\n subnet_prefix_length: Optional[pulumi.Input[int]] = None):\\n if address is not None:\\n pulumi.set(__self__, \\\"address\\\", address)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if subnet_prefix_length is not None:\\n pulumi.set(__self__, \\\"subnet_prefix_length\\\", subnet_prefix_length)\",\n \"def test_same_ip(self):\\n self.create_ptr(\\n ip_str='128.193.0.2', ip_type='4', fqdn='foo1.oregonstate.edu')\\n\\n with self.assertRaises(ValidationError):\\n self.create_ptr(\\n ip_str='128.193.0.2', ip_type='4', fqdn='foo2.oregonstate.edu')\",\n \"def __init__(self,\\r\\n name=None,\\r\\n lan_ip=None,\\r\\n uplink=None,\\r\\n public_port=None,\\r\\n local_port=None,\\r\\n allowed_ips=None,\\r\\n protocol=None):\\r\\n\\r\\n # Initialize members of the class\\r\\n self.name = name\\r\\n self.lan_ip = lan_ip\\r\\n self.uplink = uplink\\r\\n self.public_port = public_port\\r\\n self.local_port = local_port\\r\\n self.allowed_ips = allowed_ips\\r\\n self.protocol = protocol\",\n \"def __init__(__self__, *,\\n dns_servers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n gateway: Optional[pulumi.Input[str]] = None,\\n infra_vnet_profile: Optional[pulumi.Input['VirtualNetworksPropertiesInfraVnetProfileArgs']] = None,\\n ip_address_prefix: Optional[pulumi.Input[str]] = None,\\n vip_pool: Optional[pulumi.Input[Sequence[pulumi.Input['VirtualNetworksPropertiesVipPoolArgs']]]] = None,\\n vmip_pool: Optional[pulumi.Input[Sequence[pulumi.Input['VirtualNetworksPropertiesVmipPoolArgs']]]] = None):\\n if dns_servers is not None:\\n pulumi.set(__self__, \\\"dns_servers\\\", dns_servers)\\n if gateway is not None:\\n pulumi.set(__self__, \\\"gateway\\\", gateway)\\n if infra_vnet_profile is not None:\\n pulumi.set(__self__, \\\"infra_vnet_profile\\\", infra_vnet_profile)\\n if ip_address_prefix is not None:\\n pulumi.set(__self__, \\\"ip_address_prefix\\\", ip_address_prefix)\\n if vip_pool is not None:\\n pulumi.set(__self__, \\\"vip_pool\\\", vip_pool)\\n if vmip_pool is not None:\\n pulumi.set(__self__, \\\"vmip_pool\\\", vmip_pool)\",\n \"def test_init_correct(self):\\n # mocks of files\\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\\n\\n ap = APInfo(port_id=1, ip=\\\"2.2.2.2\\\", mac=\\\"bb:bb:bb:bb:bb:bb\\\", radio_mac=\\\"bb:bb:bb:bb:bb:00\\\", udp_port=12345, wlc_ip='1.1.1.1',\\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\\n\\n self.assertEqual(ap.ip, '2.2.2.2')\",\n \"def test_noop(self):\\n self.assertFalse(helpers.getBcastAddrforIPv4())\\n self.assertIsNone(helpers.no_op())\",\n \"def test_get_source_ip(self):\\n pass\",\n \"def __init__(__self__, *,\\n idle_timeout_in_minutes: pulumi.Input[int],\\n location: pulumi.Input[str],\\n public_ip_address_version: pulumi.Input[str],\\n public_ip_allocation_method: pulumi.Input[str],\\n resource_group: pulumi.Input[str],\\n sku_name: pulumi.Input[str],\\n ip_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\\n pulumi.set(__self__, \\\"idle_timeout_in_minutes\\\", idle_timeout_in_minutes)\\n pulumi.set(__self__, \\\"location\\\", location)\\n pulumi.set(__self__, \\\"public_ip_address_version\\\", public_ip_address_version)\\n pulumi.set(__self__, \\\"public_ip_allocation_method\\\", public_ip_allocation_method)\\n pulumi.set(__self__, \\\"resource_group\\\", resource_group)\\n pulumi.set(__self__, \\\"sku_name\\\", sku_name)\\n if ip_tags is not None:\\n pulumi.set(__self__, \\\"ip_tags\\\", ip_tags)\",\n \"def test_constructor_fill_fields(self):\\r\\n builder = IndicatorBuilder(\\\"url\\\")\\r\\n\\r\\n self.assertEqual(builder.url, \\\"url\\\")\\r\\n self.assertEqual(builder.data, {})\",\n \"def __init__(__self__,\\n resource_name: str,\\n opts: Optional[pulumi.ResourceOptions] = None,\\n destination_pool_name: Optional[pulumi.Input[str]] = None,\\n ip: Optional[pulumi.Input[str]] = None,\\n __props__=None):\\n ...\",\n \"def test_hostport_or_network(self):\\n # If providing host or port, must provide both\\n with self.assertRaises(AssertionError):\\n a = LedgerApi(host='host')\\n with self.assertRaises(AssertionError):\\n a = LedgerApi(port=1234)\\n # If providing network, may not provide host or port\\n with self.assertRaises(AssertionError):\\n a = LedgerApi(host='host', network='alpha')\\n with self.assertRaises(AssertionError):\\n a = LedgerApi(port=1234, network='alpha')\\n with self.assertRaises(AssertionError):\\n a = LedgerApi(host='host', port=1234, network='alpha')\",\n \"def __init__(\\n self,\\n host: str,\\n database: str,\\n user: str,\\n password: str\\n ) -> None:\\n self.host: str = host\\n self.database: str = database\\n self.user: str = user\\n self.password: str = password\\n\\n # all these values are needed\\n for attr in ('host', 'database', 'user', 'password'):\\n if not getattr(self, attr):\\n raise ValueError(f\\\"{attr} must not be None!\\\")\",\n \"def __init__(__self__, *,\\n location: pulumi.Input[str],\\n public_ip_address_name: pulumi.Input[str],\\n resource_group: pulumi.Input[str],\\n subnet_name: pulumi.Input[str],\\n vnet_name: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"location\\\", location)\\n pulumi.set(__self__, \\\"public_ip_address_name\\\", public_ip_address_name)\\n pulumi.set(__self__, \\\"resource_group\\\", resource_group)\\n pulumi.set(__self__, \\\"subnet_name\\\", subnet_name)\\n pulumi.set(__self__, \\\"vnet_name\\\", vnet_name)\",\n \"def test_exclude_ip_ban(self):\\n pass\",\n \"def test_basemodel_basic_instance_none(self):\\n with self.assertRaises(TypeError):\\n BaseModel(None)\",\n \"def __init__(self, ip):\\r\\n\\t\\tself.ip = str(ip)\\r\\n\\t\\tself.ice = IceParser(self.ip)\\r\\n\\t\\tself.versions_list = []\\r\\n\\t\\tself.alarm_list = []\\r\\n\\t\\tself.status_list = []\",\n \"def test_required_city_missing(self):\\r\\n self.url_params['city'] = ''\\r\\n response = self.client.post(self.url, self.url_params)\\r\\n self.assertEqual(response.status_code, 400)\\r\\n obj = json.loads(response.content)\\r\\n self.assertEqual(\\r\\n obj['value'],\\r\\n u'A city is required',\\r\\n )\",\n \"def __init__(__self__, *,\\n endpoint_id: pulumi.Input[str],\\n client_ip_preservation_enabled: Optional[pulumi.Input[bool]] = None,\\n weight: Optional[pulumi.Input[int]] = None):\\n pulumi.set(__self__, \\\"endpoint_id\\\", endpoint_id)\\n if client_ip_preservation_enabled is not None:\\n pulumi.set(__self__, \\\"client_ip_preservation_enabled\\\", client_ip_preservation_enabled)\\n if weight is not None:\\n pulumi.set(__self__, \\\"weight\\\", weight)\",\n \"def __init__(__self__, *,\\n http_proxy: Optional[pulumi.Input[str]] = None,\\n https_proxy: Optional[pulumi.Input[str]] = None,\\n no_proxy: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n trusted_ca: Optional[pulumi.Input[str]] = None):\\n if http_proxy is not None:\\n pulumi.set(__self__, \\\"http_proxy\\\", http_proxy)\\n if https_proxy is not None:\\n pulumi.set(__self__, \\\"https_proxy\\\", https_proxy)\\n if no_proxy is not None:\\n pulumi.set(__self__, \\\"no_proxy\\\", no_proxy)\\n if trusted_ca is not None:\\n pulumi.set(__self__, \\\"trusted_ca\\\", trusted_ca)\",\n \"def test_init(self):\\n with self.assertRaises(ValueError):\\n TraxionPay(api_key=self.api_key)\",\n \"def __init__(__self__, *,\\n group_id: pulumi.Input[str],\\n ip_protocol: pulumi.Input[str],\\n cidr_ip: Optional[pulumi.Input[str]] = None,\\n cidr_ipv6: Optional[pulumi.Input[str]] = None,\\n description: Optional[pulumi.Input[str]] = None,\\n destination_prefix_list_id: Optional[pulumi.Input[str]] = None,\\n destination_security_group_id: Optional[pulumi.Input[str]] = None,\\n from_port: Optional[pulumi.Input[int]] = None,\\n to_port: Optional[pulumi.Input[int]] = None):\\n pulumi.set(__self__, \\\"group_id\\\", group_id)\\n pulumi.set(__self__, \\\"ip_protocol\\\", ip_protocol)\\n if cidr_ip is not None:\\n pulumi.set(__self__, \\\"cidr_ip\\\", cidr_ip)\\n if cidr_ipv6 is not None:\\n pulumi.set(__self__, \\\"cidr_ipv6\\\", cidr_ipv6)\\n if description is not None:\\n pulumi.set(__self__, \\\"description\\\", description)\\n if destination_prefix_list_id is not None:\\n pulumi.set(__self__, \\\"destination_prefix_list_id\\\", destination_prefix_list_id)\\n if destination_security_group_id is not None:\\n pulumi.set(__self__, \\\"destination_security_group_id\\\", destination_security_group_id)\\n if from_port is not None:\\n pulumi.set(__self__, \\\"from_port\\\", from_port)\\n if to_port is not None:\\n pulumi.set(__self__, \\\"to_port\\\", to_port)\",\n \"def __init__(__self__,\\n resource_name: str,\\n opts: Optional[pulumi.ResourceOptions] = None,\\n droplet_id: Optional[pulumi.Input[int]] = None,\\n ip_address: Optional[pulumi.Input[str]] = None,\\n region: Optional[pulumi.Input[str]] = None,\\n __props__=None):\\n ...\",\n \"def test_allow_none():\\n value = None\\n num_a = param.Integer(value=value, allow_None=True)\\n assert num_a.value == value\",\n \"def test_init_attributes(self):\\n t = self.Test({'id': 1, 'poop': 'abc'})\\n\\n self.assertEqual(t.id, 1)\\n self.assertEqual(t.name, None)\\n self.assertRaises(AttributeError, t.__getattribute__, 'poop')\",\n \"def test_default_country_by_ip_no_settings(self):\\n\\n response = self.client.get(\\n reverse(\\\"billing_info\\\"), HTTP_X_FORWARDED_FOR=\\\"85.214.132.117\\\"\\n )\\n self.assertEqual(response.status_code, 200)\\n self.assertContains(\\n response, '<option value=\\\"\\\" selected>---------</option>', html=True\\n )\",\n \"def test_State_none_kwargs(self):\\n with self.assertRaises(TypeError):\\n State(id=None, created_at=None, updated_at=None)\",\n \"def __init__(self, IP=None, Port=None):\\n\\n self.validate_input(IP, Port)\\n self.url = ('http://{}:{}/v2/'.format(self.IP, self.Port))\\n self.get_templates()\\n self.get_data()\\n self.telnet_threads = []\",\n \"def test_init_no_mac(self):\\n # mocks of files\\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\\n\\n with self.assertRaises(ValueError):\\n ap = APInfo(port_id=1, ip=\\\"2.2.2.2\\\", mac=None, radio_mac=\\\"bb:bb:bb:bb:bb:00\\\", udp_port=12345, wlc_ip='1.1.1.1',\\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\",\n \"def test_basemodel_none_kwargs(self):\\n with self.assertRaises(TypeError):\\n BaseModel(id=None, created_at=None, updated_at=None)\",\n \"def __init__(self,address = None):\\n\\t\\t# I really should do some validation around here\\n\\t\\n\\t\\tif address != None:\\n\\t\\t\\tself.connect(address)\",\n \"def test_invalid_ip_address_as_argument(self, api_client):\\n runner = CliRunner()\\n\\n expected = 'Error: Invalid value for \\\"[IP_ADDRESS]...\\\": not-an-ip\\\\n'\\n\\n result = runner.invoke(subcommand.quick, [\\\"not-an-ip\\\"])\\n assert result.exit_code == 2\\n assert expected in result.output\\n api_client.quick.assert_not_called()\",\n \"def is_valid_ip(ip):\\n ...\",\n \"def __init__(__self__, *,\\n ip_address: str,\\n time_to_retire: str,\\n type: str):\\n pulumi.set(__self__, \\\"ip_address\\\", ip_address)\\n pulumi.set(__self__, \\\"time_to_retire\\\", time_to_retire)\\n pulumi.set(__self__, \\\"type\\\", type)\",\n \"def __init__(self, *args, **kwargs):\\n super(IPDetector, self).__init__()\\n\\n self.opts_family = kwargs.get(\\\"family\\\")\\n # ensure address family is understood:\\n af_ok = {None: AF_UNSPEC, \\\"INET\\\": AF_INET, \\\"INET6\\\": AF_INET6,\\n AF_UNSPEC: AF_UNSPEC, AF_INET: AF_INET, AF_INET6: AF_INET6}\\n if self.opts_family not in af_ok:\\n raise ValueError(\\\"IPDetector(): Unsupported address family '%s' specified, please use one of %r\\\" %\\n (self.opts_family, af_ok.keys()))\\n else:\\n self.opts_family = af_ok[self.opts_family]\",\n \"def validate_ip(ip):\\n try:\\n ipobj = IPy.IP(ip)\\n if ipobj.iptype() == 'PRIVATE':\\n print(\\\"IP addresses {} will be ignored as it is in a private network range.\\\".format(ip))\\n ip = None\\n except ValueError as ve:\\n print(\\\"Invalid IP: {}\\\".format(ve.args))\\n ip = None\\n finally:\\n return ip\",\n \"def __init__(__self__, *,\\n acl_id: pulumi.Input[str],\\n dest_cidr: pulumi.Input[str],\\n dest_port_range: pulumi.Input[str],\\n direction: pulumi.Input[str],\\n ip_protocol: pulumi.Input[str],\\n policy: pulumi.Input[str],\\n source_cidr: pulumi.Input[str],\\n source_port_range: pulumi.Input[str],\\n description: Optional[pulumi.Input[str]] = None,\\n priority: Optional[pulumi.Input[int]] = None):\\n pulumi.set(__self__, \\\"acl_id\\\", acl_id)\\n pulumi.set(__self__, \\\"dest_cidr\\\", dest_cidr)\\n pulumi.set(__self__, \\\"dest_port_range\\\", dest_port_range)\\n pulumi.set(__self__, \\\"direction\\\", direction)\\n pulumi.set(__self__, \\\"ip_protocol\\\", ip_protocol)\\n pulumi.set(__self__, \\\"policy\\\", policy)\\n pulumi.set(__self__, \\\"source_cidr\\\", source_cidr)\\n pulumi.set(__self__, \\\"source_port_range\\\", source_port_range)\\n if description is not None:\\n pulumi.set(__self__, \\\"description\\\", description)\\n if priority is not None:\\n pulumi.set(__self__, \\\"priority\\\", priority)\",\n \"def __init__(self, uuid, secret, url_base, sha=\\\"SHA512\\\") -> None:\\n self.uuid = uuid\\n self.secret = secret\\n self.url_base = url_base\\n self.sha = sha\\n self.ip = requests.get(\\\"https://jsonip.com\\\").json()[\\\"ip\\\"]\\n self.fake = Faker()\\n \\\"\\\"\\\"str: current ip from which Remindo is accessed.\\n It needs to be authorized.\\n \\\"\\\"\\\"\",\n \"def test_empty(self):\\n self.assertFalse(isIPv6Address(\\\"\\\"))\",\n \"def test_init_kwarg(self):\\n b1 = BaseModel(name=\\\"Red\\\")\\n self.assertEqual(type(b1).__name__, \\\"BaseModel\\\")\\n self.assertTrue(hasattr(b1, \\\"name\\\"))\\n self.assertTrue(hasattr(b1, \\\"__class__\\\"))\\n self.assertFalse(hasattr(b1, \\\"id\\\"))\\n self.assertFalse(hasattr(b1, \\\"created_at\\\"))\\n self.assertFalse(hasattr(b1, \\\"updated_at\\\"))\",\n \"def __init__(self):\\n self._zipcode = None\\n self._city = None\",\n \"def __init__(__self__,\\n resource_name: str,\\n opts: Optional[pulumi.ResourceOptions] = None,\\n cidr: Optional[pulumi.Input[str]] = None,\\n description: Optional[pulumi.Input[str]] = None,\\n publish_cidr_route: Optional[pulumi.Input[bool]] = None,\\n transit_router_cidr_name: Optional[pulumi.Input[str]] = None,\\n transit_router_id: Optional[pulumi.Input[str]] = None,\\n __props__=None):\\n ...\",\n \"def __init__(__self__, *,\\n arp: Optional[pulumi.Input[bool]] = None,\\n control_node_id: Optional[pulumi.Input[str]] = None,\\n display_name: Optional[pulumi.Input[str]] = None,\\n honeypot_bind_lists: Optional[pulumi.Input[Sequence[pulumi.Input['HoneypotProbeHoneypotBindListArgs']]]] = None,\\n honeypot_probe_id: Optional[pulumi.Input[str]] = None,\\n ping: Optional[pulumi.Input[bool]] = None,\\n probe_type: Optional[pulumi.Input[str]] = None,\\n probe_version: Optional[pulumi.Input[str]] = None,\\n proxy_ip: Optional[pulumi.Input[str]] = None,\\n service_ip_lists: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n status: Optional[pulumi.Input[str]] = None,\\n uuid: Optional[pulumi.Input[str]] = None,\\n vpc_id: Optional[pulumi.Input[str]] = None):\\n if arp is not None:\\n pulumi.set(__self__, \\\"arp\\\", arp)\\n if control_node_id is not None:\\n pulumi.set(__self__, \\\"control_node_id\\\", control_node_id)\\n if display_name is not None:\\n pulumi.set(__self__, \\\"display_name\\\", display_name)\\n if honeypot_bind_lists is not None:\\n pulumi.set(__self__, \\\"honeypot_bind_lists\\\", honeypot_bind_lists)\\n if honeypot_probe_id is not None:\\n pulumi.set(__self__, \\\"honeypot_probe_id\\\", honeypot_probe_id)\\n if ping is not None:\\n pulumi.set(__self__, \\\"ping\\\", ping)\\n if probe_type is not None:\\n pulumi.set(__self__, \\\"probe_type\\\", probe_type)\\n if probe_version is not None:\\n pulumi.set(__self__, \\\"probe_version\\\", probe_version)\\n if proxy_ip is not None:\\n pulumi.set(__self__, \\\"proxy_ip\\\", proxy_ip)\\n if service_ip_lists is not None:\\n pulumi.set(__self__, \\\"service_ip_lists\\\", service_ip_lists)\\n if status is not None:\\n pulumi.set(__self__, \\\"status\\\", status)\\n if uuid is not None:\\n pulumi.set(__self__, \\\"uuid\\\", uuid)\\n if vpc_id is not None:\\n pulumi.set(__self__, \\\"vpc_id\\\", vpc_id)\",\n \"def __init__(__self__, *,\\n address_family: pulumi.Input[str],\\n ipam_scope_id: pulumi.Input[str],\\n allocation_default_netmask_length: Optional[pulumi.Input[int]] = None,\\n allocation_max_netmask_length: Optional[pulumi.Input[int]] = None,\\n allocation_min_netmask_length: Optional[pulumi.Input[int]] = None,\\n allocation_resource_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n auto_import: Optional[pulumi.Input[bool]] = None,\\n aws_service: Optional[pulumi.Input[str]] = None,\\n description: Optional[pulumi.Input[str]] = None,\\n locale: Optional[pulumi.Input[str]] = None,\\n public_ip_source: Optional[pulumi.Input[str]] = None,\\n publicly_advertisable: Optional[pulumi.Input[bool]] = None,\\n source_ipam_pool_id: Optional[pulumi.Input[str]] = None,\\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\\n pulumi.set(__self__, \\\"address_family\\\", address_family)\\n pulumi.set(__self__, \\\"ipam_scope_id\\\", ipam_scope_id)\\n if allocation_default_netmask_length is not None:\\n pulumi.set(__self__, \\\"allocation_default_netmask_length\\\", allocation_default_netmask_length)\\n if allocation_max_netmask_length is not None:\\n pulumi.set(__self__, \\\"allocation_max_netmask_length\\\", allocation_max_netmask_length)\\n if allocation_min_netmask_length is not None:\\n pulumi.set(__self__, \\\"allocation_min_netmask_length\\\", allocation_min_netmask_length)\\n if allocation_resource_tags is not None:\\n pulumi.set(__self__, \\\"allocation_resource_tags\\\", allocation_resource_tags)\\n if auto_import is not None:\\n pulumi.set(__self__, \\\"auto_import\\\", auto_import)\\n if aws_service is not None:\\n pulumi.set(__self__, \\\"aws_service\\\", aws_service)\\n if description is not None:\\n pulumi.set(__self__, \\\"description\\\", description)\\n if locale is not None:\\n pulumi.set(__self__, \\\"locale\\\", locale)\\n if public_ip_source is not None:\\n pulumi.set(__self__, \\\"public_ip_source\\\", public_ip_source)\\n if publicly_advertisable is not None:\\n pulumi.set(__self__, \\\"publicly_advertisable\\\", publicly_advertisable)\\n if source_ipam_pool_id is not None:\\n pulumi.set(__self__, \\\"source_ipam_pool_id\\\", source_ipam_pool_id)\\n if tags is not None:\\n pulumi.set(__self__, \\\"tags\\\", tags)\",\n \"def __init__(__self__, *,\\n control_node_id: pulumi.Input[str],\\n display_name: pulumi.Input[str],\\n probe_type: pulumi.Input[str],\\n arp: Optional[pulumi.Input[bool]] = None,\\n honeypot_bind_lists: Optional[pulumi.Input[Sequence[pulumi.Input['HoneypotProbeHoneypotBindListArgs']]]] = None,\\n ping: Optional[pulumi.Input[bool]] = None,\\n probe_version: Optional[pulumi.Input[str]] = None,\\n proxy_ip: Optional[pulumi.Input[str]] = None,\\n service_ip_lists: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n uuid: Optional[pulumi.Input[str]] = None,\\n vpc_id: Optional[pulumi.Input[str]] = None):\\n pulumi.set(__self__, \\\"control_node_id\\\", control_node_id)\\n pulumi.set(__self__, \\\"display_name\\\", display_name)\\n pulumi.set(__self__, \\\"probe_type\\\", probe_type)\\n if arp is not None:\\n pulumi.set(__self__, \\\"arp\\\", arp)\\n if honeypot_bind_lists is not None:\\n pulumi.set(__self__, \\\"honeypot_bind_lists\\\", honeypot_bind_lists)\\n if ping is not None:\\n pulumi.set(__self__, \\\"ping\\\", ping)\\n if probe_version is not None:\\n pulumi.set(__self__, \\\"probe_version\\\", probe_version)\\n if proxy_ip is not None:\\n pulumi.set(__self__, \\\"proxy_ip\\\", proxy_ip)\\n if service_ip_lists is not None:\\n pulumi.set(__self__, \\\"service_ip_lists\\\", service_ip_lists)\\n if uuid is not None:\\n pulumi.set(__self__, \\\"uuid\\\", uuid)\\n if vpc_id is not None:\\n pulumi.set(__self__, \\\"vpc_id\\\", vpc_id)\",\n \"def test_no_ip_address_passed(self, api_client):\\n runner = CliRunner()\\n\\n with patch(\\\"greynoise.cli.helper.sys\\\") as sys:\\n sys.stdin.isatty.return_value = True\\n result = runner.invoke(\\n subcommand.quick, parent=Context(main, info_name=\\\"greynoise\\\")\\n )\\n assert result.exit_code == -1\\n assert \\\"Usage: greynoise quick\\\" in result.output\\n api_client.quick.assert_not_called()\",\n \"def __init__(__self__, *,\\n acl_id: Optional[pulumi.Input[str]] = None,\\n description: Optional[pulumi.Input[str]] = None,\\n dest_cidr: Optional[pulumi.Input[str]] = None,\\n dest_port_range: Optional[pulumi.Input[str]] = None,\\n direction: Optional[pulumi.Input[str]] = None,\\n ip_protocol: Optional[pulumi.Input[str]] = None,\\n policy: Optional[pulumi.Input[str]] = None,\\n priority: Optional[pulumi.Input[int]] = None,\\n source_cidr: Optional[pulumi.Input[str]] = None,\\n source_port_range: Optional[pulumi.Input[str]] = None):\\n if acl_id is not None:\\n pulumi.set(__self__, \\\"acl_id\\\", acl_id)\\n if description is not None:\\n pulumi.set(__self__, \\\"description\\\", description)\\n if dest_cidr is not None:\\n pulumi.set(__self__, \\\"dest_cidr\\\", dest_cidr)\\n if dest_port_range is not None:\\n pulumi.set(__self__, \\\"dest_port_range\\\", dest_port_range)\\n if direction is not None:\\n pulumi.set(__self__, \\\"direction\\\", direction)\\n if ip_protocol is not None:\\n pulumi.set(__self__, \\\"ip_protocol\\\", ip_protocol)\\n if policy is not None:\\n pulumi.set(__self__, \\\"policy\\\", policy)\\n if priority is not None:\\n pulumi.set(__self__, \\\"priority\\\", priority)\\n if source_cidr is not None:\\n pulumi.set(__self__, \\\"source_cidr\\\", source_cidr)\\n if source_port_range is not None:\\n pulumi.set(__self__, \\\"source_port_range\\\", source_port_range)\",\n \"def test_invalid_ip_address_as_argument(self, api_client):\\n runner = CliRunner()\\n\\n expected = 'Error: Invalid value for \\\"[IP_ADDRESS]...\\\": not-an-ip\\\\n'\\n\\n result = runner.invoke(subcommand.ip, [\\\"not-an-ip\\\"])\\n assert result.exit_code == 2\\n assert expected in result.output\\n api_client.ip.assert_not_called()\",\n \"def __init__(__self__, *,\\n activation_key: Optional[pulumi.Input[str]] = None,\\n ip_address: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None,\\n private_link_endpoint: Optional[pulumi.Input[str]] = None,\\n security_group_arns: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n subnet_arns: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n vpc_endpoint_id: Optional[pulumi.Input[str]] = None):\\n if activation_key is not None:\\n pulumi.set(__self__, \\\"activation_key\\\", activation_key)\\n if ip_address is not None:\\n pulumi.set(__self__, \\\"ip_address\\\", ip_address)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if private_link_endpoint is not None:\\n pulumi.set(__self__, \\\"private_link_endpoint\\\", private_link_endpoint)\\n if security_group_arns is not None:\\n pulumi.set(__self__, \\\"security_group_arns\\\", security_group_arns)\\n if subnet_arns is not None:\\n pulumi.set(__self__, \\\"subnet_arns\\\", subnet_arns)\\n if tags is not None:\\n pulumi.set(__self__, \\\"tags\\\", tags)\\n if vpc_endpoint_id is not None:\\n pulumi.set(__self__, \\\"vpc_endpoint_id\\\", vpc_endpoint_id)\",\n \"def test_ip(response):\\n \\n # from comeon_core import update\\n ip = getIP()\\n print(ip)\\n #init_db(engine)\\n #update()\\n assert True\",\n \"def test_accepts_init_with_strict_subset_of_args(self):\\n\\n class API(platform.PlatformAPI):\\n def __init__(self, base_url):\\n pass\\n\\n api = API(\\\"some-url\\\")\\n assert isinstance(api, platform.PlatformAPI)\",\n \"def __init__(__self__, *,\\n dry_run: Optional[pulumi.Input[bool]] = None,\\n load_balancer_id: Optional[pulumi.Input[str]] = None,\\n security_group_id: Optional[pulumi.Input[str]] = None):\\n if dry_run is not None:\\n pulumi.set(__self__, \\\"dry_run\\\", dry_run)\\n if load_balancer_id is not None:\\n pulumi.set(__self__, \\\"load_balancer_id\\\", load_balancer_id)\\n if security_group_id is not None:\\n pulumi.set(__self__, \\\"security_group_id\\\", security_group_id)\",\n \"def __init__(__self__, *,\\n resource_group: pulumi.Input[str],\\n server: pulumi.Input[str],\\n subnet_name: pulumi.Input[str],\\n v_net_name: pulumi.Input[str],\\n v_net_resource_group: pulumi.Input[str],\\n ignore_missing_service_endpoint: Optional[pulumi.Input[bool]] = None):\\n pulumi.set(__self__, \\\"resource_group\\\", resource_group)\\n pulumi.set(__self__, \\\"server\\\", server)\\n pulumi.set(__self__, \\\"subnet_name\\\", subnet_name)\\n pulumi.set(__self__, \\\"v_net_name\\\", v_net_name)\\n pulumi.set(__self__, \\\"v_net_resource_group\\\", v_net_resource_group)\\n if ignore_missing_service_endpoint is not None:\\n pulumi.set(__self__, \\\"ignore_missing_service_endpoint\\\", ignore_missing_service_endpoint)\",\n \"def __init__(__self__, *,\\n resource_group: pulumi.Input[str],\\n server: pulumi.Input[str],\\n subnet_name: pulumi.Input[str],\\n v_net_name: pulumi.Input[str],\\n v_net_resource_group: pulumi.Input[str],\\n ignore_missing_service_endpoint: Optional[pulumi.Input[bool]] = None):\\n pulumi.set(__self__, \\\"resource_group\\\", resource_group)\\n pulumi.set(__self__, \\\"server\\\", server)\\n pulumi.set(__self__, \\\"subnet_name\\\", subnet_name)\\n pulumi.set(__self__, \\\"v_net_name\\\", v_net_name)\\n pulumi.set(__self__, \\\"v_net_resource_group\\\", v_net_resource_group)\\n if ignore_missing_service_endpoint is not None:\\n pulumi.set(__self__, \\\"ignore_missing_service_endpoint\\\", ignore_missing_service_endpoint)\",\n \"def __init__(self):\\n # assert(self.validate('61882613000194'))\\n # assert(self.validate('061882613000190'))\\n # assert(not self.validate('61882613000195'))\\n pass\",\n \"def __init__(__self__, *,\\n end_ip_address: pulumi.Input[str],\\n resource_group: pulumi.Input[str],\\n server: pulumi.Input[str],\\n start_ip_address: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"end_ip_address\\\", end_ip_address)\\n pulumi.set(__self__, \\\"resource_group\\\", resource_group)\\n pulumi.set(__self__, \\\"server\\\", server)\\n pulumi.set(__self__, \\\"start_ip_address\\\", start_ip_address)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7619989","0.7324193","0.7324193","0.7323932","0.70612985","0.6996996","0.6709637","0.6705524","0.6618657","0.65942365","0.6415844","0.6387556","0.6366282","0.6358961","0.6319033","0.6228522","0.6208983","0.6139439","0.6108403","0.6083423","0.6066069","0.60649264","0.60638696","0.6060406","0.5978354","0.59780127","0.5971527","0.59547675","0.5952458","0.59514964","0.59512967","0.5949955","0.5934184","0.5925605","0.59053445","0.5902148","0.5901118","0.58933634","0.589113","0.58839923","0.5883026","0.5864569","0.5855067","0.58521193","0.58512723","0.5850215","0.583253","0.58250403","0.5823746","0.5820773","0.5790049","0.57827234","0.57763267","0.57727593","0.5770694","0.5762999","0.57540727","0.57218397","0.57173634","0.5710184","0.57088715","0.5704685","0.5686824","0.5681912","0.5676905","0.56735677","0.5670732","0.56670713","0.56635016","0.566248","0.56583","0.5655936","0.5651818","0.565132","0.56496894","0.5649274","0.56462127","0.56401265","0.56353915","0.56340635","0.5632975","0.5632557","0.5632552","0.5630514","0.5625715","0.56255454","0.5623444","0.56113744","0.560422","0.55947","0.55923027","0.5588811","0.5584358","0.5576081","0.5574611","0.55706567","0.5569842","0.5569842","0.5556032","0.5554201"],"string":"[\n \"0.7619989\",\n \"0.7324193\",\n \"0.7324193\",\n \"0.7323932\",\n \"0.70612985\",\n \"0.6996996\",\n \"0.6709637\",\n \"0.6705524\",\n \"0.6618657\",\n \"0.65942365\",\n \"0.6415844\",\n \"0.6387556\",\n \"0.6366282\",\n \"0.6358961\",\n \"0.6319033\",\n \"0.6228522\",\n \"0.6208983\",\n \"0.6139439\",\n \"0.6108403\",\n \"0.6083423\",\n \"0.6066069\",\n \"0.60649264\",\n \"0.60638696\",\n \"0.6060406\",\n \"0.5978354\",\n \"0.59780127\",\n \"0.5971527\",\n \"0.59547675\",\n \"0.5952458\",\n \"0.59514964\",\n \"0.59512967\",\n \"0.5949955\",\n \"0.5934184\",\n \"0.5925605\",\n \"0.59053445\",\n \"0.5902148\",\n \"0.5901118\",\n \"0.58933634\",\n \"0.589113\",\n \"0.58839923\",\n \"0.5883026\",\n \"0.5864569\",\n \"0.5855067\",\n \"0.58521193\",\n \"0.58512723\",\n \"0.5850215\",\n \"0.583253\",\n \"0.58250403\",\n \"0.5823746\",\n \"0.5820773\",\n \"0.5790049\",\n \"0.57827234\",\n \"0.57763267\",\n \"0.57727593\",\n \"0.5770694\",\n \"0.5762999\",\n \"0.57540727\",\n \"0.57218397\",\n \"0.57173634\",\n \"0.5710184\",\n \"0.57088715\",\n \"0.5704685\",\n \"0.5686824\",\n \"0.5681912\",\n \"0.5676905\",\n \"0.56735677\",\n \"0.5670732\",\n \"0.56670713\",\n \"0.56635016\",\n \"0.566248\",\n \"0.56583\",\n \"0.5655936\",\n \"0.5651818\",\n \"0.565132\",\n \"0.56496894\",\n \"0.5649274\",\n \"0.56462127\",\n \"0.56401265\",\n \"0.56353915\",\n \"0.56340635\",\n \"0.5632975\",\n \"0.5632557\",\n \"0.5632552\",\n \"0.5630514\",\n \"0.5625715\",\n \"0.56255454\",\n \"0.5623444\",\n \"0.56113744\",\n \"0.560422\",\n \"0.55947\",\n \"0.55923027\",\n \"0.5588811\",\n \"0.5584358\",\n \"0.5576081\",\n \"0.5574611\",\n \"0.55706567\",\n \"0.5569842\",\n \"0.5569842\",\n \"0.5556032\",\n \"0.5554201\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7339444"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":3988,"cells":{"query":{"kind":"string","value":"Test the __init__ method when mandatory parameter 'mac' is None."},"document":{"kind":"string","value":"def test_init_no_mac(self):\n with self.assertRaises(ValueError):\n client = ClientInfo(None, ip=\"3.3.3.3\", ap_info=self.ap)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_init_no_mac(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n with self.assertRaises(ValueError):\n ap = APInfo(port_id=1, ip=\"2.2.2.2\", mac=None, radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)","def test_init_valid(self):\n payload = payloads.MACResponsePayload(\n self.unique_identifier,\n self.mac_data)\n self.assertEqual(payload.unique_identifier, self.unique_identifier)\n self.assertEqual(payload.mac_data, self.mac_data)","def test_init_valid(self):\n payload = payloads.MACRequestPayload(\n self.unique_identifier,\n self.cryptographic_parameters,\n self.data)\n self.assertEqual(payload.unique_identifier, self.unique_identifier)\n self.assertEqual(payload.cryptographic_parameters,\n self.cryptographic_parameters)\n self.assertEqual(payload.data, self.data)","def __init__(__self__, *,\n mac_address: str,\n name: str):\n pulumi.set(__self__, \"mac_address\", mac_address)\n pulumi.set(__self__, \"name\", name)","def __init__(self, mac):\n self.go_on = True\n self.mac = mac","def test_prepare_mac_header(self):\n self.assertEqual(prepare_mac_header(**self.mac_plain), self.auth_plain)\n self.assertEqual(prepare_mac_header(**self.mac_body), self.auth_body)\n self.assertEqual(prepare_mac_header(**self.mac_both), self.auth_both)","def __init__(__self__, *,\n ios_app_info: Optional[pulumi.Input['IosAppInfoArgs']] = None,\n ios_robo_test: Optional[pulumi.Input['IosRoboTestArgs']] = None,\n ios_test_loop: Optional[pulumi.Input['IosTestLoopArgs']] = None,\n ios_xc_test: Optional[pulumi.Input['IosXcTestArgs']] = None,\n test_timeout: Optional[pulumi.Input['DurationArgs']] = None):\n if ios_app_info is not None:\n pulumi.set(__self__, \"ios_app_info\", ios_app_info)\n if ios_robo_test is not None:\n pulumi.set(__self__, \"ios_robo_test\", ios_robo_test)\n if ios_test_loop is not None:\n pulumi.set(__self__, \"ios_test_loop\", ios_test_loop)\n if ios_xc_test is not None:\n pulumi.set(__self__, \"ios_xc_test\", ios_xc_test)\n if test_timeout is not None:\n pulumi.set(__self__, \"test_timeout\", test_timeout)","def test_init_no_ip(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n ap = APInfo(port_id=1, ip=None, mac=\"bb:bb:bb:bb:bb:bb\", radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\n self.assertEqual(ap.ip, None)","def __init__(__self__, *,\n crashed: Optional[pulumi.Input[bool]] = None,\n device_out_of_memory: Optional[pulumi.Input[bool]] = None,\n failed_roboscript: Optional[pulumi.Input[bool]] = None,\n not_installed: Optional[pulumi.Input[bool]] = None,\n other_native_crash: Optional[pulumi.Input[bool]] = None,\n timed_out: Optional[pulumi.Input[bool]] = None,\n unable_to_crawl: Optional[pulumi.Input[bool]] = None):\n if crashed is not None:\n pulumi.set(__self__, \"crashed\", crashed)\n if device_out_of_memory is not None:\n pulumi.set(__self__, \"device_out_of_memory\", device_out_of_memory)\n if failed_roboscript is not None:\n pulumi.set(__self__, \"failed_roboscript\", failed_roboscript)\n if not_installed is not None:\n pulumi.set(__self__, \"not_installed\", not_installed)\n if other_native_crash is not None:\n pulumi.set(__self__, \"other_native_crash\", other_native_crash)\n if timed_out is not None:\n pulumi.set(__self__, \"timed_out\", timed_out)\n if unable_to_crawl is not None:\n pulumi.set(__self__, \"unable_to_crawl\", unable_to_crawl)","def __init__(self, mac, pin, name):\n self._name = name\n self._mac = mac\n self._pin = pin\n self._state = None\n self.update()","def _mac_test(mac):\n\n\t\tif re.search(r'([0-9A-F]{2}[:]){5}([0-9A-F]){2}', mac.upper()) is not None:\n\t\t\treturn True\n\t\telse:\n\t\t\treturn False","def test_init_correct(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n ap = APInfo(port_id=1, ip=\"2.2.2.2\", mac=\"bb:bb:bb:bb:bb:bb\", radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\n\n self.assertEqual(ap.ip, '2.2.2.2')","def test_read_no_mac_data(self):\n payload = payloads.MACResponsePayload()\n args = (self.encoding_no_mac_data,)\n self.assertRaisesRegex(\n exceptions.InvalidKmipEncoding,\n \"expected mac response mac data not found\",\n payload.read,\n *args\n )","def __init__(__self__, *,\n android_test: Optional[pulumi.Input['AndroidTestArgs']] = None,\n ios_test: Optional[pulumi.Input['IosTestArgs']] = None):\n if android_test is not None:\n pulumi.set(__self__, \"android_test\", android_test)\n if ios_test is not None:\n pulumi.set(__self__, \"ios_test\", ios_test)","def test_init():\n machine = Machine(['a', 'b', 'c', '_'])\n assert machine.alphabet == ['a', 'b', 'c', '_']\n assert machine.head is None\n assert machine.state is None\n assert machine.tape is None","def test_init_no_ip(self):\n client = ClientInfo(\"cc:cc:cc:cc:cc:cc\", ip=None, ap_info=self.ap)\n self.assertEqual(client.ip, None)\n self.assertEqual(client.ip_bytes, None)","def test_init(self):\n self.assertEqual(self.device_key, self.factory.device_key)","def __init__(self) -> None:\n super().__init__()\n self.version = 6\n (self.ofproto, self.ofparser) = ofproto_protocol._versions[self.version]\n self.mac_to_port = {}","def __init__(__self__, *,\n crashed: bool,\n device_out_of_memory: bool,\n failed_roboscript: bool,\n not_installed: bool,\n other_native_crash: bool,\n timed_out: bool,\n unable_to_crawl: bool):\n pulumi.set(__self__, \"crashed\", crashed)\n pulumi.set(__self__, \"device_out_of_memory\", device_out_of_memory)\n pulumi.set(__self__, \"failed_roboscript\", failed_roboscript)\n pulumi.set(__self__, \"not_installed\", not_installed)\n pulumi.set(__self__, \"other_native_crash\", other_native_crash)\n pulumi.set(__self__, \"timed_out\", timed_out)\n pulumi.set(__self__, \"unable_to_crawl\", unable_to_crawl)","def _check_init(self):\n # instantiate the guest class we want to test\n system_name = 'dummy_system'\n host_name = 'dummy.domain.com'\n user = 'root'\n passwd = 'somepwd'\n extensions = {}\n guest_obj = linux.GuestLinux(\n system_name, host_name, user, passwd, extensions)\n\n # validate if attributes were correctly assigned to object\n self.assertEqual('linux', guest_obj.GUEST_ID)\n self.assertIs(system_name, guest_obj.name)\n self.assertIs(host_name, guest_obj.host_name)\n self.assertIs(user, guest_obj.user)\n self.assertIs(passwd, guest_obj.passwd)\n self.assertIs(extensions, guest_obj.extensions)\n\n # return object for further testing\n return guest_obj","def __init__(__self__, *,\n incompatible_app_version: Optional[pulumi.Input[bool]] = None,\n incompatible_architecture: Optional[pulumi.Input[bool]] = None,\n incompatible_device: Optional[pulumi.Input[bool]] = None):\n if incompatible_app_version is not None:\n pulumi.set(__self__, \"incompatible_app_version\", incompatible_app_version)\n if incompatible_architecture is not None:\n pulumi.set(__self__, \"incompatible_architecture\", incompatible_architecture)\n if incompatible_device is not None:\n pulumi.set(__self__, \"incompatible_device\", incompatible_device)","def test__init__raise_exception(self):\n self.assertRaises(TypeError, MasterNodeInterface)","def __init__(self, router: NetgearRouter, device: dict) -> None:\n self._router = router\n self._device = device\n self._mac = device[\"mac\"]\n self._name = self.get_device_name()\n self._device_name = self._name\n self._unique_id = self._mac\n self._active = device[\"active\"]","def __init__(self, dmac: bytes, smac: bytes, typ: int, payload: bytes):\n self.dmac = dmac\n self.smac = smac\n self.typ = typ\n self.payload = payload","def test_init_wrong_ap_type(self):\n ap_wrong = object()\n with self.assertRaises(ValueError):\n client = ClientInfo(\"cc:cc:cc:cc:cc:cc\",\n ip=\"3.3.3.3\", ap_info=ap_wrong)","def test_init(self):\n self.assertEqual(self.foo._base_cmd, 'sleep 10; hostname')\n self.assertEqual(self.foo._base_args, {})\n self.assertEqual(self.foo.InputArgs, {})\n self.assertEqual(self.foo.OracleJobName, 'job1')","def __init__(self, bus=None, alternativeAddress=False):\n super().__init__(bus, alternativeAddress)","def __init__(self,\n device_name,\n create_device_func,\n props,\n hub_name_prop,\n primary_port_prop,\n secondary_port_prop,\n ethernet_switch_prop,\n ethernet_port_prop,\n get_switchboard_if_initialized,\n power_and_data_share_cable=False,\n pre_off_func=None):\n super().__init__(device_name=device_name)\n\n self._create_device_func = create_device_func\n self._hub_name_prop = hub_name_prop\n self._primary_port_prop = primary_port_prop\n self._secondary_port_prop = secondary_port_prop\n self._props = props\n self._ethernet_switch = None\n\n # Set the properties\n self._get_switchboard_if_initialized = get_switchboard_if_initialized\n self._power_and_data_share_cable = power_and_data_share_cable\n self._pre_off_func = pre_off_func\n self._ethernet_switch_prop = ethernet_switch_prop\n self._ethernet_port_prop = ethernet_port_prop","def cna(mac):\n return mock.Mock(spec=pvm_net.CNA, mac=mac, vswitch_uri='fake_href')","def __init__(self, fake_apple_tv):\n self.device = fake_apple_tv","def test_write_with_no_data(self):\n stream = utils.BytearrayStream()\n payload = payloads.MACRequestPayload(\n self.unique_identifier,\n self.cryptographic_parameters,\n None)\n args = (stream,)\n self.assertRaisesRegex(\n exceptions.InvalidField,\n \"The mac request data is required\",\n payload.write,\n *args\n )","def __init__(__self__, *,\n cpu: Optional[pulumi.Input[str]] = None,\n memory: Optional[pulumi.Input[str]] = None):\n if cpu is not None:\n pulumi.set(__self__, \"cpu\", cpu)\n if memory is not None:\n pulumi.set(__self__, \"memory\", memory)","def __init__(self,address = None):\n\t\t# I really should do some validation around here\n\t\n\t\tif address != None:\n\t\t\tself.connect(address)","def test_read_no_data(self):\n payload = payloads.MACRequestPayload()\n args = (self.encoding_no_data,)\n self.assertRaisesRegex(\n exceptions.InvalidKmipEncoding,\n \"expected mac request data not found\",\n payload.read,\n *args\n )","def __init__(__self__, *,\n host_ip: Optional[pulumi.Input[str]] = None,\n port: Optional[pulumi.Input[str]] = None):\n if host_ip is not None:\n pulumi.set(__self__, \"host_ip\", host_ip)\n if port is not None:\n pulumi.set(__self__, \"port\", port)","def valid_mikettle_mac(mac, pat=re.compile(r\"[0-9A-F]{2}:[0-9A-F]{2}:[0-9A-F]{2}:[0-9A-F]{2}:[0-9A-F]{2}:[0-9A-F]{2}\")):\n if not pat.match(mac.upper()):\n raise argparse.ArgumentTypeError('The MAC address \"{}\" seems to be in the wrong format'.format(mac))\n return mac","def __init__(__self__, *,\n other_native_crash: Optional[pulumi.Input[bool]] = None):\n if other_native_crash is not None:\n pulumi.set(__self__, \"other_native_crash\", other_native_crash)","def __init__(self, pcap_file_path, mac_address = None):\n self.pcap_file_path = pcap_file_path\n self.mac_address = mac_address\n\n self.mac_address_binary = utils.eth_aton(mac_address) if (mac_address is not None) else None\n self.parsed_data = self.get_pcap_traffic_series()","def mac(self, mac):\n\n self._mac = mac","def isMac(cls, mac):\n return mac.startswith(cls.MAC_PREFIX)","def __init__(self):\n self.dhcp_client_state = store.MacToIP() # mac => DHCP_State","def _get_mac(self):\n return self.__mac","def test_wrong_init(self):\n xknx = XKNX()\n knxipframe = KNXIPFrame(xknx)\n with self.assertRaises(TypeError):\n knxipframe.init(23)","def __init__(__self__, *,\n incompatible_app_version: bool,\n incompatible_architecture: bool,\n incompatible_device: bool):\n pulumi.set(__self__, \"incompatible_app_version\", incompatible_app_version)\n pulumi.set(__self__, \"incompatible_architecture\", incompatible_architecture)\n pulumi.set(__self__, \"incompatible_device\", incompatible_device)","def __init__(self, **kwargs):\n members = ('ip', 'mac', 'port', 'timeout', 'flags',\n 'index', 'tag', 'hostname')\n\n # copy the given value or default to None\n for member in members:\n self.__dict__[member] = kwargs.setdefault (member, None)","def test_init_correct(self):\n client = ClientInfo(\"cc:cc:cc:cc:cc:cc\", ip=\"3.3.3.3\", ap_info=self.ap)\n self.assertEqual(client.ip, \"3.3.3.3\")\n self.assertEqual(client.ip_bytes, b'\\x03\\x03\\x03\\x03')","def test_constructor(self):\n pass","def test_init(self):\n DummyCryptographicObject()","def test_device_init_command(self):\n default_val = 0\n self.assertEqual(self.sim_device.integer1, default_val)\n # Write to the attribute integer1\n self.sim_device.integer1 = 45\n self.assertEqual(self.sim_device.integer1, 45)\n # Reset the values of the device attributes to default.\n self.sim_device.Init()\n # Check that the desiredPointing attribute is reset.\n self.assertEqual(self.sim_device.integer1, default_val)","def _identify_mac(self, request):\n params = parse_authz_header(request, None)\n if params is None:\n return None\n if params.get(\"scheme\") != \"MAC\":\n return None\n # Check that various parameters are as expected.\n token = params.get(\"id\")\n if token is None:\n msg = \"missing MAC id\"\n return self._respond_unauthorized(request, msg)\n # Check the timestamp and nonce for freshness or reuse.\n # TODO: the spec requires us to adjust for per-client clock skew.\n try:\n timestamp = int(params[\"ts\"])\n except (KeyError, ValueError):\n msg = \"missing or malformed MAC timestamp\"\n return self._respond_unauthorized(request, msg)\n nonce = params.get(\"nonce\")\n if nonce is None:\n msg = \"missing MAC nonce\"\n return self._respond_unauthorized(request, msg)\n if not self.nonce_manager.is_fresh(token, timestamp, nonce):\n msg = \"MAC has stale token or nonce\"\n return self._respond_unauthorized(request, msg)\n # OK, they seem like sensible MAC paramters.\n return params","def __init__(self):\n # self.baud = baud\n # self.protocol = protocol\n pass","def test_write_with_no_data(self):\n stream = utils.BytearrayStream()\n payload = payloads.MACResponsePayload(\n self.unique_identifier,\n None)\n args = (stream,)\n self.assertRaisesRegex(\n exceptions.InvalidField,\n \"The mac response mac data is required\",\n payload.write,\n *args\n )","def __init__(__self__, *,\n cpu: Optional[pulumi.Input[str]] = None,\n memory: Optional[pulumi.Input[str]] = None):\n if cpu is None:\n cpu = '1'\n if cpu is not None:\n pulumi.set(__self__, \"cpu\", cpu)\n if memory is None:\n memory = '2Gi'\n if memory is not None:\n pulumi.set(__self__, \"memory\", memory)","def __init__(__self__, *,\n cpu: Optional[pulumi.Input[str]] = None,\n memory: Optional[pulumi.Input[str]] = None):\n if cpu is None:\n cpu = '1'\n if cpu is not None:\n pulumi.set(__self__, \"cpu\", cpu)\n if memory is None:\n memory = '2Gi'\n if memory is not None:\n pulumi.set(__self__, \"memory\", memory)","def __init__(__self__, *,\n ios_app_info: 'outputs.IosAppInfoResponse',\n ios_robo_test: 'outputs.IosRoboTestResponse',\n ios_test_loop: 'outputs.IosTestLoopResponse',\n ios_xc_test: 'outputs.IosXcTestResponse',\n test_timeout: 'outputs.DurationResponse'):\n pulumi.set(__self__, \"ios_app_info\", ios_app_info)\n pulumi.set(__self__, \"ios_robo_test\", ios_robo_test)\n pulumi.set(__self__, \"ios_test_loop\", ios_test_loop)\n pulumi.set(__self__, \"ios_xc_test\", ios_xc_test)\n pulumi.set(__self__, \"test_timeout\", test_timeout)","def test_init_arg(self):\n b1 = BaseModel(12)\n self.assertEqual(type(b1).__name__, \"BaseModel\")\n self.assertFalse(hasattr(b1, \"12\"))","def test_init(self):\n nt.assert_raises(Exception, CisInterface.CisInput, 'error')","def from_mac(self):\n try:\n dt_obj = self.epoch_2001 + timedelta(seconds=int(mac))\n self.in_mac = dt_obj.strftime('%Y-%m-%d %H:%M:%S.%f')\n except Exception as e:\n if not args.log:\n pass\n else:\n logging.error(str(type(e)) + \",\" + str(e))\n self.in_mac = False\n return self.in_mac","def __init__(self, simulator):\r\n self.initialize(simulator)","def __init__(self, id_phone, header, app_port):\n path = os.path.join(os.curdir, smartphone_directory)\n os.mkdir(path) if not os.path.exists(path) else None\n path = os.path.join(path, id_phone)\n os.mkdir(path) if not os.path.exists(path) else None\n super().__init__(path, app_port)\n\n self._on = True # smartphone initialized always on\n self._bluetooth = True # bluetooth initialized always on\n self._wifi = True # wifi initialized always on\n self._id_phone = id_phone # skt of the phone\n self._header = header # header of bluetooth packets\n self._log_path = os.path.join(path, smartphone_log_filename) # path of smartphone's offline logfile\n self._packets_root = os.path.join(os.curdir, packets_directory) # packets' root directory\n\n if os.path.exists(self._log_path):\n with open(self._log_path, \"r\") as j:\n self._log = json.load(j) # offline logfile load from json file\n else:\n self._log = dict() # offline logfile initialization","def __init__(self, pin: str) -> None:\n ...","def __init__(self,family = 2, protocol = 2, router_mac=\"T\",verbose=False,debug=False):\n \n\n # Setup booleans to validate that socket is used correctly\n self.validFamilyAndProtocol = False;\n self.validIPAndPort = False;\n\n \n \n # Setup MAC Data\n self.my_mac = MAC.my_ad;\n if self.my_mac != router_mac:\n self.macDict = dict();\n self.macDict['router_mac'] = router_mac;\n\n if debug:\n self.macDict['II'] = 'I';\n self.macDict['IN'] = 'N';\n self.macDict['IR'] = 'R';\n self.macDict['ID'] = 'D';\n \n self.verbose = verbose;\n self.debug = debug;\n\n # ------ Set Up Family and Protocol ------ #\n if family!=2: #AF_INET\n print(\"Sorry, this address family is not currently supported!\");\n else:\n self.family = 2;\n\n if protocol!=2: #UDP\n print(\"Sorry, this sending protocol is not currently supported!\");\n else:\n self.protocol = 2;\n\n #Our \"UDP\" imports (importing our Morse implementation of UDP)\n if protocol==2: \n self.validFamilyAndProtocol = True;\n self.protocol_identifier = 'E'; #The standard defined base 36 char designating UDP\n\n # Default bind to simulate the ability of the kernel to generate these at runtime if unbound\n self.bind((g.server_ip,g.server_port),False);\n \n if self.debug:\n self.bind((\"0.0.73.78\",\"69\"));","def __init__(self, *args, **kwargs):\n super().__init__(*args, **kwargs)\n self.expected_cont_uuid = None\n self.daos_cmd = None","def __init__(self, bus=0, device=0):\n ...","def __init__(self, person_mac=None, person_name=None, person_phone_number=None, notification=None, dest_mac=None): # noqa: E501\n self.openapi_types = {\n 'person_mac': List[str],\n 'person_name': str,\n 'person_phone_number': str,\n 'notification': bool,\n 'dest_mac': str\n }\n\n self.attribute_map = {\n 'person_mac': 'person_MAC',\n 'person_name': 'person_name',\n 'person_phone_number': 'person_phone_number',\n 'notification': 'notification',\n 'dest_mac': 'dest_MAC'\n }\n\n self._person_mac = person_mac\n self._person_name = person_name\n self._person_phone_number = person_phone_number\n self._notification = notification\n self._dest_mac = dest_mac","def test_create_device(self):\n pass","def test_create_device(self):\n pass","def __init__(self, machine, vm_name):\n self.machine = machine\n self.vm_name = vm_name","def __init__(self, os_device_name: str, mac_address: str = None,\n subnets: 'list[SubnetAffiliation]' = None):\n self.os_device_name = os_device_name\n self.mac_address = mac_address\n self.subnets = []\n\n if subnets:\n for subnet in subnets:\n self.add_to_subnet(subnet)","def __init__(self, device: Device, router: KeeneticRouter) -> None:\n self._device = device\n self._router = router\n self._last_seen = (\n dt_util.utcnow() if device.mac in router.last_devices else None\n )","def __init__(\n self, name: str = \"\", protocol: int | None = None, **kwargs: Any\n ) -> None:\n\n super().__init__(name=name, **kwargs)\n if not ipaddress:\n raise SoftDependencyError(\"ipaddress\")\n if protocol not in [None, 4, 6]:\n raise ValueError(\"IpAddress protocol needs to be either 4, 6 or None\")\n self.protocol = protocol","def __init__(self, platform, test_type, fork_id, branch, commit, pr_nr=0, token=None) -> None:\n self.platform = platform\n self.test_type = test_type\n self.fork_id = fork_id\n self.branch = branch\n self.commit = commit\n self.pr_nr = pr_nr\n if token is None:\n # Auto-generate token\n token = self.create_token(64)\n self.token = token","def __init__(\n self, name: str = \"\", protocol: int | None = None, **kwargs: Any\n ) -> None:\n\n super().__init__(name=name, **kwargs)\n\n if protocol not in [None, 4, 6]:\n raise ValueError(\"IpAddress protocol needs to be either 4, 6 or None\")\n self.protocol = protocol","def __init__(self):\n raise NoInitiation","def __init__(__self__, *,\n host: Optional[pulumi.Input[str]] = None,\n port: Optional[pulumi.Input[int]] = None):\n if host is not None:\n pulumi.set(__self__, \"host\", host)\n if port is not None:\n pulumi.set(__self__, \"port\", port)","def test_initialization(self):\n self.assertEqual(self.installer.host_name, \"ec2.amazon.com\")\n self.assertEqual(self.installer.user_name, \"ec2\")\n self.assertEqual(self.installer.os, \"ubuntu\")\n self.assertEqual(self.installer.key_path, \"./ODFEAMIInstanceKey.pem\")\n self.assertEqual(self.installer.RPM_package_version, \"1.4.0\")\n self.assertEqual(self.installer.APT_OSS_version, \"7.4.2\")","def test_init_(self):\n card = Card('Archer', 3, 0, 2)\n self.assertEqual(card.name, 'Archer')\n self.assertEqual(card.attack, 3)\n self.assertEqual(card.money, 0)\n self.assertEqual(card.cost, 2)","def call_init(mac_address, ip_address, start_port, free_ports):\n url = INIT_URL\n init_dict = {'IPAddress': ip_address, 'MacAddress': mac_address, 'OpenPorts': free_ports, 'StartPort': start_port}\n logging.info(\"Calling coordinator at url: %s, with dict: %s\", url, str(init_dict))\n try:\n resp = requests.post(url, json=init_dict, timeout=10)\n except requests.exceptions.RequestException as e:\n return None, e\n return resp, None","def test_init_kwarg(self):\n b1 = BaseModel(name=\"Red\")\n self.assertEqual(type(b1).__name__, \"BaseModel\")\n self.assertTrue(hasattr(b1, \"name\"))\n self.assertTrue(hasattr(b1, \"__class__\"))\n self.assertFalse(hasattr(b1, \"id\"))\n self.assertFalse(hasattr(b1, \"created_at\"))\n self.assertFalse(hasattr(b1, \"updated_at\"))","def test_init_default_values(self):\n card = Card('Archer')\n self.assertEqual(card.name, 'Archer')\n self.assertEqual(card.attack, 0)\n self.assertEqual(card.money, 0)\n self.assertEqual(card.cost, 0)","def __init__(self):\n # assert(self.validate('61882613000194'))\n # assert(self.validate('061882613000190'))\n # assert(not self.validate('61882613000195'))\n pass","def __init__(self, hostiface: str, **kwargs):\n super().__init__(**kwargs)\n self.hostiface = hostiface","def test_002_init(self):\n self.assertIsInstance(ionchrom.ionchrom(\"id\"),ionchrom.ionchrom)","def test_init(self):\n nt.assert_raises(Exception, CisInterface.CisOutput, 'error')","def __init__(self, addr, name=None, i2c=None):\n\n # Initialize the device and save the simulator\n super().__init__(addr, name=name, i2c=i2c)\n self.sim = None","def mock_constructor(host, username, password, port, web_proto):\n mock_device.host = host\n mock_device.username = username\n mock_device.password = password\n mock_device.port = port\n return mock_device","def __init__(self) -> None:\n self.ip_address: str | None = None","def test_constructor(self):\n assert self.parser is not None","def valid_mitemp_mac(mac, pat=re.compile(r\"4C:65:A8:[0-9A-F]{2}:[0-9A-F]{2}:[0-9A-F]{2}\")):\n if not pat.match(mac.upper()):\n raise argparse.ArgumentTypeError('The MAC address \"{}\" seems to be in the wrong format'.format(mac))\n return mac","def __init__(self):\n super(UpnpEmbeddedDevice, self).__init__()\n return","def __eq__(self,other):\n if isinstance(other, self.__class__):\n return self.mac == other.mac\n else: return False","def __init__(self, game, net_args: DotDict, architecture: str) -> None:\n super().__init__(game, net_args, Agents.MuZeroNetworks[architecture])\n self.action_size = game.getActionSize()\n self.architecture = architecture","def test_001_init(self):\n self.assertRaises(TypeError,ionchrom.ionchrom)","def test_write_with_no_unique_identifier(self):\n stream = utils.BytearrayStream()\n payload = payloads.MACResponsePayload(\n None,\n self.mac_data)\n args = (stream,)\n self.assertRaisesRegex(\n exceptions.InvalidField,\n \"The mac response unique identifier is required\",\n payload.write,\n *args\n )","def test_init(self):\n with self.assertRaises(ValueError):\n TraxionPay(api_key=self.api_key)","def __init__(self, device: Dict[str, Union[str, int, float]]) -> None:\n super().__init__()\n log_int.debug(f\"Initializing serial device for {device['name']} :: Port: {device['port']} - Baud rate: \"\n f\"{device['baudrate']} - Timeout: {device['timeout']} - RTS/CTS: {bool(device['flowcontrol'])}\")\n self.device = serial.Serial(port=device['port'], baudrate=device['baudrate'],\n timeout=device['timeout'], rtscts=device['flowcontrol'])","def checkMac(self, mac):\n\t\tif mac in self.seenMacs:\n\t\t\treturn True\n\t\treturn False","def __init__(__self__, *,\n spec: Optional[pulumi.Input['InstanceSpecArgs']] = None):\n if spec is not None:\n pulumi.set(__self__, \"spec\", spec)","def initialize(self) -> bool:\n raise NotImplementedError","def __init__(__self__, *,\n os_version: Optional[pulumi.Input['WindowsNodeConfigOsVersion']] = None):\n if os_version is not None:\n pulumi.set(__self__, \"os_version\", os_version)"],"string":"[\n \"def test_init_no_mac(self):\\n # mocks of files\\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\\n\\n with self.assertRaises(ValueError):\\n ap = APInfo(port_id=1, ip=\\\"2.2.2.2\\\", mac=None, radio_mac=\\\"bb:bb:bb:bb:bb:00\\\", udp_port=12345, wlc_ip='1.1.1.1',\\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\",\n \"def test_init_valid(self):\\n payload = payloads.MACResponsePayload(\\n self.unique_identifier,\\n self.mac_data)\\n self.assertEqual(payload.unique_identifier, self.unique_identifier)\\n self.assertEqual(payload.mac_data, self.mac_data)\",\n \"def test_init_valid(self):\\n payload = payloads.MACRequestPayload(\\n self.unique_identifier,\\n self.cryptographic_parameters,\\n self.data)\\n self.assertEqual(payload.unique_identifier, self.unique_identifier)\\n self.assertEqual(payload.cryptographic_parameters,\\n self.cryptographic_parameters)\\n self.assertEqual(payload.data, self.data)\",\n \"def __init__(__self__, *,\\n mac_address: str,\\n name: str):\\n pulumi.set(__self__, \\\"mac_address\\\", mac_address)\\n pulumi.set(__self__, \\\"name\\\", name)\",\n \"def __init__(self, mac):\\n self.go_on = True\\n self.mac = mac\",\n \"def test_prepare_mac_header(self):\\n self.assertEqual(prepare_mac_header(**self.mac_plain), self.auth_plain)\\n self.assertEqual(prepare_mac_header(**self.mac_body), self.auth_body)\\n self.assertEqual(prepare_mac_header(**self.mac_both), self.auth_both)\",\n \"def __init__(__self__, *,\\n ios_app_info: Optional[pulumi.Input['IosAppInfoArgs']] = None,\\n ios_robo_test: Optional[pulumi.Input['IosRoboTestArgs']] = None,\\n ios_test_loop: Optional[pulumi.Input['IosTestLoopArgs']] = None,\\n ios_xc_test: Optional[pulumi.Input['IosXcTestArgs']] = None,\\n test_timeout: Optional[pulumi.Input['DurationArgs']] = None):\\n if ios_app_info is not None:\\n pulumi.set(__self__, \\\"ios_app_info\\\", ios_app_info)\\n if ios_robo_test is not None:\\n pulumi.set(__self__, \\\"ios_robo_test\\\", ios_robo_test)\\n if ios_test_loop is not None:\\n pulumi.set(__self__, \\\"ios_test_loop\\\", ios_test_loop)\\n if ios_xc_test is not None:\\n pulumi.set(__self__, \\\"ios_xc_test\\\", ios_xc_test)\\n if test_timeout is not None:\\n pulumi.set(__self__, \\\"test_timeout\\\", test_timeout)\",\n \"def test_init_no_ip(self):\\n # mocks of files\\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\\n\\n ap = APInfo(port_id=1, ip=None, mac=\\\"bb:bb:bb:bb:bb:bb\\\", radio_mac=\\\"bb:bb:bb:bb:bb:00\\\", udp_port=12345, wlc_ip='1.1.1.1',\\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\\n self.assertEqual(ap.ip, None)\",\n \"def __init__(__self__, *,\\n crashed: Optional[pulumi.Input[bool]] = None,\\n device_out_of_memory: Optional[pulumi.Input[bool]] = None,\\n failed_roboscript: Optional[pulumi.Input[bool]] = None,\\n not_installed: Optional[pulumi.Input[bool]] = None,\\n other_native_crash: Optional[pulumi.Input[bool]] = None,\\n timed_out: Optional[pulumi.Input[bool]] = None,\\n unable_to_crawl: Optional[pulumi.Input[bool]] = None):\\n if crashed is not None:\\n pulumi.set(__self__, \\\"crashed\\\", crashed)\\n if device_out_of_memory is not None:\\n pulumi.set(__self__, \\\"device_out_of_memory\\\", device_out_of_memory)\\n if failed_roboscript is not None:\\n pulumi.set(__self__, \\\"failed_roboscript\\\", failed_roboscript)\\n if not_installed is not None:\\n pulumi.set(__self__, \\\"not_installed\\\", not_installed)\\n if other_native_crash is not None:\\n pulumi.set(__self__, \\\"other_native_crash\\\", other_native_crash)\\n if timed_out is not None:\\n pulumi.set(__self__, \\\"timed_out\\\", timed_out)\\n if unable_to_crawl is not None:\\n pulumi.set(__self__, \\\"unable_to_crawl\\\", unable_to_crawl)\",\n \"def __init__(self, mac, pin, name):\\n self._name = name\\n self._mac = mac\\n self._pin = pin\\n self._state = None\\n self.update()\",\n \"def _mac_test(mac):\\n\\n\\t\\tif re.search(r'([0-9A-F]{2}[:]){5}([0-9A-F]){2}', mac.upper()) is not None:\\n\\t\\t\\treturn True\\n\\t\\telse:\\n\\t\\t\\treturn False\",\n \"def test_init_correct(self):\\n # mocks of files\\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\\n\\n ap = APInfo(port_id=1, ip=\\\"2.2.2.2\\\", mac=\\\"bb:bb:bb:bb:bb:bb\\\", radio_mac=\\\"bb:bb:bb:bb:bb:00\\\", udp_port=12345, wlc_ip='1.1.1.1',\\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\\n\\n self.assertEqual(ap.ip, '2.2.2.2')\",\n \"def test_read_no_mac_data(self):\\n payload = payloads.MACResponsePayload()\\n args = (self.encoding_no_mac_data,)\\n self.assertRaisesRegex(\\n exceptions.InvalidKmipEncoding,\\n \\\"expected mac response mac data not found\\\",\\n payload.read,\\n *args\\n )\",\n \"def __init__(__self__, *,\\n android_test: Optional[pulumi.Input['AndroidTestArgs']] = None,\\n ios_test: Optional[pulumi.Input['IosTestArgs']] = None):\\n if android_test is not None:\\n pulumi.set(__self__, \\\"android_test\\\", android_test)\\n if ios_test is not None:\\n pulumi.set(__self__, \\\"ios_test\\\", ios_test)\",\n \"def test_init():\\n machine = Machine(['a', 'b', 'c', '_'])\\n assert machine.alphabet == ['a', 'b', 'c', '_']\\n assert machine.head is None\\n assert machine.state is None\\n assert machine.tape is None\",\n \"def test_init_no_ip(self):\\n client = ClientInfo(\\\"cc:cc:cc:cc:cc:cc\\\", ip=None, ap_info=self.ap)\\n self.assertEqual(client.ip, None)\\n self.assertEqual(client.ip_bytes, None)\",\n \"def test_init(self):\\n self.assertEqual(self.device_key, self.factory.device_key)\",\n \"def __init__(self) -> None:\\n super().__init__()\\n self.version = 6\\n (self.ofproto, self.ofparser) = ofproto_protocol._versions[self.version]\\n self.mac_to_port = {}\",\n \"def __init__(__self__, *,\\n crashed: bool,\\n device_out_of_memory: bool,\\n failed_roboscript: bool,\\n not_installed: bool,\\n other_native_crash: bool,\\n timed_out: bool,\\n unable_to_crawl: bool):\\n pulumi.set(__self__, \\\"crashed\\\", crashed)\\n pulumi.set(__self__, \\\"device_out_of_memory\\\", device_out_of_memory)\\n pulumi.set(__self__, \\\"failed_roboscript\\\", failed_roboscript)\\n pulumi.set(__self__, \\\"not_installed\\\", not_installed)\\n pulumi.set(__self__, \\\"other_native_crash\\\", other_native_crash)\\n pulumi.set(__self__, \\\"timed_out\\\", timed_out)\\n pulumi.set(__self__, \\\"unable_to_crawl\\\", unable_to_crawl)\",\n \"def _check_init(self):\\n # instantiate the guest class we want to test\\n system_name = 'dummy_system'\\n host_name = 'dummy.domain.com'\\n user = 'root'\\n passwd = 'somepwd'\\n extensions = {}\\n guest_obj = linux.GuestLinux(\\n system_name, host_name, user, passwd, extensions)\\n\\n # validate if attributes were correctly assigned to object\\n self.assertEqual('linux', guest_obj.GUEST_ID)\\n self.assertIs(system_name, guest_obj.name)\\n self.assertIs(host_name, guest_obj.host_name)\\n self.assertIs(user, guest_obj.user)\\n self.assertIs(passwd, guest_obj.passwd)\\n self.assertIs(extensions, guest_obj.extensions)\\n\\n # return object for further testing\\n return guest_obj\",\n \"def __init__(__self__, *,\\n incompatible_app_version: Optional[pulumi.Input[bool]] = None,\\n incompatible_architecture: Optional[pulumi.Input[bool]] = None,\\n incompatible_device: Optional[pulumi.Input[bool]] = None):\\n if incompatible_app_version is not None:\\n pulumi.set(__self__, \\\"incompatible_app_version\\\", incompatible_app_version)\\n if incompatible_architecture is not None:\\n pulumi.set(__self__, \\\"incompatible_architecture\\\", incompatible_architecture)\\n if incompatible_device is not None:\\n pulumi.set(__self__, \\\"incompatible_device\\\", incompatible_device)\",\n \"def test__init__raise_exception(self):\\n self.assertRaises(TypeError, MasterNodeInterface)\",\n \"def __init__(self, router: NetgearRouter, device: dict) -> None:\\n self._router = router\\n self._device = device\\n self._mac = device[\\\"mac\\\"]\\n self._name = self.get_device_name()\\n self._device_name = self._name\\n self._unique_id = self._mac\\n self._active = device[\\\"active\\\"]\",\n \"def __init__(self, dmac: bytes, smac: bytes, typ: int, payload: bytes):\\n self.dmac = dmac\\n self.smac = smac\\n self.typ = typ\\n self.payload = payload\",\n \"def test_init_wrong_ap_type(self):\\n ap_wrong = object()\\n with self.assertRaises(ValueError):\\n client = ClientInfo(\\\"cc:cc:cc:cc:cc:cc\\\",\\n ip=\\\"3.3.3.3\\\", ap_info=ap_wrong)\",\n \"def test_init(self):\\n self.assertEqual(self.foo._base_cmd, 'sleep 10; hostname')\\n self.assertEqual(self.foo._base_args, {})\\n self.assertEqual(self.foo.InputArgs, {})\\n self.assertEqual(self.foo.OracleJobName, 'job1')\",\n \"def __init__(self, bus=None, alternativeAddress=False):\\n super().__init__(bus, alternativeAddress)\",\n \"def __init__(self,\\n device_name,\\n create_device_func,\\n props,\\n hub_name_prop,\\n primary_port_prop,\\n secondary_port_prop,\\n ethernet_switch_prop,\\n ethernet_port_prop,\\n get_switchboard_if_initialized,\\n power_and_data_share_cable=False,\\n pre_off_func=None):\\n super().__init__(device_name=device_name)\\n\\n self._create_device_func = create_device_func\\n self._hub_name_prop = hub_name_prop\\n self._primary_port_prop = primary_port_prop\\n self._secondary_port_prop = secondary_port_prop\\n self._props = props\\n self._ethernet_switch = None\\n\\n # Set the properties\\n self._get_switchboard_if_initialized = get_switchboard_if_initialized\\n self._power_and_data_share_cable = power_and_data_share_cable\\n self._pre_off_func = pre_off_func\\n self._ethernet_switch_prop = ethernet_switch_prop\\n self._ethernet_port_prop = ethernet_port_prop\",\n \"def cna(mac):\\n return mock.Mock(spec=pvm_net.CNA, mac=mac, vswitch_uri='fake_href')\",\n \"def __init__(self, fake_apple_tv):\\n self.device = fake_apple_tv\",\n \"def test_write_with_no_data(self):\\n stream = utils.BytearrayStream()\\n payload = payloads.MACRequestPayload(\\n self.unique_identifier,\\n self.cryptographic_parameters,\\n None)\\n args = (stream,)\\n self.assertRaisesRegex(\\n exceptions.InvalidField,\\n \\\"The mac request data is required\\\",\\n payload.write,\\n *args\\n )\",\n \"def __init__(__self__, *,\\n cpu: Optional[pulumi.Input[str]] = None,\\n memory: Optional[pulumi.Input[str]] = None):\\n if cpu is not None:\\n pulumi.set(__self__, \\\"cpu\\\", cpu)\\n if memory is not None:\\n pulumi.set(__self__, \\\"memory\\\", memory)\",\n \"def __init__(self,address = None):\\n\\t\\t# I really should do some validation around here\\n\\t\\n\\t\\tif address != None:\\n\\t\\t\\tself.connect(address)\",\n \"def test_read_no_data(self):\\n payload = payloads.MACRequestPayload()\\n args = (self.encoding_no_data,)\\n self.assertRaisesRegex(\\n exceptions.InvalidKmipEncoding,\\n \\\"expected mac request data not found\\\",\\n payload.read,\\n *args\\n )\",\n \"def __init__(__self__, *,\\n host_ip: Optional[pulumi.Input[str]] = None,\\n port: Optional[pulumi.Input[str]] = None):\\n if host_ip is not None:\\n pulumi.set(__self__, \\\"host_ip\\\", host_ip)\\n if port is not None:\\n pulumi.set(__self__, \\\"port\\\", port)\",\n \"def valid_mikettle_mac(mac, pat=re.compile(r\\\"[0-9A-F]{2}:[0-9A-F]{2}:[0-9A-F]{2}:[0-9A-F]{2}:[0-9A-F]{2}:[0-9A-F]{2}\\\")):\\n if not pat.match(mac.upper()):\\n raise argparse.ArgumentTypeError('The MAC address \\\"{}\\\" seems to be in the wrong format'.format(mac))\\n return mac\",\n \"def __init__(__self__, *,\\n other_native_crash: Optional[pulumi.Input[bool]] = None):\\n if other_native_crash is not None:\\n pulumi.set(__self__, \\\"other_native_crash\\\", other_native_crash)\",\n \"def __init__(self, pcap_file_path, mac_address = None):\\n self.pcap_file_path = pcap_file_path\\n self.mac_address = mac_address\\n\\n self.mac_address_binary = utils.eth_aton(mac_address) if (mac_address is not None) else None\\n self.parsed_data = self.get_pcap_traffic_series()\",\n \"def mac(self, mac):\\n\\n self._mac = mac\",\n \"def isMac(cls, mac):\\n return mac.startswith(cls.MAC_PREFIX)\",\n \"def __init__(self):\\n self.dhcp_client_state = store.MacToIP() # mac => DHCP_State\",\n \"def _get_mac(self):\\n return self.__mac\",\n \"def test_wrong_init(self):\\n xknx = XKNX()\\n knxipframe = KNXIPFrame(xknx)\\n with self.assertRaises(TypeError):\\n knxipframe.init(23)\",\n \"def __init__(__self__, *,\\n incompatible_app_version: bool,\\n incompatible_architecture: bool,\\n incompatible_device: bool):\\n pulumi.set(__self__, \\\"incompatible_app_version\\\", incompatible_app_version)\\n pulumi.set(__self__, \\\"incompatible_architecture\\\", incompatible_architecture)\\n pulumi.set(__self__, \\\"incompatible_device\\\", incompatible_device)\",\n \"def __init__(self, **kwargs):\\n members = ('ip', 'mac', 'port', 'timeout', 'flags',\\n 'index', 'tag', 'hostname')\\n\\n # copy the given value or default to None\\n for member in members:\\n self.__dict__[member] = kwargs.setdefault (member, None)\",\n \"def test_init_correct(self):\\n client = ClientInfo(\\\"cc:cc:cc:cc:cc:cc\\\", ip=\\\"3.3.3.3\\\", ap_info=self.ap)\\n self.assertEqual(client.ip, \\\"3.3.3.3\\\")\\n self.assertEqual(client.ip_bytes, b'\\\\x03\\\\x03\\\\x03\\\\x03')\",\n \"def test_constructor(self):\\n pass\",\n \"def test_init(self):\\n DummyCryptographicObject()\",\n \"def test_device_init_command(self):\\n default_val = 0\\n self.assertEqual(self.sim_device.integer1, default_val)\\n # Write to the attribute integer1\\n self.sim_device.integer1 = 45\\n self.assertEqual(self.sim_device.integer1, 45)\\n # Reset the values of the device attributes to default.\\n self.sim_device.Init()\\n # Check that the desiredPointing attribute is reset.\\n self.assertEqual(self.sim_device.integer1, default_val)\",\n \"def _identify_mac(self, request):\\n params = parse_authz_header(request, None)\\n if params is None:\\n return None\\n if params.get(\\\"scheme\\\") != \\\"MAC\\\":\\n return None\\n # Check that various parameters are as expected.\\n token = params.get(\\\"id\\\")\\n if token is None:\\n msg = \\\"missing MAC id\\\"\\n return self._respond_unauthorized(request, msg)\\n # Check the timestamp and nonce for freshness or reuse.\\n # TODO: the spec requires us to adjust for per-client clock skew.\\n try:\\n timestamp = int(params[\\\"ts\\\"])\\n except (KeyError, ValueError):\\n msg = \\\"missing or malformed MAC timestamp\\\"\\n return self._respond_unauthorized(request, msg)\\n nonce = params.get(\\\"nonce\\\")\\n if nonce is None:\\n msg = \\\"missing MAC nonce\\\"\\n return self._respond_unauthorized(request, msg)\\n if not self.nonce_manager.is_fresh(token, timestamp, nonce):\\n msg = \\\"MAC has stale token or nonce\\\"\\n return self._respond_unauthorized(request, msg)\\n # OK, they seem like sensible MAC paramters.\\n return params\",\n \"def __init__(self):\\n # self.baud = baud\\n # self.protocol = protocol\\n pass\",\n \"def test_write_with_no_data(self):\\n stream = utils.BytearrayStream()\\n payload = payloads.MACResponsePayload(\\n self.unique_identifier,\\n None)\\n args = (stream,)\\n self.assertRaisesRegex(\\n exceptions.InvalidField,\\n \\\"The mac response mac data is required\\\",\\n payload.write,\\n *args\\n )\",\n \"def __init__(__self__, *,\\n cpu: Optional[pulumi.Input[str]] = None,\\n memory: Optional[pulumi.Input[str]] = None):\\n if cpu is None:\\n cpu = '1'\\n if cpu is not None:\\n pulumi.set(__self__, \\\"cpu\\\", cpu)\\n if memory is None:\\n memory = '2Gi'\\n if memory is not None:\\n pulumi.set(__self__, \\\"memory\\\", memory)\",\n \"def __init__(__self__, *,\\n cpu: Optional[pulumi.Input[str]] = None,\\n memory: Optional[pulumi.Input[str]] = None):\\n if cpu is None:\\n cpu = '1'\\n if cpu is not None:\\n pulumi.set(__self__, \\\"cpu\\\", cpu)\\n if memory is None:\\n memory = '2Gi'\\n if memory is not None:\\n pulumi.set(__self__, \\\"memory\\\", memory)\",\n \"def __init__(__self__, *,\\n ios_app_info: 'outputs.IosAppInfoResponse',\\n ios_robo_test: 'outputs.IosRoboTestResponse',\\n ios_test_loop: 'outputs.IosTestLoopResponse',\\n ios_xc_test: 'outputs.IosXcTestResponse',\\n test_timeout: 'outputs.DurationResponse'):\\n pulumi.set(__self__, \\\"ios_app_info\\\", ios_app_info)\\n pulumi.set(__self__, \\\"ios_robo_test\\\", ios_robo_test)\\n pulumi.set(__self__, \\\"ios_test_loop\\\", ios_test_loop)\\n pulumi.set(__self__, \\\"ios_xc_test\\\", ios_xc_test)\\n pulumi.set(__self__, \\\"test_timeout\\\", test_timeout)\",\n \"def test_init_arg(self):\\n b1 = BaseModel(12)\\n self.assertEqual(type(b1).__name__, \\\"BaseModel\\\")\\n self.assertFalse(hasattr(b1, \\\"12\\\"))\",\n \"def test_init(self):\\n nt.assert_raises(Exception, CisInterface.CisInput, 'error')\",\n \"def from_mac(self):\\n try:\\n dt_obj = self.epoch_2001 + timedelta(seconds=int(mac))\\n self.in_mac = dt_obj.strftime('%Y-%m-%d %H:%M:%S.%f')\\n except Exception as e:\\n if not args.log:\\n pass\\n else:\\n logging.error(str(type(e)) + \\\",\\\" + str(e))\\n self.in_mac = False\\n return self.in_mac\",\n \"def __init__(self, simulator):\\r\\n self.initialize(simulator)\",\n \"def __init__(self, id_phone, header, app_port):\\n path = os.path.join(os.curdir, smartphone_directory)\\n os.mkdir(path) if not os.path.exists(path) else None\\n path = os.path.join(path, id_phone)\\n os.mkdir(path) if not os.path.exists(path) else None\\n super().__init__(path, app_port)\\n\\n self._on = True # smartphone initialized always on\\n self._bluetooth = True # bluetooth initialized always on\\n self._wifi = True # wifi initialized always on\\n self._id_phone = id_phone # skt of the phone\\n self._header = header # header of bluetooth packets\\n self._log_path = os.path.join(path, smartphone_log_filename) # path of smartphone's offline logfile\\n self._packets_root = os.path.join(os.curdir, packets_directory) # packets' root directory\\n\\n if os.path.exists(self._log_path):\\n with open(self._log_path, \\\"r\\\") as j:\\n self._log = json.load(j) # offline logfile load from json file\\n else:\\n self._log = dict() # offline logfile initialization\",\n \"def __init__(self, pin: str) -> None:\\n ...\",\n \"def __init__(self,family = 2, protocol = 2, router_mac=\\\"T\\\",verbose=False,debug=False):\\n \\n\\n # Setup booleans to validate that socket is used correctly\\n self.validFamilyAndProtocol = False;\\n self.validIPAndPort = False;\\n\\n \\n \\n # Setup MAC Data\\n self.my_mac = MAC.my_ad;\\n if self.my_mac != router_mac:\\n self.macDict = dict();\\n self.macDict['router_mac'] = router_mac;\\n\\n if debug:\\n self.macDict['II'] = 'I';\\n self.macDict['IN'] = 'N';\\n self.macDict['IR'] = 'R';\\n self.macDict['ID'] = 'D';\\n \\n self.verbose = verbose;\\n self.debug = debug;\\n\\n # ------ Set Up Family and Protocol ------ #\\n if family!=2: #AF_INET\\n print(\\\"Sorry, this address family is not currently supported!\\\");\\n else:\\n self.family = 2;\\n\\n if protocol!=2: #UDP\\n print(\\\"Sorry, this sending protocol is not currently supported!\\\");\\n else:\\n self.protocol = 2;\\n\\n #Our \\\"UDP\\\" imports (importing our Morse implementation of UDP)\\n if protocol==2: \\n self.validFamilyAndProtocol = True;\\n self.protocol_identifier = 'E'; #The standard defined base 36 char designating UDP\\n\\n # Default bind to simulate the ability of the kernel to generate these at runtime if unbound\\n self.bind((g.server_ip,g.server_port),False);\\n \\n if self.debug:\\n self.bind((\\\"0.0.73.78\\\",\\\"69\\\"));\",\n \"def __init__(self, *args, **kwargs):\\n super().__init__(*args, **kwargs)\\n self.expected_cont_uuid = None\\n self.daos_cmd = None\",\n \"def __init__(self, bus=0, device=0):\\n ...\",\n \"def __init__(self, person_mac=None, person_name=None, person_phone_number=None, notification=None, dest_mac=None): # noqa: E501\\n self.openapi_types = {\\n 'person_mac': List[str],\\n 'person_name': str,\\n 'person_phone_number': str,\\n 'notification': bool,\\n 'dest_mac': str\\n }\\n\\n self.attribute_map = {\\n 'person_mac': 'person_MAC',\\n 'person_name': 'person_name',\\n 'person_phone_number': 'person_phone_number',\\n 'notification': 'notification',\\n 'dest_mac': 'dest_MAC'\\n }\\n\\n self._person_mac = person_mac\\n self._person_name = person_name\\n self._person_phone_number = person_phone_number\\n self._notification = notification\\n self._dest_mac = dest_mac\",\n \"def test_create_device(self):\\n pass\",\n \"def test_create_device(self):\\n pass\",\n \"def __init__(self, machine, vm_name):\\n self.machine = machine\\n self.vm_name = vm_name\",\n \"def __init__(self, os_device_name: str, mac_address: str = None,\\n subnets: 'list[SubnetAffiliation]' = None):\\n self.os_device_name = os_device_name\\n self.mac_address = mac_address\\n self.subnets = []\\n\\n if subnets:\\n for subnet in subnets:\\n self.add_to_subnet(subnet)\",\n \"def __init__(self, device: Device, router: KeeneticRouter) -> None:\\n self._device = device\\n self._router = router\\n self._last_seen = (\\n dt_util.utcnow() if device.mac in router.last_devices else None\\n )\",\n \"def __init__(\\n self, name: str = \\\"\\\", protocol: int | None = None, **kwargs: Any\\n ) -> None:\\n\\n super().__init__(name=name, **kwargs)\\n if not ipaddress:\\n raise SoftDependencyError(\\\"ipaddress\\\")\\n if protocol not in [None, 4, 6]:\\n raise ValueError(\\\"IpAddress protocol needs to be either 4, 6 or None\\\")\\n self.protocol = protocol\",\n \"def __init__(self, platform, test_type, fork_id, branch, commit, pr_nr=0, token=None) -> None:\\n self.platform = platform\\n self.test_type = test_type\\n self.fork_id = fork_id\\n self.branch = branch\\n self.commit = commit\\n self.pr_nr = pr_nr\\n if token is None:\\n # Auto-generate token\\n token = self.create_token(64)\\n self.token = token\",\n \"def __init__(\\n self, name: str = \\\"\\\", protocol: int | None = None, **kwargs: Any\\n ) -> None:\\n\\n super().__init__(name=name, **kwargs)\\n\\n if protocol not in [None, 4, 6]:\\n raise ValueError(\\\"IpAddress protocol needs to be either 4, 6 or None\\\")\\n self.protocol = protocol\",\n \"def __init__(self):\\n raise NoInitiation\",\n \"def __init__(__self__, *,\\n host: Optional[pulumi.Input[str]] = None,\\n port: Optional[pulumi.Input[int]] = None):\\n if host is not None:\\n pulumi.set(__self__, \\\"host\\\", host)\\n if port is not None:\\n pulumi.set(__self__, \\\"port\\\", port)\",\n \"def test_initialization(self):\\n self.assertEqual(self.installer.host_name, \\\"ec2.amazon.com\\\")\\n self.assertEqual(self.installer.user_name, \\\"ec2\\\")\\n self.assertEqual(self.installer.os, \\\"ubuntu\\\")\\n self.assertEqual(self.installer.key_path, \\\"./ODFEAMIInstanceKey.pem\\\")\\n self.assertEqual(self.installer.RPM_package_version, \\\"1.4.0\\\")\\n self.assertEqual(self.installer.APT_OSS_version, \\\"7.4.2\\\")\",\n \"def test_init_(self):\\n card = Card('Archer', 3, 0, 2)\\n self.assertEqual(card.name, 'Archer')\\n self.assertEqual(card.attack, 3)\\n self.assertEqual(card.money, 0)\\n self.assertEqual(card.cost, 2)\",\n \"def call_init(mac_address, ip_address, start_port, free_ports):\\n url = INIT_URL\\n init_dict = {'IPAddress': ip_address, 'MacAddress': mac_address, 'OpenPorts': free_ports, 'StartPort': start_port}\\n logging.info(\\\"Calling coordinator at url: %s, with dict: %s\\\", url, str(init_dict))\\n try:\\n resp = requests.post(url, json=init_dict, timeout=10)\\n except requests.exceptions.RequestException as e:\\n return None, e\\n return resp, None\",\n \"def test_init_kwarg(self):\\n b1 = BaseModel(name=\\\"Red\\\")\\n self.assertEqual(type(b1).__name__, \\\"BaseModel\\\")\\n self.assertTrue(hasattr(b1, \\\"name\\\"))\\n self.assertTrue(hasattr(b1, \\\"__class__\\\"))\\n self.assertFalse(hasattr(b1, \\\"id\\\"))\\n self.assertFalse(hasattr(b1, \\\"created_at\\\"))\\n self.assertFalse(hasattr(b1, \\\"updated_at\\\"))\",\n \"def test_init_default_values(self):\\n card = Card('Archer')\\n self.assertEqual(card.name, 'Archer')\\n self.assertEqual(card.attack, 0)\\n self.assertEqual(card.money, 0)\\n self.assertEqual(card.cost, 0)\",\n \"def __init__(self):\\n # assert(self.validate('61882613000194'))\\n # assert(self.validate('061882613000190'))\\n # assert(not self.validate('61882613000195'))\\n pass\",\n \"def __init__(self, hostiface: str, **kwargs):\\n super().__init__(**kwargs)\\n self.hostiface = hostiface\",\n \"def test_002_init(self):\\n self.assertIsInstance(ionchrom.ionchrom(\\\"id\\\"),ionchrom.ionchrom)\",\n \"def test_init(self):\\n nt.assert_raises(Exception, CisInterface.CisOutput, 'error')\",\n \"def __init__(self, addr, name=None, i2c=None):\\n\\n # Initialize the device and save the simulator\\n super().__init__(addr, name=name, i2c=i2c)\\n self.sim = None\",\n \"def mock_constructor(host, username, password, port, web_proto):\\n mock_device.host = host\\n mock_device.username = username\\n mock_device.password = password\\n mock_device.port = port\\n return mock_device\",\n \"def __init__(self) -> None:\\n self.ip_address: str | None = None\",\n \"def test_constructor(self):\\n assert self.parser is not None\",\n \"def valid_mitemp_mac(mac, pat=re.compile(r\\\"4C:65:A8:[0-9A-F]{2}:[0-9A-F]{2}:[0-9A-F]{2}\\\")):\\n if not pat.match(mac.upper()):\\n raise argparse.ArgumentTypeError('The MAC address \\\"{}\\\" seems to be in the wrong format'.format(mac))\\n return mac\",\n \"def __init__(self):\\n super(UpnpEmbeddedDevice, self).__init__()\\n return\",\n \"def __eq__(self,other):\\n if isinstance(other, self.__class__):\\n return self.mac == other.mac\\n else: return False\",\n \"def __init__(self, game, net_args: DotDict, architecture: str) -> None:\\n super().__init__(game, net_args, Agents.MuZeroNetworks[architecture])\\n self.action_size = game.getActionSize()\\n self.architecture = architecture\",\n \"def test_001_init(self):\\n self.assertRaises(TypeError,ionchrom.ionchrom)\",\n \"def test_write_with_no_unique_identifier(self):\\n stream = utils.BytearrayStream()\\n payload = payloads.MACResponsePayload(\\n None,\\n self.mac_data)\\n args = (stream,)\\n self.assertRaisesRegex(\\n exceptions.InvalidField,\\n \\\"The mac response unique identifier is required\\\",\\n payload.write,\\n *args\\n )\",\n \"def test_init(self):\\n with self.assertRaises(ValueError):\\n TraxionPay(api_key=self.api_key)\",\n \"def __init__(self, device: Dict[str, Union[str, int, float]]) -> None:\\n super().__init__()\\n log_int.debug(f\\\"Initializing serial device for {device['name']} :: Port: {device['port']} - Baud rate: \\\"\\n f\\\"{device['baudrate']} - Timeout: {device['timeout']} - RTS/CTS: {bool(device['flowcontrol'])}\\\")\\n self.device = serial.Serial(port=device['port'], baudrate=device['baudrate'],\\n timeout=device['timeout'], rtscts=device['flowcontrol'])\",\n \"def checkMac(self, mac):\\n\\t\\tif mac in self.seenMacs:\\n\\t\\t\\treturn True\\n\\t\\treturn False\",\n \"def __init__(__self__, *,\\n spec: Optional[pulumi.Input['InstanceSpecArgs']] = None):\\n if spec is not None:\\n pulumi.set(__self__, \\\"spec\\\", spec)\",\n \"def initialize(self) -> bool:\\n raise NotImplementedError\",\n \"def __init__(__self__, *,\\n os_version: Optional[pulumi.Input['WindowsNodeConfigOsVersion']] = None):\\n if os_version is not None:\\n pulumi.set(__self__, \\\"os_version\\\", os_version)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7700126","0.718434","0.7076505","0.69038445","0.68528235","0.64499795","0.6309808","0.6301054","0.6203087","0.616466","0.6155142","0.61442065","0.61114347","0.609657","0.607744","0.6011186","0.6001735","0.59643024","0.5931269","0.5910585","0.5905488","0.5900017","0.58970076","0.5887437","0.5868467","0.58156866","0.58098906","0.5798898","0.57897395","0.57893056","0.5776164","0.576799","0.57493","0.57467663","0.5744599","0.5741692","0.5729985","0.5715522","0.5682917","0.5682833","0.56724095","0.56714064","0.5665011","0.56552356","0.56399184","0.5634584","0.5624045","0.56007874","0.55932105","0.558716","0.55842066","0.55776757","0.5565055","0.5565055","0.554807","0.55428165","0.5539181","0.5534758","0.5533624","0.5527534","0.552624","0.5518679","0.55010295","0.54952806","0.5493209","0.5491021","0.5491021","0.5488888","0.548633","0.5474327","0.5467995","0.54676527","0.54654783","0.5461927","0.5459847","0.54535735","0.5444591","0.54386","0.54383713","0.5437683","0.54362726","0.54192287","0.5417626","0.54146385","0.5406573","0.5402362","0.53989506","0.53954846","0.5390986","0.53896534","0.53895843","0.5379548","0.5374608","0.5371951","0.5358102","0.5355055","0.53475034","0.5345975","0.5344683","0.53414124"],"string":"[\n \"0.7700126\",\n \"0.718434\",\n \"0.7076505\",\n \"0.69038445\",\n \"0.68528235\",\n \"0.64499795\",\n \"0.6309808\",\n \"0.6301054\",\n \"0.6203087\",\n \"0.616466\",\n \"0.6155142\",\n \"0.61442065\",\n \"0.61114347\",\n \"0.609657\",\n \"0.607744\",\n \"0.6011186\",\n \"0.6001735\",\n \"0.59643024\",\n \"0.5931269\",\n \"0.5910585\",\n \"0.5905488\",\n \"0.5900017\",\n \"0.58970076\",\n \"0.5887437\",\n \"0.5868467\",\n \"0.58156866\",\n \"0.58098906\",\n \"0.5798898\",\n \"0.57897395\",\n \"0.57893056\",\n \"0.5776164\",\n \"0.576799\",\n \"0.57493\",\n \"0.57467663\",\n \"0.5744599\",\n \"0.5741692\",\n \"0.5729985\",\n \"0.5715522\",\n \"0.5682917\",\n \"0.5682833\",\n \"0.56724095\",\n \"0.56714064\",\n \"0.5665011\",\n \"0.56552356\",\n \"0.56399184\",\n \"0.5634584\",\n \"0.5624045\",\n \"0.56007874\",\n \"0.55932105\",\n \"0.558716\",\n \"0.55842066\",\n \"0.55776757\",\n \"0.5565055\",\n \"0.5565055\",\n \"0.554807\",\n \"0.55428165\",\n \"0.5539181\",\n \"0.5534758\",\n \"0.5533624\",\n \"0.5527534\",\n \"0.552624\",\n \"0.5518679\",\n \"0.55010295\",\n \"0.54952806\",\n \"0.5493209\",\n \"0.5491021\",\n \"0.5491021\",\n \"0.5488888\",\n \"0.548633\",\n \"0.5474327\",\n \"0.5467995\",\n \"0.54676527\",\n \"0.54654783\",\n \"0.5461927\",\n \"0.5459847\",\n \"0.54535735\",\n \"0.5444591\",\n \"0.54386\",\n \"0.54383713\",\n \"0.5437683\",\n \"0.54362726\",\n \"0.54192287\",\n \"0.5417626\",\n \"0.54146385\",\n \"0.5406573\",\n \"0.5402362\",\n \"0.53989506\",\n \"0.53954846\",\n \"0.5390986\",\n \"0.53896534\",\n \"0.53895843\",\n \"0.5379548\",\n \"0.5374608\",\n \"0.5371951\",\n \"0.5358102\",\n \"0.5355055\",\n \"0.53475034\",\n \"0.5345975\",\n \"0.5344683\",\n \"0.53414124\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.79045194"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":3989,"cells":{"query":{"kind":"string","value":"Test the __init__ method when parameter 'ip' is None. Since the field is optional, it should pass."},"document":{"kind":"string","value":"def test_init_no_ip(self):\n client = ClientInfo(\"cc:cc:cc:cc:cc:cc\", ip=None, ap_info=self.ap)\n self.assertEqual(client.ip, None)\n self.assertEqual(client.ip_bytes, None)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_init_no_ip(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n ap = APInfo(port_id=1, ip=None, mac=\"bb:bb:bb:bb:bb:bb\", radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\n self.assertEqual(ap.ip, None)","def __init__(__self__, *,\n ip: Optional[pulumi.Input['IPAccessControlArgs']] = None):\n if ip is not None:\n pulumi.set(__self__, \"ip\", ip)","def __init__(__self__, *,\n ip: Optional[pulumi.Input['IPAccessControlArgs']] = None):\n if ip is not None:\n pulumi.set(__self__, \"ip\", ip)","def __init__(self) -> None:\n self.ip_address: str | None = None","def __init__(__self__, *,\n host_ip: Optional[pulumi.Input[str]] = None,\n port: Optional[pulumi.Input[str]] = None):\n if host_ip is not None:\n pulumi.set(__self__, \"host_ip\", host_ip)\n if port is not None:\n pulumi.set(__self__, \"port\", port)","def __init__(\n self, name: str = \"\", protocol: int | None = None, **kwargs: Any\n ) -> None:\n\n super().__init__(name=name, **kwargs)\n if not ipaddress:\n raise SoftDependencyError(\"ipaddress\")\n if protocol not in [None, 4, 6]:\n raise ValueError(\"IpAddress protocol needs to be either 4, 6 or None\")\n self.protocol = protocol","def __init__(\n self, name: str = \"\", protocol: int | None = None, **kwargs: Any\n ) -> None:\n\n super().__init__(name=name, **kwargs)\n\n if protocol not in [None, 4, 6]:\n raise ValueError(\"IpAddress protocol needs to be either 4, 6 or None\")\n self.protocol = protocol","def test_validate_ip_ok():\n ip = '1.1.1.1'\n assert howisresolved.validate_ip(ip) is None","def test_field_none_nullable(self):\n node_dict = {\n 'host_name': 'abc'\n }\n try:\n Node(**node_dict)\n except Exception as e:\n self.assertEqual(type(e), ValueError)","def __init__(__self__, *,\n ip_tag_type: Optional[pulumi.Input[str]] = None,\n tag: Optional[pulumi.Input[str]] = None):\n if ip_tag_type is not None:\n pulumi.set(__self__, \"ip_tag_type\", ip_tag_type)\n if tag is not None:\n pulumi.set(__self__, \"tag\", tag)","def __init__(self, allow_none=False):\n if allow_none:\n self.validate = self.validate_none\n self.info = self.info_none\n self.fast_validate = (2, None)\n else:\n self.fast_validate = (2,)","def __init__(__self__, *,\n destination_pool_name: Optional[pulumi.Input[str]] = None,\n ip: Optional[pulumi.Input[str]] = None):\n if destination_pool_name is not None:\n pulumi.set(__self__, \"destination_pool_name\", destination_pool_name)\n if ip is not None:\n pulumi.set(__self__, \"ip\", ip)","def test_init_no_mac(self):\n with self.assertRaises(ValueError):\n client = ClientInfo(None, ip=\"3.3.3.3\", ap_info=self.ap)","def __init__(self, ip, mask):\n self.vip = ip\n self.mask = mask","def __init__(__self__, *,\n end_ip: pulumi.Input[str],\n start_ip: pulumi.Input[str]):\n pulumi.set(__self__, \"end_ip\", end_ip)\n pulumi.set(__self__, \"start_ip\", start_ip)","def __init__(__self__, *,\n host: Optional[pulumi.Input[str]] = None,\n port: Optional[pulumi.Input[int]] = None):\n if host is not None:\n pulumi.set(__self__, \"host\", host)\n if port is not None:\n pulumi.set(__self__, \"port\", port)","def __init__(self, ip: str):\n self.api = API(f\"http://{ip}\")\n self.ip = ip\n self.board_data = None","def test_no_ip_address_passed(self, api_client):\n runner = CliRunner()\n\n with patch(\"greynoise.cli.helper.sys\") as sys:\n sys.stdin.isatty.return_value = True\n result = runner.invoke(\n subcommand.ip, parent=Context(main, info_name=\"greynoise\")\n )\n assert result.exit_code == -1\n assert \"Usage: greynoise ip\" in result.output\n api_client.ip.assert_not_called()","def __init__(__self__, *,\n ignore_missing_v_net_service_endpoint: Optional[pulumi.Input[bool]] = None,\n subnet_id: Optional[pulumi.Input[str]] = None):\n if ignore_missing_v_net_service_endpoint is not None:\n pulumi.set(__self__, \"ignore_missing_v_net_service_endpoint\", ignore_missing_v_net_service_endpoint)\n if subnet_id is not None:\n pulumi.set(__self__, \"subnet_id\", subnet_id)","def test_optional_arg(self):\n obj = Base()\n self.assertEqual(obj.id, 1)","def __init__(__self__, *,\n droplet_id: Optional[pulumi.Input[int]] = None,\n ip_address: Optional[pulumi.Input[str]] = None,\n region: Optional[pulumi.Input[str]] = None,\n urn: Optional[pulumi.Input[str]] = None):\n if droplet_id is not None:\n pulumi.set(__self__, \"droplet_id\", droplet_id)\n if ip_address is not None:\n pulumi.set(__self__, \"ip_address\", ip_address)\n if region is not None:\n pulumi.set(__self__, \"region\", region)\n if urn is not None:\n pulumi.set(__self__, \"urn\", urn)","def __init__(__self__, *,\n allow: Optional[pulumi.Input[Sequence[pulumi.Input['IPRangeArgs']]]] = None):\n if allow is not None:\n pulumi.set(__self__, \"allow\", allow)","def __init__(__self__, *,\n region: pulumi.Input[str],\n droplet_id: Optional[pulumi.Input[int]] = None,\n ip_address: Optional[pulumi.Input[str]] = None):\n pulumi.set(__self__, \"region\", region)\n if droplet_id is not None:\n pulumi.set(__self__, \"droplet_id\", droplet_id)\n if ip_address is not None:\n pulumi.set(__self__, \"ip_address\", ip_address)","def __init__(self):\n self.clean_optional()","def __init__(__self__, *,\n resourcegroup: pulumi.Input[str],\n server: pulumi.Input[str],\n endipaddress: Optional[pulumi.Input[str]] = None,\n startipaddress: Optional[pulumi.Input[str]] = None):\n pulumi.set(__self__, \"resourcegroup\", resourcegroup)\n pulumi.set(__self__, \"server\", server)\n if endipaddress is not None:\n pulumi.set(__self__, \"endipaddress\", endipaddress)\n if startipaddress is not None:\n pulumi.set(__self__, \"startipaddress\", startipaddress)","def __init__(self, ip=None, header=None, hostname=None, aliases=None):\n self.id = header or \"\"\n self.hostname = hostname or \"\"\n self.aliases = aliases or []\n self.ip = \"\"\n if ip:\n try:\n self.ip=ipaddress.ip_address(ip)\n except ipaddress.AddressValueError as e:\n print(\"Error parsing ip address from hosts.conf file\")\n raise e\n self.stored_state = None","def __init__(self, **kwargs):\n self.swagger_types = {\n 'assign_public_ip': 'bool',\n 'defined_tags': 'dict(str, dict(str, object))',\n 'display_name': 'str',\n 'freeform_tags': 'dict(str, str)',\n 'hostname_label': 'str',\n 'nsg_ids': 'list[str]',\n 'private_ip': 'str',\n 'skip_source_dest_check': 'bool',\n 'subnet_id': 'str'\n }\n\n self.attribute_map = {\n 'assign_public_ip': 'assignPublicIp',\n 'defined_tags': 'definedTags',\n 'display_name': 'displayName',\n 'freeform_tags': 'freeformTags',\n 'hostname_label': 'hostnameLabel',\n 'nsg_ids': 'nsgIds',\n 'private_ip': 'privateIp',\n 'skip_source_dest_check': 'skipSourceDestCheck',\n 'subnet_id': 'subnetId'\n }\n\n self._assign_public_ip = None\n self._defined_tags = None\n self._display_name = None\n self._freeform_tags = None\n self._hostname_label = None\n self._nsg_ids = None\n self._private_ip = None\n self._skip_source_dest_check = None\n self._subnet_id = None","def __init__(__self__,\n resource_name: str,\n args: ReservedIpArgs,\n opts: Optional[pulumi.ResourceOptions] = None):\n ...","def __init__(self, **kwargs):\n members = ('ip', 'mac', 'port', 'timeout', 'flags',\n 'index', 'tag', 'hostname')\n\n # copy the given value or default to None\n for member in members:\n self.__dict__[member] = kwargs.setdefault (member, None)","def test_init_without_kwargs(self):\n c = City()\n self.assertTrue('id' in c.__dict__)\n self.assertTrue('created_at' in c.__dict__)\n self.assertTrue('updated_at' in c.__dict__)\n self.assertIsInstance(c, BaseModel)","def validate_ip(argname, param, safe, optional = False):\n _validate_one(argname, param, safe, _check_ip, optional)","def test_init_wrong_ap_type(self):\n ap_wrong = object()\n with self.assertRaises(ValueError):\n client = ClientInfo(\"cc:cc:cc:cc:cc:cc\",\n ip=\"3.3.3.3\", ap_info=ap_wrong)","def __init__(__self__, *,\n protocol: Optional[pulumi.Input[str]] = None,\n url: Optional[pulumi.Input[str]] = None):\n if protocol is not None:\n pulumi.set(__self__, \"protocol\", protocol)\n if url is not None:\n pulumi.set(__self__, \"url\", url)","def __init__(__self__, *,\n public_ips: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceReferenceArgs']]]] = None):\n if public_ips is not None:\n pulumi.set(__self__, \"public_ips\", public_ips)","def __init__(__self__, *,\n cidr: pulumi.Input[str],\n resource_group_name: pulumi.Input[str],\n commissioning_enabled: Optional[pulumi.Input[bool]] = None,\n internet_advertising_disabled: Optional[pulumi.Input[bool]] = None,\n location: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None,\n parent_custom_ip_prefix_id: Optional[pulumi.Input[str]] = None,\n roa_validity_end_date: Optional[pulumi.Input[str]] = None,\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n wan_validation_signed_message: Optional[pulumi.Input[str]] = None,\n zones: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\n pulumi.set(__self__, \"cidr\", cidr)\n pulumi.set(__self__, \"resource_group_name\", resource_group_name)\n if commissioning_enabled is not None:\n pulumi.set(__self__, \"commissioning_enabled\", commissioning_enabled)\n if internet_advertising_disabled is not None:\n pulumi.set(__self__, \"internet_advertising_disabled\", internet_advertising_disabled)\n if location is not None:\n pulumi.set(__self__, \"location\", location)\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if parent_custom_ip_prefix_id is not None:\n pulumi.set(__self__, \"parent_custom_ip_prefix_id\", parent_custom_ip_prefix_id)\n if roa_validity_end_date is not None:\n pulumi.set(__self__, \"roa_validity_end_date\", roa_validity_end_date)\n if tags is not None:\n pulumi.set(__self__, \"tags\", tags)\n if wan_validation_signed_message is not None:\n pulumi.set(__self__, \"wan_validation_signed_message\", wan_validation_signed_message)\n if zones is not None:\n pulumi.set(__self__, \"zones\", zones)","def test_control_create_with_empty_field(self, field):\n request = self.prepare_control_request_body()\n request[field] = None\n\n response = self.api.post(all_models.Control, data=request)\n\n self.assert400(response)","def test_init_correct(self):\n client = ClientInfo(\"cc:cc:cc:cc:cc:cc\", ip=\"3.3.3.3\", ap_info=self.ap)\n self.assertEqual(client.ip, \"3.3.3.3\")\n self.assertEqual(client.ip_bytes, b'\\x03\\x03\\x03\\x03')","def __init__(__self__, *,\n id: str,\n private_ip_address: Optional[str] = None):\n pulumi.set(__self__, \"id\", id)\n if private_ip_address is not None:\n pulumi.set(__self__, \"private_ip_address\", private_ip_address)","def test_creation_notallow_none():\n with pytest.raises(ValueError) as __:\n value = None\n __ = param.Integer(value=value, allow_None=False)","def validate_ip(self, ip):\n if not ip:\n raise ValidationError(\"Please provide an actual IP or web address. You gave me: \" + ip)","def __init__(__self__, *,\n destination_pool_name: pulumi.Input[str],\n ip: pulumi.Input[str]):\n pulumi.set(__self__, \"destination_pool_name\", destination_pool_name)\n pulumi.set(__self__, \"ip\", ip)","def test_field_nullable(self):\n node_dict = {\n 'host_name': 'abc',\n 'local_router_id': '1.1.1.1',\n 'as_num': 100,\n 'bgpls_id': '0.0.0.0',\n 'igp_id': '0.0.0.0'\n }\n node = Node(**node_dict)\n for name, field in node_dict.items():\n self.assertEqual(field, node.__dict__[name])","def __init__(__self__, *,\n cidr: Optional[pulumi.Input[str]] = None,\n commissioning_enabled: Optional[pulumi.Input[bool]] = None,\n internet_advertising_disabled: Optional[pulumi.Input[bool]] = None,\n location: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None,\n parent_custom_ip_prefix_id: Optional[pulumi.Input[str]] = None,\n resource_group_name: Optional[pulumi.Input[str]] = None,\n roa_validity_end_date: Optional[pulumi.Input[str]] = None,\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n wan_validation_signed_message: Optional[pulumi.Input[str]] = None,\n zones: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\n if cidr is not None:\n pulumi.set(__self__, \"cidr\", cidr)\n if commissioning_enabled is not None:\n pulumi.set(__self__, \"commissioning_enabled\", commissioning_enabled)\n if internet_advertising_disabled is not None:\n pulumi.set(__self__, \"internet_advertising_disabled\", internet_advertising_disabled)\n if location is not None:\n pulumi.set(__self__, \"location\", location)\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if parent_custom_ip_prefix_id is not None:\n pulumi.set(__self__, \"parent_custom_ip_prefix_id\", parent_custom_ip_prefix_id)\n if resource_group_name is not None:\n pulumi.set(__self__, \"resource_group_name\", resource_group_name)\n if roa_validity_end_date is not None:\n pulumi.set(__self__, \"roa_validity_end_date\", roa_validity_end_date)\n if tags is not None:\n pulumi.set(__self__, \"tags\", tags)\n if wan_validation_signed_message is not None:\n pulumi.set(__self__, \"wan_validation_signed_message\", wan_validation_signed_message)\n if zones is not None:\n pulumi.set(__self__, \"zones\", zones)","def __init__(__self__, *,\n allowed_host_ports: Optional[pulumi.Input[Sequence[pulumi.Input['PortRangeArgs']]]] = None,\n application_security_groups: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n node_public_ip_tags: Optional[pulumi.Input[Sequence[pulumi.Input['IPTagArgs']]]] = None):\n if allowed_host_ports is not None:\n pulumi.set(__self__, \"allowed_host_ports\", allowed_host_ports)\n if application_security_groups is not None:\n pulumi.set(__self__, \"application_security_groups\", application_security_groups)\n if node_public_ip_tags is not None:\n pulumi.set(__self__, \"node_public_ip_tags\", node_public_ip_tags)","def validate_input(self, IP, Port):\n exception = ServerInitError\n try:\n if IP != None:\n if re.match(IPRegex, IP):\n self.IP = IP\n else:\n exception = InavlidIPError\n raise\n\n if Port != None:\n if int(Port) in range(0,65535):\n self.Port = Port\n else:\n exception = InvalidPortError\n raise\n except:\n traceback_print_exc()","def __init__(__self__, *,\n address: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None,\n subnet_prefix_length: Optional[pulumi.Input[int]] = None):\n if address is not None:\n pulumi.set(__self__, \"address\", address)\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if subnet_prefix_length is not None:\n pulumi.set(__self__, \"subnet_prefix_length\", subnet_prefix_length)","def test_same_ip(self):\n self.create_ptr(\n ip_str='128.193.0.2', ip_type='4', fqdn='foo1.oregonstate.edu')\n\n with self.assertRaises(ValidationError):\n self.create_ptr(\n ip_str='128.193.0.2', ip_type='4', fqdn='foo2.oregonstate.edu')","def __init__(self,\r\n name=None,\r\n lan_ip=None,\r\n uplink=None,\r\n public_port=None,\r\n local_port=None,\r\n allowed_ips=None,\r\n protocol=None):\r\n\r\n # Initialize members of the class\r\n self.name = name\r\n self.lan_ip = lan_ip\r\n self.uplink = uplink\r\n self.public_port = public_port\r\n self.local_port = local_port\r\n self.allowed_ips = allowed_ips\r\n self.protocol = protocol","def __init__(__self__, *,\n dns_servers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n gateway: Optional[pulumi.Input[str]] = None,\n infra_vnet_profile: Optional[pulumi.Input['VirtualNetworksPropertiesInfraVnetProfileArgs']] = None,\n ip_address_prefix: Optional[pulumi.Input[str]] = None,\n vip_pool: Optional[pulumi.Input[Sequence[pulumi.Input['VirtualNetworksPropertiesVipPoolArgs']]]] = None,\n vmip_pool: Optional[pulumi.Input[Sequence[pulumi.Input['VirtualNetworksPropertiesVmipPoolArgs']]]] = None):\n if dns_servers is not None:\n pulumi.set(__self__, \"dns_servers\", dns_servers)\n if gateway is not None:\n pulumi.set(__self__, \"gateway\", gateway)\n if infra_vnet_profile is not None:\n pulumi.set(__self__, \"infra_vnet_profile\", infra_vnet_profile)\n if ip_address_prefix is not None:\n pulumi.set(__self__, \"ip_address_prefix\", ip_address_prefix)\n if vip_pool is not None:\n pulumi.set(__self__, \"vip_pool\", vip_pool)\n if vmip_pool is not None:\n pulumi.set(__self__, \"vmip_pool\", vmip_pool)","def test_init_correct(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n ap = APInfo(port_id=1, ip=\"2.2.2.2\", mac=\"bb:bb:bb:bb:bb:bb\", radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\n\n self.assertEqual(ap.ip, '2.2.2.2')","def test_noop(self):\n self.assertFalse(helpers.getBcastAddrforIPv4())\n self.assertIsNone(helpers.no_op())","def test_get_source_ip(self):\n pass","def __init__(__self__, *,\n idle_timeout_in_minutes: pulumi.Input[int],\n location: pulumi.Input[str],\n public_ip_address_version: pulumi.Input[str],\n public_ip_allocation_method: pulumi.Input[str],\n resource_group: pulumi.Input[str],\n sku_name: pulumi.Input[str],\n ip_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\n pulumi.set(__self__, \"idle_timeout_in_minutes\", idle_timeout_in_minutes)\n pulumi.set(__self__, \"location\", location)\n pulumi.set(__self__, \"public_ip_address_version\", public_ip_address_version)\n pulumi.set(__self__, \"public_ip_allocation_method\", public_ip_allocation_method)\n pulumi.set(__self__, \"resource_group\", resource_group)\n pulumi.set(__self__, \"sku_name\", sku_name)\n if ip_tags is not None:\n pulumi.set(__self__, \"ip_tags\", ip_tags)","def test_constructor_fill_fields(self):\r\n builder = IndicatorBuilder(\"url\")\r\n\r\n self.assertEqual(builder.url, \"url\")\r\n self.assertEqual(builder.data, {})","def __init__(__self__,\n resource_name: str,\n opts: Optional[pulumi.ResourceOptions] = None,\n destination_pool_name: Optional[pulumi.Input[str]] = None,\n ip: Optional[pulumi.Input[str]] = None,\n __props__=None):\n ...","def test_hostport_or_network(self):\n # If providing host or port, must provide both\n with self.assertRaises(AssertionError):\n a = LedgerApi(host='host')\n with self.assertRaises(AssertionError):\n a = LedgerApi(port=1234)\n # If providing network, may not provide host or port\n with self.assertRaises(AssertionError):\n a = LedgerApi(host='host', network='alpha')\n with self.assertRaises(AssertionError):\n a = LedgerApi(port=1234, network='alpha')\n with self.assertRaises(AssertionError):\n a = LedgerApi(host='host', port=1234, network='alpha')","def __init__(\n self,\n host: str,\n database: str,\n user: str,\n password: str\n ) -> None:\n self.host: str = host\n self.database: str = database\n self.user: str = user\n self.password: str = password\n\n # all these values are needed\n for attr in ('host', 'database', 'user', 'password'):\n if not getattr(self, attr):\n raise ValueError(f\"{attr} must not be None!\")","def __init__(__self__, *,\n location: pulumi.Input[str],\n public_ip_address_name: pulumi.Input[str],\n resource_group: pulumi.Input[str],\n subnet_name: pulumi.Input[str],\n vnet_name: pulumi.Input[str]):\n pulumi.set(__self__, \"location\", location)\n pulumi.set(__self__, \"public_ip_address_name\", public_ip_address_name)\n pulumi.set(__self__, \"resource_group\", resource_group)\n pulumi.set(__self__, \"subnet_name\", subnet_name)\n pulumi.set(__self__, \"vnet_name\", vnet_name)","def test_exclude_ip_ban(self):\n pass","def test_basemodel_basic_instance_none(self):\n with self.assertRaises(TypeError):\n BaseModel(None)","def __init__(self, ip):\r\n\t\tself.ip = str(ip)\r\n\t\tself.ice = IceParser(self.ip)\r\n\t\tself.versions_list = []\r\n\t\tself.alarm_list = []\r\n\t\tself.status_list = []","def test_required_city_missing(self):\r\n self.url_params['city'] = ''\r\n response = self.client.post(self.url, self.url_params)\r\n self.assertEqual(response.status_code, 400)\r\n obj = json.loads(response.content)\r\n self.assertEqual(\r\n obj['value'],\r\n u'A city is required',\r\n )","def __init__(__self__, *,\n endpoint_id: pulumi.Input[str],\n client_ip_preservation_enabled: Optional[pulumi.Input[bool]] = None,\n weight: Optional[pulumi.Input[int]] = None):\n pulumi.set(__self__, \"endpoint_id\", endpoint_id)\n if client_ip_preservation_enabled is not None:\n pulumi.set(__self__, \"client_ip_preservation_enabled\", client_ip_preservation_enabled)\n if weight is not None:\n pulumi.set(__self__, \"weight\", weight)","def __init__(__self__, *,\n http_proxy: Optional[pulumi.Input[str]] = None,\n https_proxy: Optional[pulumi.Input[str]] = None,\n no_proxy: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n trusted_ca: Optional[pulumi.Input[str]] = None):\n if http_proxy is not None:\n pulumi.set(__self__, \"http_proxy\", http_proxy)\n if https_proxy is not None:\n pulumi.set(__self__, \"https_proxy\", https_proxy)\n if no_proxy is not None:\n pulumi.set(__self__, \"no_proxy\", no_proxy)\n if trusted_ca is not None:\n pulumi.set(__self__, \"trusted_ca\", trusted_ca)","def test_init(self):\n with self.assertRaises(ValueError):\n TraxionPay(api_key=self.api_key)","def __init__(__self__, *,\n group_id: pulumi.Input[str],\n ip_protocol: pulumi.Input[str],\n cidr_ip: Optional[pulumi.Input[str]] = None,\n cidr_ipv6: Optional[pulumi.Input[str]] = None,\n description: Optional[pulumi.Input[str]] = None,\n destination_prefix_list_id: Optional[pulumi.Input[str]] = None,\n destination_security_group_id: Optional[pulumi.Input[str]] = None,\n from_port: Optional[pulumi.Input[int]] = None,\n to_port: Optional[pulumi.Input[int]] = None):\n pulumi.set(__self__, \"group_id\", group_id)\n pulumi.set(__self__, \"ip_protocol\", ip_protocol)\n if cidr_ip is not None:\n pulumi.set(__self__, \"cidr_ip\", cidr_ip)\n if cidr_ipv6 is not None:\n pulumi.set(__self__, \"cidr_ipv6\", cidr_ipv6)\n if description is not None:\n pulumi.set(__self__, \"description\", description)\n if destination_prefix_list_id is not None:\n pulumi.set(__self__, \"destination_prefix_list_id\", destination_prefix_list_id)\n if destination_security_group_id is not None:\n pulumi.set(__self__, \"destination_security_group_id\", destination_security_group_id)\n if from_port is not None:\n pulumi.set(__self__, \"from_port\", from_port)\n if to_port is not None:\n pulumi.set(__self__, \"to_port\", to_port)","def __init__(__self__,\n resource_name: str,\n opts: Optional[pulumi.ResourceOptions] = None,\n droplet_id: Optional[pulumi.Input[int]] = None,\n ip_address: Optional[pulumi.Input[str]] = None,\n region: Optional[pulumi.Input[str]] = None,\n __props__=None):\n ...","def test_allow_none():\n value = None\n num_a = param.Integer(value=value, allow_None=True)\n assert num_a.value == value","def test_init_attributes(self):\n t = self.Test({'id': 1, 'poop': 'abc'})\n\n self.assertEqual(t.id, 1)\n self.assertEqual(t.name, None)\n self.assertRaises(AttributeError, t.__getattribute__, 'poop')","def test_default_country_by_ip_no_settings(self):\n\n response = self.client.get(\n reverse(\"billing_info\"), HTTP_X_FORWARDED_FOR=\"85.214.132.117\"\n )\n self.assertEqual(response.status_code, 200)\n self.assertContains(\n response, '<option value=\"\" selected>---------</option>', html=True\n )","def test_State_none_kwargs(self):\n with self.assertRaises(TypeError):\n State(id=None, created_at=None, updated_at=None)","def __init__(self, IP=None, Port=None):\n\n self.validate_input(IP, Port)\n self.url = ('http://{}:{}/v2/'.format(self.IP, self.Port))\n self.get_templates()\n self.get_data()\n self.telnet_threads = []","def test_init_no_mac(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n with self.assertRaises(ValueError):\n ap = APInfo(port_id=1, ip=\"2.2.2.2\", mac=None, radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)","def test_basemodel_none_kwargs(self):\n with self.assertRaises(TypeError):\n BaseModel(id=None, created_at=None, updated_at=None)","def __init__(self,address = None):\n\t\t# I really should do some validation around here\n\t\n\t\tif address != None:\n\t\t\tself.connect(address)","def test_invalid_ip_address_as_argument(self, api_client):\n runner = CliRunner()\n\n expected = 'Error: Invalid value for \"[IP_ADDRESS]...\": not-an-ip\\n'\n\n result = runner.invoke(subcommand.quick, [\"not-an-ip\"])\n assert result.exit_code == 2\n assert expected in result.output\n api_client.quick.assert_not_called()","def is_valid_ip(ip):\n ...","def __init__(__self__, *,\n ip_address: str,\n time_to_retire: str,\n type: str):\n pulumi.set(__self__, \"ip_address\", ip_address)\n pulumi.set(__self__, \"time_to_retire\", time_to_retire)\n pulumi.set(__self__, \"type\", type)","def __init__(self, *args, **kwargs):\n super(IPDetector, self).__init__()\n\n self.opts_family = kwargs.get(\"family\")\n # ensure address family is understood:\n af_ok = {None: AF_UNSPEC, \"INET\": AF_INET, \"INET6\": AF_INET6,\n AF_UNSPEC: AF_UNSPEC, AF_INET: AF_INET, AF_INET6: AF_INET6}\n if self.opts_family not in af_ok:\n raise ValueError(\"IPDetector(): Unsupported address family '%s' specified, please use one of %r\" %\n (self.opts_family, af_ok.keys()))\n else:\n self.opts_family = af_ok[self.opts_family]","def validate_ip(ip):\n try:\n ipobj = IPy.IP(ip)\n if ipobj.iptype() == 'PRIVATE':\n print(\"IP addresses {} will be ignored as it is in a private network range.\".format(ip))\n ip = None\n except ValueError as ve:\n print(\"Invalid IP: {}\".format(ve.args))\n ip = None\n finally:\n return ip","def __init__(__self__, *,\n acl_id: pulumi.Input[str],\n dest_cidr: pulumi.Input[str],\n dest_port_range: pulumi.Input[str],\n direction: pulumi.Input[str],\n ip_protocol: pulumi.Input[str],\n policy: pulumi.Input[str],\n source_cidr: pulumi.Input[str],\n source_port_range: pulumi.Input[str],\n description: Optional[pulumi.Input[str]] = None,\n priority: Optional[pulumi.Input[int]] = None):\n pulumi.set(__self__, \"acl_id\", acl_id)\n pulumi.set(__self__, \"dest_cidr\", dest_cidr)\n pulumi.set(__self__, \"dest_port_range\", dest_port_range)\n pulumi.set(__self__, \"direction\", direction)\n pulumi.set(__self__, \"ip_protocol\", ip_protocol)\n pulumi.set(__self__, \"policy\", policy)\n pulumi.set(__self__, \"source_cidr\", source_cidr)\n pulumi.set(__self__, \"source_port_range\", source_port_range)\n if description is not None:\n pulumi.set(__self__, \"description\", description)\n if priority is not None:\n pulumi.set(__self__, \"priority\", priority)","def __init__(self, uuid, secret, url_base, sha=\"SHA512\") -> None:\n self.uuid = uuid\n self.secret = secret\n self.url_base = url_base\n self.sha = sha\n self.ip = requests.get(\"https://jsonip.com\").json()[\"ip\"]\n self.fake = Faker()\n \"\"\"str: current ip from which Remindo is accessed.\n It needs to be authorized.\n \"\"\"","def test_empty(self):\n self.assertFalse(isIPv6Address(\"\"))","def test_init_kwarg(self):\n b1 = BaseModel(name=\"Red\")\n self.assertEqual(type(b1).__name__, \"BaseModel\")\n self.assertTrue(hasattr(b1, \"name\"))\n self.assertTrue(hasattr(b1, \"__class__\"))\n self.assertFalse(hasattr(b1, \"id\"))\n self.assertFalse(hasattr(b1, \"created_at\"))\n self.assertFalse(hasattr(b1, \"updated_at\"))","def __init__(self):\n self._zipcode = None\n self._city = None","def __init__(__self__,\n resource_name: str,\n opts: Optional[pulumi.ResourceOptions] = None,\n cidr: Optional[pulumi.Input[str]] = None,\n description: Optional[pulumi.Input[str]] = None,\n publish_cidr_route: Optional[pulumi.Input[bool]] = None,\n transit_router_cidr_name: Optional[pulumi.Input[str]] = None,\n transit_router_id: Optional[pulumi.Input[str]] = None,\n __props__=None):\n ...","def __init__(__self__, *,\n arp: Optional[pulumi.Input[bool]] = None,\n control_node_id: Optional[pulumi.Input[str]] = None,\n display_name: Optional[pulumi.Input[str]] = None,\n honeypot_bind_lists: Optional[pulumi.Input[Sequence[pulumi.Input['HoneypotProbeHoneypotBindListArgs']]]] = None,\n honeypot_probe_id: Optional[pulumi.Input[str]] = None,\n ping: Optional[pulumi.Input[bool]] = None,\n probe_type: Optional[pulumi.Input[str]] = None,\n probe_version: Optional[pulumi.Input[str]] = None,\n proxy_ip: Optional[pulumi.Input[str]] = None,\n service_ip_lists: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n status: Optional[pulumi.Input[str]] = None,\n uuid: Optional[pulumi.Input[str]] = None,\n vpc_id: Optional[pulumi.Input[str]] = None):\n if arp is not None:\n pulumi.set(__self__, \"arp\", arp)\n if control_node_id is not None:\n pulumi.set(__self__, \"control_node_id\", control_node_id)\n if display_name is not None:\n pulumi.set(__self__, \"display_name\", display_name)\n if honeypot_bind_lists is not None:\n pulumi.set(__self__, \"honeypot_bind_lists\", honeypot_bind_lists)\n if honeypot_probe_id is not None:\n pulumi.set(__self__, \"honeypot_probe_id\", honeypot_probe_id)\n if ping is not None:\n pulumi.set(__self__, \"ping\", ping)\n if probe_type is not None:\n pulumi.set(__self__, \"probe_type\", probe_type)\n if probe_version is not None:\n pulumi.set(__self__, \"probe_version\", probe_version)\n if proxy_ip is not None:\n pulumi.set(__self__, \"proxy_ip\", proxy_ip)\n if service_ip_lists is not None:\n pulumi.set(__self__, \"service_ip_lists\", service_ip_lists)\n if status is not None:\n pulumi.set(__self__, \"status\", status)\n if uuid is not None:\n pulumi.set(__self__, \"uuid\", uuid)\n if vpc_id is not None:\n pulumi.set(__self__, \"vpc_id\", vpc_id)","def __init__(__self__, *,\n address_family: pulumi.Input[str],\n ipam_scope_id: pulumi.Input[str],\n allocation_default_netmask_length: Optional[pulumi.Input[int]] = None,\n allocation_max_netmask_length: Optional[pulumi.Input[int]] = None,\n allocation_min_netmask_length: Optional[pulumi.Input[int]] = None,\n allocation_resource_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n auto_import: Optional[pulumi.Input[bool]] = None,\n aws_service: Optional[pulumi.Input[str]] = None,\n description: Optional[pulumi.Input[str]] = None,\n locale: Optional[pulumi.Input[str]] = None,\n public_ip_source: Optional[pulumi.Input[str]] = None,\n publicly_advertisable: Optional[pulumi.Input[bool]] = None,\n source_ipam_pool_id: Optional[pulumi.Input[str]] = None,\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\n pulumi.set(__self__, \"address_family\", address_family)\n pulumi.set(__self__, \"ipam_scope_id\", ipam_scope_id)\n if allocation_default_netmask_length is not None:\n pulumi.set(__self__, \"allocation_default_netmask_length\", allocation_default_netmask_length)\n if allocation_max_netmask_length is not None:\n pulumi.set(__self__, \"allocation_max_netmask_length\", allocation_max_netmask_length)\n if allocation_min_netmask_length is not None:\n pulumi.set(__self__, \"allocation_min_netmask_length\", allocation_min_netmask_length)\n if allocation_resource_tags is not None:\n pulumi.set(__self__, \"allocation_resource_tags\", allocation_resource_tags)\n if auto_import is not None:\n pulumi.set(__self__, \"auto_import\", auto_import)\n if aws_service is not None:\n pulumi.set(__self__, \"aws_service\", aws_service)\n if description is not None:\n pulumi.set(__self__, \"description\", description)\n if locale is not None:\n pulumi.set(__self__, \"locale\", locale)\n if public_ip_source is not None:\n pulumi.set(__self__, \"public_ip_source\", public_ip_source)\n if publicly_advertisable is not None:\n pulumi.set(__self__, \"publicly_advertisable\", publicly_advertisable)\n if source_ipam_pool_id is not None:\n pulumi.set(__self__, \"source_ipam_pool_id\", source_ipam_pool_id)\n if tags is not None:\n pulumi.set(__self__, \"tags\", tags)","def __init__(__self__, *,\n control_node_id: pulumi.Input[str],\n display_name: pulumi.Input[str],\n probe_type: pulumi.Input[str],\n arp: Optional[pulumi.Input[bool]] = None,\n honeypot_bind_lists: Optional[pulumi.Input[Sequence[pulumi.Input['HoneypotProbeHoneypotBindListArgs']]]] = None,\n ping: Optional[pulumi.Input[bool]] = None,\n probe_version: Optional[pulumi.Input[str]] = None,\n proxy_ip: Optional[pulumi.Input[str]] = None,\n service_ip_lists: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n uuid: Optional[pulumi.Input[str]] = None,\n vpc_id: Optional[pulumi.Input[str]] = None):\n pulumi.set(__self__, \"control_node_id\", control_node_id)\n pulumi.set(__self__, \"display_name\", display_name)\n pulumi.set(__self__, \"probe_type\", probe_type)\n if arp is not None:\n pulumi.set(__self__, \"arp\", arp)\n if honeypot_bind_lists is not None:\n pulumi.set(__self__, \"honeypot_bind_lists\", honeypot_bind_lists)\n if ping is not None:\n pulumi.set(__self__, \"ping\", ping)\n if probe_version is not None:\n pulumi.set(__self__, \"probe_version\", probe_version)\n if proxy_ip is not None:\n pulumi.set(__self__, \"proxy_ip\", proxy_ip)\n if service_ip_lists is not None:\n pulumi.set(__self__, \"service_ip_lists\", service_ip_lists)\n if uuid is not None:\n pulumi.set(__self__, \"uuid\", uuid)\n if vpc_id is not None:\n pulumi.set(__self__, \"vpc_id\", vpc_id)","def test_no_ip_address_passed(self, api_client):\n runner = CliRunner()\n\n with patch(\"greynoise.cli.helper.sys\") as sys:\n sys.stdin.isatty.return_value = True\n result = runner.invoke(\n subcommand.quick, parent=Context(main, info_name=\"greynoise\")\n )\n assert result.exit_code == -1\n assert \"Usage: greynoise quick\" in result.output\n api_client.quick.assert_not_called()","def __init__(__self__, *,\n acl_id: Optional[pulumi.Input[str]] = None,\n description: Optional[pulumi.Input[str]] = None,\n dest_cidr: Optional[pulumi.Input[str]] = None,\n dest_port_range: Optional[pulumi.Input[str]] = None,\n direction: Optional[pulumi.Input[str]] = None,\n ip_protocol: Optional[pulumi.Input[str]] = None,\n policy: Optional[pulumi.Input[str]] = None,\n priority: Optional[pulumi.Input[int]] = None,\n source_cidr: Optional[pulumi.Input[str]] = None,\n source_port_range: Optional[pulumi.Input[str]] = None):\n if acl_id is not None:\n pulumi.set(__self__, \"acl_id\", acl_id)\n if description is not None:\n pulumi.set(__self__, \"description\", description)\n if dest_cidr is not None:\n pulumi.set(__self__, \"dest_cidr\", dest_cidr)\n if dest_port_range is not None:\n pulumi.set(__self__, \"dest_port_range\", dest_port_range)\n if direction is not None:\n pulumi.set(__self__, \"direction\", direction)\n if ip_protocol is not None:\n pulumi.set(__self__, \"ip_protocol\", ip_protocol)\n if policy is not None:\n pulumi.set(__self__, \"policy\", policy)\n if priority is not None:\n pulumi.set(__self__, \"priority\", priority)\n if source_cidr is not None:\n pulumi.set(__self__, \"source_cidr\", source_cidr)\n if source_port_range is not None:\n pulumi.set(__self__, \"source_port_range\", source_port_range)","def test_invalid_ip_address_as_argument(self, api_client):\n runner = CliRunner()\n\n expected = 'Error: Invalid value for \"[IP_ADDRESS]...\": not-an-ip\\n'\n\n result = runner.invoke(subcommand.ip, [\"not-an-ip\"])\n assert result.exit_code == 2\n assert expected in result.output\n api_client.ip.assert_not_called()","def __init__(__self__, *,\n activation_key: Optional[pulumi.Input[str]] = None,\n ip_address: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None,\n private_link_endpoint: Optional[pulumi.Input[str]] = None,\n security_group_arns: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n subnet_arns: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n vpc_endpoint_id: Optional[pulumi.Input[str]] = None):\n if activation_key is not None:\n pulumi.set(__self__, \"activation_key\", activation_key)\n if ip_address is not None:\n pulumi.set(__self__, \"ip_address\", ip_address)\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if private_link_endpoint is not None:\n pulumi.set(__self__, \"private_link_endpoint\", private_link_endpoint)\n if security_group_arns is not None:\n pulumi.set(__self__, \"security_group_arns\", security_group_arns)\n if subnet_arns is not None:\n pulumi.set(__self__, \"subnet_arns\", subnet_arns)\n if tags is not None:\n pulumi.set(__self__, \"tags\", tags)\n if vpc_endpoint_id is not None:\n pulumi.set(__self__, \"vpc_endpoint_id\", vpc_endpoint_id)","def test_ip(response):\n \n # from comeon_core import update\n ip = getIP()\n print(ip)\n #init_db(engine)\n #update()\n assert True","def test_accepts_init_with_strict_subset_of_args(self):\n\n class API(platform.PlatformAPI):\n def __init__(self, base_url):\n pass\n\n api = API(\"some-url\")\n assert isinstance(api, platform.PlatformAPI)","def __init__(__self__, *,\n dry_run: Optional[pulumi.Input[bool]] = None,\n load_balancer_id: Optional[pulumi.Input[str]] = None,\n security_group_id: Optional[pulumi.Input[str]] = None):\n if dry_run is not None:\n pulumi.set(__self__, \"dry_run\", dry_run)\n if load_balancer_id is not None:\n pulumi.set(__self__, \"load_balancer_id\", load_balancer_id)\n if security_group_id is not None:\n pulumi.set(__self__, \"security_group_id\", security_group_id)","def __init__(__self__, *,\n resource_group: pulumi.Input[str],\n server: pulumi.Input[str],\n subnet_name: pulumi.Input[str],\n v_net_name: pulumi.Input[str],\n v_net_resource_group: pulumi.Input[str],\n ignore_missing_service_endpoint: Optional[pulumi.Input[bool]] = None):\n pulumi.set(__self__, \"resource_group\", resource_group)\n pulumi.set(__self__, \"server\", server)\n pulumi.set(__self__, \"subnet_name\", subnet_name)\n pulumi.set(__self__, \"v_net_name\", v_net_name)\n pulumi.set(__self__, \"v_net_resource_group\", v_net_resource_group)\n if ignore_missing_service_endpoint is not None:\n pulumi.set(__self__, \"ignore_missing_service_endpoint\", ignore_missing_service_endpoint)","def __init__(__self__, *,\n resource_group: pulumi.Input[str],\n server: pulumi.Input[str],\n subnet_name: pulumi.Input[str],\n v_net_name: pulumi.Input[str],\n v_net_resource_group: pulumi.Input[str],\n ignore_missing_service_endpoint: Optional[pulumi.Input[bool]] = None):\n pulumi.set(__self__, \"resource_group\", resource_group)\n pulumi.set(__self__, \"server\", server)\n pulumi.set(__self__, \"subnet_name\", subnet_name)\n pulumi.set(__self__, \"v_net_name\", v_net_name)\n pulumi.set(__self__, \"v_net_resource_group\", v_net_resource_group)\n if ignore_missing_service_endpoint is not None:\n pulumi.set(__self__, \"ignore_missing_service_endpoint\", ignore_missing_service_endpoint)","def __init__(self):\n # assert(self.validate('61882613000194'))\n # assert(self.validate('061882613000190'))\n # assert(not self.validate('61882613000195'))\n pass","def __init__(__self__, *,\n end_ip_address: pulumi.Input[str],\n resource_group: pulumi.Input[str],\n server: pulumi.Input[str],\n start_ip_address: pulumi.Input[str]):\n pulumi.set(__self__, \"end_ip_address\", end_ip_address)\n pulumi.set(__self__, \"resource_group\", resource_group)\n pulumi.set(__self__, \"server\", server)\n pulumi.set(__self__, \"start_ip_address\", start_ip_address)"],"string":"[\n \"def test_init_no_ip(self):\\n # mocks of files\\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\\n\\n ap = APInfo(port_id=1, ip=None, mac=\\\"bb:bb:bb:bb:bb:bb\\\", radio_mac=\\\"bb:bb:bb:bb:bb:00\\\", udp_port=12345, wlc_ip='1.1.1.1',\\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\\n self.assertEqual(ap.ip, None)\",\n \"def __init__(__self__, *,\\n ip: Optional[pulumi.Input['IPAccessControlArgs']] = None):\\n if ip is not None:\\n pulumi.set(__self__, \\\"ip\\\", ip)\",\n \"def __init__(__self__, *,\\n ip: Optional[pulumi.Input['IPAccessControlArgs']] = None):\\n if ip is not None:\\n pulumi.set(__self__, \\\"ip\\\", ip)\",\n \"def __init__(self) -> None:\\n self.ip_address: str | None = None\",\n \"def __init__(__self__, *,\\n host_ip: Optional[pulumi.Input[str]] = None,\\n port: Optional[pulumi.Input[str]] = None):\\n if host_ip is not None:\\n pulumi.set(__self__, \\\"host_ip\\\", host_ip)\\n if port is not None:\\n pulumi.set(__self__, \\\"port\\\", port)\",\n \"def __init__(\\n self, name: str = \\\"\\\", protocol: int | None = None, **kwargs: Any\\n ) -> None:\\n\\n super().__init__(name=name, **kwargs)\\n if not ipaddress:\\n raise SoftDependencyError(\\\"ipaddress\\\")\\n if protocol not in [None, 4, 6]:\\n raise ValueError(\\\"IpAddress protocol needs to be either 4, 6 or None\\\")\\n self.protocol = protocol\",\n \"def __init__(\\n self, name: str = \\\"\\\", protocol: int | None = None, **kwargs: Any\\n ) -> None:\\n\\n super().__init__(name=name, **kwargs)\\n\\n if protocol not in [None, 4, 6]:\\n raise ValueError(\\\"IpAddress protocol needs to be either 4, 6 or None\\\")\\n self.protocol = protocol\",\n \"def test_validate_ip_ok():\\n ip = '1.1.1.1'\\n assert howisresolved.validate_ip(ip) is None\",\n \"def test_field_none_nullable(self):\\n node_dict = {\\n 'host_name': 'abc'\\n }\\n try:\\n Node(**node_dict)\\n except Exception as e:\\n self.assertEqual(type(e), ValueError)\",\n \"def __init__(__self__, *,\\n ip_tag_type: Optional[pulumi.Input[str]] = None,\\n tag: Optional[pulumi.Input[str]] = None):\\n if ip_tag_type is not None:\\n pulumi.set(__self__, \\\"ip_tag_type\\\", ip_tag_type)\\n if tag is not None:\\n pulumi.set(__self__, \\\"tag\\\", tag)\",\n \"def __init__(self, allow_none=False):\\n if allow_none:\\n self.validate = self.validate_none\\n self.info = self.info_none\\n self.fast_validate = (2, None)\\n else:\\n self.fast_validate = (2,)\",\n \"def __init__(__self__, *,\\n destination_pool_name: Optional[pulumi.Input[str]] = None,\\n ip: Optional[pulumi.Input[str]] = None):\\n if destination_pool_name is not None:\\n pulumi.set(__self__, \\\"destination_pool_name\\\", destination_pool_name)\\n if ip is not None:\\n pulumi.set(__self__, \\\"ip\\\", ip)\",\n \"def test_init_no_mac(self):\\n with self.assertRaises(ValueError):\\n client = ClientInfo(None, ip=\\\"3.3.3.3\\\", ap_info=self.ap)\",\n \"def __init__(self, ip, mask):\\n self.vip = ip\\n self.mask = mask\",\n \"def __init__(__self__, *,\\n end_ip: pulumi.Input[str],\\n start_ip: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"end_ip\\\", end_ip)\\n pulumi.set(__self__, \\\"start_ip\\\", start_ip)\",\n \"def __init__(__self__, *,\\n host: Optional[pulumi.Input[str]] = None,\\n port: Optional[pulumi.Input[int]] = None):\\n if host is not None:\\n pulumi.set(__self__, \\\"host\\\", host)\\n if port is not None:\\n pulumi.set(__self__, \\\"port\\\", port)\",\n \"def __init__(self, ip: str):\\n self.api = API(f\\\"http://{ip}\\\")\\n self.ip = ip\\n self.board_data = None\",\n \"def test_no_ip_address_passed(self, api_client):\\n runner = CliRunner()\\n\\n with patch(\\\"greynoise.cli.helper.sys\\\") as sys:\\n sys.stdin.isatty.return_value = True\\n result = runner.invoke(\\n subcommand.ip, parent=Context(main, info_name=\\\"greynoise\\\")\\n )\\n assert result.exit_code == -1\\n assert \\\"Usage: greynoise ip\\\" in result.output\\n api_client.ip.assert_not_called()\",\n \"def __init__(__self__, *,\\n ignore_missing_v_net_service_endpoint: Optional[pulumi.Input[bool]] = None,\\n subnet_id: Optional[pulumi.Input[str]] = None):\\n if ignore_missing_v_net_service_endpoint is not None:\\n pulumi.set(__self__, \\\"ignore_missing_v_net_service_endpoint\\\", ignore_missing_v_net_service_endpoint)\\n if subnet_id is not None:\\n pulumi.set(__self__, \\\"subnet_id\\\", subnet_id)\",\n \"def test_optional_arg(self):\\n obj = Base()\\n self.assertEqual(obj.id, 1)\",\n \"def __init__(__self__, *,\\n droplet_id: Optional[pulumi.Input[int]] = None,\\n ip_address: Optional[pulumi.Input[str]] = None,\\n region: Optional[pulumi.Input[str]] = None,\\n urn: Optional[pulumi.Input[str]] = None):\\n if droplet_id is not None:\\n pulumi.set(__self__, \\\"droplet_id\\\", droplet_id)\\n if ip_address is not None:\\n pulumi.set(__self__, \\\"ip_address\\\", ip_address)\\n if region is not None:\\n pulumi.set(__self__, \\\"region\\\", region)\\n if urn is not None:\\n pulumi.set(__self__, \\\"urn\\\", urn)\",\n \"def __init__(__self__, *,\\n allow: Optional[pulumi.Input[Sequence[pulumi.Input['IPRangeArgs']]]] = None):\\n if allow is not None:\\n pulumi.set(__self__, \\\"allow\\\", allow)\",\n \"def __init__(__self__, *,\\n region: pulumi.Input[str],\\n droplet_id: Optional[pulumi.Input[int]] = None,\\n ip_address: Optional[pulumi.Input[str]] = None):\\n pulumi.set(__self__, \\\"region\\\", region)\\n if droplet_id is not None:\\n pulumi.set(__self__, \\\"droplet_id\\\", droplet_id)\\n if ip_address is not None:\\n pulumi.set(__self__, \\\"ip_address\\\", ip_address)\",\n \"def __init__(self):\\n self.clean_optional()\",\n \"def __init__(__self__, *,\\n resourcegroup: pulumi.Input[str],\\n server: pulumi.Input[str],\\n endipaddress: Optional[pulumi.Input[str]] = None,\\n startipaddress: Optional[pulumi.Input[str]] = None):\\n pulumi.set(__self__, \\\"resourcegroup\\\", resourcegroup)\\n pulumi.set(__self__, \\\"server\\\", server)\\n if endipaddress is not None:\\n pulumi.set(__self__, \\\"endipaddress\\\", endipaddress)\\n if startipaddress is not None:\\n pulumi.set(__self__, \\\"startipaddress\\\", startipaddress)\",\n \"def __init__(self, ip=None, header=None, hostname=None, aliases=None):\\n self.id = header or \\\"\\\"\\n self.hostname = hostname or \\\"\\\"\\n self.aliases = aliases or []\\n self.ip = \\\"\\\"\\n if ip:\\n try:\\n self.ip=ipaddress.ip_address(ip)\\n except ipaddress.AddressValueError as e:\\n print(\\\"Error parsing ip address from hosts.conf file\\\")\\n raise e\\n self.stored_state = None\",\n \"def __init__(self, **kwargs):\\n self.swagger_types = {\\n 'assign_public_ip': 'bool',\\n 'defined_tags': 'dict(str, dict(str, object))',\\n 'display_name': 'str',\\n 'freeform_tags': 'dict(str, str)',\\n 'hostname_label': 'str',\\n 'nsg_ids': 'list[str]',\\n 'private_ip': 'str',\\n 'skip_source_dest_check': 'bool',\\n 'subnet_id': 'str'\\n }\\n\\n self.attribute_map = {\\n 'assign_public_ip': 'assignPublicIp',\\n 'defined_tags': 'definedTags',\\n 'display_name': 'displayName',\\n 'freeform_tags': 'freeformTags',\\n 'hostname_label': 'hostnameLabel',\\n 'nsg_ids': 'nsgIds',\\n 'private_ip': 'privateIp',\\n 'skip_source_dest_check': 'skipSourceDestCheck',\\n 'subnet_id': 'subnetId'\\n }\\n\\n self._assign_public_ip = None\\n self._defined_tags = None\\n self._display_name = None\\n self._freeform_tags = None\\n self._hostname_label = None\\n self._nsg_ids = None\\n self._private_ip = None\\n self._skip_source_dest_check = None\\n self._subnet_id = None\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: ReservedIpArgs,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\",\n \"def __init__(self, **kwargs):\\n members = ('ip', 'mac', 'port', 'timeout', 'flags',\\n 'index', 'tag', 'hostname')\\n\\n # copy the given value or default to None\\n for member in members:\\n self.__dict__[member] = kwargs.setdefault (member, None)\",\n \"def test_init_without_kwargs(self):\\n c = City()\\n self.assertTrue('id' in c.__dict__)\\n self.assertTrue('created_at' in c.__dict__)\\n self.assertTrue('updated_at' in c.__dict__)\\n self.assertIsInstance(c, BaseModel)\",\n \"def validate_ip(argname, param, safe, optional = False):\\n _validate_one(argname, param, safe, _check_ip, optional)\",\n \"def test_init_wrong_ap_type(self):\\n ap_wrong = object()\\n with self.assertRaises(ValueError):\\n client = ClientInfo(\\\"cc:cc:cc:cc:cc:cc\\\",\\n ip=\\\"3.3.3.3\\\", ap_info=ap_wrong)\",\n \"def __init__(__self__, *,\\n protocol: Optional[pulumi.Input[str]] = None,\\n url: Optional[pulumi.Input[str]] = None):\\n if protocol is not None:\\n pulumi.set(__self__, \\\"protocol\\\", protocol)\\n if url is not None:\\n pulumi.set(__self__, \\\"url\\\", url)\",\n \"def __init__(__self__, *,\\n public_ips: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceReferenceArgs']]]] = None):\\n if public_ips is not None:\\n pulumi.set(__self__, \\\"public_ips\\\", public_ips)\",\n \"def __init__(__self__, *,\\n cidr: pulumi.Input[str],\\n resource_group_name: pulumi.Input[str],\\n commissioning_enabled: Optional[pulumi.Input[bool]] = None,\\n internet_advertising_disabled: Optional[pulumi.Input[bool]] = None,\\n location: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None,\\n parent_custom_ip_prefix_id: Optional[pulumi.Input[str]] = None,\\n roa_validity_end_date: Optional[pulumi.Input[str]] = None,\\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n wan_validation_signed_message: Optional[pulumi.Input[str]] = None,\\n zones: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\\n pulumi.set(__self__, \\\"cidr\\\", cidr)\\n pulumi.set(__self__, \\\"resource_group_name\\\", resource_group_name)\\n if commissioning_enabled is not None:\\n pulumi.set(__self__, \\\"commissioning_enabled\\\", commissioning_enabled)\\n if internet_advertising_disabled is not None:\\n pulumi.set(__self__, \\\"internet_advertising_disabled\\\", internet_advertising_disabled)\\n if location is not None:\\n pulumi.set(__self__, \\\"location\\\", location)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if parent_custom_ip_prefix_id is not None:\\n pulumi.set(__self__, \\\"parent_custom_ip_prefix_id\\\", parent_custom_ip_prefix_id)\\n if roa_validity_end_date is not None:\\n pulumi.set(__self__, \\\"roa_validity_end_date\\\", roa_validity_end_date)\\n if tags is not None:\\n pulumi.set(__self__, \\\"tags\\\", tags)\\n if wan_validation_signed_message is not None:\\n pulumi.set(__self__, \\\"wan_validation_signed_message\\\", wan_validation_signed_message)\\n if zones is not None:\\n pulumi.set(__self__, \\\"zones\\\", zones)\",\n \"def test_control_create_with_empty_field(self, field):\\n request = self.prepare_control_request_body()\\n request[field] = None\\n\\n response = self.api.post(all_models.Control, data=request)\\n\\n self.assert400(response)\",\n \"def test_init_correct(self):\\n client = ClientInfo(\\\"cc:cc:cc:cc:cc:cc\\\", ip=\\\"3.3.3.3\\\", ap_info=self.ap)\\n self.assertEqual(client.ip, \\\"3.3.3.3\\\")\\n self.assertEqual(client.ip_bytes, b'\\\\x03\\\\x03\\\\x03\\\\x03')\",\n \"def __init__(__self__, *,\\n id: str,\\n private_ip_address: Optional[str] = None):\\n pulumi.set(__self__, \\\"id\\\", id)\\n if private_ip_address is not None:\\n pulumi.set(__self__, \\\"private_ip_address\\\", private_ip_address)\",\n \"def test_creation_notallow_none():\\n with pytest.raises(ValueError) as __:\\n value = None\\n __ = param.Integer(value=value, allow_None=False)\",\n \"def validate_ip(self, ip):\\n if not ip:\\n raise ValidationError(\\\"Please provide an actual IP or web address. You gave me: \\\" + ip)\",\n \"def __init__(__self__, *,\\n destination_pool_name: pulumi.Input[str],\\n ip: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"destination_pool_name\\\", destination_pool_name)\\n pulumi.set(__self__, \\\"ip\\\", ip)\",\n \"def test_field_nullable(self):\\n node_dict = {\\n 'host_name': 'abc',\\n 'local_router_id': '1.1.1.1',\\n 'as_num': 100,\\n 'bgpls_id': '0.0.0.0',\\n 'igp_id': '0.0.0.0'\\n }\\n node = Node(**node_dict)\\n for name, field in node_dict.items():\\n self.assertEqual(field, node.__dict__[name])\",\n \"def __init__(__self__, *,\\n cidr: Optional[pulumi.Input[str]] = None,\\n commissioning_enabled: Optional[pulumi.Input[bool]] = None,\\n internet_advertising_disabled: Optional[pulumi.Input[bool]] = None,\\n location: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None,\\n parent_custom_ip_prefix_id: Optional[pulumi.Input[str]] = None,\\n resource_group_name: Optional[pulumi.Input[str]] = None,\\n roa_validity_end_date: Optional[pulumi.Input[str]] = None,\\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n wan_validation_signed_message: Optional[pulumi.Input[str]] = None,\\n zones: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\\n if cidr is not None:\\n pulumi.set(__self__, \\\"cidr\\\", cidr)\\n if commissioning_enabled is not None:\\n pulumi.set(__self__, \\\"commissioning_enabled\\\", commissioning_enabled)\\n if internet_advertising_disabled is not None:\\n pulumi.set(__self__, \\\"internet_advertising_disabled\\\", internet_advertising_disabled)\\n if location is not None:\\n pulumi.set(__self__, \\\"location\\\", location)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if parent_custom_ip_prefix_id is not None:\\n pulumi.set(__self__, \\\"parent_custom_ip_prefix_id\\\", parent_custom_ip_prefix_id)\\n if resource_group_name is not None:\\n pulumi.set(__self__, \\\"resource_group_name\\\", resource_group_name)\\n if roa_validity_end_date is not None:\\n pulumi.set(__self__, \\\"roa_validity_end_date\\\", roa_validity_end_date)\\n if tags is not None:\\n pulumi.set(__self__, \\\"tags\\\", tags)\\n if wan_validation_signed_message is not None:\\n pulumi.set(__self__, \\\"wan_validation_signed_message\\\", wan_validation_signed_message)\\n if zones is not None:\\n pulumi.set(__self__, \\\"zones\\\", zones)\",\n \"def __init__(__self__, *,\\n allowed_host_ports: Optional[pulumi.Input[Sequence[pulumi.Input['PortRangeArgs']]]] = None,\\n application_security_groups: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n node_public_ip_tags: Optional[pulumi.Input[Sequence[pulumi.Input['IPTagArgs']]]] = None):\\n if allowed_host_ports is not None:\\n pulumi.set(__self__, \\\"allowed_host_ports\\\", allowed_host_ports)\\n if application_security_groups is not None:\\n pulumi.set(__self__, \\\"application_security_groups\\\", application_security_groups)\\n if node_public_ip_tags is not None:\\n pulumi.set(__self__, \\\"node_public_ip_tags\\\", node_public_ip_tags)\",\n \"def validate_input(self, IP, Port):\\n exception = ServerInitError\\n try:\\n if IP != None:\\n if re.match(IPRegex, IP):\\n self.IP = IP\\n else:\\n exception = InavlidIPError\\n raise\\n\\n if Port != None:\\n if int(Port) in range(0,65535):\\n self.Port = Port\\n else:\\n exception = InvalidPortError\\n raise\\n except:\\n traceback_print_exc()\",\n \"def __init__(__self__, *,\\n address: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None,\\n subnet_prefix_length: Optional[pulumi.Input[int]] = None):\\n if address is not None:\\n pulumi.set(__self__, \\\"address\\\", address)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if subnet_prefix_length is not None:\\n pulumi.set(__self__, \\\"subnet_prefix_length\\\", subnet_prefix_length)\",\n \"def test_same_ip(self):\\n self.create_ptr(\\n ip_str='128.193.0.2', ip_type='4', fqdn='foo1.oregonstate.edu')\\n\\n with self.assertRaises(ValidationError):\\n self.create_ptr(\\n ip_str='128.193.0.2', ip_type='4', fqdn='foo2.oregonstate.edu')\",\n \"def __init__(self,\\r\\n name=None,\\r\\n lan_ip=None,\\r\\n uplink=None,\\r\\n public_port=None,\\r\\n local_port=None,\\r\\n allowed_ips=None,\\r\\n protocol=None):\\r\\n\\r\\n # Initialize members of the class\\r\\n self.name = name\\r\\n self.lan_ip = lan_ip\\r\\n self.uplink = uplink\\r\\n self.public_port = public_port\\r\\n self.local_port = local_port\\r\\n self.allowed_ips = allowed_ips\\r\\n self.protocol = protocol\",\n \"def __init__(__self__, *,\\n dns_servers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n gateway: Optional[pulumi.Input[str]] = None,\\n infra_vnet_profile: Optional[pulumi.Input['VirtualNetworksPropertiesInfraVnetProfileArgs']] = None,\\n ip_address_prefix: Optional[pulumi.Input[str]] = None,\\n vip_pool: Optional[pulumi.Input[Sequence[pulumi.Input['VirtualNetworksPropertiesVipPoolArgs']]]] = None,\\n vmip_pool: Optional[pulumi.Input[Sequence[pulumi.Input['VirtualNetworksPropertiesVmipPoolArgs']]]] = None):\\n if dns_servers is not None:\\n pulumi.set(__self__, \\\"dns_servers\\\", dns_servers)\\n if gateway is not None:\\n pulumi.set(__self__, \\\"gateway\\\", gateway)\\n if infra_vnet_profile is not None:\\n pulumi.set(__self__, \\\"infra_vnet_profile\\\", infra_vnet_profile)\\n if ip_address_prefix is not None:\\n pulumi.set(__self__, \\\"ip_address_prefix\\\", ip_address_prefix)\\n if vip_pool is not None:\\n pulumi.set(__self__, \\\"vip_pool\\\", vip_pool)\\n if vmip_pool is not None:\\n pulumi.set(__self__, \\\"vmip_pool\\\", vmip_pool)\",\n \"def test_init_correct(self):\\n # mocks of files\\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\\n\\n ap = APInfo(port_id=1, ip=\\\"2.2.2.2\\\", mac=\\\"bb:bb:bb:bb:bb:bb\\\", radio_mac=\\\"bb:bb:bb:bb:bb:00\\\", udp_port=12345, wlc_ip='1.1.1.1',\\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\\n\\n self.assertEqual(ap.ip, '2.2.2.2')\",\n \"def test_noop(self):\\n self.assertFalse(helpers.getBcastAddrforIPv4())\\n self.assertIsNone(helpers.no_op())\",\n \"def test_get_source_ip(self):\\n pass\",\n \"def __init__(__self__, *,\\n idle_timeout_in_minutes: pulumi.Input[int],\\n location: pulumi.Input[str],\\n public_ip_address_version: pulumi.Input[str],\\n public_ip_allocation_method: pulumi.Input[str],\\n resource_group: pulumi.Input[str],\\n sku_name: pulumi.Input[str],\\n ip_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\\n pulumi.set(__self__, \\\"idle_timeout_in_minutes\\\", idle_timeout_in_minutes)\\n pulumi.set(__self__, \\\"location\\\", location)\\n pulumi.set(__self__, \\\"public_ip_address_version\\\", public_ip_address_version)\\n pulumi.set(__self__, \\\"public_ip_allocation_method\\\", public_ip_allocation_method)\\n pulumi.set(__self__, \\\"resource_group\\\", resource_group)\\n pulumi.set(__self__, \\\"sku_name\\\", sku_name)\\n if ip_tags is not None:\\n pulumi.set(__self__, \\\"ip_tags\\\", ip_tags)\",\n \"def test_constructor_fill_fields(self):\\r\\n builder = IndicatorBuilder(\\\"url\\\")\\r\\n\\r\\n self.assertEqual(builder.url, \\\"url\\\")\\r\\n self.assertEqual(builder.data, {})\",\n \"def __init__(__self__,\\n resource_name: str,\\n opts: Optional[pulumi.ResourceOptions] = None,\\n destination_pool_name: Optional[pulumi.Input[str]] = None,\\n ip: Optional[pulumi.Input[str]] = None,\\n __props__=None):\\n ...\",\n \"def test_hostport_or_network(self):\\n # If providing host or port, must provide both\\n with self.assertRaises(AssertionError):\\n a = LedgerApi(host='host')\\n with self.assertRaises(AssertionError):\\n a = LedgerApi(port=1234)\\n # If providing network, may not provide host or port\\n with self.assertRaises(AssertionError):\\n a = LedgerApi(host='host', network='alpha')\\n with self.assertRaises(AssertionError):\\n a = LedgerApi(port=1234, network='alpha')\\n with self.assertRaises(AssertionError):\\n a = LedgerApi(host='host', port=1234, network='alpha')\",\n \"def __init__(\\n self,\\n host: str,\\n database: str,\\n user: str,\\n password: str\\n ) -> None:\\n self.host: str = host\\n self.database: str = database\\n self.user: str = user\\n self.password: str = password\\n\\n # all these values are needed\\n for attr in ('host', 'database', 'user', 'password'):\\n if not getattr(self, attr):\\n raise ValueError(f\\\"{attr} must not be None!\\\")\",\n \"def __init__(__self__, *,\\n location: pulumi.Input[str],\\n public_ip_address_name: pulumi.Input[str],\\n resource_group: pulumi.Input[str],\\n subnet_name: pulumi.Input[str],\\n vnet_name: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"location\\\", location)\\n pulumi.set(__self__, \\\"public_ip_address_name\\\", public_ip_address_name)\\n pulumi.set(__self__, \\\"resource_group\\\", resource_group)\\n pulumi.set(__self__, \\\"subnet_name\\\", subnet_name)\\n pulumi.set(__self__, \\\"vnet_name\\\", vnet_name)\",\n \"def test_exclude_ip_ban(self):\\n pass\",\n \"def test_basemodel_basic_instance_none(self):\\n with self.assertRaises(TypeError):\\n BaseModel(None)\",\n \"def __init__(self, ip):\\r\\n\\t\\tself.ip = str(ip)\\r\\n\\t\\tself.ice = IceParser(self.ip)\\r\\n\\t\\tself.versions_list = []\\r\\n\\t\\tself.alarm_list = []\\r\\n\\t\\tself.status_list = []\",\n \"def test_required_city_missing(self):\\r\\n self.url_params['city'] = ''\\r\\n response = self.client.post(self.url, self.url_params)\\r\\n self.assertEqual(response.status_code, 400)\\r\\n obj = json.loads(response.content)\\r\\n self.assertEqual(\\r\\n obj['value'],\\r\\n u'A city is required',\\r\\n )\",\n \"def __init__(__self__, *,\\n endpoint_id: pulumi.Input[str],\\n client_ip_preservation_enabled: Optional[pulumi.Input[bool]] = None,\\n weight: Optional[pulumi.Input[int]] = None):\\n pulumi.set(__self__, \\\"endpoint_id\\\", endpoint_id)\\n if client_ip_preservation_enabled is not None:\\n pulumi.set(__self__, \\\"client_ip_preservation_enabled\\\", client_ip_preservation_enabled)\\n if weight is not None:\\n pulumi.set(__self__, \\\"weight\\\", weight)\",\n \"def __init__(__self__, *,\\n http_proxy: Optional[pulumi.Input[str]] = None,\\n https_proxy: Optional[pulumi.Input[str]] = None,\\n no_proxy: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n trusted_ca: Optional[pulumi.Input[str]] = None):\\n if http_proxy is not None:\\n pulumi.set(__self__, \\\"http_proxy\\\", http_proxy)\\n if https_proxy is not None:\\n pulumi.set(__self__, \\\"https_proxy\\\", https_proxy)\\n if no_proxy is not None:\\n pulumi.set(__self__, \\\"no_proxy\\\", no_proxy)\\n if trusted_ca is not None:\\n pulumi.set(__self__, \\\"trusted_ca\\\", trusted_ca)\",\n \"def test_init(self):\\n with self.assertRaises(ValueError):\\n TraxionPay(api_key=self.api_key)\",\n \"def __init__(__self__, *,\\n group_id: pulumi.Input[str],\\n ip_protocol: pulumi.Input[str],\\n cidr_ip: Optional[pulumi.Input[str]] = None,\\n cidr_ipv6: Optional[pulumi.Input[str]] = None,\\n description: Optional[pulumi.Input[str]] = None,\\n destination_prefix_list_id: Optional[pulumi.Input[str]] = None,\\n destination_security_group_id: Optional[pulumi.Input[str]] = None,\\n from_port: Optional[pulumi.Input[int]] = None,\\n to_port: Optional[pulumi.Input[int]] = None):\\n pulumi.set(__self__, \\\"group_id\\\", group_id)\\n pulumi.set(__self__, \\\"ip_protocol\\\", ip_protocol)\\n if cidr_ip is not None:\\n pulumi.set(__self__, \\\"cidr_ip\\\", cidr_ip)\\n if cidr_ipv6 is not None:\\n pulumi.set(__self__, \\\"cidr_ipv6\\\", cidr_ipv6)\\n if description is not None:\\n pulumi.set(__self__, \\\"description\\\", description)\\n if destination_prefix_list_id is not None:\\n pulumi.set(__self__, \\\"destination_prefix_list_id\\\", destination_prefix_list_id)\\n if destination_security_group_id is not None:\\n pulumi.set(__self__, \\\"destination_security_group_id\\\", destination_security_group_id)\\n if from_port is not None:\\n pulumi.set(__self__, \\\"from_port\\\", from_port)\\n if to_port is not None:\\n pulumi.set(__self__, \\\"to_port\\\", to_port)\",\n \"def __init__(__self__,\\n resource_name: str,\\n opts: Optional[pulumi.ResourceOptions] = None,\\n droplet_id: Optional[pulumi.Input[int]] = None,\\n ip_address: Optional[pulumi.Input[str]] = None,\\n region: Optional[pulumi.Input[str]] = None,\\n __props__=None):\\n ...\",\n \"def test_allow_none():\\n value = None\\n num_a = param.Integer(value=value, allow_None=True)\\n assert num_a.value == value\",\n \"def test_init_attributes(self):\\n t = self.Test({'id': 1, 'poop': 'abc'})\\n\\n self.assertEqual(t.id, 1)\\n self.assertEqual(t.name, None)\\n self.assertRaises(AttributeError, t.__getattribute__, 'poop')\",\n \"def test_default_country_by_ip_no_settings(self):\\n\\n response = self.client.get(\\n reverse(\\\"billing_info\\\"), HTTP_X_FORWARDED_FOR=\\\"85.214.132.117\\\"\\n )\\n self.assertEqual(response.status_code, 200)\\n self.assertContains(\\n response, '<option value=\\\"\\\" selected>---------</option>', html=True\\n )\",\n \"def test_State_none_kwargs(self):\\n with self.assertRaises(TypeError):\\n State(id=None, created_at=None, updated_at=None)\",\n \"def __init__(self, IP=None, Port=None):\\n\\n self.validate_input(IP, Port)\\n self.url = ('http://{}:{}/v2/'.format(self.IP, self.Port))\\n self.get_templates()\\n self.get_data()\\n self.telnet_threads = []\",\n \"def test_init_no_mac(self):\\n # mocks of files\\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\\n\\n with self.assertRaises(ValueError):\\n ap = APInfo(port_id=1, ip=\\\"2.2.2.2\\\", mac=None, radio_mac=\\\"bb:bb:bb:bb:bb:00\\\", udp_port=12345, wlc_ip='1.1.1.1',\\n gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_priv_file=rsa_ca_priv_file, rsa_priv_file=rsa_priv_file, rsa_cert_file=rsa_cert_file)\",\n \"def test_basemodel_none_kwargs(self):\\n with self.assertRaises(TypeError):\\n BaseModel(id=None, created_at=None, updated_at=None)\",\n \"def __init__(self,address = None):\\n\\t\\t# I really should do some validation around here\\n\\t\\n\\t\\tif address != None:\\n\\t\\t\\tself.connect(address)\",\n \"def test_invalid_ip_address_as_argument(self, api_client):\\n runner = CliRunner()\\n\\n expected = 'Error: Invalid value for \\\"[IP_ADDRESS]...\\\": not-an-ip\\\\n'\\n\\n result = runner.invoke(subcommand.quick, [\\\"not-an-ip\\\"])\\n assert result.exit_code == 2\\n assert expected in result.output\\n api_client.quick.assert_not_called()\",\n \"def is_valid_ip(ip):\\n ...\",\n \"def __init__(__self__, *,\\n ip_address: str,\\n time_to_retire: str,\\n type: str):\\n pulumi.set(__self__, \\\"ip_address\\\", ip_address)\\n pulumi.set(__self__, \\\"time_to_retire\\\", time_to_retire)\\n pulumi.set(__self__, \\\"type\\\", type)\",\n \"def __init__(self, *args, **kwargs):\\n super(IPDetector, self).__init__()\\n\\n self.opts_family = kwargs.get(\\\"family\\\")\\n # ensure address family is understood:\\n af_ok = {None: AF_UNSPEC, \\\"INET\\\": AF_INET, \\\"INET6\\\": AF_INET6,\\n AF_UNSPEC: AF_UNSPEC, AF_INET: AF_INET, AF_INET6: AF_INET6}\\n if self.opts_family not in af_ok:\\n raise ValueError(\\\"IPDetector(): Unsupported address family '%s' specified, please use one of %r\\\" %\\n (self.opts_family, af_ok.keys()))\\n else:\\n self.opts_family = af_ok[self.opts_family]\",\n \"def validate_ip(ip):\\n try:\\n ipobj = IPy.IP(ip)\\n if ipobj.iptype() == 'PRIVATE':\\n print(\\\"IP addresses {} will be ignored as it is in a private network range.\\\".format(ip))\\n ip = None\\n except ValueError as ve:\\n print(\\\"Invalid IP: {}\\\".format(ve.args))\\n ip = None\\n finally:\\n return ip\",\n \"def __init__(__self__, *,\\n acl_id: pulumi.Input[str],\\n dest_cidr: pulumi.Input[str],\\n dest_port_range: pulumi.Input[str],\\n direction: pulumi.Input[str],\\n ip_protocol: pulumi.Input[str],\\n policy: pulumi.Input[str],\\n source_cidr: pulumi.Input[str],\\n source_port_range: pulumi.Input[str],\\n description: Optional[pulumi.Input[str]] = None,\\n priority: Optional[pulumi.Input[int]] = None):\\n pulumi.set(__self__, \\\"acl_id\\\", acl_id)\\n pulumi.set(__self__, \\\"dest_cidr\\\", dest_cidr)\\n pulumi.set(__self__, \\\"dest_port_range\\\", dest_port_range)\\n pulumi.set(__self__, \\\"direction\\\", direction)\\n pulumi.set(__self__, \\\"ip_protocol\\\", ip_protocol)\\n pulumi.set(__self__, \\\"policy\\\", policy)\\n pulumi.set(__self__, \\\"source_cidr\\\", source_cidr)\\n pulumi.set(__self__, \\\"source_port_range\\\", source_port_range)\\n if description is not None:\\n pulumi.set(__self__, \\\"description\\\", description)\\n if priority is not None:\\n pulumi.set(__self__, \\\"priority\\\", priority)\",\n \"def __init__(self, uuid, secret, url_base, sha=\\\"SHA512\\\") -> None:\\n self.uuid = uuid\\n self.secret = secret\\n self.url_base = url_base\\n self.sha = sha\\n self.ip = requests.get(\\\"https://jsonip.com\\\").json()[\\\"ip\\\"]\\n self.fake = Faker()\\n \\\"\\\"\\\"str: current ip from which Remindo is accessed.\\n It needs to be authorized.\\n \\\"\\\"\\\"\",\n \"def test_empty(self):\\n self.assertFalse(isIPv6Address(\\\"\\\"))\",\n \"def test_init_kwarg(self):\\n b1 = BaseModel(name=\\\"Red\\\")\\n self.assertEqual(type(b1).__name__, \\\"BaseModel\\\")\\n self.assertTrue(hasattr(b1, \\\"name\\\"))\\n self.assertTrue(hasattr(b1, \\\"__class__\\\"))\\n self.assertFalse(hasattr(b1, \\\"id\\\"))\\n self.assertFalse(hasattr(b1, \\\"created_at\\\"))\\n self.assertFalse(hasattr(b1, \\\"updated_at\\\"))\",\n \"def __init__(self):\\n self._zipcode = None\\n self._city = None\",\n \"def __init__(__self__,\\n resource_name: str,\\n opts: Optional[pulumi.ResourceOptions] = None,\\n cidr: Optional[pulumi.Input[str]] = None,\\n description: Optional[pulumi.Input[str]] = None,\\n publish_cidr_route: Optional[pulumi.Input[bool]] = None,\\n transit_router_cidr_name: Optional[pulumi.Input[str]] = None,\\n transit_router_id: Optional[pulumi.Input[str]] = None,\\n __props__=None):\\n ...\",\n \"def __init__(__self__, *,\\n arp: Optional[pulumi.Input[bool]] = None,\\n control_node_id: Optional[pulumi.Input[str]] = None,\\n display_name: Optional[pulumi.Input[str]] = None,\\n honeypot_bind_lists: Optional[pulumi.Input[Sequence[pulumi.Input['HoneypotProbeHoneypotBindListArgs']]]] = None,\\n honeypot_probe_id: Optional[pulumi.Input[str]] = None,\\n ping: Optional[pulumi.Input[bool]] = None,\\n probe_type: Optional[pulumi.Input[str]] = None,\\n probe_version: Optional[pulumi.Input[str]] = None,\\n proxy_ip: Optional[pulumi.Input[str]] = None,\\n service_ip_lists: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n status: Optional[pulumi.Input[str]] = None,\\n uuid: Optional[pulumi.Input[str]] = None,\\n vpc_id: Optional[pulumi.Input[str]] = None):\\n if arp is not None:\\n pulumi.set(__self__, \\\"arp\\\", arp)\\n if control_node_id is not None:\\n pulumi.set(__self__, \\\"control_node_id\\\", control_node_id)\\n if display_name is not None:\\n pulumi.set(__self__, \\\"display_name\\\", display_name)\\n if honeypot_bind_lists is not None:\\n pulumi.set(__self__, \\\"honeypot_bind_lists\\\", honeypot_bind_lists)\\n if honeypot_probe_id is not None:\\n pulumi.set(__self__, \\\"honeypot_probe_id\\\", honeypot_probe_id)\\n if ping is not None:\\n pulumi.set(__self__, \\\"ping\\\", ping)\\n if probe_type is not None:\\n pulumi.set(__self__, \\\"probe_type\\\", probe_type)\\n if probe_version is not None:\\n pulumi.set(__self__, \\\"probe_version\\\", probe_version)\\n if proxy_ip is not None:\\n pulumi.set(__self__, \\\"proxy_ip\\\", proxy_ip)\\n if service_ip_lists is not None:\\n pulumi.set(__self__, \\\"service_ip_lists\\\", service_ip_lists)\\n if status is not None:\\n pulumi.set(__self__, \\\"status\\\", status)\\n if uuid is not None:\\n pulumi.set(__self__, \\\"uuid\\\", uuid)\\n if vpc_id is not None:\\n pulumi.set(__self__, \\\"vpc_id\\\", vpc_id)\",\n \"def __init__(__self__, *,\\n address_family: pulumi.Input[str],\\n ipam_scope_id: pulumi.Input[str],\\n allocation_default_netmask_length: Optional[pulumi.Input[int]] = None,\\n allocation_max_netmask_length: Optional[pulumi.Input[int]] = None,\\n allocation_min_netmask_length: Optional[pulumi.Input[int]] = None,\\n allocation_resource_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n auto_import: Optional[pulumi.Input[bool]] = None,\\n aws_service: Optional[pulumi.Input[str]] = None,\\n description: Optional[pulumi.Input[str]] = None,\\n locale: Optional[pulumi.Input[str]] = None,\\n public_ip_source: Optional[pulumi.Input[str]] = None,\\n publicly_advertisable: Optional[pulumi.Input[bool]] = None,\\n source_ipam_pool_id: Optional[pulumi.Input[str]] = None,\\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\\n pulumi.set(__self__, \\\"address_family\\\", address_family)\\n pulumi.set(__self__, \\\"ipam_scope_id\\\", ipam_scope_id)\\n if allocation_default_netmask_length is not None:\\n pulumi.set(__self__, \\\"allocation_default_netmask_length\\\", allocation_default_netmask_length)\\n if allocation_max_netmask_length is not None:\\n pulumi.set(__self__, \\\"allocation_max_netmask_length\\\", allocation_max_netmask_length)\\n if allocation_min_netmask_length is not None:\\n pulumi.set(__self__, \\\"allocation_min_netmask_length\\\", allocation_min_netmask_length)\\n if allocation_resource_tags is not None:\\n pulumi.set(__self__, \\\"allocation_resource_tags\\\", allocation_resource_tags)\\n if auto_import is not None:\\n pulumi.set(__self__, \\\"auto_import\\\", auto_import)\\n if aws_service is not None:\\n pulumi.set(__self__, \\\"aws_service\\\", aws_service)\\n if description is not None:\\n pulumi.set(__self__, \\\"description\\\", description)\\n if locale is not None:\\n pulumi.set(__self__, \\\"locale\\\", locale)\\n if public_ip_source is not None:\\n pulumi.set(__self__, \\\"public_ip_source\\\", public_ip_source)\\n if publicly_advertisable is not None:\\n pulumi.set(__self__, \\\"publicly_advertisable\\\", publicly_advertisable)\\n if source_ipam_pool_id is not None:\\n pulumi.set(__self__, \\\"source_ipam_pool_id\\\", source_ipam_pool_id)\\n if tags is not None:\\n pulumi.set(__self__, \\\"tags\\\", tags)\",\n \"def __init__(__self__, *,\\n control_node_id: pulumi.Input[str],\\n display_name: pulumi.Input[str],\\n probe_type: pulumi.Input[str],\\n arp: Optional[pulumi.Input[bool]] = None,\\n honeypot_bind_lists: Optional[pulumi.Input[Sequence[pulumi.Input['HoneypotProbeHoneypotBindListArgs']]]] = None,\\n ping: Optional[pulumi.Input[bool]] = None,\\n probe_version: Optional[pulumi.Input[str]] = None,\\n proxy_ip: Optional[pulumi.Input[str]] = None,\\n service_ip_lists: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n uuid: Optional[pulumi.Input[str]] = None,\\n vpc_id: Optional[pulumi.Input[str]] = None):\\n pulumi.set(__self__, \\\"control_node_id\\\", control_node_id)\\n pulumi.set(__self__, \\\"display_name\\\", display_name)\\n pulumi.set(__self__, \\\"probe_type\\\", probe_type)\\n if arp is not None:\\n pulumi.set(__self__, \\\"arp\\\", arp)\\n if honeypot_bind_lists is not None:\\n pulumi.set(__self__, \\\"honeypot_bind_lists\\\", honeypot_bind_lists)\\n if ping is not None:\\n pulumi.set(__self__, \\\"ping\\\", ping)\\n if probe_version is not None:\\n pulumi.set(__self__, \\\"probe_version\\\", probe_version)\\n if proxy_ip is not None:\\n pulumi.set(__self__, \\\"proxy_ip\\\", proxy_ip)\\n if service_ip_lists is not None:\\n pulumi.set(__self__, \\\"service_ip_lists\\\", service_ip_lists)\\n if uuid is not None:\\n pulumi.set(__self__, \\\"uuid\\\", uuid)\\n if vpc_id is not None:\\n pulumi.set(__self__, \\\"vpc_id\\\", vpc_id)\",\n \"def test_no_ip_address_passed(self, api_client):\\n runner = CliRunner()\\n\\n with patch(\\\"greynoise.cli.helper.sys\\\") as sys:\\n sys.stdin.isatty.return_value = True\\n result = runner.invoke(\\n subcommand.quick, parent=Context(main, info_name=\\\"greynoise\\\")\\n )\\n assert result.exit_code == -1\\n assert \\\"Usage: greynoise quick\\\" in result.output\\n api_client.quick.assert_not_called()\",\n \"def __init__(__self__, *,\\n acl_id: Optional[pulumi.Input[str]] = None,\\n description: Optional[pulumi.Input[str]] = None,\\n dest_cidr: Optional[pulumi.Input[str]] = None,\\n dest_port_range: Optional[pulumi.Input[str]] = None,\\n direction: Optional[pulumi.Input[str]] = None,\\n ip_protocol: Optional[pulumi.Input[str]] = None,\\n policy: Optional[pulumi.Input[str]] = None,\\n priority: Optional[pulumi.Input[int]] = None,\\n source_cidr: Optional[pulumi.Input[str]] = None,\\n source_port_range: Optional[pulumi.Input[str]] = None):\\n if acl_id is not None:\\n pulumi.set(__self__, \\\"acl_id\\\", acl_id)\\n if description is not None:\\n pulumi.set(__self__, \\\"description\\\", description)\\n if dest_cidr is not None:\\n pulumi.set(__self__, \\\"dest_cidr\\\", dest_cidr)\\n if dest_port_range is not None:\\n pulumi.set(__self__, \\\"dest_port_range\\\", dest_port_range)\\n if direction is not None:\\n pulumi.set(__self__, \\\"direction\\\", direction)\\n if ip_protocol is not None:\\n pulumi.set(__self__, \\\"ip_protocol\\\", ip_protocol)\\n if policy is not None:\\n pulumi.set(__self__, \\\"policy\\\", policy)\\n if priority is not None:\\n pulumi.set(__self__, \\\"priority\\\", priority)\\n if source_cidr is not None:\\n pulumi.set(__self__, \\\"source_cidr\\\", source_cidr)\\n if source_port_range is not None:\\n pulumi.set(__self__, \\\"source_port_range\\\", source_port_range)\",\n \"def test_invalid_ip_address_as_argument(self, api_client):\\n runner = CliRunner()\\n\\n expected = 'Error: Invalid value for \\\"[IP_ADDRESS]...\\\": not-an-ip\\\\n'\\n\\n result = runner.invoke(subcommand.ip, [\\\"not-an-ip\\\"])\\n assert result.exit_code == 2\\n assert expected in result.output\\n api_client.ip.assert_not_called()\",\n \"def __init__(__self__, *,\\n activation_key: Optional[pulumi.Input[str]] = None,\\n ip_address: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None,\\n private_link_endpoint: Optional[pulumi.Input[str]] = None,\\n security_group_arns: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n subnet_arns: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n vpc_endpoint_id: Optional[pulumi.Input[str]] = None):\\n if activation_key is not None:\\n pulumi.set(__self__, \\\"activation_key\\\", activation_key)\\n if ip_address is not None:\\n pulumi.set(__self__, \\\"ip_address\\\", ip_address)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if private_link_endpoint is not None:\\n pulumi.set(__self__, \\\"private_link_endpoint\\\", private_link_endpoint)\\n if security_group_arns is not None:\\n pulumi.set(__self__, \\\"security_group_arns\\\", security_group_arns)\\n if subnet_arns is not None:\\n pulumi.set(__self__, \\\"subnet_arns\\\", subnet_arns)\\n if tags is not None:\\n pulumi.set(__self__, \\\"tags\\\", tags)\\n if vpc_endpoint_id is not None:\\n pulumi.set(__self__, \\\"vpc_endpoint_id\\\", vpc_endpoint_id)\",\n \"def test_ip(response):\\n \\n # from comeon_core import update\\n ip = getIP()\\n print(ip)\\n #init_db(engine)\\n #update()\\n assert True\",\n \"def test_accepts_init_with_strict_subset_of_args(self):\\n\\n class API(platform.PlatformAPI):\\n def __init__(self, base_url):\\n pass\\n\\n api = API(\\\"some-url\\\")\\n assert isinstance(api, platform.PlatformAPI)\",\n \"def __init__(__self__, *,\\n dry_run: Optional[pulumi.Input[bool]] = None,\\n load_balancer_id: Optional[pulumi.Input[str]] = None,\\n security_group_id: Optional[pulumi.Input[str]] = None):\\n if dry_run is not None:\\n pulumi.set(__self__, \\\"dry_run\\\", dry_run)\\n if load_balancer_id is not None:\\n pulumi.set(__self__, \\\"load_balancer_id\\\", load_balancer_id)\\n if security_group_id is not None:\\n pulumi.set(__self__, \\\"security_group_id\\\", security_group_id)\",\n \"def __init__(__self__, *,\\n resource_group: pulumi.Input[str],\\n server: pulumi.Input[str],\\n subnet_name: pulumi.Input[str],\\n v_net_name: pulumi.Input[str],\\n v_net_resource_group: pulumi.Input[str],\\n ignore_missing_service_endpoint: Optional[pulumi.Input[bool]] = None):\\n pulumi.set(__self__, \\\"resource_group\\\", resource_group)\\n pulumi.set(__self__, \\\"server\\\", server)\\n pulumi.set(__self__, \\\"subnet_name\\\", subnet_name)\\n pulumi.set(__self__, \\\"v_net_name\\\", v_net_name)\\n pulumi.set(__self__, \\\"v_net_resource_group\\\", v_net_resource_group)\\n if ignore_missing_service_endpoint is not None:\\n pulumi.set(__self__, \\\"ignore_missing_service_endpoint\\\", ignore_missing_service_endpoint)\",\n \"def __init__(__self__, *,\\n resource_group: pulumi.Input[str],\\n server: pulumi.Input[str],\\n subnet_name: pulumi.Input[str],\\n v_net_name: pulumi.Input[str],\\n v_net_resource_group: pulumi.Input[str],\\n ignore_missing_service_endpoint: Optional[pulumi.Input[bool]] = None):\\n pulumi.set(__self__, \\\"resource_group\\\", resource_group)\\n pulumi.set(__self__, \\\"server\\\", server)\\n pulumi.set(__self__, \\\"subnet_name\\\", subnet_name)\\n pulumi.set(__self__, \\\"v_net_name\\\", v_net_name)\\n pulumi.set(__self__, \\\"v_net_resource_group\\\", v_net_resource_group)\\n if ignore_missing_service_endpoint is not None:\\n pulumi.set(__self__, \\\"ignore_missing_service_endpoint\\\", ignore_missing_service_endpoint)\",\n \"def __init__(self):\\n # assert(self.validate('61882613000194'))\\n # assert(self.validate('061882613000190'))\\n # assert(not self.validate('61882613000195'))\\n pass\",\n \"def __init__(__self__, *,\\n end_ip_address: pulumi.Input[str],\\n resource_group: pulumi.Input[str],\\n server: pulumi.Input[str],\\n start_ip_address: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"end_ip_address\\\", end_ip_address)\\n pulumi.set(__self__, \\\"resource_group\\\", resource_group)\\n pulumi.set(__self__, \\\"server\\\", server)\\n pulumi.set(__self__, \\\"start_ip_address\\\", start_ip_address)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7339444","0.7324193","0.7324193","0.7323932","0.70612985","0.6996996","0.6709637","0.6705524","0.6618657","0.65942365","0.6415844","0.6387556","0.6366282","0.6358961","0.6319033","0.6228522","0.6208983","0.6139439","0.6108403","0.6083423","0.6066069","0.60649264","0.60638696","0.6060406","0.5978354","0.59780127","0.5971527","0.59547675","0.5952458","0.59514964","0.59512967","0.5949955","0.5934184","0.5925605","0.59053445","0.5902148","0.5901118","0.58933634","0.589113","0.58839923","0.5883026","0.5864569","0.5855067","0.58521193","0.58512723","0.5850215","0.583253","0.58250403","0.5823746","0.5820773","0.5790049","0.57827234","0.57763267","0.57727593","0.5770694","0.5762999","0.57540727","0.57218397","0.57173634","0.5710184","0.57088715","0.5704685","0.5686824","0.5681912","0.5676905","0.56735677","0.5670732","0.56670713","0.56635016","0.566248","0.56583","0.5655936","0.5651818","0.565132","0.56496894","0.5649274","0.56462127","0.56401265","0.56353915","0.56340635","0.5632975","0.5632557","0.5632552","0.5630514","0.5625715","0.56255454","0.5623444","0.56113744","0.560422","0.55947","0.55923027","0.5588811","0.5584358","0.5576081","0.5574611","0.55706567","0.5569842","0.5569842","0.5556032","0.5554201"],"string":"[\n \"0.7339444\",\n \"0.7324193\",\n \"0.7324193\",\n \"0.7323932\",\n \"0.70612985\",\n \"0.6996996\",\n \"0.6709637\",\n \"0.6705524\",\n \"0.6618657\",\n \"0.65942365\",\n \"0.6415844\",\n \"0.6387556\",\n \"0.6366282\",\n \"0.6358961\",\n \"0.6319033\",\n \"0.6228522\",\n \"0.6208983\",\n \"0.6139439\",\n \"0.6108403\",\n \"0.6083423\",\n \"0.6066069\",\n \"0.60649264\",\n \"0.60638696\",\n \"0.6060406\",\n \"0.5978354\",\n \"0.59780127\",\n \"0.5971527\",\n \"0.59547675\",\n \"0.5952458\",\n \"0.59514964\",\n \"0.59512967\",\n \"0.5949955\",\n \"0.5934184\",\n \"0.5925605\",\n \"0.59053445\",\n \"0.5902148\",\n \"0.5901118\",\n \"0.58933634\",\n \"0.589113\",\n \"0.58839923\",\n \"0.5883026\",\n \"0.5864569\",\n \"0.5855067\",\n \"0.58521193\",\n \"0.58512723\",\n \"0.5850215\",\n \"0.583253\",\n \"0.58250403\",\n \"0.5823746\",\n \"0.5820773\",\n \"0.5790049\",\n \"0.57827234\",\n \"0.57763267\",\n \"0.57727593\",\n \"0.5770694\",\n \"0.5762999\",\n \"0.57540727\",\n \"0.57218397\",\n \"0.57173634\",\n \"0.5710184\",\n \"0.57088715\",\n \"0.5704685\",\n \"0.5686824\",\n \"0.5681912\",\n \"0.5676905\",\n \"0.56735677\",\n \"0.5670732\",\n \"0.56670713\",\n \"0.56635016\",\n \"0.566248\",\n \"0.56583\",\n \"0.5655936\",\n \"0.5651818\",\n \"0.565132\",\n \"0.56496894\",\n \"0.5649274\",\n \"0.56462127\",\n \"0.56401265\",\n \"0.56353915\",\n \"0.56340635\",\n \"0.5632975\",\n \"0.5632557\",\n \"0.5632552\",\n \"0.5630514\",\n \"0.5625715\",\n \"0.56255454\",\n \"0.5623444\",\n \"0.56113744\",\n \"0.560422\",\n \"0.55947\",\n \"0.55923027\",\n \"0.5588811\",\n \"0.5584358\",\n \"0.5576081\",\n \"0.5574611\",\n \"0.55706567\",\n \"0.5569842\",\n \"0.5569842\",\n \"0.5556032\",\n \"0.5554201\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7619989"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":3990,"cells":{"query":{"kind":"string","value":"User not logged in returns 200"},"document":{"kind":"string","value":"def test_not_logged_in(self):\n response = self.c.get(reverse(map_page), {'lat': 34.0, 'lng': 45.3})\n self.assertEqual(response.status_code, 200)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def user_logged_in():\n if not session.get('user_id'):\n return \"nope\", 401\n else:\n return \"yep\", 200","def test_returns_401_if_user_not_logged_in(self):\n # Act\n response = self.client.get(self.url)\n self.assertEqual(response.status_code, 401)","def test_returns_401_if_user_not_logged_in(self):\n # Act\n response = self.client.get(self.url)\n self.assertEqual(response.status_code, 401)","def test_returns_401_if_user_not_logged_in(self):\n # Act\n response = self.client.get(self.url)\n self.assertEqual(response.status_code, 401)","def check_user_and_login(self) -> Response:\n pass","def check_if_logged_in(request):\n if request.user.username:\n try:\n data = {'username': request.user.username, 'logged in': True}\n return JsonResponse(data=data, status=status.HTTP_200_OK)\n except:\n print(request.user.username)\n data = {'logged in': False}\n return JsonResponse(data=data, status=status.HTTP_200_OK)\n else:\n data = {'logged in': False}\n return JsonResponse(data=data, status=status.HTTP_200_OK)\n return JsonResponse(data=data, status=status.HTTP_200_OK)","def get(self):\n if(logout()):\n return \"User successfully logged out\", 200\n else:\n return \"Error logging out\", 400","def post(self):\n if \"user\" in session.keys():\n session.pop(\"user\")\n return jsonify(\"You are logged Out!\")\n else:\n return jsonify(\"You are not logged in\")","def test_retrive_user_unauthenticated(self):\n res = self.client.get(ME_URL)\n\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def test_not_logged_in(self):\n response = self.c.get(reverse(submit_point), {'lat': 34.0, 'lng': 45.3, 'zoom': 13})\n self.assertEqual(response.status_code, 403)","def test_not_authenticated(self):\n self.client.logout()\n response = self._get(get_kwargs=self._data())\n self._check_response(response, 101)\n self.assertEqual(UserFitbit.objects.count(), 1)","def test_not_logged_in(self):\n self.request.user = None\n result = user_id_put_view(self.request)['d']\n self.assertEqual(result, error_dict('api_errors', 'not authenticated for this request'))","def test_not_authenticated(self):\n pass # lint-amnesty, pylint: disable=unnecessary-pass","def test_not_authenticated(self):\n pass # lint-amnesty, pylint: disable=unnecessary-pass","def test_loggin_required(self):\n response = self.client.get(RESGATE_URL)\n\n self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED)","def test_emotion_analysis_route_get_has_200_logged_in(self):\n self.client.login(username='dan', password='password')\n response = self.client.get(reverse_lazy('emotion_analysis'))\n self.assertEqual(response.status_code, 200)","def test_status_code_for_signed_user(self):\n self.client.login(username=\"john\", password=\"pass\")\n response = self.client.get(self.get_url())\n self.assertEqual(response.status_code, self.status_no_permission)","def test_retrieve_user_unautherized(self):\n res = self.client.get(ME_URL)\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def post(self, request):\n try:\n user = User.objects.all()\n print(user)\n if user.filter(username=request.GET.get(\"username\")).filter(password=request.GET.get(\"password\")):\n return Response({\"message\": \"USER LOGGED IN\"}, status=200)\n print(request.user)\n return Response({\"message\": \"USER LOGGED IN\"}, status=200)\n except ObjectDoesNotExist as e:\n return Response(e)","def test_get_authenticated(self):\n self.verify_get_response(self.client.get(STATUS_PATH))","def test_login_required(self):\n res = self.client.get(INGREDIENT_URL)\n\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def authcheck():\n user = get_user()\n return jsonify({'current_identity': user.username})","def get (self):\n\n logged_in, db_user = ADayThere.logged_in_user ()\n if not logged_in:\n self.response.status = 401\n return\n\n res = self.__build_response (db_user)\n self.response.write (json.dumps (res))","def test_login_required(self):\n res = self.client.get(INGREDIENTS_URL)\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def test_retrieve_unauthorized_user(self):\n\n response = self.client.get(URL_ME)\n self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED)","def ping_missing_user(request):\r\n return _api_response(request, {\r\n 'success': False,\r\n 'message': 'Missing username in your api url.'\r\n })","def test_profile_api_anon(self):\n self.client.logout()\n response = self.client.get(self.url)\n self.assertEqual(response.status_code, 403)","def test_unauthenticated_request(self):\n url = self.get_url(self.active_user.id)\n response = self.client.get(url)\n\n expected_status_code = 401\n self.assertEqual(response.status_code, expected_status_code)","def test_retrieve_user_unauthorized(self):\r\n res = self.client.get(ME_URL)\r\n\r\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def test_retrieve_user_unauthorized(self):\n res = self.client.get(ME_URL)\n\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def test_retrieve_user_unauthorized(self):\n res = self.client.get(ME_URL)\n\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def test_login_required(self):\n\n res = self.client.get(INGREDIENTS_URL)\n\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def test_login_required(self):\n\n res = self.client.get(INGREDIENTS_URL)\n\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def test_status_code_for_anonymous_user(self):\n response = self.client.get(self.get_url())\n self.assertEqual(response.status_code, self.status_anonymous)","def test_get_unauthenticated(self):\n del self.client.request_kwargs['auth']\n self.verify_get_response(self.client.get(STATUS_PATH))","def noauth(self):\n try:\n # some endpoints dont return json\n return self.json['response'].get('error_id') == 'NOAUTH'\n except:\n return False","def before_request():\n if g.current_user.is_anonymous:\n return forbidden('Not signed in')\n\n if not g.current_user.confirmed:\n return forbidden('Unconfirmed account')","def test_homepage_logged_in_except(self):\r\n\r\n u1 = User.query.filter_by(username='testuser').one()\r\n u1.location = 'US-FAKE'\r\n db.session.add(u1)\r\n db.session.commit()\r\n\r\n with self.client as c:\r\n with c.session_transaction() as sess:\r\n sess[CURR_USER_KEY] = u1.id\r\n response = c.get('/')\r\n self.assertEqual(response.status_code, 200)\r\n self.assertIn(b'No data found for your region.', response.data)","def test_non_existing_user_login(self):\n user = {\n 'email': 'test@gmail.com',\n 'password': 'password123'}\n res = self.app.post('/login', data=user)\n self.assertEqual(res.status_code, 200)\n self.assertIn(\"You have no account\", str(res.data))","def before_request() -> None:\n if current_user.is_anonymous() or not current_user.is_allowed():\n abort(401)","def test_token(self):\n api_response = requests.get(self.api_config.get_api_url() + \"greetings/isloggedin\",\n headers={\"Authorization\": \"Bearer \" + self.API_TOKEN})\n\n if api_response.status_code == 401 or 403:\n return False\n else:\n return True","def test_login_get(self, *_):\n login = views.Login.as_view()\n request = self.factory.get(\"\")\n request.user = self.anonymous_user\n\n result = login(request)\n self.assertIsInstance(result, TemplateResponse)\n validate_html(result.render())\n self.assertEqual(result.status_code, 200)\n\n request.user = self.local_user\n result = login(request)\n self.assertEqual(result.url, \"/\")\n self.assertEqual(result.status_code, 302)","def test_retrieve_author_unlogged(self):\n request = self.client.get(self.epoint)\n\n self.assertEqual(request.status_code, status.HTTP_200_OK)","def get_logged_info():\n user = current_identity\n return make_response(dumps({\"status\": True, \"user\": user}), 200)","def test_if_not_available_for_unauthorized(self):\r\n res = self.not_authenticated.get(reverse(LIST_USER_URL),data={})\r\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def testNoPermission(self):\n self.login_user(self.user)\n response = self.client.get(self.url, self.args)\n self.assertEqual(response.status_code, 302)","def test_no_user(self):\n self.request.user = None\n result = user_id_get_view(self.request)['d']\n self.assertEqual(result, error_dict('api_errors', 'not authenticated for this request'))","def test_unknown_user(self):\n self.sign_in()\n response = self.client.get(reverse('backend:user_details', args=(0,)))\n self.assertEqual(response.status_code, 404)","def check_user():\n token = request.headers['Authorization'].replace('Bearer ', '')\n return jsonify({\"access_token\": token}), 200","def test_get_main_page_without_logged_in_user(self):\n response = self.testapp.get('/')\n self.assertEqual(response.status_int, 200)","def test_whoami_by_anonymous_user(self):\n response = self.client.get(\"/api/users/whoami/\")\n self.assertEqual(response.status_code, 401)","def kualalumpur():\n if \"username\" in session:\n return render_template(\"kualalumpur.html\")\n return abort(401)","def test_emotion_history_route_has_200_response_logged_in(self):\n self.client.login(username='dan', password='password')\n now = timezone.now()\n response = self.client.get(reverse_lazy('emotion_history',\n kwargs={\n 'year': now.year,\n 'month': now.month,\n 'day': now.day\n }))\n self.assertEqual(response.status_code, 200)","def special(request):\n return HttpResponse(\"You are logged in !\")","def test_login_required(self):\n res = self.client.get(RAINGAUGEREADING_URL)\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def test_login_required(self):\n res = self.client.get(RECIPE_URL)\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def test_retrieve_user_unauthorized(self):\n # HTTP GET Request\n response = self.client.get(ME_URL)\n\n # If you call the URL without authorization\n self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED)","def test_nonexistent_user(self):\n self.client.login(username=self.global_staff.username, password=self.password)\n resp = self.client.get(self.get_url('IDoNotExist'))\n assert resp.status_code == status.HTTP_404_NOT_FOUND","def getUser():\n\n if 'token' in session:\n return \"Authenticated\"\n else:\n return \"Unauthenticated\"","def test_login_for_user_not_registered(self):\n response = self.client.post(LOGIN_URL,\n data=json.dumps(\n {'username': 'otieno', 'password': 'otieno254'}),\n content_type='application/json')\n self.assertEqual(response.status_code, 404)\n result = json.loads(response.data.decode())\n self.assertEqual(result['message'], 'User unavailable')","def unauthorized():\n flash('You must be logged in to view that page')\n return redirect(url_for('catalog_bp.index'))","def test_login_required(self):\n res = self.client.get(RETETA_URL)\n\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def unauthorized():\n #flash('You must be logged in to view that page.')\n return redirect(url_for('login'))","def test_login_no_user(self):\n post_data = client.post(LOGIN_URL, json=self.post_data1)\n self.assertEqual(post_data.status_code, 401)\n self.assertEqual(post_data.get_json()[\"msg\"], \"Incorrect username.\")","def test_user_not_authorized(self):\n response = self.client.post(self.url)\n self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN)","def index():\n if auth.user:\n message=\"Welcome: \"\n user=auth.user\n else:\n message=\"Please use login for testing...\"\n user=None\n return dict(message=message, user=user)","def test_no_redirect(self):\n self.create_user_and_login(\n agreed_to_terms_of_service=True,\n filled_out=True\n )\n\n resp = self.client.get(DASHBOARD_URL)\n assert resp.status_code == 200","def login_require(request):\n\n if request.method == \"GET\":\n data = request.GET\n else:\n data = request.POST\n user = authenticate(username=data[\"username\"], password=data[\"password\"])\n if user and user.is_active:\n ret = Response(SUCCESS, error_code[SUCCESS])\n else: \n ret = Response(AUTHENTICATION_FAIL, error_code[AUTHENTICATION_FAIL])\n return HttpResponse(ret.serialize(f))\n\n # Generate a token for authentication\n token = token_generator(30)\n try:\n user_token = Token.objects.get(username=data[\"username\"])\n user_token.token = token\n user_token.start_time = datetime.now()\n except: \n user_token = Token(token=token, username=data[\"username\"])\n user_token.save()\n ret.set_ret(\"auth_token\", token) \n user = User.objects.get(username=data[\"username\"])\n ret.set_ret(\"data\", UserSerializer(user.appuser).serialize())\n return HttpResponse(ret.serialize(f))","def test_unauthenticated_user_denial(self):\n\n self.response = self.client.get(\"/api/users/users_list/\")\n self.assertEqual(self.response.status_code, status.HTTP_403_FORBIDDEN)\n self.assertEqual(\n 'Authentication credentials were not provided.', self.response.data['detail'])","def rest_test_no_auth():\n # Permission check is not applicable here\n return jsonify({\"answer\": 42})","def get_user():\n\treturn '1', 200","def test_login_required(self):\n self.client.logout()\n response = self.client.post(self.get_url(), {})\n self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN)","def test_auth_required(self):\n res = self.client.get(INGREDIENTS_URL)\n\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def test_login_required(self):\n res = self.client.get(TAGS_URL)\n\n self.assertEqual(res.status_code,status.HTTP_401_UNAUTHORIZED)","def test_authentication_is_not_required(self):\n # Act\n response = self.client.get(self.url)\n self.assertEqual(response.status_code, 200)","def singapore():\n if \"username\" in session:\n return render_template(\"singapore.html\")\n return abort(401)","def view_login(self):\n with self.client.get(\"/login\", catch_response=True) as response:\n for r_hist in response.history:\n if r_hist.status_code > 200 and r_hist.status_code < 400:\n response.failure(\"Logged on: Got redirect to /home\")","def test_not_logged_user_cannot_access(self):\n\n utils.test_not_logged_cannot_access(self, self.url)","def test_not_logged_user_cannot_access(self):\n\n utils.test_not_logged_cannot_access(self, self.url)","def test_not_logged_user_cannot_access(self):\n\n utils.test_not_logged_cannot_access(self, self.url)","def test_not_logged_user_cannot_access(self):\n\n utils.test_not_logged_cannot_access(self, self.url)","def is_authenticated(self):\n return False","def penang():\n if \"username\" in session:\n return render_template(\"penang.html\")\n return abort(401)","def test_non_registered_user_login(self):\n response = self.client.post(\n '/api/v1/auth/login',\n data=json.dumps(dict(\n username='jimmy',\n password='123456'\n )),\n content_type='application/json'\n )\n data = json.loads(response.data.decode())\n self.assertTrue(response.content_type == 'application/json')\n self.assertEqual(response.status_code, 404)","def unauthorized_handler(self):\n return flask.redirect(\"/login\")","def test_getting_inactive_user(self):\n url = self.get_url(self.inactive_user.id)\n with authenticated_user_api_client(self.client, self.active_user):\n expected_response_code = 404\n response = self.client.get(url)\n\n self.assertEqual(response.status_code, expected_response_code)","def failed(request):\n\n user = request.authenticated_userid\n return {'user': user}","def user_must_authenticate():\n return Response(\n 'Could not verify your access level for that URL.\\n'\n 'You have to login with proper credentials', 401,\n {'WWW-Authenticate': 'Basic realm=\"Login Required\"'})","def logged_in(request):\n return request.current_user is not None","def test_anonymous(self):\n self.logout_user()\n\n response = self.client.get(self.api_link)\n self.assertContains(response, \"sign in to use private threads\", status_code=403)","def GET_validuser(self):\r\n c.response_content_type = 'text/plain'\r\n if c.user_is_loggedin:\r\n return c.user.name\r\n else:\r\n return ''","def test_logout_un_logged_in_user_false(self):\n resp = self.client().post('/api/v1/auth/logout/1')\n self.assertEqual(resp.status_code, 400)\n resp = resp.get_json()\n self.assertEqual(resp['error'],\n 'That user is not logged in')","def view_index(self):\n with self.client.get(\"/\", catch_response=True) as response:\n for r_hist in response.history:\n if r_hist.status_code > 200 and r_hist.status_code < 400:\n response.failure(\"Not logged on: Got redirect to /login\")","def test_login_route_no_user(self):\n result = self.client.post(\"/login\",\n data={\"username\":\"test_user2\", \"password\":\"test_pass1\"}, follow_redirects=True)\n self.assertEqual(result.status_code, 200)\n self.assertIn(b\"Looks like you have not made an account yet!\", result.data)","def __call__(self,request):\n if not request.user.is_anonymous:\n if not request.user.is_staff:\n profile = request.user.profile\n if not profile.picture or not profile.biography:\n if request.path not in [reverse('users:update'), reverse('users:logout')]:\n return redirect('users:update')\n response = self.get_response(request)\n return response","def auth_user(request):\n print('user', request.COOKIES, request.user)\n if request.user.is_authenticated:\n response = json.dumps({\"user\":True, \"username\":request.user.username})\n else:\n response = json.dumps({\"user\":False})\n return HttpResponse(response, content_type='application/json')","def test_login_required(self):\n res = self.client.get(TAG_URL)\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)","def profile_unlogged():\n cookie = {'session_id': None}\n response = requests.get(f'{URL}/profile', cookies=cookie)\n assert response.status_code == 403","def unauthorized():\n flask.flash('You must be logged in to view that page.')\n return redirect(url_for('auth.sign_in'))","def test_login_required(self):\n res = self.client.get(TAGS_URL)\n\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)"],"string":"[\n \"def user_logged_in():\\n if not session.get('user_id'):\\n return \\\"nope\\\", 401\\n else:\\n return \\\"yep\\\", 200\",\n \"def test_returns_401_if_user_not_logged_in(self):\\n # Act\\n response = self.client.get(self.url)\\n self.assertEqual(response.status_code, 401)\",\n \"def test_returns_401_if_user_not_logged_in(self):\\n # Act\\n response = self.client.get(self.url)\\n self.assertEqual(response.status_code, 401)\",\n \"def test_returns_401_if_user_not_logged_in(self):\\n # Act\\n response = self.client.get(self.url)\\n self.assertEqual(response.status_code, 401)\",\n \"def check_user_and_login(self) -> Response:\\n pass\",\n \"def check_if_logged_in(request):\\n if request.user.username:\\n try:\\n data = {'username': request.user.username, 'logged in': True}\\n return JsonResponse(data=data, status=status.HTTP_200_OK)\\n except:\\n print(request.user.username)\\n data = {'logged in': False}\\n return JsonResponse(data=data, status=status.HTTP_200_OK)\\n else:\\n data = {'logged in': False}\\n return JsonResponse(data=data, status=status.HTTP_200_OK)\\n return JsonResponse(data=data, status=status.HTTP_200_OK)\",\n \"def get(self):\\n if(logout()):\\n return \\\"User successfully logged out\\\", 200\\n else:\\n return \\\"Error logging out\\\", 400\",\n \"def post(self):\\n if \\\"user\\\" in session.keys():\\n session.pop(\\\"user\\\")\\n return jsonify(\\\"You are logged Out!\\\")\\n else:\\n return jsonify(\\\"You are not logged in\\\")\",\n \"def test_retrive_user_unauthenticated(self):\\n res = self.client.get(ME_URL)\\n\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_not_logged_in(self):\\n response = self.c.get(reverse(submit_point), {'lat': 34.0, 'lng': 45.3, 'zoom': 13})\\n self.assertEqual(response.status_code, 403)\",\n \"def test_not_authenticated(self):\\n self.client.logout()\\n response = self._get(get_kwargs=self._data())\\n self._check_response(response, 101)\\n self.assertEqual(UserFitbit.objects.count(), 1)\",\n \"def test_not_logged_in(self):\\n self.request.user = None\\n result = user_id_put_view(self.request)['d']\\n self.assertEqual(result, error_dict('api_errors', 'not authenticated for this request'))\",\n \"def test_not_authenticated(self):\\n pass # lint-amnesty, pylint: disable=unnecessary-pass\",\n \"def test_not_authenticated(self):\\n pass # lint-amnesty, pylint: disable=unnecessary-pass\",\n \"def test_loggin_required(self):\\n response = self.client.get(RESGATE_URL)\\n\\n self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_emotion_analysis_route_get_has_200_logged_in(self):\\n self.client.login(username='dan', password='password')\\n response = self.client.get(reverse_lazy('emotion_analysis'))\\n self.assertEqual(response.status_code, 200)\",\n \"def test_status_code_for_signed_user(self):\\n self.client.login(username=\\\"john\\\", password=\\\"pass\\\")\\n response = self.client.get(self.get_url())\\n self.assertEqual(response.status_code, self.status_no_permission)\",\n \"def test_retrieve_user_unautherized(self):\\n res = self.client.get(ME_URL)\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def post(self, request):\\n try:\\n user = User.objects.all()\\n print(user)\\n if user.filter(username=request.GET.get(\\\"username\\\")).filter(password=request.GET.get(\\\"password\\\")):\\n return Response({\\\"message\\\": \\\"USER LOGGED IN\\\"}, status=200)\\n print(request.user)\\n return Response({\\\"message\\\": \\\"USER LOGGED IN\\\"}, status=200)\\n except ObjectDoesNotExist as e:\\n return Response(e)\",\n \"def test_get_authenticated(self):\\n self.verify_get_response(self.client.get(STATUS_PATH))\",\n \"def test_login_required(self):\\n res = self.client.get(INGREDIENT_URL)\\n\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def authcheck():\\n user = get_user()\\n return jsonify({'current_identity': user.username})\",\n \"def get (self):\\n\\n logged_in, db_user = ADayThere.logged_in_user ()\\n if not logged_in:\\n self.response.status = 401\\n return\\n\\n res = self.__build_response (db_user)\\n self.response.write (json.dumps (res))\",\n \"def test_login_required(self):\\n res = self.client.get(INGREDIENTS_URL)\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_retrieve_unauthorized_user(self):\\n\\n response = self.client.get(URL_ME)\\n self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def ping_missing_user(request):\\r\\n return _api_response(request, {\\r\\n 'success': False,\\r\\n 'message': 'Missing username in your api url.'\\r\\n })\",\n \"def test_profile_api_anon(self):\\n self.client.logout()\\n response = self.client.get(self.url)\\n self.assertEqual(response.status_code, 403)\",\n \"def test_unauthenticated_request(self):\\n url = self.get_url(self.active_user.id)\\n response = self.client.get(url)\\n\\n expected_status_code = 401\\n self.assertEqual(response.status_code, expected_status_code)\",\n \"def test_retrieve_user_unauthorized(self):\\r\\n res = self.client.get(ME_URL)\\r\\n\\r\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_retrieve_user_unauthorized(self):\\n res = self.client.get(ME_URL)\\n\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_retrieve_user_unauthorized(self):\\n res = self.client.get(ME_URL)\\n\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_login_required(self):\\n\\n res = self.client.get(INGREDIENTS_URL)\\n\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_login_required(self):\\n\\n res = self.client.get(INGREDIENTS_URL)\\n\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_status_code_for_anonymous_user(self):\\n response = self.client.get(self.get_url())\\n self.assertEqual(response.status_code, self.status_anonymous)\",\n \"def test_get_unauthenticated(self):\\n del self.client.request_kwargs['auth']\\n self.verify_get_response(self.client.get(STATUS_PATH))\",\n \"def noauth(self):\\n try:\\n # some endpoints dont return json\\n return self.json['response'].get('error_id') == 'NOAUTH'\\n except:\\n return False\",\n \"def before_request():\\n if g.current_user.is_anonymous:\\n return forbidden('Not signed in')\\n\\n if not g.current_user.confirmed:\\n return forbidden('Unconfirmed account')\",\n \"def test_homepage_logged_in_except(self):\\r\\n\\r\\n u1 = User.query.filter_by(username='testuser').one()\\r\\n u1.location = 'US-FAKE'\\r\\n db.session.add(u1)\\r\\n db.session.commit()\\r\\n\\r\\n with self.client as c:\\r\\n with c.session_transaction() as sess:\\r\\n sess[CURR_USER_KEY] = u1.id\\r\\n response = c.get('/')\\r\\n self.assertEqual(response.status_code, 200)\\r\\n self.assertIn(b'No data found for your region.', response.data)\",\n \"def test_non_existing_user_login(self):\\n user = {\\n 'email': 'test@gmail.com',\\n 'password': 'password123'}\\n res = self.app.post('/login', data=user)\\n self.assertEqual(res.status_code, 200)\\n self.assertIn(\\\"You have no account\\\", str(res.data))\",\n \"def before_request() -> None:\\n if current_user.is_anonymous() or not current_user.is_allowed():\\n abort(401)\",\n \"def test_token(self):\\n api_response = requests.get(self.api_config.get_api_url() + \\\"greetings/isloggedin\\\",\\n headers={\\\"Authorization\\\": \\\"Bearer \\\" + self.API_TOKEN})\\n\\n if api_response.status_code == 401 or 403:\\n return False\\n else:\\n return True\",\n \"def test_login_get(self, *_):\\n login = views.Login.as_view()\\n request = self.factory.get(\\\"\\\")\\n request.user = self.anonymous_user\\n\\n result = login(request)\\n self.assertIsInstance(result, TemplateResponse)\\n validate_html(result.render())\\n self.assertEqual(result.status_code, 200)\\n\\n request.user = self.local_user\\n result = login(request)\\n self.assertEqual(result.url, \\\"/\\\")\\n self.assertEqual(result.status_code, 302)\",\n \"def test_retrieve_author_unlogged(self):\\n request = self.client.get(self.epoint)\\n\\n self.assertEqual(request.status_code, status.HTTP_200_OK)\",\n \"def get_logged_info():\\n user = current_identity\\n return make_response(dumps({\\\"status\\\": True, \\\"user\\\": user}), 200)\",\n \"def test_if_not_available_for_unauthorized(self):\\r\\n res = self.not_authenticated.get(reverse(LIST_USER_URL),data={})\\r\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def testNoPermission(self):\\n self.login_user(self.user)\\n response = self.client.get(self.url, self.args)\\n self.assertEqual(response.status_code, 302)\",\n \"def test_no_user(self):\\n self.request.user = None\\n result = user_id_get_view(self.request)['d']\\n self.assertEqual(result, error_dict('api_errors', 'not authenticated for this request'))\",\n \"def test_unknown_user(self):\\n self.sign_in()\\n response = self.client.get(reverse('backend:user_details', args=(0,)))\\n self.assertEqual(response.status_code, 404)\",\n \"def check_user():\\n token = request.headers['Authorization'].replace('Bearer ', '')\\n return jsonify({\\\"access_token\\\": token}), 200\",\n \"def test_get_main_page_without_logged_in_user(self):\\n response = self.testapp.get('/')\\n self.assertEqual(response.status_int, 200)\",\n \"def test_whoami_by_anonymous_user(self):\\n response = self.client.get(\\\"/api/users/whoami/\\\")\\n self.assertEqual(response.status_code, 401)\",\n \"def kualalumpur():\\n if \\\"username\\\" in session:\\n return render_template(\\\"kualalumpur.html\\\")\\n return abort(401)\",\n \"def test_emotion_history_route_has_200_response_logged_in(self):\\n self.client.login(username='dan', password='password')\\n now = timezone.now()\\n response = self.client.get(reverse_lazy('emotion_history',\\n kwargs={\\n 'year': now.year,\\n 'month': now.month,\\n 'day': now.day\\n }))\\n self.assertEqual(response.status_code, 200)\",\n \"def special(request):\\n return HttpResponse(\\\"You are logged in !\\\")\",\n \"def test_login_required(self):\\n res = self.client.get(RAINGAUGEREADING_URL)\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_login_required(self):\\n res = self.client.get(RECIPE_URL)\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_retrieve_user_unauthorized(self):\\n # HTTP GET Request\\n response = self.client.get(ME_URL)\\n\\n # If you call the URL without authorization\\n self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_nonexistent_user(self):\\n self.client.login(username=self.global_staff.username, password=self.password)\\n resp = self.client.get(self.get_url('IDoNotExist'))\\n assert resp.status_code == status.HTTP_404_NOT_FOUND\",\n \"def getUser():\\n\\n if 'token' in session:\\n return \\\"Authenticated\\\"\\n else:\\n return \\\"Unauthenticated\\\"\",\n \"def test_login_for_user_not_registered(self):\\n response = self.client.post(LOGIN_URL,\\n data=json.dumps(\\n {'username': 'otieno', 'password': 'otieno254'}),\\n content_type='application/json')\\n self.assertEqual(response.status_code, 404)\\n result = json.loads(response.data.decode())\\n self.assertEqual(result['message'], 'User unavailable')\",\n \"def unauthorized():\\n flash('You must be logged in to view that page')\\n return redirect(url_for('catalog_bp.index'))\",\n \"def test_login_required(self):\\n res = self.client.get(RETETA_URL)\\n\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def unauthorized():\\n #flash('You must be logged in to view that page.')\\n return redirect(url_for('login'))\",\n \"def test_login_no_user(self):\\n post_data = client.post(LOGIN_URL, json=self.post_data1)\\n self.assertEqual(post_data.status_code, 401)\\n self.assertEqual(post_data.get_json()[\\\"msg\\\"], \\\"Incorrect username.\\\")\",\n \"def test_user_not_authorized(self):\\n response = self.client.post(self.url)\\n self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN)\",\n \"def index():\\n if auth.user:\\n message=\\\"Welcome: \\\"\\n user=auth.user\\n else:\\n message=\\\"Please use login for testing...\\\"\\n user=None\\n return dict(message=message, user=user)\",\n \"def test_no_redirect(self):\\n self.create_user_and_login(\\n agreed_to_terms_of_service=True,\\n filled_out=True\\n )\\n\\n resp = self.client.get(DASHBOARD_URL)\\n assert resp.status_code == 200\",\n \"def login_require(request):\\n\\n if request.method == \\\"GET\\\":\\n data = request.GET\\n else:\\n data = request.POST\\n user = authenticate(username=data[\\\"username\\\"], password=data[\\\"password\\\"])\\n if user and user.is_active:\\n ret = Response(SUCCESS, error_code[SUCCESS])\\n else: \\n ret = Response(AUTHENTICATION_FAIL, error_code[AUTHENTICATION_FAIL])\\n return HttpResponse(ret.serialize(f))\\n\\n # Generate a token for authentication\\n token = token_generator(30)\\n try:\\n user_token = Token.objects.get(username=data[\\\"username\\\"])\\n user_token.token = token\\n user_token.start_time = datetime.now()\\n except: \\n user_token = Token(token=token, username=data[\\\"username\\\"])\\n user_token.save()\\n ret.set_ret(\\\"auth_token\\\", token) \\n user = User.objects.get(username=data[\\\"username\\\"])\\n ret.set_ret(\\\"data\\\", UserSerializer(user.appuser).serialize())\\n return HttpResponse(ret.serialize(f))\",\n \"def test_unauthenticated_user_denial(self):\\n\\n self.response = self.client.get(\\\"/api/users/users_list/\\\")\\n self.assertEqual(self.response.status_code, status.HTTP_403_FORBIDDEN)\\n self.assertEqual(\\n 'Authentication credentials were not provided.', self.response.data['detail'])\",\n \"def rest_test_no_auth():\\n # Permission check is not applicable here\\n return jsonify({\\\"answer\\\": 42})\",\n \"def get_user():\\n\\treturn '1', 200\",\n \"def test_login_required(self):\\n self.client.logout()\\n response = self.client.post(self.get_url(), {})\\n self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN)\",\n \"def test_auth_required(self):\\n res = self.client.get(INGREDIENTS_URL)\\n\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def test_login_required(self):\\n res = self.client.get(TAGS_URL)\\n\\n self.assertEqual(res.status_code,status.HTTP_401_UNAUTHORIZED)\",\n \"def test_authentication_is_not_required(self):\\n # Act\\n response = self.client.get(self.url)\\n self.assertEqual(response.status_code, 200)\",\n \"def singapore():\\n if \\\"username\\\" in session:\\n return render_template(\\\"singapore.html\\\")\\n return abort(401)\",\n \"def view_login(self):\\n with self.client.get(\\\"/login\\\", catch_response=True) as response:\\n for r_hist in response.history:\\n if r_hist.status_code > 200 and r_hist.status_code < 400:\\n response.failure(\\\"Logged on: Got redirect to /home\\\")\",\n \"def test_not_logged_user_cannot_access(self):\\n\\n utils.test_not_logged_cannot_access(self, self.url)\",\n \"def test_not_logged_user_cannot_access(self):\\n\\n utils.test_not_logged_cannot_access(self, self.url)\",\n \"def test_not_logged_user_cannot_access(self):\\n\\n utils.test_not_logged_cannot_access(self, self.url)\",\n \"def test_not_logged_user_cannot_access(self):\\n\\n utils.test_not_logged_cannot_access(self, self.url)\",\n \"def is_authenticated(self):\\n return False\",\n \"def penang():\\n if \\\"username\\\" in session:\\n return render_template(\\\"penang.html\\\")\\n return abort(401)\",\n \"def test_non_registered_user_login(self):\\n response = self.client.post(\\n '/api/v1/auth/login',\\n data=json.dumps(dict(\\n username='jimmy',\\n password='123456'\\n )),\\n content_type='application/json'\\n )\\n data = json.loads(response.data.decode())\\n self.assertTrue(response.content_type == 'application/json')\\n self.assertEqual(response.status_code, 404)\",\n \"def unauthorized_handler(self):\\n return flask.redirect(\\\"/login\\\")\",\n \"def test_getting_inactive_user(self):\\n url = self.get_url(self.inactive_user.id)\\n with authenticated_user_api_client(self.client, self.active_user):\\n expected_response_code = 404\\n response = self.client.get(url)\\n\\n self.assertEqual(response.status_code, expected_response_code)\",\n \"def failed(request):\\n\\n user = request.authenticated_userid\\n return {'user': user}\",\n \"def user_must_authenticate():\\n return Response(\\n 'Could not verify your access level for that URL.\\\\n'\\n 'You have to login with proper credentials', 401,\\n {'WWW-Authenticate': 'Basic realm=\\\"Login Required\\\"'})\",\n \"def logged_in(request):\\n return request.current_user is not None\",\n \"def test_anonymous(self):\\n self.logout_user()\\n\\n response = self.client.get(self.api_link)\\n self.assertContains(response, \\\"sign in to use private threads\\\", status_code=403)\",\n \"def GET_validuser(self):\\r\\n c.response_content_type = 'text/plain'\\r\\n if c.user_is_loggedin:\\r\\n return c.user.name\\r\\n else:\\r\\n return ''\",\n \"def test_logout_un_logged_in_user_false(self):\\n resp = self.client().post('/api/v1/auth/logout/1')\\n self.assertEqual(resp.status_code, 400)\\n resp = resp.get_json()\\n self.assertEqual(resp['error'],\\n 'That user is not logged in')\",\n \"def view_index(self):\\n with self.client.get(\\\"/\\\", catch_response=True) as response:\\n for r_hist in response.history:\\n if r_hist.status_code > 200 and r_hist.status_code < 400:\\n response.failure(\\\"Not logged on: Got redirect to /login\\\")\",\n \"def test_login_route_no_user(self):\\n result = self.client.post(\\\"/login\\\",\\n data={\\\"username\\\":\\\"test_user2\\\", \\\"password\\\":\\\"test_pass1\\\"}, follow_redirects=True)\\n self.assertEqual(result.status_code, 200)\\n self.assertIn(b\\\"Looks like you have not made an account yet!\\\", result.data)\",\n \"def __call__(self,request):\\n if not request.user.is_anonymous:\\n if not request.user.is_staff:\\n profile = request.user.profile\\n if not profile.picture or not profile.biography:\\n if request.path not in [reverse('users:update'), reverse('users:logout')]:\\n return redirect('users:update')\\n response = self.get_response(request)\\n return response\",\n \"def auth_user(request):\\n print('user', request.COOKIES, request.user)\\n if request.user.is_authenticated:\\n response = json.dumps({\\\"user\\\":True, \\\"username\\\":request.user.username})\\n else:\\n response = json.dumps({\\\"user\\\":False})\\n return HttpResponse(response, content_type='application/json')\",\n \"def test_login_required(self):\\n res = self.client.get(TAG_URL)\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\",\n \"def profile_unlogged():\\n cookie = {'session_id': None}\\n response = requests.get(f'{URL}/profile', cookies=cookie)\\n assert response.status_code == 403\",\n \"def unauthorized():\\n flask.flash('You must be logged in to view that page.')\\n return redirect(url_for('auth.sign_in'))\",\n \"def test_login_required(self):\\n res = self.client.get(TAGS_URL)\\n\\n self.assertEqual(res.status_code, status.HTTP_401_UNAUTHORIZED)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.803735","0.7406583","0.7406583","0.7406583","0.7374086","0.7358094","0.73388165","0.72660834","0.72058254","0.7197486","0.7057259","0.69839096","0.6981634","0.6981634","0.6972179","0.6965677","0.6945636","0.69440126","0.68950224","0.68555284","0.6853421","0.685191","0.6836244","0.68302596","0.6813587","0.67933834","0.67921513","0.6784798","0.6784315","0.67841417","0.67841417","0.67765146","0.67765146","0.6770026","0.6755982","0.67347544","0.6710689","0.6697473","0.6652806","0.66424453","0.66319054","0.6611848","0.6608846","0.66045576","0.6602328","0.65905744","0.6590449","0.6586766","0.6584367","0.65796685","0.6572343","0.6560589","0.6556005","0.65488815","0.65429604","0.65353703","0.65329915","0.6527011","0.65240085","0.65235656","0.6522384","0.65192044","0.65144205","0.65142643","0.651082","0.64971864","0.6493165","0.64895827","0.6484136","0.6482015","0.64807355","0.6480157","0.64736766","0.64717686","0.64714885","0.64666396","0.6454917","0.6454257","0.6454257","0.6454257","0.6454257","0.6451972","0.6446855","0.64451796","0.64339435","0.642298","0.6405341","0.6405036","0.6393498","0.63923156","0.6390262","0.6386426","0.63834304","0.63826543","0.637537","0.6373378","0.637135","0.63699144","0.63567716","0.6346964"],"string":"[\n \"0.803735\",\n \"0.7406583\",\n \"0.7406583\",\n \"0.7406583\",\n \"0.7374086\",\n \"0.7358094\",\n \"0.73388165\",\n \"0.72660834\",\n \"0.72058254\",\n \"0.7197486\",\n \"0.7057259\",\n \"0.69839096\",\n \"0.6981634\",\n \"0.6981634\",\n \"0.6972179\",\n \"0.6965677\",\n \"0.6945636\",\n \"0.69440126\",\n \"0.68950224\",\n \"0.68555284\",\n \"0.6853421\",\n \"0.685191\",\n \"0.6836244\",\n \"0.68302596\",\n \"0.6813587\",\n \"0.67933834\",\n \"0.67921513\",\n \"0.6784798\",\n \"0.6784315\",\n \"0.67841417\",\n \"0.67841417\",\n \"0.67765146\",\n \"0.67765146\",\n \"0.6770026\",\n \"0.6755982\",\n \"0.67347544\",\n \"0.6710689\",\n \"0.6697473\",\n \"0.6652806\",\n \"0.66424453\",\n \"0.66319054\",\n \"0.6611848\",\n \"0.6608846\",\n \"0.66045576\",\n \"0.6602328\",\n \"0.65905744\",\n \"0.6590449\",\n \"0.6586766\",\n \"0.6584367\",\n \"0.65796685\",\n \"0.6572343\",\n \"0.6560589\",\n \"0.6556005\",\n \"0.65488815\",\n \"0.65429604\",\n \"0.65353703\",\n \"0.65329915\",\n \"0.6527011\",\n \"0.65240085\",\n \"0.65235656\",\n \"0.6522384\",\n \"0.65192044\",\n \"0.65144205\",\n \"0.65142643\",\n \"0.651082\",\n \"0.64971864\",\n \"0.6493165\",\n \"0.64895827\",\n \"0.6484136\",\n \"0.6482015\",\n \"0.64807355\",\n \"0.6480157\",\n \"0.64736766\",\n \"0.64717686\",\n \"0.64714885\",\n \"0.64666396\",\n \"0.6454917\",\n \"0.6454257\",\n \"0.6454257\",\n \"0.6454257\",\n \"0.6454257\",\n \"0.6451972\",\n \"0.6446855\",\n \"0.64451796\",\n \"0.64339435\",\n \"0.642298\",\n \"0.6405341\",\n \"0.6405036\",\n \"0.6393498\",\n \"0.63923156\",\n \"0.6390262\",\n \"0.6386426\",\n \"0.63834304\",\n \"0.63826543\",\n \"0.637537\",\n \"0.6373378\",\n \"0.637135\",\n \"0.63699144\",\n \"0.63567716\",\n \"0.6346964\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6876522"},"document_rank":{"kind":"string","value":"19"}}},{"rowIdx":3991,"cells":{"query":{"kind":"string","value":"The expression pt1 == pt2 returns True when pt1 is close to pt2"},"document":{"kind":"string","value":"def test_almost_equal(self):\n x = Point(\n lat=23.4,\n lng=23.1,\n author=self.u\n )\n self.assertTrue(self.a == x)\n self.assertFalse(self.a != x)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _same(p1,p2,prec=0.0001):\n #return num.all(num.equal(p1,p2))\n t1 = num.fabs(p1[0]-p2[0]) < prec\n t2 = num.fabs(p1[1]-p2[1]) < prec\n if t1 and t2:\n #print \"same\", p1,p2\n return True","def test_eq_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoint(1, 'Q2.8')\n assert a == b","def test_ge_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoint(1.1, 'Q2.8')\n assert b > a","def are_equal(self, sp1, sp2):\n return True","def _point_equal(a,b):\n return np.array_equal(a._Point__loc, b._Point__loc)","def almost_equals(self, other):\n import math\n ox, oy = other\n dx = self[0] - ox\n dy = self[1] - oy\n return (dx*dx + dy*dy) < pygonal.EPSILON2","def test_gt_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoint(1.1, 'Q2.8')\n assert b > a","def _point_almost_equal(a,b, rtol=RTOL, atol=ATOL):\n return np.allclose(a._Point__loc, b._Point__loc,\n rtol=rtol, atol=atol)","def fp_eq(x: float, y: float) -> bool:\n return fabs(x-y) < 10**-12","def are_equal(self, sp1, sp2):\n return sp1 == sp2","def realEqual(x,y,eps=10e-10):\n return abs(x-y) < eps","def test_lt_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoint(1.1, 'Q2.8')\n assert a < b","def are_equal(self, sp1, sp2):\n return","def __eq__(self, other):\n if isinstance(other, self.__class__):\n return math.isclose(self.x, other.x, rel_tol=1e-12, abs_tol=1e-12) and\\\n math.isclose(self.y, other.y, rel_tol=1e-12, abs_tol=1e-12)\n else:\n return False","def __comparing_points(self, point1, point2) -> bool:\n return (abs(point1.x - point2.x) <= self.dirt_pos_tolerance and abs(\n point1.y - point2.y) <= self.dirt_pos_tolerance)","def __eq__(self,v2):\n\t\treturn -1e-13<(self-v2).norm()<1e-13","def almost_equal(x, y):\n return abs(x-y) < FP_PREC","def approx_eq(a, b):\n return abs(a-b) < approx_eq.eps","def __eq__(self, other):\n return abs(self - other) < 10e-10","def test_le_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoint(1.1, 'Q2.8')\n assert a < b","def is_almost_equal(self, x ,y ,epsilon=1*10**(-8)):\n \treturn abs(x-y) <= epsilon","def almost_eq(e1,e2) :\n\treturn round(e1-e2,4) == 0.0","def eq(a, b):\n return abs(a - b) < .05","def __gt__(self, other):\n return self.x ** 2 + self.y ** 2 > other.x ** 2 + other.y ** 2","def __eq__(self, other):\r\n return abs(self.x - other.x) + abs(self.y - other.y) < Vertex.epsilon","def __eq__(self, pt):\n return self.x == pt.x and self.y == pt.y","def almost_equal_values(x, y, precision):\n return round(x - y, precision) == 0","def nearly_equal(a, b, sig_fig=5):\n return a == b or int(a*10**sig_fig) == int(b*10**sig_fig)","def __eq__(self, other: 'LTL'):\n if self.formula == other.formula:\n return True\n implied_a = self >= other\n implied_b = self <= other\n return implied_a and implied_b","def __eq__(self, other):\n return self.point == other.point","def __eq__(self, secondPoint):\n return self.xCoordinate == secondPoint.xCoordinate and self.yCoordinate == secondPoint.yCoordinate","def eq(df1, df2, precision=0.5) -> bool:\n return ((df1 - df2).abs() < precision).all()","def almost_equals(self, other, decimal=...): # -> bool:\n ...","def __eq__(self, other):\n return self.points == other.points","def test_point_relations(p1, p2):\n assert p1.left_of(p2) or p1.x >= p2.x\n assert p1.is_right_of(p2) or p1.x <= p2.x\n\n assert p1.left_of(p2) == p2.is_right_of(p1) or p1.x == p2.x\n assert not p1.left_of(p2) or not p1.is_right_of(p2)\n assert not p2.left_of(p1) or not p2.is_right_of(p1)","def __ge__(self, other):\n return self.x ** 2 + self.y ** 2 >= other.x ** 2 + other.y ** 2","def Q1_test():\n A, p1, p2 = [0,0], [2,4], [6,5]\n return (distance(A,p1) > 4.472135) and (distance(p1,p2) < 4.472136)","def fequal(pos_act, pos_exp, eps=1e-5):\n return abs(pos_act - pos_exp) < eps","def checarPs(self,p1,p2):\n return abs(p1-p2) < 0.00001","def verticesEqual(self, v1, v2, eps=1e-8):\n if abs(v1[0] - v2[0]) > eps:\n return False\n if abs(v1[1] - v2[1]) > eps:\n return False\n if abs(v1[2] - v2[2]) > eps:\n return False\n return True","def are_equal(self, sp1, sp2):\n for s1 in sp1.keys():\n spin1 = getattr(s1, \"spin\", 0)\n oxi1 = getattr(s1, \"oxi_state\", 0)\n for s2 in sp2.keys():\n spin2 = getattr(s2, \"spin\", 0)\n oxi2 = getattr(s2, \"oxi_state\", 0)\n if (s1.symbol == s2.symbol and oxi1 == oxi2 and\n spin2 == -spin1):\n break\n else:\n return False\n return True","def equals_exact(self, other, tolerance): # -> bool:\n ...","def _almost_equal(x, y):\n pass","def _eq(a, b):\n return (a - b) % 2 == 0","def same(self, other, epsilon_=None):\n if epsilon_ is None:\n return self-other < epsilon\n else:\n return self-other < epsilon_","def closeTo(pointOne, pointTwo):\r\n\tif abs(pointOne.lat-pointTwo.lat) < 0.0002:\r\n\t\tif abs(pointOne.lon-pointTwo.lon) < 0.0002:\r\n\t\t\treturn True\r\n\treturn False","def equal_points_2d(p1, p2, tol=None):\r\n if tol is None:\r\n tol = get_tol_2d()\r\n return geometry.gmEqualPointsXY(p1, p2, tol)","def assertTPsEqual(self, tp1, tp2):\n self.assertEqual(tp1, tp2, tp1.diff(tp2))\n self.assertTrue(fdrutilities.tpDiff2(tp1, tp2, 1, False))","def __lt__(self, other):\n return self.x ** 2 + self.y ** 2 < other.x ** 2 + other.y ** 2","def __eq__(self, second):\r\n\t\treturn self.x == other.x and self.y == other.y","def is_equal_approx(x, y, epsilon=1e-6):\r\n # Check absolute precision.\r\n if -epsilon <= x - y <= epsilon:\r\n return True\r\n\r\n # Is x or y too close to zero?\r\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\r\n return False\r\n\r\n # Check relative precision.\r\n return (-epsilon <= (x - y) / x <= epsilon\r\n or -epsilon <= (x - y) / y <= epsilon)","def __flt_eq_pos(self, other):\n if self.position is None:\n return True\n\n return (\n self.position == other.position\n and self.is_lean == other.is_lean\n )","def __eq__(self, other):\n return sorted(self.points) == sorted(other.points)","def __eq__(self, other):\n return np.allclose(self.P, other.P)","def close(a,b):\n return abs(a-b) < epsilon","def __le__(self, other):\n return self.x ** 2 + self.y ** 2 <= other.x ** 2 + other.y ** 2","def torch_the_same(X, Y, eps=1e-8):\n return (X - Y).abs().min() < eps","def are_symmetrically_related(self, point_a, point_b, tol=0.001):\n if np.allclose(self.operate(point_a), point_b, atol=tol):\n return True\n if np.allclose(self.operate(point_b), point_a, atol=tol):\n return True\n return False","def __eq__(self, other):\n return self <= other and self >= other","def compare(self, t2) -> bool:\n return True if self.get_edge(t2) >= 0 else False","def __eq__(self, other):\n x_eq = self.x == other.x\n y_eq = self.y == other.y\n return x_eq and y_eq","def __eq__(self, other):\n x_eq = self.x == other.x\n y_eq = self.y == other.y\n return x_eq and y_eq","def fuzzy_equals(a, b):\n epsilon = 10**(-6) \n return (abs(a - b) < epsilon)","def comparison_test():\n for pose in SE2.interesting_points():\n se2 = se2_from_SE2(pose)\n SE2a = SE2_from_se2_slow(se2)\n SE2b = SE2_from_se2(se2)\n # printm('pose', pose, 'se2', se2)\n # printm('SE2a', SE2a, 'SE2b', SE2b)\n SE2.assert_close(SE2a, pose)\n # print('SE2a = pose Their distance is %f' % d)\n SE2.assert_close(SE2b, pose)\n # print('SE2b = pose Their distance is %f' % d)\n assert_allclose(SE2a, SE2b, atol=1e-8, err_msg=\"SE2a != SE2b\")\n assert_allclose(SE2a, pose, atol=1e-8, err_msg=\"SE2a != pose\")\n assert_allclose(SE2b, pose, atol=1e-8, err_msg=\"SE2b != pose\")","def _is_same_position(pos1, pos2, position_tolerance):\n return np.isclose(_pos_distance(pos1, pos2), 0, atol=position_tolerance)","def is_tautology_equality(t):\n return type(t) is Eq and t.t1 == t.t2","def has_converged(x, y, epsilon=EPSILON):\n for a, b in itertools.izip(x, y):\n if abs(a - b) > epsilon:\n return False\n return True","def has_converged(x, y, epsilon=EPSILON):\n for a, b in itertools.izip(x, y):\n if abs(a - b) > epsilon:\n return False\n return True","def is_equal(self, a, b):\n return a.X[0] == b.X[0]","def sameLocation(self, other):\n if not isinstance(other,Point):\n return False\n return self.longitude == other.getLongitude() and self.latitude == other.getLatitude()","def __eq__(self, other):\n from numpy.linalg import norm\n from numpy import array\n\n # Upcast to an Atom\n othercomp = Atom(other)\n\n # Compare Symbols\n sym1 = self.sym\n sym2 = othercomp.sym\n if sym1 != sym2:\n return False\n\n # Compare position\n pos1 = array(self.get_position())\n pos2 = array(othercomp.get_position())\n\n return norm(pos1 - pos2) < 1e-3","def IsApproximatelyEqual(x, y, epsilon = 1e-6):\n # Check absolute precision.\n if -epsilon <= x - y <= epsilon:\n return True\n\n # Is x or y too close to zero?\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\n return False\n\n # Check relative precision.\n return (-epsilon <= (x - y) / x <= epsilon or -epsilon <= (x - y) / y <= epsilon)","def almost_equal(first, second, places=None, delta=0.1):\n if first == second:\n # shortcut\n return True\n if delta is not None and places is not None:\n raise TypeError(\"specify delta or places not both\")\n if delta is not None:\n if abs(first - second) <= delta:\n return True\n else:\n if places is None:\n places = 2\n\n if round(abs(second-first), places) == 0:\n return True\n return False","def series_are_equivalent(series_1: Series, series_2: Series) -> bool:\n d1 = series_1.copy().reset_index()\n cols_1 = sorted([c for c in d1.columns if c != 'p'])\n cols_p = cols_1 + ['p']\n s1 = d1[cols_p].set_index(cols_1)['p']\n d2 = series_2.copy().reset_index()\n cols_2 = sorted([c for c in d2.columns if c != 'p'])\n if cols_1 != cols_2:\n return False\n s2 = d2[cols_p].set_index(cols_2)['p']\n for k, v in s1.iteritems():\n if v == 0:\n continue\n if k not in s2.keys() or abs(s2[k] - v) > 1e-10:\n return False\n return True","def IsApproximatelyEqual(x, y, epsilon):\n # Check absolute precision.\n if -epsilon <= x - y <= epsilon:\n return True\n\n # Is x or y too close to zero?0.\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\n return False\n\n # Check relative precision.\n return (-epsilon <= (x - y) / x <= epsilon\n or -epsilon <= (x - y) / y <= epsilon)","def equals(a, b, tol=1e-10):\n return np.abs(a-b) <= tol","def vector_equal(v1,v2):\n if (v2.x - 0.001 <= v1.x <= v2.x + 0.001) and \\\n (v2.y - 0.001 <= v1.y <= v2.y + 0.001) and \\\n (v2.z - 0.001 <= v1.z <= v2.z + 0.001):\n return True","def approx_eq(x, y, tolerance=1e-15):\n return abs(x - y) < tolerance","def __eq__(self, other):\n if self.rows != other.rows or self.cols != other.cols:\n return False\n for i in range(self.rows):\n for j in range(self.cols):\n # Need isclose (Python >= 3.5) for float precision\n if not math.isclose(self[i, j], other[i, j]):\n return False\n return True","def approx_eq(x, y, tolerance = 0.000001):\n\treturn abs(x - y) < tolerance","def __eq__(self, other):\n return self.x == other.x and self.y == other.y","def __eq__(self, other):\n return self.x == other.x and self.y == other.y","def __eq__(self, rhs):\n return self.x == rhs.x and self.y == rhs.y","def __eq__(self,other):\n return (self - other == 0.)","def compare_answer(self, ans1, ans2):\r\n return compare_with_tolerance(\r\n evaluator({}, {}, ans1),\r\n evaluator({}, {}, ans2),\r\n self.tolerance\r\n )","def nearlyEqual(self, x, y):\n return self.absoluteerror(x).nearlyEqual(x, y)","def is_equal(self, other):\n return self.close(other) & (abs(self.width - other.width) < 100) & (abs(self.height - other.height) < 50)","def overlap(p1: Tuple, p2: Tuple) -> bool:\n if (p2[1] - p1[0]) * (p2[0] - p1[1]) <= 0:\n return True\n else:\n return False","def equal(self,other):\n if(self.x == other.x) and (self.y == other.y):\n return True\n else:\n return False","def isGE(self, a : float, b : float) -> bool:\n return (a >= b - self.tol * max(abs(a), abs(b), 1.0)) #and (a >= b - 0.1)","def fp_gt(x: float, y: float) -> bool:\n return not fp_eq(x, y) and x > y","def __gt__(self, other: Compound[Scalar]) -> bool:\n return (self._points_set > other._points_set\n if isinstance(other, Multipoint)\n else NotImplemented)","def test_LessThanorEqualto(self):\n self.assertTrue(Fraction(-7,10)<=Fraction(-7,10))","def equals(x, y):\n return x == y","def __ge__(self: _TT, other: _TT) -> bool:\n if type(self) != type(other):\n raise TypeError(\"Types do not match\")\n return self.value >= other.value","def position_equal(self, a, b):\n return None","def __eq__(self, other):\n return self.start == other.start and self.end == other.end","def test_equator_example(self):\n\n # Test data from http://www.movable-type.co.uk/scripts/latlong.html\n D = 11448.0959593 # True Distance [m]\n\n p1 = Point(latitude=-0.59, longitude=117.10)\n p2 = Point(latitude=-0.50, longitude=117.15)\n\n d = p1.distance_to(p2)\n msg = 'Dist to point failed %f. Expected %f' % (d, D)\n assert numpy.allclose(d, D, rtol=1.0e-3), msg","def __eq__(self, other):\n return self.key == other.key \\\n and self.get_inside() == other.get_inside() \\\n and self.get_outside() == other.get_outside()","def equalWithinTolerance(a, b, tol):\n return abs(a - b) <= tol"],"string":"[\n \"def _same(p1,p2,prec=0.0001):\\n #return num.all(num.equal(p1,p2))\\n t1 = num.fabs(p1[0]-p2[0]) < prec\\n t2 = num.fabs(p1[1]-p2[1]) < prec\\n if t1 and t2:\\n #print \\\"same\\\", p1,p2\\n return True\",\n \"def test_eq_2():\\n a = FixedPoint(1, 'Q2.8')\\n b = FixedPoint(1, 'Q2.8')\\n assert a == b\",\n \"def test_ge_2():\\n a = FixedPoint(1, 'Q2.8')\\n b = FixedPoint(1.1, 'Q2.8')\\n assert b > a\",\n \"def are_equal(self, sp1, sp2):\\n return True\",\n \"def _point_equal(a,b):\\n return np.array_equal(a._Point__loc, b._Point__loc)\",\n \"def almost_equals(self, other):\\n import math\\n ox, oy = other\\n dx = self[0] - ox\\n dy = self[1] - oy\\n return (dx*dx + dy*dy) < pygonal.EPSILON2\",\n \"def test_gt_2():\\n a = FixedPoint(1, 'Q2.8')\\n b = FixedPoint(1.1, 'Q2.8')\\n assert b > a\",\n \"def _point_almost_equal(a,b, rtol=RTOL, atol=ATOL):\\n return np.allclose(a._Point__loc, b._Point__loc,\\n rtol=rtol, atol=atol)\",\n \"def fp_eq(x: float, y: float) -> bool:\\n return fabs(x-y) < 10**-12\",\n \"def are_equal(self, sp1, sp2):\\n return sp1 == sp2\",\n \"def realEqual(x,y,eps=10e-10):\\n return abs(x-y) < eps\",\n \"def test_lt_2():\\n a = FixedPoint(1, 'Q2.8')\\n b = FixedPoint(1.1, 'Q2.8')\\n assert a < b\",\n \"def are_equal(self, sp1, sp2):\\n return\",\n \"def __eq__(self, other):\\n if isinstance(other, self.__class__):\\n return math.isclose(self.x, other.x, rel_tol=1e-12, abs_tol=1e-12) and\\\\\\n math.isclose(self.y, other.y, rel_tol=1e-12, abs_tol=1e-12)\\n else:\\n return False\",\n \"def __comparing_points(self, point1, point2) -> bool:\\n return (abs(point1.x - point2.x) <= self.dirt_pos_tolerance and abs(\\n point1.y - point2.y) <= self.dirt_pos_tolerance)\",\n \"def __eq__(self,v2):\\n\\t\\treturn -1e-13<(self-v2).norm()<1e-13\",\n \"def almost_equal(x, y):\\n return abs(x-y) < FP_PREC\",\n \"def approx_eq(a, b):\\n return abs(a-b) < approx_eq.eps\",\n \"def __eq__(self, other):\\n return abs(self - other) < 10e-10\",\n \"def test_le_2():\\n a = FixedPoint(1, 'Q2.8')\\n b = FixedPoint(1.1, 'Q2.8')\\n assert a < b\",\n \"def is_almost_equal(self, x ,y ,epsilon=1*10**(-8)):\\n \\treturn abs(x-y) <= epsilon\",\n \"def almost_eq(e1,e2) :\\n\\treturn round(e1-e2,4) == 0.0\",\n \"def eq(a, b):\\n return abs(a - b) < .05\",\n \"def __gt__(self, other):\\n return self.x ** 2 + self.y ** 2 > other.x ** 2 + other.y ** 2\",\n \"def __eq__(self, other):\\r\\n return abs(self.x - other.x) + abs(self.y - other.y) < Vertex.epsilon\",\n \"def __eq__(self, pt):\\n return self.x == pt.x and self.y == pt.y\",\n \"def almost_equal_values(x, y, precision):\\n return round(x - y, precision) == 0\",\n \"def nearly_equal(a, b, sig_fig=5):\\n return a == b or int(a*10**sig_fig) == int(b*10**sig_fig)\",\n \"def __eq__(self, other: 'LTL'):\\n if self.formula == other.formula:\\n return True\\n implied_a = self >= other\\n implied_b = self <= other\\n return implied_a and implied_b\",\n \"def __eq__(self, other):\\n return self.point == other.point\",\n \"def __eq__(self, secondPoint):\\n return self.xCoordinate == secondPoint.xCoordinate and self.yCoordinate == secondPoint.yCoordinate\",\n \"def eq(df1, df2, precision=0.5) -> bool:\\n return ((df1 - df2).abs() < precision).all()\",\n \"def almost_equals(self, other, decimal=...): # -> bool:\\n ...\",\n \"def __eq__(self, other):\\n return self.points == other.points\",\n \"def test_point_relations(p1, p2):\\n assert p1.left_of(p2) or p1.x >= p2.x\\n assert p1.is_right_of(p2) or p1.x <= p2.x\\n\\n assert p1.left_of(p2) == p2.is_right_of(p1) or p1.x == p2.x\\n assert not p1.left_of(p2) or not p1.is_right_of(p2)\\n assert not p2.left_of(p1) or not p2.is_right_of(p1)\",\n \"def __ge__(self, other):\\n return self.x ** 2 + self.y ** 2 >= other.x ** 2 + other.y ** 2\",\n \"def Q1_test():\\n A, p1, p2 = [0,0], [2,4], [6,5]\\n return (distance(A,p1) > 4.472135) and (distance(p1,p2) < 4.472136)\",\n \"def fequal(pos_act, pos_exp, eps=1e-5):\\n return abs(pos_act - pos_exp) < eps\",\n \"def checarPs(self,p1,p2):\\n return abs(p1-p2) < 0.00001\",\n \"def verticesEqual(self, v1, v2, eps=1e-8):\\n if abs(v1[0] - v2[0]) > eps:\\n return False\\n if abs(v1[1] - v2[1]) > eps:\\n return False\\n if abs(v1[2] - v2[2]) > eps:\\n return False\\n return True\",\n \"def are_equal(self, sp1, sp2):\\n for s1 in sp1.keys():\\n spin1 = getattr(s1, \\\"spin\\\", 0)\\n oxi1 = getattr(s1, \\\"oxi_state\\\", 0)\\n for s2 in sp2.keys():\\n spin2 = getattr(s2, \\\"spin\\\", 0)\\n oxi2 = getattr(s2, \\\"oxi_state\\\", 0)\\n if (s1.symbol == s2.symbol and oxi1 == oxi2 and\\n spin2 == -spin1):\\n break\\n else:\\n return False\\n return True\",\n \"def equals_exact(self, other, tolerance): # -> bool:\\n ...\",\n \"def _almost_equal(x, y):\\n pass\",\n \"def _eq(a, b):\\n return (a - b) % 2 == 0\",\n \"def same(self, other, epsilon_=None):\\n if epsilon_ is None:\\n return self-other < epsilon\\n else:\\n return self-other < epsilon_\",\n \"def closeTo(pointOne, pointTwo):\\r\\n\\tif abs(pointOne.lat-pointTwo.lat) < 0.0002:\\r\\n\\t\\tif abs(pointOne.lon-pointTwo.lon) < 0.0002:\\r\\n\\t\\t\\treturn True\\r\\n\\treturn False\",\n \"def equal_points_2d(p1, p2, tol=None):\\r\\n if tol is None:\\r\\n tol = get_tol_2d()\\r\\n return geometry.gmEqualPointsXY(p1, p2, tol)\",\n \"def assertTPsEqual(self, tp1, tp2):\\n self.assertEqual(tp1, tp2, tp1.diff(tp2))\\n self.assertTrue(fdrutilities.tpDiff2(tp1, tp2, 1, False))\",\n \"def __lt__(self, other):\\n return self.x ** 2 + self.y ** 2 < other.x ** 2 + other.y ** 2\",\n \"def __eq__(self, second):\\r\\n\\t\\treturn self.x == other.x and self.y == other.y\",\n \"def is_equal_approx(x, y, epsilon=1e-6):\\r\\n # Check absolute precision.\\r\\n if -epsilon <= x - y <= epsilon:\\r\\n return True\\r\\n\\r\\n # Is x or y too close to zero?\\r\\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\\r\\n return False\\r\\n\\r\\n # Check relative precision.\\r\\n return (-epsilon <= (x - y) / x <= epsilon\\r\\n or -epsilon <= (x - y) / y <= epsilon)\",\n \"def __flt_eq_pos(self, other):\\n if self.position is None:\\n return True\\n\\n return (\\n self.position == other.position\\n and self.is_lean == other.is_lean\\n )\",\n \"def __eq__(self, other):\\n return sorted(self.points) == sorted(other.points)\",\n \"def __eq__(self, other):\\n return np.allclose(self.P, other.P)\",\n \"def close(a,b):\\n return abs(a-b) < epsilon\",\n \"def __le__(self, other):\\n return self.x ** 2 + self.y ** 2 <= other.x ** 2 + other.y ** 2\",\n \"def torch_the_same(X, Y, eps=1e-8):\\n return (X - Y).abs().min() < eps\",\n \"def are_symmetrically_related(self, point_a, point_b, tol=0.001):\\n if np.allclose(self.operate(point_a), point_b, atol=tol):\\n return True\\n if np.allclose(self.operate(point_b), point_a, atol=tol):\\n return True\\n return False\",\n \"def __eq__(self, other):\\n return self <= other and self >= other\",\n \"def compare(self, t2) -> bool:\\n return True if self.get_edge(t2) >= 0 else False\",\n \"def __eq__(self, other):\\n x_eq = self.x == other.x\\n y_eq = self.y == other.y\\n return x_eq and y_eq\",\n \"def __eq__(self, other):\\n x_eq = self.x == other.x\\n y_eq = self.y == other.y\\n return x_eq and y_eq\",\n \"def fuzzy_equals(a, b):\\n epsilon = 10**(-6) \\n return (abs(a - b) < epsilon)\",\n \"def comparison_test():\\n for pose in SE2.interesting_points():\\n se2 = se2_from_SE2(pose)\\n SE2a = SE2_from_se2_slow(se2)\\n SE2b = SE2_from_se2(se2)\\n # printm('pose', pose, 'se2', se2)\\n # printm('SE2a', SE2a, 'SE2b', SE2b)\\n SE2.assert_close(SE2a, pose)\\n # print('SE2a = pose Their distance is %f' % d)\\n SE2.assert_close(SE2b, pose)\\n # print('SE2b = pose Their distance is %f' % d)\\n assert_allclose(SE2a, SE2b, atol=1e-8, err_msg=\\\"SE2a != SE2b\\\")\\n assert_allclose(SE2a, pose, atol=1e-8, err_msg=\\\"SE2a != pose\\\")\\n assert_allclose(SE2b, pose, atol=1e-8, err_msg=\\\"SE2b != pose\\\")\",\n \"def _is_same_position(pos1, pos2, position_tolerance):\\n return np.isclose(_pos_distance(pos1, pos2), 0, atol=position_tolerance)\",\n \"def is_tautology_equality(t):\\n return type(t) is Eq and t.t1 == t.t2\",\n \"def has_converged(x, y, epsilon=EPSILON):\\n for a, b in itertools.izip(x, y):\\n if abs(a - b) > epsilon:\\n return False\\n return True\",\n \"def has_converged(x, y, epsilon=EPSILON):\\n for a, b in itertools.izip(x, y):\\n if abs(a - b) > epsilon:\\n return False\\n return True\",\n \"def is_equal(self, a, b):\\n return a.X[0] == b.X[0]\",\n \"def sameLocation(self, other):\\n if not isinstance(other,Point):\\n return False\\n return self.longitude == other.getLongitude() and self.latitude == other.getLatitude()\",\n \"def __eq__(self, other):\\n from numpy.linalg import norm\\n from numpy import array\\n\\n # Upcast to an Atom\\n othercomp = Atom(other)\\n\\n # Compare Symbols\\n sym1 = self.sym\\n sym2 = othercomp.sym\\n if sym1 != sym2:\\n return False\\n\\n # Compare position\\n pos1 = array(self.get_position())\\n pos2 = array(othercomp.get_position())\\n\\n return norm(pos1 - pos2) < 1e-3\",\n \"def IsApproximatelyEqual(x, y, epsilon = 1e-6):\\n # Check absolute precision.\\n if -epsilon <= x - y <= epsilon:\\n return True\\n\\n # Is x or y too close to zero?\\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\\n return False\\n\\n # Check relative precision.\\n return (-epsilon <= (x - y) / x <= epsilon or -epsilon <= (x - y) / y <= epsilon)\",\n \"def almost_equal(first, second, places=None, delta=0.1):\\n if first == second:\\n # shortcut\\n return True\\n if delta is not None and places is not None:\\n raise TypeError(\\\"specify delta or places not both\\\")\\n if delta is not None:\\n if abs(first - second) <= delta:\\n return True\\n else:\\n if places is None:\\n places = 2\\n\\n if round(abs(second-first), places) == 0:\\n return True\\n return False\",\n \"def series_are_equivalent(series_1: Series, series_2: Series) -> bool:\\n d1 = series_1.copy().reset_index()\\n cols_1 = sorted([c for c in d1.columns if c != 'p'])\\n cols_p = cols_1 + ['p']\\n s1 = d1[cols_p].set_index(cols_1)['p']\\n d2 = series_2.copy().reset_index()\\n cols_2 = sorted([c for c in d2.columns if c != 'p'])\\n if cols_1 != cols_2:\\n return False\\n s2 = d2[cols_p].set_index(cols_2)['p']\\n for k, v in s1.iteritems():\\n if v == 0:\\n continue\\n if k not in s2.keys() or abs(s2[k] - v) > 1e-10:\\n return False\\n return True\",\n \"def IsApproximatelyEqual(x, y, epsilon):\\n # Check absolute precision.\\n if -epsilon <= x - y <= epsilon:\\n return True\\n\\n # Is x or y too close to zero?0.\\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\\n return False\\n\\n # Check relative precision.\\n return (-epsilon <= (x - y) / x <= epsilon\\n or -epsilon <= (x - y) / y <= epsilon)\",\n \"def equals(a, b, tol=1e-10):\\n return np.abs(a-b) <= tol\",\n \"def vector_equal(v1,v2):\\n if (v2.x - 0.001 <= v1.x <= v2.x + 0.001) and \\\\\\n (v2.y - 0.001 <= v1.y <= v2.y + 0.001) and \\\\\\n (v2.z - 0.001 <= v1.z <= v2.z + 0.001):\\n return True\",\n \"def approx_eq(x, y, tolerance=1e-15):\\n return abs(x - y) < tolerance\",\n \"def __eq__(self, other):\\n if self.rows != other.rows or self.cols != other.cols:\\n return False\\n for i in range(self.rows):\\n for j in range(self.cols):\\n # Need isclose (Python >= 3.5) for float precision\\n if not math.isclose(self[i, j], other[i, j]):\\n return False\\n return True\",\n \"def approx_eq(x, y, tolerance = 0.000001):\\n\\treturn abs(x - y) < tolerance\",\n \"def __eq__(self, other):\\n return self.x == other.x and self.y == other.y\",\n \"def __eq__(self, other):\\n return self.x == other.x and self.y == other.y\",\n \"def __eq__(self, rhs):\\n return self.x == rhs.x and self.y == rhs.y\",\n \"def __eq__(self,other):\\n return (self - other == 0.)\",\n \"def compare_answer(self, ans1, ans2):\\r\\n return compare_with_tolerance(\\r\\n evaluator({}, {}, ans1),\\r\\n evaluator({}, {}, ans2),\\r\\n self.tolerance\\r\\n )\",\n \"def nearlyEqual(self, x, y):\\n return self.absoluteerror(x).nearlyEqual(x, y)\",\n \"def is_equal(self, other):\\n return self.close(other) & (abs(self.width - other.width) < 100) & (abs(self.height - other.height) < 50)\",\n \"def overlap(p1: Tuple, p2: Tuple) -> bool:\\n if (p2[1] - p1[0]) * (p2[0] - p1[1]) <= 0:\\n return True\\n else:\\n return False\",\n \"def equal(self,other):\\n if(self.x == other.x) and (self.y == other.y):\\n return True\\n else:\\n return False\",\n \"def isGE(self, a : float, b : float) -> bool:\\n return (a >= b - self.tol * max(abs(a), abs(b), 1.0)) #and (a >= b - 0.1)\",\n \"def fp_gt(x: float, y: float) -> bool:\\n return not fp_eq(x, y) and x > y\",\n \"def __gt__(self, other: Compound[Scalar]) -> bool:\\n return (self._points_set > other._points_set\\n if isinstance(other, Multipoint)\\n else NotImplemented)\",\n \"def test_LessThanorEqualto(self):\\n self.assertTrue(Fraction(-7,10)<=Fraction(-7,10))\",\n \"def equals(x, y):\\n return x == y\",\n \"def __ge__(self: _TT, other: _TT) -> bool:\\n if type(self) != type(other):\\n raise TypeError(\\\"Types do not match\\\")\\n return self.value >= other.value\",\n \"def position_equal(self, a, b):\\n return None\",\n \"def __eq__(self, other):\\n return self.start == other.start and self.end == other.end\",\n \"def test_equator_example(self):\\n\\n # Test data from http://www.movable-type.co.uk/scripts/latlong.html\\n D = 11448.0959593 # True Distance [m]\\n\\n p1 = Point(latitude=-0.59, longitude=117.10)\\n p2 = Point(latitude=-0.50, longitude=117.15)\\n\\n d = p1.distance_to(p2)\\n msg = 'Dist to point failed %f. Expected %f' % (d, D)\\n assert numpy.allclose(d, D, rtol=1.0e-3), msg\",\n \"def __eq__(self, other):\\n return self.key == other.key \\\\\\n and self.get_inside() == other.get_inside() \\\\\\n and self.get_outside() == other.get_outside()\",\n \"def equalWithinTolerance(a, b, tol):\\n return abs(a - b) <= tol\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.78786254","0.73442125","0.73271257","0.73021305","0.72471225","0.72312576","0.7224132","0.72203106","0.7208399","0.7186101","0.7171681","0.71665627","0.71387106","0.71274626","0.71209747","0.7108511","0.7045949","0.7042352","0.7017369","0.7011124","0.69991857","0.6981131","0.69707","0.69612086","0.6958381","0.6929555","0.69084","0.6862804","0.68485683","0.6839242","0.68386513","0.68336403","0.6776948","0.6743811","0.6717396","0.671481","0.66813046","0.66622955","0.66502064","0.66342777","0.66295904","0.6626424","0.66208595","0.6619092","0.6617364","0.66081643","0.6606639","0.6595644","0.6570375","0.6556905","0.6553691","0.65463626","0.6535363","0.6532666","0.652915","0.65267575","0.6500392","0.6483319","0.64702797","0.64682096","0.64655054","0.64655054","0.646438","0.6462964","0.6458879","0.64587057","0.6447265","0.6447265","0.6444531","0.6443297","0.6441557","0.64396536","0.6430717","0.64219296","0.6421077","0.6415068","0.64139605","0.64120907","0.6411153","0.63922656","0.639163","0.63772005","0.6363162","0.63616526","0.635865","0.63561875","0.63560444","0.63546616","0.63526773","0.63274795","0.6315349","0.6314472","0.63132024","0.6304475","0.63000965","0.62935466","0.62830573","0.6281806","0.62793434","0.6266833"],"string":"[\n \"0.78786254\",\n \"0.73442125\",\n \"0.73271257\",\n \"0.73021305\",\n \"0.72471225\",\n \"0.72312576\",\n \"0.7224132\",\n \"0.72203106\",\n \"0.7208399\",\n \"0.7186101\",\n \"0.7171681\",\n \"0.71665627\",\n \"0.71387106\",\n \"0.71274626\",\n \"0.71209747\",\n \"0.7108511\",\n \"0.7045949\",\n \"0.7042352\",\n \"0.7017369\",\n \"0.7011124\",\n \"0.69991857\",\n \"0.6981131\",\n \"0.69707\",\n \"0.69612086\",\n \"0.6958381\",\n \"0.6929555\",\n \"0.69084\",\n \"0.6862804\",\n \"0.68485683\",\n \"0.6839242\",\n \"0.68386513\",\n \"0.68336403\",\n \"0.6776948\",\n \"0.6743811\",\n \"0.6717396\",\n \"0.671481\",\n \"0.66813046\",\n \"0.66622955\",\n \"0.66502064\",\n \"0.66342777\",\n \"0.66295904\",\n \"0.6626424\",\n \"0.66208595\",\n \"0.6619092\",\n \"0.6617364\",\n \"0.66081643\",\n \"0.6606639\",\n \"0.6595644\",\n \"0.6570375\",\n \"0.6556905\",\n \"0.6553691\",\n \"0.65463626\",\n \"0.6535363\",\n \"0.6532666\",\n \"0.652915\",\n \"0.65267575\",\n \"0.6500392\",\n \"0.6483319\",\n \"0.64702797\",\n \"0.64682096\",\n \"0.64655054\",\n \"0.64655054\",\n \"0.646438\",\n \"0.6462964\",\n \"0.6458879\",\n \"0.64587057\",\n \"0.6447265\",\n \"0.6447265\",\n \"0.6444531\",\n \"0.6443297\",\n \"0.6441557\",\n \"0.64396536\",\n \"0.6430717\",\n \"0.64219296\",\n \"0.6421077\",\n \"0.6415068\",\n \"0.64139605\",\n \"0.64120907\",\n \"0.6411153\",\n \"0.63922656\",\n \"0.639163\",\n \"0.63772005\",\n \"0.6363162\",\n \"0.63616526\",\n \"0.635865\",\n \"0.63561875\",\n \"0.63560444\",\n \"0.63546616\",\n \"0.63526773\",\n \"0.63274795\",\n \"0.6315349\",\n \"0.6314472\",\n \"0.63132024\",\n \"0.6304475\",\n \"0.63000965\",\n \"0.62935466\",\n \"0.62830573\",\n \"0.6281806\",\n \"0.62793434\",\n \"0.6266833\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6642547"},"document_rank":{"kind":"string","value":"39"}}},{"rowIdx":3992,"cells":{"query":{"kind":"string","value":"The expression pt1 == pt2 returns False when pt1 is not close to pt2"},"document":{"kind":"string","value":"def test_not_equal(self):\n x = Point(\n lat=24.4,\n lng=23.1,\n author=self.u\n )\n self.assertFalse(self.a == x)\n self.assertTrue(self.a != x)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _same(p1,p2,prec=0.0001):\n #return num.all(num.equal(p1,p2))\n t1 = num.fabs(p1[0]-p2[0]) < prec\n t2 = num.fabs(p1[1]-p2[1]) < prec\n if t1 and t2:\n #print \"same\", p1,p2\n return True","def almost_equals(self, other):\n import math\n ox, oy = other\n dx = self[0] - ox\n dy = self[1] - oy\n return (dx*dx + dy*dy) < pygonal.EPSILON2","def _point_almost_equal(a,b, rtol=RTOL, atol=ATOL):\n return np.allclose(a._Point__loc, b._Point__loc,\n rtol=rtol, atol=atol)","def test_eq_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoint(1, 'Q2.8')\n assert a == b","def test_ge_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoint(1.1, 'Q2.8')\n assert b > a","def are_equal(self, sp1, sp2):\n return True","def realEqual(x,y,eps=10e-10):\n return abs(x-y) < eps","def _point_equal(a,b):\n return np.array_equal(a._Point__loc, b._Point__loc)","def __eq__(self, other):\n return abs(self - other) < 10e-10","def is_almost_equal(self, x ,y ,epsilon=1*10**(-8)):\n \treturn abs(x-y) <= epsilon","def __comparing_points(self, point1, point2) -> bool:\n return (abs(point1.x - point2.x) <= self.dirt_pos_tolerance and abs(\n point1.y - point2.y) <= self.dirt_pos_tolerance)","def __eq__(self, other):\n if isinstance(other, self.__class__):\n return math.isclose(self.x, other.x, rel_tol=1e-12, abs_tol=1e-12) and\\\n math.isclose(self.y, other.y, rel_tol=1e-12, abs_tol=1e-12)\n else:\n return False","def fp_eq(x: float, y: float) -> bool:\n return fabs(x-y) < 10**-12","def test_lt_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoint(1.1, 'Q2.8')\n assert a < b","def almost_equal(x, y):\n return abs(x-y) < FP_PREC","def test_gt_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoint(1.1, 'Q2.8')\n assert b > a","def almost_eq(e1,e2) :\n\treturn round(e1-e2,4) == 0.0","def __eq__(self,v2):\n\t\treturn -1e-13<(self-v2).norm()<1e-13","def are_equal(self, sp1, sp2):\n return","def almost_equal_values(x, y, precision):\n return round(x - y, precision) == 0","def __eq__(self, other):\r\n return abs(self.x - other.x) + abs(self.y - other.y) < Vertex.epsilon","def are_equal(self, sp1, sp2):\n return sp1 == sp2","def __gt__(self, other):\n return self.x ** 2 + self.y ** 2 > other.x ** 2 + other.y ** 2","def test_le_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoint(1.1, 'Q2.8')\n assert a < b","def approx_eq(a, b):\n return abs(a-b) < approx_eq.eps","def __eq__(self, pt):\n return self.x == pt.x and self.y == pt.y","def nearly_equal(a, b, sig_fig=5):\n return a == b or int(a*10**sig_fig) == int(b*10**sig_fig)","def almost_equals(self, other, decimal=...): # -> bool:\n ...","def eq(a, b):\n return abs(a - b) < .05","def __eq__(self, secondPoint):\n return self.xCoordinate == secondPoint.xCoordinate and self.yCoordinate == secondPoint.yCoordinate","def __eq__(self, other):\n return self.point == other.point","def test_almost_equal(self):\n x = Point(\n lat=23.4,\n lng=23.1,\n author=self.u\n )\n self.assertTrue(self.a == x)\n self.assertFalse(self.a != x)","def _almost_equal(x, y):\n pass","def __eq__(self, other: 'LTL'):\n if self.formula == other.formula:\n return True\n implied_a = self >= other\n implied_b = self <= other\n return implied_a and implied_b","def test_point_relations(p1, p2):\n assert p1.left_of(p2) or p1.x >= p2.x\n assert p1.is_right_of(p2) or p1.x <= p2.x\n\n assert p1.left_of(p2) == p2.is_right_of(p1) or p1.x == p2.x\n assert not p1.left_of(p2) or not p1.is_right_of(p2)\n assert not p2.left_of(p1) or not p2.is_right_of(p1)","def __ge__(self, other):\n return self.x ** 2 + self.y ** 2 >= other.x ** 2 + other.y ** 2","def __lt__(self, other):\n return self.x ** 2 + self.y ** 2 < other.x ** 2 + other.y ** 2","def __eq__(self, other):\n return self.points == other.points","def Q1_test():\n A, p1, p2 = [0,0], [2,4], [6,5]\n return (distance(A,p1) > 4.472135) and (distance(p1,p2) < 4.472136)","def checarPs(self,p1,p2):\n return abs(p1-p2) < 0.00001","def eq(df1, df2, precision=0.5) -> bool:\n return ((df1 - df2).abs() < precision).all()","def verticesEqual(self, v1, v2, eps=1e-8):\n if abs(v1[0] - v2[0]) > eps:\n return False\n if abs(v1[1] - v2[1]) > eps:\n return False\n if abs(v1[2] - v2[2]) > eps:\n return False\n return True","def equals_exact(self, other, tolerance): # -> bool:\n ...","def are_equal(self, sp1, sp2):\n for s1 in sp1.keys():\n spin1 = getattr(s1, \"spin\", 0)\n oxi1 = getattr(s1, \"oxi_state\", 0)\n for s2 in sp2.keys():\n spin2 = getattr(s2, \"spin\", 0)\n oxi2 = getattr(s2, \"oxi_state\", 0)\n if (s1.symbol == s2.symbol and oxi1 == oxi2 and\n spin2 == -spin1):\n break\n else:\n return False\n return True","def _eq(a, b):\n return (a - b) % 2 == 0","def __le__(self, other):\n return self.x ** 2 + self.y ** 2 <= other.x ** 2 + other.y ** 2","def is_equal_approx(x, y, epsilon=1e-6):\r\n # Check absolute precision.\r\n if -epsilon <= x - y <= epsilon:\r\n return True\r\n\r\n # Is x or y too close to zero?\r\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\r\n return False\r\n\r\n # Check relative precision.\r\n return (-epsilon <= (x - y) / x <= epsilon\r\n or -epsilon <= (x - y) / y <= epsilon)","def close(a,b):\n return abs(a-b) < epsilon","def __ne__(self, other):\n return self.point != other.point","def same(self, other, epsilon_=None):\n if epsilon_ is None:\n return self-other < epsilon\n else:\n return self-other < epsilon_","def assertTPsEqual(self, tp1, tp2):\n self.assertEqual(tp1, tp2, tp1.diff(tp2))\n self.assertTrue(fdrutilities.tpDiff2(tp1, tp2, 1, False))","def __eq__(self, other):\n return np.allclose(self.P, other.P)","def __eq__(self, second):\r\n\t\treturn self.x == other.x and self.y == other.y","def is_tautology_equality(t):\n return type(t) is Eq and t.t1 == t.t2","def __eq__(self, other):\n return sorted(self.points) == sorted(other.points)","def fequal(pos_act, pos_exp, eps=1e-5):\n return abs(pos_act - pos_exp) < eps","def are_symmetrically_related(self, point_a, point_b, tol=0.001):\n if np.allclose(self.operate(point_a), point_b, atol=tol):\n return True\n if np.allclose(self.operate(point_b), point_a, atol=tol):\n return True\n return False","def __eq__(self, other):\n return self <= other and self >= other","def compare(self, t2) -> bool:\n return True if self.get_edge(t2) >= 0 else False","def __flt_eq_pos(self, other):\n if self.position is None:\n return True\n\n return (\n self.position == other.position\n and self.is_lean == other.is_lean\n )","def __eq__(self, other):\n if self.rows != other.rows or self.cols != other.cols:\n return False\n for i in range(self.rows):\n for j in range(self.cols):\n # Need isclose (Python >= 3.5) for float precision\n if not math.isclose(self[i, j], other[i, j]):\n return False\n return True","def has_converged(x, y, epsilon=EPSILON):\n for a, b in itertools.izip(x, y):\n if abs(a - b) > epsilon:\n return False\n return True","def has_converged(x, y, epsilon=EPSILON):\n for a, b in itertools.izip(x, y):\n if abs(a - b) > epsilon:\n return False\n return True","def __eq__(self, other):\n from numpy.linalg import norm\n from numpy import array\n\n # Upcast to an Atom\n othercomp = Atom(other)\n\n # Compare Symbols\n sym1 = self.sym\n sym2 = othercomp.sym\n if sym1 != sym2:\n return False\n\n # Compare position\n pos1 = array(self.get_position())\n pos2 = array(othercomp.get_position())\n\n return norm(pos1 - pos2) < 1e-3","def validate_points(a, b):\r\n\tdiff_y = b[0] - a[0]\r\n\tdiff_x = b[1] - a[1]\r\n\r\n\treturn (diff_y == 0 and diff_x != 0) or (diff_x == 0 and diff_y != 0) or abs(diff_x) == abs(diff_y)","def __eq__(self, other):\n x_eq = self.x == other.x\n y_eq = self.y == other.y\n return x_eq and y_eq","def __eq__(self, other):\n x_eq = self.x == other.x\n y_eq = self.y == other.y\n return x_eq and y_eq","def equal_points_2d(p1, p2, tol=None):\r\n if tol is None:\r\n tol = get_tol_2d()\r\n return geometry.gmEqualPointsXY(p1, p2, tol)","def nearlyEqual(self, x, y):\n return abs(x-y) < self.absoluteerrorrange","def closeTo(pointOne, pointTwo):\r\n\tif abs(pointOne.lat-pointTwo.lat) < 0.0002:\r\n\t\tif abs(pointOne.lon-pointTwo.lon) < 0.0002:\r\n\t\t\treturn True\r\n\treturn False","def IsApproximatelyEqual(x, y, epsilon = 1e-6):\n # Check absolute precision.\n if -epsilon <= x - y <= epsilon:\n return True\n\n # Is x or y too close to zero?\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\n return False\n\n # Check relative precision.\n return (-epsilon <= (x - y) / x <= epsilon or -epsilon <= (x - y) / y <= epsilon)","def __le__(self, other: Compound[Scalar]) -> bool:\n return (self._points_set <= other._points_set\n if isinstance(other, Multipoint)\n else NotImplemented)","def __eq__(self, other):\n return self.x == other.x and self.y == other.y","def __eq__(self,other):\n return (self - other == 0.)","def torch_the_same(X, Y, eps=1e-8):\n return (X - Y).abs().min() < eps","def comparison_test():\n for pose in SE2.interesting_points():\n se2 = se2_from_SE2(pose)\n SE2a = SE2_from_se2_slow(se2)\n SE2b = SE2_from_se2(se2)\n # printm('pose', pose, 'se2', se2)\n # printm('SE2a', SE2a, 'SE2b', SE2b)\n SE2.assert_close(SE2a, pose)\n # print('SE2a = pose Their distance is %f' % d)\n SE2.assert_close(SE2b, pose)\n # print('SE2b = pose Their distance is %f' % d)\n assert_allclose(SE2a, SE2b, atol=1e-8, err_msg=\"SE2a != SE2b\")\n assert_allclose(SE2a, pose, atol=1e-8, err_msg=\"SE2a != pose\")\n assert_allclose(SE2b, pose, atol=1e-8, err_msg=\"SE2b != pose\")","def is_equal(self, a, b):\n return a.X[0] == b.X[0]","def __gt__(self, other: Compound[Scalar]) -> bool:\n return (self._points_set > other._points_set\n if isinstance(other, Multipoint)\n else NotImplemented)","def is_equal(self, other):\n return self.close(other) & (abs(self.width - other.width) < 100) & (abs(self.height - other.height) < 50)","def series_are_equivalent(series_1: Series, series_2: Series) -> bool:\n d1 = series_1.copy().reset_index()\n cols_1 = sorted([c for c in d1.columns if c != 'p'])\n cols_p = cols_1 + ['p']\n s1 = d1[cols_p].set_index(cols_1)['p']\n d2 = series_2.copy().reset_index()\n cols_2 = sorted([c for c in d2.columns if c != 'p'])\n if cols_1 != cols_2:\n return False\n s2 = d2[cols_p].set_index(cols_2)['p']\n for k, v in s1.iteritems():\n if v == 0:\n continue\n if k not in s2.keys() or abs(s2[k] - v) > 1e-10:\n return False\n return True","def __eq__(self, other):\n return self.x == other.x and self.y == other.y","def IsApproximatelyEqual(x, y, epsilon):\n # Check absolute precision.\n if -epsilon <= x - y <= epsilon:\n return True\n\n # Is x or y too close to zero?0.\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\n return False\n\n # Check relative precision.\n return (-epsilon <= (x - y) / x <= epsilon\n or -epsilon <= (x - y) / y <= epsilon)","def __eq__(self, other):\n return self.start == other.start and self.end == other.end","def test_LessThanorEqualto(self):\n self.assertTrue(Fraction(-7,10)<=Fraction(-7,10))","def sameLocation(self, other):\n if not isinstance(other,Point):\n return False\n return self.longitude == other.getLongitude() and self.latitude == other.getLatitude()","def overlap(p1: Tuple, p2: Tuple) -> bool:\n if (p2[1] - p1[0]) * (p2[0] - p1[1]) <= 0:\n return True\n else:\n return False","def approx_eq(x, y, tolerance=1e-15):\n return abs(x - y) < tolerance","def position_equal(self, a, b):\n return None","def nearlyEqual(self, x, y):\n return self.absoluteerror(x).nearlyEqual(x, y)","def almost_equal(first, second, places=None, delta=0.1):\n if first == second:\n # shortcut\n return True\n if delta is not None and places is not None:\n raise TypeError(\"specify delta or places not both\")\n if delta is not None:\n if abs(first - second) <= delta:\n return True\n else:\n if places is None:\n places = 2\n\n if round(abs(second-first), places) == 0:\n return True\n return False","def fuzzy_equals(a, b):\n epsilon = 10**(-6) \n return (abs(a - b) < epsilon)","def _is_same_position(pos1, pos2, position_tolerance):\n return np.isclose(_pos_distance(pos1, pos2), 0, atol=position_tolerance)","def approx_eq(x, y, tolerance = 0.000001):\n\treturn abs(x - y) < tolerance","def __ge__(self, other: Compound[Scalar]) -> bool:\n return (self._points_set >= other._points_set\n if isinstance(other, Multipoint)\n else NotImplemented)","def __eq__(self, rhs):\n return self.x == rhs.x and self.y == rhs.y","def isGE(self, a : float, b : float) -> bool:\n return (a >= b - self.tol * max(abs(a), abs(b), 1.0)) #and (a >= b - 0.1)","def equals(a, b, tol=1e-10):\n return np.abs(a-b) <= tol","def __eq__(self, other):\n return self.key == other.key \\\n and self.get_inside() == other.get_inside() \\\n and self.get_outside() == other.get_outside()","def __eq__(self, other):\n return (self.start == other.start and self.end == other.end)","def equal(self,other):\n if(self.x == other.x) and (self.y == other.y):\n return True\n else:\n return False","def __ge__(self: _TT, other: _TT) -> bool:\n if type(self) != type(other):\n raise TypeError(\"Types do not match\")\n return self.value >= other.value"],"string":"[\n \"def _same(p1,p2,prec=0.0001):\\n #return num.all(num.equal(p1,p2))\\n t1 = num.fabs(p1[0]-p2[0]) < prec\\n t2 = num.fabs(p1[1]-p2[1]) < prec\\n if t1 and t2:\\n #print \\\"same\\\", p1,p2\\n return True\",\n \"def almost_equals(self, other):\\n import math\\n ox, oy = other\\n dx = self[0] - ox\\n dy = self[1] - oy\\n return (dx*dx + dy*dy) < pygonal.EPSILON2\",\n \"def _point_almost_equal(a,b, rtol=RTOL, atol=ATOL):\\n return np.allclose(a._Point__loc, b._Point__loc,\\n rtol=rtol, atol=atol)\",\n \"def test_eq_2():\\n a = FixedPoint(1, 'Q2.8')\\n b = FixedPoint(1, 'Q2.8')\\n assert a == b\",\n \"def test_ge_2():\\n a = FixedPoint(1, 'Q2.8')\\n b = FixedPoint(1.1, 'Q2.8')\\n assert b > a\",\n \"def are_equal(self, sp1, sp2):\\n return True\",\n \"def realEqual(x,y,eps=10e-10):\\n return abs(x-y) < eps\",\n \"def _point_equal(a,b):\\n return np.array_equal(a._Point__loc, b._Point__loc)\",\n \"def __eq__(self, other):\\n return abs(self - other) < 10e-10\",\n \"def is_almost_equal(self, x ,y ,epsilon=1*10**(-8)):\\n \\treturn abs(x-y) <= epsilon\",\n \"def __comparing_points(self, point1, point2) -> bool:\\n return (abs(point1.x - point2.x) <= self.dirt_pos_tolerance and abs(\\n point1.y - point2.y) <= self.dirt_pos_tolerance)\",\n \"def __eq__(self, other):\\n if isinstance(other, self.__class__):\\n return math.isclose(self.x, other.x, rel_tol=1e-12, abs_tol=1e-12) and\\\\\\n math.isclose(self.y, other.y, rel_tol=1e-12, abs_tol=1e-12)\\n else:\\n return False\",\n \"def fp_eq(x: float, y: float) -> bool:\\n return fabs(x-y) < 10**-12\",\n \"def test_lt_2():\\n a = FixedPoint(1, 'Q2.8')\\n b = FixedPoint(1.1, 'Q2.8')\\n assert a < b\",\n \"def almost_equal(x, y):\\n return abs(x-y) < FP_PREC\",\n \"def test_gt_2():\\n a = FixedPoint(1, 'Q2.8')\\n b = FixedPoint(1.1, 'Q2.8')\\n assert b > a\",\n \"def almost_eq(e1,e2) :\\n\\treturn round(e1-e2,4) == 0.0\",\n \"def __eq__(self,v2):\\n\\t\\treturn -1e-13<(self-v2).norm()<1e-13\",\n \"def are_equal(self, sp1, sp2):\\n return\",\n \"def almost_equal_values(x, y, precision):\\n return round(x - y, precision) == 0\",\n \"def __eq__(self, other):\\r\\n return abs(self.x - other.x) + abs(self.y - other.y) < Vertex.epsilon\",\n \"def are_equal(self, sp1, sp2):\\n return sp1 == sp2\",\n \"def __gt__(self, other):\\n return self.x ** 2 + self.y ** 2 > other.x ** 2 + other.y ** 2\",\n \"def test_le_2():\\n a = FixedPoint(1, 'Q2.8')\\n b = FixedPoint(1.1, 'Q2.8')\\n assert a < b\",\n \"def approx_eq(a, b):\\n return abs(a-b) < approx_eq.eps\",\n \"def __eq__(self, pt):\\n return self.x == pt.x and self.y == pt.y\",\n \"def nearly_equal(a, b, sig_fig=5):\\n return a == b or int(a*10**sig_fig) == int(b*10**sig_fig)\",\n \"def almost_equals(self, other, decimal=...): # -> bool:\\n ...\",\n \"def eq(a, b):\\n return abs(a - b) < .05\",\n \"def __eq__(self, secondPoint):\\n return self.xCoordinate == secondPoint.xCoordinate and self.yCoordinate == secondPoint.yCoordinate\",\n \"def __eq__(self, other):\\n return self.point == other.point\",\n \"def test_almost_equal(self):\\n x = Point(\\n lat=23.4,\\n lng=23.1,\\n author=self.u\\n )\\n self.assertTrue(self.a == x)\\n self.assertFalse(self.a != x)\",\n \"def _almost_equal(x, y):\\n pass\",\n \"def __eq__(self, other: 'LTL'):\\n if self.formula == other.formula:\\n return True\\n implied_a = self >= other\\n implied_b = self <= other\\n return implied_a and implied_b\",\n \"def test_point_relations(p1, p2):\\n assert p1.left_of(p2) or p1.x >= p2.x\\n assert p1.is_right_of(p2) or p1.x <= p2.x\\n\\n assert p1.left_of(p2) == p2.is_right_of(p1) or p1.x == p2.x\\n assert not p1.left_of(p2) or not p1.is_right_of(p2)\\n assert not p2.left_of(p1) or not p2.is_right_of(p1)\",\n \"def __ge__(self, other):\\n return self.x ** 2 + self.y ** 2 >= other.x ** 2 + other.y ** 2\",\n \"def __lt__(self, other):\\n return self.x ** 2 + self.y ** 2 < other.x ** 2 + other.y ** 2\",\n \"def __eq__(self, other):\\n return self.points == other.points\",\n \"def Q1_test():\\n A, p1, p2 = [0,0], [2,4], [6,5]\\n return (distance(A,p1) > 4.472135) and (distance(p1,p2) < 4.472136)\",\n \"def checarPs(self,p1,p2):\\n return abs(p1-p2) < 0.00001\",\n \"def eq(df1, df2, precision=0.5) -> bool:\\n return ((df1 - df2).abs() < precision).all()\",\n \"def verticesEqual(self, v1, v2, eps=1e-8):\\n if abs(v1[0] - v2[0]) > eps:\\n return False\\n if abs(v1[1] - v2[1]) > eps:\\n return False\\n if abs(v1[2] - v2[2]) > eps:\\n return False\\n return True\",\n \"def equals_exact(self, other, tolerance): # -> bool:\\n ...\",\n \"def are_equal(self, sp1, sp2):\\n for s1 in sp1.keys():\\n spin1 = getattr(s1, \\\"spin\\\", 0)\\n oxi1 = getattr(s1, \\\"oxi_state\\\", 0)\\n for s2 in sp2.keys():\\n spin2 = getattr(s2, \\\"spin\\\", 0)\\n oxi2 = getattr(s2, \\\"oxi_state\\\", 0)\\n if (s1.symbol == s2.symbol and oxi1 == oxi2 and\\n spin2 == -spin1):\\n break\\n else:\\n return False\\n return True\",\n \"def _eq(a, b):\\n return (a - b) % 2 == 0\",\n \"def __le__(self, other):\\n return self.x ** 2 + self.y ** 2 <= other.x ** 2 + other.y ** 2\",\n \"def is_equal_approx(x, y, epsilon=1e-6):\\r\\n # Check absolute precision.\\r\\n if -epsilon <= x - y <= epsilon:\\r\\n return True\\r\\n\\r\\n # Is x or y too close to zero?\\r\\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\\r\\n return False\\r\\n\\r\\n # Check relative precision.\\r\\n return (-epsilon <= (x - y) / x <= epsilon\\r\\n or -epsilon <= (x - y) / y <= epsilon)\",\n \"def close(a,b):\\n return abs(a-b) < epsilon\",\n \"def __ne__(self, other):\\n return self.point != other.point\",\n \"def same(self, other, epsilon_=None):\\n if epsilon_ is None:\\n return self-other < epsilon\\n else:\\n return self-other < epsilon_\",\n \"def assertTPsEqual(self, tp1, tp2):\\n self.assertEqual(tp1, tp2, tp1.diff(tp2))\\n self.assertTrue(fdrutilities.tpDiff2(tp1, tp2, 1, False))\",\n \"def __eq__(self, other):\\n return np.allclose(self.P, other.P)\",\n \"def __eq__(self, second):\\r\\n\\t\\treturn self.x == other.x and self.y == other.y\",\n \"def is_tautology_equality(t):\\n return type(t) is Eq and t.t1 == t.t2\",\n \"def __eq__(self, other):\\n return sorted(self.points) == sorted(other.points)\",\n \"def fequal(pos_act, pos_exp, eps=1e-5):\\n return abs(pos_act - pos_exp) < eps\",\n \"def are_symmetrically_related(self, point_a, point_b, tol=0.001):\\n if np.allclose(self.operate(point_a), point_b, atol=tol):\\n return True\\n if np.allclose(self.operate(point_b), point_a, atol=tol):\\n return True\\n return False\",\n \"def __eq__(self, other):\\n return self <= other and self >= other\",\n \"def compare(self, t2) -> bool:\\n return True if self.get_edge(t2) >= 0 else False\",\n \"def __flt_eq_pos(self, other):\\n if self.position is None:\\n return True\\n\\n return (\\n self.position == other.position\\n and self.is_lean == other.is_lean\\n )\",\n \"def __eq__(self, other):\\n if self.rows != other.rows or self.cols != other.cols:\\n return False\\n for i in range(self.rows):\\n for j in range(self.cols):\\n # Need isclose (Python >= 3.5) for float precision\\n if not math.isclose(self[i, j], other[i, j]):\\n return False\\n return True\",\n \"def has_converged(x, y, epsilon=EPSILON):\\n for a, b in itertools.izip(x, y):\\n if abs(a - b) > epsilon:\\n return False\\n return True\",\n \"def has_converged(x, y, epsilon=EPSILON):\\n for a, b in itertools.izip(x, y):\\n if abs(a - b) > epsilon:\\n return False\\n return True\",\n \"def __eq__(self, other):\\n from numpy.linalg import norm\\n from numpy import array\\n\\n # Upcast to an Atom\\n othercomp = Atom(other)\\n\\n # Compare Symbols\\n sym1 = self.sym\\n sym2 = othercomp.sym\\n if sym1 != sym2:\\n return False\\n\\n # Compare position\\n pos1 = array(self.get_position())\\n pos2 = array(othercomp.get_position())\\n\\n return norm(pos1 - pos2) < 1e-3\",\n \"def validate_points(a, b):\\r\\n\\tdiff_y = b[0] - a[0]\\r\\n\\tdiff_x = b[1] - a[1]\\r\\n\\r\\n\\treturn (diff_y == 0 and diff_x != 0) or (diff_x == 0 and diff_y != 0) or abs(diff_x) == abs(diff_y)\",\n \"def __eq__(self, other):\\n x_eq = self.x == other.x\\n y_eq = self.y == other.y\\n return x_eq and y_eq\",\n \"def __eq__(self, other):\\n x_eq = self.x == other.x\\n y_eq = self.y == other.y\\n return x_eq and y_eq\",\n \"def equal_points_2d(p1, p2, tol=None):\\r\\n if tol is None:\\r\\n tol = get_tol_2d()\\r\\n return geometry.gmEqualPointsXY(p1, p2, tol)\",\n \"def nearlyEqual(self, x, y):\\n return abs(x-y) < self.absoluteerrorrange\",\n \"def closeTo(pointOne, pointTwo):\\r\\n\\tif abs(pointOne.lat-pointTwo.lat) < 0.0002:\\r\\n\\t\\tif abs(pointOne.lon-pointTwo.lon) < 0.0002:\\r\\n\\t\\t\\treturn True\\r\\n\\treturn False\",\n \"def IsApproximatelyEqual(x, y, epsilon = 1e-6):\\n # Check absolute precision.\\n if -epsilon <= x - y <= epsilon:\\n return True\\n\\n # Is x or y too close to zero?\\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\\n return False\\n\\n # Check relative precision.\\n return (-epsilon <= (x - y) / x <= epsilon or -epsilon <= (x - y) / y <= epsilon)\",\n \"def __le__(self, other: Compound[Scalar]) -> bool:\\n return (self._points_set <= other._points_set\\n if isinstance(other, Multipoint)\\n else NotImplemented)\",\n \"def __eq__(self, other):\\n return self.x == other.x and self.y == other.y\",\n \"def __eq__(self,other):\\n return (self - other == 0.)\",\n \"def torch_the_same(X, Y, eps=1e-8):\\n return (X - Y).abs().min() < eps\",\n \"def comparison_test():\\n for pose in SE2.interesting_points():\\n se2 = se2_from_SE2(pose)\\n SE2a = SE2_from_se2_slow(se2)\\n SE2b = SE2_from_se2(se2)\\n # printm('pose', pose, 'se2', se2)\\n # printm('SE2a', SE2a, 'SE2b', SE2b)\\n SE2.assert_close(SE2a, pose)\\n # print('SE2a = pose Their distance is %f' % d)\\n SE2.assert_close(SE2b, pose)\\n # print('SE2b = pose Their distance is %f' % d)\\n assert_allclose(SE2a, SE2b, atol=1e-8, err_msg=\\\"SE2a != SE2b\\\")\\n assert_allclose(SE2a, pose, atol=1e-8, err_msg=\\\"SE2a != pose\\\")\\n assert_allclose(SE2b, pose, atol=1e-8, err_msg=\\\"SE2b != pose\\\")\",\n \"def is_equal(self, a, b):\\n return a.X[0] == b.X[0]\",\n \"def __gt__(self, other: Compound[Scalar]) -> bool:\\n return (self._points_set > other._points_set\\n if isinstance(other, Multipoint)\\n else NotImplemented)\",\n \"def is_equal(self, other):\\n return self.close(other) & (abs(self.width - other.width) < 100) & (abs(self.height - other.height) < 50)\",\n \"def series_are_equivalent(series_1: Series, series_2: Series) -> bool:\\n d1 = series_1.copy().reset_index()\\n cols_1 = sorted([c for c in d1.columns if c != 'p'])\\n cols_p = cols_1 + ['p']\\n s1 = d1[cols_p].set_index(cols_1)['p']\\n d2 = series_2.copy().reset_index()\\n cols_2 = sorted([c for c in d2.columns if c != 'p'])\\n if cols_1 != cols_2:\\n return False\\n s2 = d2[cols_p].set_index(cols_2)['p']\\n for k, v in s1.iteritems():\\n if v == 0:\\n continue\\n if k not in s2.keys() or abs(s2[k] - v) > 1e-10:\\n return False\\n return True\",\n \"def __eq__(self, other):\\n return self.x == other.x and self.y == other.y\",\n \"def IsApproximatelyEqual(x, y, epsilon):\\n # Check absolute precision.\\n if -epsilon <= x - y <= epsilon:\\n return True\\n\\n # Is x or y too close to zero?0.\\n if -epsilon <= x <= epsilon or -epsilon <= y <= epsilon:\\n return False\\n\\n # Check relative precision.\\n return (-epsilon <= (x - y) / x <= epsilon\\n or -epsilon <= (x - y) / y <= epsilon)\",\n \"def __eq__(self, other):\\n return self.start == other.start and self.end == other.end\",\n \"def test_LessThanorEqualto(self):\\n self.assertTrue(Fraction(-7,10)<=Fraction(-7,10))\",\n \"def sameLocation(self, other):\\n if not isinstance(other,Point):\\n return False\\n return self.longitude == other.getLongitude() and self.latitude == other.getLatitude()\",\n \"def overlap(p1: Tuple, p2: Tuple) -> bool:\\n if (p2[1] - p1[0]) * (p2[0] - p1[1]) <= 0:\\n return True\\n else:\\n return False\",\n \"def approx_eq(x, y, tolerance=1e-15):\\n return abs(x - y) < tolerance\",\n \"def position_equal(self, a, b):\\n return None\",\n \"def nearlyEqual(self, x, y):\\n return self.absoluteerror(x).nearlyEqual(x, y)\",\n \"def almost_equal(first, second, places=None, delta=0.1):\\n if first == second:\\n # shortcut\\n return True\\n if delta is not None and places is not None:\\n raise TypeError(\\\"specify delta or places not both\\\")\\n if delta is not None:\\n if abs(first - second) <= delta:\\n return True\\n else:\\n if places is None:\\n places = 2\\n\\n if round(abs(second-first), places) == 0:\\n return True\\n return False\",\n \"def fuzzy_equals(a, b):\\n epsilon = 10**(-6) \\n return (abs(a - b) < epsilon)\",\n \"def _is_same_position(pos1, pos2, position_tolerance):\\n return np.isclose(_pos_distance(pos1, pos2), 0, atol=position_tolerance)\",\n \"def approx_eq(x, y, tolerance = 0.000001):\\n\\treturn abs(x - y) < tolerance\",\n \"def __ge__(self, other: Compound[Scalar]) -> bool:\\n return (self._points_set >= other._points_set\\n if isinstance(other, Multipoint)\\n else NotImplemented)\",\n \"def __eq__(self, rhs):\\n return self.x == rhs.x and self.y == rhs.y\",\n \"def isGE(self, a : float, b : float) -> bool:\\n return (a >= b - self.tol * max(abs(a), abs(b), 1.0)) #and (a >= b - 0.1)\",\n \"def equals(a, b, tol=1e-10):\\n return np.abs(a-b) <= tol\",\n \"def __eq__(self, other):\\n return self.key == other.key \\\\\\n and self.get_inside() == other.get_inside() \\\\\\n and self.get_outside() == other.get_outside()\",\n \"def __eq__(self, other):\\n return (self.start == other.start and self.end == other.end)\",\n \"def equal(self,other):\\n if(self.x == other.x) and (self.y == other.y):\\n return True\\n else:\\n return False\",\n \"def __ge__(self: _TT, other: _TT) -> bool:\\n if type(self) != type(other):\\n raise TypeError(\\\"Types do not match\\\")\\n return self.value >= other.value\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7833791","0.7375096","0.73340034","0.7259631","0.7250514","0.72273964","0.7221379","0.7205826","0.7195672","0.7176461","0.716174","0.7157015","0.7149755","0.7145545","0.7136548","0.7128811","0.7119354","0.71039134","0.7080448","0.7078054","0.706964","0.7067201","0.70246196","0.69982904","0.699119","0.6936114","0.69301784","0.68957317","0.6885012","0.6854464","0.6840439","0.6833217","0.68292654","0.6827435","0.6810657","0.679566","0.67386913","0.6733382","0.67239666","0.67093605","0.66875654","0.66804063","0.66557294","0.6644461","0.66346836","0.6625925","0.66124785","0.6611491","0.6598877","0.6594731","0.6592178","0.65638524","0.65620786","0.65558404","0.6550091","0.65431464","0.65424514","0.65280336","0.6527809","0.6516272","0.6513411","0.65119386","0.65119386","0.64959085","0.6491115","0.6488812","0.6488812","0.64846456","0.6472074","0.64700496","0.64602524","0.64598197","0.6458351","0.6457986","0.6451353","0.6447432","0.644279","0.6441369","0.64405775","0.6438706","0.6434201","0.6427598","0.6426866","0.6424115","0.64159507","0.6414453","0.64131624","0.6412213","0.64093727","0.64088476","0.64076924","0.64005876","0.63974744","0.63972884","0.6391962","0.6391909","0.6386953","0.63787866","0.6369599","0.636841","0.63681036"],"string":"[\n \"0.7833791\",\n \"0.7375096\",\n \"0.73340034\",\n \"0.7259631\",\n \"0.7250514\",\n \"0.72273964\",\n \"0.7221379\",\n \"0.7205826\",\n \"0.7195672\",\n \"0.7176461\",\n \"0.716174\",\n \"0.7157015\",\n \"0.7149755\",\n \"0.7145545\",\n \"0.7136548\",\n \"0.7128811\",\n \"0.7119354\",\n \"0.71039134\",\n \"0.7080448\",\n \"0.7078054\",\n \"0.706964\",\n \"0.7067201\",\n \"0.70246196\",\n \"0.69982904\",\n \"0.699119\",\n \"0.6936114\",\n \"0.69301784\",\n \"0.68957317\",\n \"0.6885012\",\n \"0.6854464\",\n \"0.6840439\",\n \"0.6833217\",\n \"0.68292654\",\n \"0.6827435\",\n \"0.6810657\",\n \"0.679566\",\n \"0.67386913\",\n \"0.6733382\",\n \"0.67239666\",\n \"0.67093605\",\n \"0.66875654\",\n \"0.66804063\",\n \"0.66557294\",\n \"0.6644461\",\n \"0.66346836\",\n \"0.6625925\",\n \"0.66124785\",\n \"0.6611491\",\n \"0.6598877\",\n \"0.6594731\",\n \"0.6592178\",\n \"0.65638524\",\n \"0.65620786\",\n \"0.65558404\",\n \"0.6550091\",\n \"0.65431464\",\n \"0.65424514\",\n \"0.65280336\",\n \"0.6527809\",\n \"0.6516272\",\n \"0.6513411\",\n \"0.65119386\",\n \"0.65119386\",\n \"0.64959085\",\n \"0.6491115\",\n \"0.6488812\",\n \"0.6488812\",\n \"0.64846456\",\n \"0.6472074\",\n \"0.64700496\",\n \"0.64602524\",\n \"0.64598197\",\n \"0.6458351\",\n \"0.6457986\",\n \"0.6451353\",\n \"0.6447432\",\n \"0.644279\",\n \"0.6441369\",\n \"0.64405775\",\n \"0.6438706\",\n \"0.6434201\",\n \"0.6427598\",\n \"0.6426866\",\n \"0.6424115\",\n \"0.64159507\",\n \"0.6414453\",\n \"0.64131624\",\n \"0.6412213\",\n \"0.64093727\",\n \"0.64088476\",\n \"0.64076924\",\n \"0.64005876\",\n \"0.63974744\",\n \"0.63972884\",\n \"0.6391962\",\n \"0.6391909\",\n \"0.6386953\",\n \"0.63787866\",\n \"0.6369599\",\n \"0.636841\",\n \"0.63681036\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":3993,"cells":{"query":{"kind":"string","value":"Cast schema names which containing special characters to valid names. Here special characters means any characters in"},"document":{"kind":"string","value":"def cast_name(key):\n special_symbols = set('{}{}'.format(punctuation, ' '))\n special_symbols.remove('_')\n new_key = ['_' if x in special_symbols else x for x in key]\n casted_key = ''.join(new_key)\n return casted_key"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def encodeSchemaName(self, schema):\r\n return '\"{}\"'.format(schema)","def _scrub(self, string):\n if not string.isalnum():\n raise ValueError(\"Table name cannot include non-alphanumerics.\")\n return string","def normalize_name(word):\n return word.strip(\"0123456789!@#$%^&*_() +=\\/?<>,.`~;:\").lower().replace(\" \",\"_\")","def clean_name(name, allowed_chars):\n ok = identifier_chars + allowed_chars\n newname = \"\".join(c if c in ok else \"-\" for c in name)\n newname = newname.lstrip(\"-\")\n if not newname:\n raise RuntimeError(f\"No valid chars in name '{name}'.\")\n return newname","def test_normalize_name(self):\n name = self.t.normalize_name('\\\\\\\\test')\n name2 = self.t.normalize_name('\\\\test')\n name3 = self.t.normalize_name('/test')\n name4 = self.t.normalize_name('//test')\n\n self.assertEqual(name, ' test')\n self.assertEqual(name2, ' test')\n self.assertEqual(name3, ' test')\n self.assertEqual(name4, ' test')","def check_schema_name(name: str):\n if not is_valid_schema_name(name):\n raise ValidationError(\"Invalid string used for the schema name.\")","def safe_name(self, name):\n\n output = \"\"\n for char in name:\n if char not in '\\\\/<>:\"|?*':\n output += char\n\n return output","def MakeValidName(name):\n if name:\n goodName = []\n if not xml.is_name_start_char(name[0]):\n goodName.append(u'_')\n for c in name:\n if xml.is_name_char(c):\n goodName.append(c)\n else:\n goodName.append(u'_')\n return string.join(goodName, u'')\n else:\n return u'_'","def _sanitizeName(name):\n\n name = name.lower() # lower.\n name = name.replace('.','') # remove periods.\n name = name.replace('-','') # remove dashes.\n name = name.replace(\"'\",'') # remove apostrophies.\n # return it.\n return name","def normalize_pipeline_name(name=''):\n normalized_name = name\n for bad in '\\\\/?%#':\n normalized_name = normalized_name.replace(bad, '_')\n return normalized_name","def sanitize_name(name):\n # For now just change dashes to underscores. Fix this more in the future\n return name.replace(\"-\", \"_\")","def name_cleaning(df):\n # Custom cleaning\n df.columns = [re.sub(\"[\\\\. \\\\(\\\\)\\\\/]+\", \"_\", elem) for elem in df.columns]\n df.columns = [re.sub(\"-\", \"_\", elem) for elem in df.columns]\n df.columns = [re.sub(\"'\", \"\", elem) for elem in df.columns]\n df.columns = [re.sub(\",\", \"_\", elem) for elem in df.columns]\n df.columns = [re.sub(\":\", \"_\", elem) for elem in df.columns]\n df.columns = [re.sub(\"<\", \"MIN\", elem) for elem in df.columns]\n df.columns = [re.sub(\">\", \"MAG\", elem) for elem in df.columns]\n df.columns = [re.sub(\"&\", \"E\", elem) for elem in df.columns]\n df.columns = [re.sub(\"°\", \"\", elem) for elem in df.columns]\n df.columns = [re.sub(\"%\", \"PERC\", elem) for elem in df.columns]\n df.columns = [re.sub(\"\\\\+\", \"_\", elem) for elem in df.columns]\n # String upper\n df.columns = [elem.upper() for elem in df.columns]\n # Trim\n df.columns = [elem.strip() for elem in df.columns]\n # Cut recurring underscore\n df.columns = [re.sub(\"_+\", \"_\", elem) for elem in df.columns]\n return(df)","def sql_name_pattern(pattern):\n\n inquotes = False\n relname = ''\n schema = None\n pattern_len = len(pattern)\n i = 0\n\n while i < pattern_len:\n c = pattern[i]\n if c == '\"':\n if inquotes and i + 1 < pattern_len and pattern[i + 1] == '\"':\n relname += '\"'\n i += 1\n else:\n inquotes = not inquotes\n elif not inquotes and c.isupper():\n relname += c.lower()\n elif not inquotes and c == '*':\n relname += '.*'\n elif not inquotes and c == '?':\n relname += '.'\n elif not inquotes and c == '.':\n # Found schema/name separator, move current pattern to schema\n schema = relname\n relname = ''\n else:\n # Dollar is always quoted, whether inside quotes or not.\n if c == '$' or inquotes and c in '|*+?()[]{}.^\\\\':\n relname += '\\\\'\n relname += c\n i += 1\n\n if relname:\n relname = '^(' + relname + ')$'\n\n if schema:\n schema = '^(' + schema + ')$'\n\n return schema, relname","def legal_variable_name(name):\n var_name = name.replace(' ', '_')\n for char in r'''[]{}\\/^%$#@!+-<>?|'\"=~`,.;:''':\n if char in var_name:\n var_name = var_name.replace(char, '')\n for char in var_name:\n if ord(char) > 127: # remove non-ascii characters\n var_name = var_name.replace(char, '')\n return var_name","def check_funny_chars_in_names(names, is_full_qualified_name=True):\n if names and len(names) > 0:\n for name in names:\n if ('\\t' in name or '\\n' in name or '!' in name or ',' in name or\n (is_full_qualified_name and name.count('.') > 1) or (not is_full_qualified_name and name.count('.') > 0)):\n raise Exception('Name has an invalid character \"\\\\t\" \"\\\\n\" \"!\" \",\" \".\": \"%s\"' % name)","def test_normalize_star_name(self):\n self.assertEqual(normalize_star_name(\"RR LYR\"), \"RR LYR\")\n self.assertEqual(normalize_star_name(\"V1339 CYG\"), \"V1339 CYG\")\n self.assertEqual(normalize_star_name(\"V838 MON\"), \"V0838 MON\")","def scrub(self, table_name):\n\n return ''.join( chr for chr in table_name if chr.isalnum() )","def test_underscore(self):\n try:\n db_name_validator('logstash_')\n except ValidationError:\n self.fail('Name raised ValidationError unexpectedly')","def valid_identifier_name(name):\n remove_characters_regex = '[^a-zA-Z0-9_]'\n name = re.sub(remove_characters_regex, '', name)\n # Remove beginning characters that are numbers\n name = re.sub('^[0-9]*', '', name)\n return name","def regular_edge_name(name: str) -> str:\n regular = \"\"\n for char in name:\n if char.isalpha() or char.isdigit():\n regular = f\"{regular}{char}\"\n else:\n regular = f\"{regular}_\"\n if not regular[0].isalpha():\n regular = f\"auto_legalized__{regular}\"\n return regular","def _clean_non_alphanumeric_chars(self):\n\n for i,variable in enumerate(self.model_description.modelVariables):\n clean_name = re.sub(r'[^a-zA-Z0-9_]', '', variable.name)\n if clean_name != variable.name:\n log = \"Sim variable '{}' has been renamed to '{}' \".format(variable.name, clean_name)\n log += \"to comply with Bonsai naming requirements.\"\n print(log)\n self.model_description.modelVariables[i].name = clean_name\n\n return","def safe_column_name(string):\n string = unidecode(string.replace(' ', '_').lower())\n return re.sub(r'[^0-9a-z_]','', string)","def fix_natural_language(name):\n\tfor ch in r\"\\`*{}[]()>#+-.!$\":\n\t\tif ch in name:\n\t\t\tname = name.replace(ch,\"_\")\n\treturn name","def sanitize_luxcore_name(string):\r\n return re.sub(\"[^_0-9a-zA-Z]+\", \"__\", string)","def test_sanitize_name(self):\n assert scrape_category.sanitize_name(\" foo \") == \"foo\"\n assert scrape_category.sanitize_name(' foo\" ') == \"foo\"\n assert scrape_category.sanitize_name(' foo...bar ') == \"foo.bar\"","def _validate_names(mapping: Mapping[str, Any],\n ref: str) -> Tuple[Set[str], List[SchemaError]]:\n errs = [] # type: List[SchemaError]\n\n names = {mapping['name']}\n\n if 'classes' in mapping:\n for i, obj in enumerate(mapping['classes']):\n name = obj['name']\n if name in names:\n errs.append(\n SchemaError(\n message=\"Duplicate names: {!r}\".format(name),\n ref=\"{}/classes/{}/name\".format(ref, i)))\n\n names.add(name)\n\n if 'embeds' in mapping:\n for i, obj in enumerate(mapping['embeds']):\n name = obj['name']\n if name in names:\n errs.append(\n SchemaError(\n message=\"Duplicate names: {!r}\".format(name),\n ref=\"{}/embeds/{}/name\".format(ref, i)))\n\n names.add(name)\n\n return names, errs","def _sanitize_to_identifer(name):\n n = name.strip()\n n = re.sub('/', ' ', n)\n n = re.sub('-', ' ', n)\n n = re.sub(' +', '_', n)\n n = re.sub('[\\W]+', '', n)\n return n","def FilterName(namefilter, safechar='P', reserved_names=None):\n # remove non accepted characters\n for c in r' -[]/\\;,><&*:%=+@!#^|?^':\n namefilter = namefilter.replace(c, '')\n\n # remove non english characters\n char_list = (c for c in namefilter if 0 < ord(c) < 127)\n namefilter = ''.join(char_list)\n\n # Make sure we have a non empty string\n if len(namefilter) <= 0:\n namefilter = safechar\n\n # Make sure we don't start with a number\n if namefilter[0].isdigit():\n print(namefilter)\n namefilter = safechar + namefilter\n\n # Make sure we are not using a reserved name\n if reserved_names is not None:\n while namefilter.lower() in reserved_names:\n namefilter = safechar + namefilter\n\n # Add the name to reserved names\n reserved_names.append(namefilter)\n\n return namefilter","def symbolize_sensorname(name):\n return name.lower().replace(\" \", \"_\")","def sanitize(name):\n ## Disallowed characters in filenames\n DISALLOWED_CHARS = \"\\\\/:<>?*|\"\n if name == None:\n name = \"Unknown\"\n for character in DISALLOWED_CHARS:\n name = name.replace(character,'_')\n # Replace \" with '\n name = name.replace('\"', \"'\")\n\n return name","def test_normalize_name_bug_1762789(self):\n name = u'Fu\\xdfball'\n self.assertEqual(u'CUSTOM_FU_BALL', utils.normalize_rc_name(name))","def normalize_name(cls, name):\n\t\treturn ' '.join(name.lower().strip().split())","def normalize_name(cls, name):\n\t\treturn ' '.join(name.lower().strip().split())","def normalize_name(cls, name):\n\t\treturn ' '.join(name.lower().strip().split())","def sanitize_name(self, value):\n if self.sanitize_names:\n new_value = re.sub('[^a-zA-Z0-9_]', '_', value[:127])\n else:\n new_value = value\n return new_value","def test_white_space(self):\n with self.assertRaises(ValidationError):\n db_name_validator('http log')","def test_legal_names(self):\n names = [prod.name for prod in generate_products()]\n sep = [(name.split()[0], name.split()[1]) for name in names]\n for name in sep:\n self.assertIn(name[0], ADJS)\n self.assertIn(name[1], NOUNS)","def sanitize(name):\n return re.sub(\"\\\\W|^(?=\\\\d)\", \"_\", name)","def name_to_goodreads(name):\n name = to_ascii(name.title())\n for char in CHARS:\n name = name.replace(*char)\n return name","def sanitize(name):\n return re.sub('\\\\W|^(?=\\\\d)', '_', name)","def python_safe_name(s):\n no_punctuation = re.compile(r'[\\W_]', re.MULTILINE).sub\n s = s.lower()\n s = no_punctuation(' ', s)\n s = '_'.join(s.split())\n if py2 and isinstance(s, unicode):\n s = s.encode('ascii', 'ignore')\n return s","def validName(varname):\r\n if (len(varname[0])>32):\r\n return False\r\n if not(varname[0][0].isalpha()):\r\n return False \r\n for ch in varname[0][1:]:\r\n if not(ch.isalpha() or ch.isdigit() or ch=='_'):\r\n return False\r\n \r\n return True","def test_value_special_chars(self):\n raw = [\n 0x48,\n 0x65,\n 0x79,\n 0x21,\n 0x3F,\n 0x24,\n 0x20,\n 0xC4,\n 0xD6,\n 0xDC,\n 0xE4,\n 0xF6,\n 0xFC,\n 0xDF,\n ]\n string = \"Hey!?$ ÄÖÜäöüß\"\n self.assertEqual(DPTString.to_knx(string), raw)\n self.assertEqual(DPTString.from_knx(raw), string)","def isValidDataTypeName(name: unicode) -> bool:\n ...","def sanitize_name(name: str) -> str:\n return re.sub(r\"[^A-Za-z0-9_-]\", \"-\", name)[0:128]","def _convert_name(self, name):\n if not self.re_name.match(name):\n org_name = name\n name = self.re_white.sub('_', name)\n name = self.re_alpha.sub('_', name)\n if not self.re_name.match(name):\n name = 'x_' + name2\n self.warn('Converting name <' + org_name + '> to <' + name + '>.')\n return name","def test_hyphen(self):\n try:\n db_name_validator('logstash-')\n except ValidationError:\n self.fail('Name raised ValidationError unexpectedly')","def _database_username_validate(s):\n if len(s) < 1 or len(s) > 63:\n raise ValueError('Database user name must be 1 to 63 characters long')\n if s[0] not in string.ascii_letters:\n raise ValueError('Database user name must start with a letter')\n allowed_characters = frozenset(string.ascii_letters + string.digits + '_')\n if frozenset(s).issuperset(allowed_characters):\n raise ValueError('Invalid character in database user name. Only '\n 'numbers, letters, and _ are acceptable.')","def normalize(s):\n s = str(s.strip())\n patt = re.compile(r'^\\?\\w+$')\n if patt.match(s):\n name = s[1:]\n return Variable(name)\n return s","def __sanitize(name):\n if name[-1] == \"/\":\n return name[:-1]\n return name","def create_schema(self, schema: str):\n return","def clean_name(s):\n return re.sub('[\\W_]+', '', s).lower()","def normalize_reference_name(name):\n return name.strip().lower().replace(\"-\", \"_\").replace(\" \", \"_\")","def test_legal_names(self):\n prods = generate_products()\n for obj in prods:\n self.assertRegexpMatches(\n '(\\w{2,10} \\w{0,12}|\\?{0,3}){1}', obj.name)","def validate_names(name):\n return isinstance(name, str) and not re.search(r'[\\s]', name)","def safe_formal_name(name):\n return re.sub(r\"\\s+\", \" \", re.sub(r'[!/\\\\:<>\"\\?\\*\\|]', \"\", name)).strip()","def test_special_characters_business_name(self):\n user = \"chairman\"\n msg = self.business_item_class.create_business(\"Ma@en_deleo\", user, \"soft*%ware\", \"nairo@&\")\n print(msg)\n self.assertEqual(msg, {\"message\":\"Business name should not contain special characters\"})","def standardize_name_for_look_up(name: Any) -> str:\n if not isinstance(name, str):\n return name\n\n name = name.lower().strip()\n name = \" \".join(name.split(\"_\"))\n name = name.translate(\n str.maketrans(\"\", \"\", string.punctuation)\n ) # remove punctuation\n name = \" \".join(\n [part for part in name.split(\" \") if part]\n ) # ensure there is only a single space between words\n return name","def test_instance_type_create_with_special_characters(self):\n name = \"foo.bar!@#$%^-test_name\"\n flavorid = \"flavor1\"\n self.assertRaises(exception.InvalidInput, instance_types.create,\n name, 256, 1, 120, 100, flavorid)","def check_valid_key_name(name):\n if type(name) not in [str]:\n return False\n bad_chars = [\"*\", \".\", \"&&&&\"]\n for k in bad_chars:\n if k in name:\n return False\n return True","def to_safe_name(name: str) -> str:\n return regex_replace(r'\\-|\\.|:', \"\", name.replace(' ', '_'))","def sanitize_diagnoses(df):\n df = df.str.replace(\"\\W\", \"\") # \"\\W\" regex represents ANY non-alphanumeric character\n# assert (df.str.contains(\"\\W\")).any(), \"At least one diagnosis has a non-alphanumeric character in it\"\n return df","def test_nonreserved_name(self):\n try:\n field_name_validator('_identifier')\n except ValidationError:\n self.fail('Field name raised ValidationError unexpectedly')","def normalizeName(fullName):\n\n fullName = fullName.lower()\n\n fullName = fullName.split('\\n')[0].strip()\n fullName = re.sub(r'\\([^()]*\\)', '', fullName) # Remove parenthesis\n fullName = re.sub(r\"\\'[^'']*\\'\", '', fullName) # Remove commas\n fullName = unidecode.unidecode(fullName) # Remove diacritics\n fullName = fullName.replace(' ', '_')\n # Remove all non-alphanumerics characters (except _)\n fullName = re.sub(r'\\W+', '', fullName)\n fullName = re.sub(r\"[_]+\", '_', fullName)\n return fullName","def fromSSQL(s):\n return s.replace('___', '.')","def validVarConstructName(self,varname):\r\n if (len(varname[0])>32):\r\n return False, ''\r\n if not(varname[0][0].isalpha()):\r\n return False, '' \r\n for ch in varname[0][1:]:\r\n if not(ch.isalpha() or ch.isdigit() or ch=='_'):\r\n return False, ''\r\n \r\n return True, varname","def _check_if_valid_dataset_name(dataset_name: str) -> str:\n if not re.match(r\"^[A-Za-z0-9_]+$\", dataset_name):\n raise ExecutionEngineError(\n f\"dataset_name: {dataset_name} is not valid, because it contains non-alphanumeric and _ characters.\"\n f\"Please check your configuration.\"\n )\n\n if len(dataset_name) >= MAX_TABLE_NAME_LENGTH:\n # starting from the end, so that we always get the index and sub_index\n new_dataset_name = dataset_name[-MAX_TABLE_NAME_LENGTH:]\n logger.info(\n f\"dataset_name: '{dataset_name}' was truncated to '{new_dataset_name}' to keep within length limits.\"\n )\n dataset_name = new_dataset_name\n\n while not re.match(r\"^[A-Za-z]+$\", dataset_name[0]):\n dataset_name = dataset_name[1:]\n\n return dataset_name","def test_asterisk(self):\n with self.assertRaises(ValidationError):\n db_name_validator('logstash*')","def _normalize_show_name(name):\n\tname = name.casefold()\n\tname = re.sub(\"[^a-z0-9]\", \" \", name)\n\tname = re.sub(\"_\", \" \", name)\n\tname = re.sub(\"season \\d( part \\d)?\", \" \", name)\n\tname = re.sub(\"\\s+\", \" \", name)\n\treturn name","def normalize(name):\n name = name.lower()\n name = name.replace('-', '')\n name = name.replace(' ', '')\n return name","def clean(name):\n name = remove_extra(name)\n name = unidecode.unidecode(name) # Remove diacritics\n name = \"\".join(\n list(filter(lambda c: c in (string.ascii_letters + string.digits + \" \"), name))\n )\n name = name.lower().strip()\n return name","def normalize_name(field_name):\n fixes = (\n (r\"/\", \"_per_\"),\n (r\"%\", \"_pct_\"),\n (r\"\\W\", \"_\"),\n (r\"^_+\", \"\"), # remove '_' if field_name begins with '_'\n (r\"_+$\", \"\"),\n (r\"__+\", \"_\"),\n )\n result = field_name.strip().lower() or None\n # result = field_name.strip().upper() or None\n if result:\n if result.endswith(\"?\"):\n if not re.match(r\"is[_\\W]\", result):\n result = \"is_\" + result\n for pattern, replacement in fixes:\n result = re.sub(pattern, replacement, result)\n return result","def clean_name(name: str) -> str:\n if not re.match(\"[a-zA-Z_]\", name[0]):\n name = \"_\" + name\n name = re.sub(\"[^0-9a-zA-Z_]+\", \"_\", name)\n if all(c == \"_\" for c in name):\n name = \"v\"\n return name","def normalize_name(name):\n return PUNCT_RE.sub('-', name.lower()).strip('-')","def _bcl_scrub_name(name):\n return re.sub('[^0-9a-zA-Z\\-\\_]+', '_', name)","def adjust_name_for_printing(name):\n if name is not None:\n name2 = name\n name = name.replace(\" \", \"_\").replace(\".\", \"_\").replace(\"-\", \"_m_\")\n name = name.replace(\"+\", \"_p_\").replace(\"!\", \"_I_\")\n name = name.replace(\"**\", \"_xx_\").replace(\"*\", \"_x_\")\n name = name.replace(\"/\", \"_l_\").replace(\"@\", '_at_')\n name = name.replace(\"(\", \"_of_\").replace(\")\", \"\")\n if re.match(r'^[a-zA-Z_][a-zA-Z0-9-_]*$', name) is None:\n raise NameError(\"name {} converted to {} cannot be further converted to valid python variable name!\".format(name2, name))\n return name\n return ''","def resolver(schema):\n name = schema.__name__\n if name.endswith(\"Schema\"):\n return name[:-6] or name\n return name","def validate_output_name(value):\n internal_name_prefix = u'___'\n if value.startswith(internal_name_prefix):\n raise GraphQLCompilationError(\n u'The prefix \"___\" (three underscores) for output names is reserved by the compiler.')","def mangle_name(name):\n import re\n try:\n return re.sub('_+','_',re.sub('[^\\w_]','_',name).lower()).rstrip('_')\n except TypeError:\n raise TypeError(\n 'Trying to mangle name with invalid type of: ' + str(type(name)))","def test_split_table_name(self):\n\n self.assertEqual(\n {\"database\": \"database\", \"database_schema\": \"schema\", \"table\": \"table\"},\n fqn.split_table_name(table_name=\"database.schema.table\"),\n )\n\n self.assertEqual(\n {\"database\": None, \"database_schema\": \"schema\", \"table\": \"table\"},\n fqn.split_table_name(table_name=\"schema.table\"),\n )\n\n self.assertEqual(\n {\"database\": None, \"database_schema\": None, \"table\": \"table\"},\n fqn.split_table_name(table_name=\"table\"),\n )\n\n # We also clean quotes\n self.assertEqual(\n {\"database\": \"database\", \"database_schema\": \"schema\", \"table\": \"table\"},\n fqn.split_table_name(table_name='database.\"schema\".table'),\n )","def to_safe(self, word):\n return re.sub(\"[^A-Za-z0-9\\-]\", \"_\", word)","def clean_strain_name(raw_name):\n strain_name = clean_string(raw_name)\n strain_name = strain_name.split(' Strain')[0]\n return strain_name","def normalize_symbol_name(symbol_name):\n if symbol_name == \"\\\\frac\":\n return \"\\\\frac{}{}\" # noqa\n elif symbol_name == \"\\\\sqrt\":\n return \"\\\\sqrt{}\" # noqa\n elif symbol_name in [\"<\", r\"\\lt\"]:\n return \"<\"\n elif symbol_name in [\">\", r\"\\gt\"]:\n return \">\"\n elif symbol_name == \"{\":\n return r\"\\{\"\n elif symbol_name == \"}\":\n return r\"\\}\"\n return symbol_name","def test_space_stripping(self):\n descriptor = clone(SPECIES_OBSERVATION_SCHEMA)\n species_name = 'Chubby Bat'\n record = {\n 'Observation Date': \"18/08/2016\",\n 'Latitude': -32,\n 'Longitude': 115,\n 'Species Name': ' Chubby Bat '\n }\n schema = SpeciesObservationSchema(descriptor)\n self.assertEqual(species_name, schema.cast_species_name(record))","def clean_table_name(table_name):\n path_underscore = table_name.translate(table_name.maketrans(\"-. \", \"___\"))\n return \"_\".join(filter(None, path_underscore.split(\"_\")))","def clean_schema(schema):\n # type: (Dict) -> Dict\n return {k: v for k, v in schema.items()\n if k not in _SWAGGER_FIELDS and not k.lower().startswith(\"x-\")}","def check_file_name_components(self):\n illegal_characters = [\".\", \"-\", \" \"]\n components_to_check = [self.location_id, self.dataset_name, self.qualifier, self.temporal]\n valid = lambda component: sum([bad_char in component for bad_char in illegal_characters]) == 0\n bad_components = [component for component in components_to_check if not valid(component)]\n if bad_components:\n message = f\"The following properties contained one or more illegal characters: \"\n message += f\"{bad_components}\\n\"\n message += f\"Illegal characters include: {illegal_characters}\"\n raise DefinitionError(message)","def _is_valid_keyspace_name(self, keyspace_name):\n if keyspace_name == None or not keyspace_name:\n return False\n return re.match(r\"^[a-z_]*[^-]$\", keyspace_name)","def normalize_const(var_name):\n return var_name.lower().split('_')","def alias(name):\n name = name.strip().replace(\" \", \"_\").replace(\"-\", \"_\")\n while \"__\" in name:\n name = name.replace(\"__\", \"_\")\n return \"\".join(x for x in name if x.isalnum() or x == \"_\").lower()","def _slugify_columns(column_names):\n\n encoded_names = []\n\n for column_name in column_names:\n slug = RE_ENCODED_COLUMN.sub('_', column_name).lower()\n slug = make_unique(slug, encoded_names + Parser.reserved_words)\n encoded_names.append(slug)\n\n return encoded_names","def k8s_safe_name(name):\n return name.lower().replace('_', '-')","def _filter_hotkey_set_name(hotkey_set_name):\n # Replace spaces with underscores\n hotkey_set_name = hotkey_set_name.replace(' ', '_')\n # Remove special characters\n hotkey_set_name = ''.join(re.findall(r\"[_a-zA-Z0-9]+\", hotkey_set_name))\n return hotkey_set_name","def test_special_characters(self):\n testString = sanitize('[-;]\\`{\\}')\n self.assertEqual(testString, '_________')","def testValidCastToStringAfterParse(self):\n correct = 0\n for example in VALID_EXAMPLES:\n schema_data = schema.Parse(example.schema_string)\n schema.Parse(str(schema_data))\n correct += 1\n\n fail_msg = \"Cast to string success on %d out of %d schemas\" % \\\n (correct, len(VALID_EXAMPLES))\n self.assertEqual(correct, len(VALID_EXAMPLES), fail_msg)","def get_names(view, sel):\n word = view.word(sel)\n schema = None\n if view.substr(word.begin() - 1) == '.':\n schema = view.substr(view.word(word.begin() - 2)).lower()\n return schema, view.substr(word).lower()","def standardize(self, name: str) -> str:\n clean_name = name\n for rule in rules.RULES:\n clean_name = rule(clean_name)\n return clean_name","def test_normalize_separator(self):\n sep = '-'\n text = 'test'\n expected = sep + text\n name = self.t.normalize_name('\\\\\\\\' + text, separator=sep)\n name2 = self.t.normalize_name('\\\\' + text, separator=sep)\n name3 = self.t.normalize_name('/' + text, separator=sep)\n name4 = self.t.normalize_name('//' + text, separator=sep)\n\n self.assertEqual(name, expected)\n self.assertEqual(name2, expected)\n self.assertEqual(name3, expected)\n self.assertEqual(name4, expected)","def cleanName(name):\n return ''.join(char for char in name.lower() if char in (string.digits + string.ascii_lowercase))","def sanitize_input(term: str) -> str:\n return term.strip().replace(\"*\", \"\").replace(\"'\", \"\\\\'\").replace(\"~\", \"\")"],"string":"[\n \"def encodeSchemaName(self, schema):\\r\\n return '\\\"{}\\\"'.format(schema)\",\n \"def _scrub(self, string):\\n if not string.isalnum():\\n raise ValueError(\\\"Table name cannot include non-alphanumerics.\\\")\\n return string\",\n \"def normalize_name(word):\\n return word.strip(\\\"0123456789!@#$%^&*_() +=\\\\/?<>,.`~;:\\\").lower().replace(\\\" \\\",\\\"_\\\")\",\n \"def clean_name(name, allowed_chars):\\n ok = identifier_chars + allowed_chars\\n newname = \\\"\\\".join(c if c in ok else \\\"-\\\" for c in name)\\n newname = newname.lstrip(\\\"-\\\")\\n if not newname:\\n raise RuntimeError(f\\\"No valid chars in name '{name}'.\\\")\\n return newname\",\n \"def test_normalize_name(self):\\n name = self.t.normalize_name('\\\\\\\\\\\\\\\\test')\\n name2 = self.t.normalize_name('\\\\\\\\test')\\n name3 = self.t.normalize_name('/test')\\n name4 = self.t.normalize_name('//test')\\n\\n self.assertEqual(name, ' test')\\n self.assertEqual(name2, ' test')\\n self.assertEqual(name3, ' test')\\n self.assertEqual(name4, ' test')\",\n \"def check_schema_name(name: str):\\n if not is_valid_schema_name(name):\\n raise ValidationError(\\\"Invalid string used for the schema name.\\\")\",\n \"def safe_name(self, name):\\n\\n output = \\\"\\\"\\n for char in name:\\n if char not in '\\\\\\\\/<>:\\\"|?*':\\n output += char\\n\\n return output\",\n \"def MakeValidName(name):\\n if name:\\n goodName = []\\n if not xml.is_name_start_char(name[0]):\\n goodName.append(u'_')\\n for c in name:\\n if xml.is_name_char(c):\\n goodName.append(c)\\n else:\\n goodName.append(u'_')\\n return string.join(goodName, u'')\\n else:\\n return u'_'\",\n \"def _sanitizeName(name):\\n\\n name = name.lower() # lower.\\n name = name.replace('.','') # remove periods.\\n name = name.replace('-','') # remove dashes.\\n name = name.replace(\\\"'\\\",'') # remove apostrophies.\\n # return it.\\n return name\",\n \"def normalize_pipeline_name(name=''):\\n normalized_name = name\\n for bad in '\\\\\\\\/?%#':\\n normalized_name = normalized_name.replace(bad, '_')\\n return normalized_name\",\n \"def sanitize_name(name):\\n # For now just change dashes to underscores. Fix this more in the future\\n return name.replace(\\\"-\\\", \\\"_\\\")\",\n \"def name_cleaning(df):\\n # Custom cleaning\\n df.columns = [re.sub(\\\"[\\\\\\\\. \\\\\\\\(\\\\\\\\)\\\\\\\\/]+\\\", \\\"_\\\", elem) for elem in df.columns]\\n df.columns = [re.sub(\\\"-\\\", \\\"_\\\", elem) for elem in df.columns]\\n df.columns = [re.sub(\\\"'\\\", \\\"\\\", elem) for elem in df.columns]\\n df.columns = [re.sub(\\\",\\\", \\\"_\\\", elem) for elem in df.columns]\\n df.columns = [re.sub(\\\":\\\", \\\"_\\\", elem) for elem in df.columns]\\n df.columns = [re.sub(\\\"<\\\", \\\"MIN\\\", elem) for elem in df.columns]\\n df.columns = [re.sub(\\\">\\\", \\\"MAG\\\", elem) for elem in df.columns]\\n df.columns = [re.sub(\\\"&\\\", \\\"E\\\", elem) for elem in df.columns]\\n df.columns = [re.sub(\\\"°\\\", \\\"\\\", elem) for elem in df.columns]\\n df.columns = [re.sub(\\\"%\\\", \\\"PERC\\\", elem) for elem in df.columns]\\n df.columns = [re.sub(\\\"\\\\\\\\+\\\", \\\"_\\\", elem) for elem in df.columns]\\n # String upper\\n df.columns = [elem.upper() for elem in df.columns]\\n # Trim\\n df.columns = [elem.strip() for elem in df.columns]\\n # Cut recurring underscore\\n df.columns = [re.sub(\\\"_+\\\", \\\"_\\\", elem) for elem in df.columns]\\n return(df)\",\n \"def sql_name_pattern(pattern):\\n\\n inquotes = False\\n relname = ''\\n schema = None\\n pattern_len = len(pattern)\\n i = 0\\n\\n while i < pattern_len:\\n c = pattern[i]\\n if c == '\\\"':\\n if inquotes and i + 1 < pattern_len and pattern[i + 1] == '\\\"':\\n relname += '\\\"'\\n i += 1\\n else:\\n inquotes = not inquotes\\n elif not inquotes and c.isupper():\\n relname += c.lower()\\n elif not inquotes and c == '*':\\n relname += '.*'\\n elif not inquotes and c == '?':\\n relname += '.'\\n elif not inquotes and c == '.':\\n # Found schema/name separator, move current pattern to schema\\n schema = relname\\n relname = ''\\n else:\\n # Dollar is always quoted, whether inside quotes or not.\\n if c == '$' or inquotes and c in '|*+?()[]{}.^\\\\\\\\':\\n relname += '\\\\\\\\'\\n relname += c\\n i += 1\\n\\n if relname:\\n relname = '^(' + relname + ')$'\\n\\n if schema:\\n schema = '^(' + schema + ')$'\\n\\n return schema, relname\",\n \"def legal_variable_name(name):\\n var_name = name.replace(' ', '_')\\n for char in r'''[]{}\\\\/^%$#@!+-<>?|'\\\"=~`,.;:''':\\n if char in var_name:\\n var_name = var_name.replace(char, '')\\n for char in var_name:\\n if ord(char) > 127: # remove non-ascii characters\\n var_name = var_name.replace(char, '')\\n return var_name\",\n \"def check_funny_chars_in_names(names, is_full_qualified_name=True):\\n if names and len(names) > 0:\\n for name in names:\\n if ('\\\\t' in name or '\\\\n' in name or '!' in name or ',' in name or\\n (is_full_qualified_name and name.count('.') > 1) or (not is_full_qualified_name and name.count('.') > 0)):\\n raise Exception('Name has an invalid character \\\"\\\\\\\\t\\\" \\\"\\\\\\\\n\\\" \\\"!\\\" \\\",\\\" \\\".\\\": \\\"%s\\\"' % name)\",\n \"def test_normalize_star_name(self):\\n self.assertEqual(normalize_star_name(\\\"RR LYR\\\"), \\\"RR LYR\\\")\\n self.assertEqual(normalize_star_name(\\\"V1339 CYG\\\"), \\\"V1339 CYG\\\")\\n self.assertEqual(normalize_star_name(\\\"V838 MON\\\"), \\\"V0838 MON\\\")\",\n \"def scrub(self, table_name):\\n\\n return ''.join( chr for chr in table_name if chr.isalnum() )\",\n \"def test_underscore(self):\\n try:\\n db_name_validator('logstash_')\\n except ValidationError:\\n self.fail('Name raised ValidationError unexpectedly')\",\n \"def valid_identifier_name(name):\\n remove_characters_regex = '[^a-zA-Z0-9_]'\\n name = re.sub(remove_characters_regex, '', name)\\n # Remove beginning characters that are numbers\\n name = re.sub('^[0-9]*', '', name)\\n return name\",\n \"def regular_edge_name(name: str) -> str:\\n regular = \\\"\\\"\\n for char in name:\\n if char.isalpha() or char.isdigit():\\n regular = f\\\"{regular}{char}\\\"\\n else:\\n regular = f\\\"{regular}_\\\"\\n if not regular[0].isalpha():\\n regular = f\\\"auto_legalized__{regular}\\\"\\n return regular\",\n \"def _clean_non_alphanumeric_chars(self):\\n\\n for i,variable in enumerate(self.model_description.modelVariables):\\n clean_name = re.sub(r'[^a-zA-Z0-9_]', '', variable.name)\\n if clean_name != variable.name:\\n log = \\\"Sim variable '{}' has been renamed to '{}' \\\".format(variable.name, clean_name)\\n log += \\\"to comply with Bonsai naming requirements.\\\"\\n print(log)\\n self.model_description.modelVariables[i].name = clean_name\\n\\n return\",\n \"def safe_column_name(string):\\n string = unidecode(string.replace(' ', '_').lower())\\n return re.sub(r'[^0-9a-z_]','', string)\",\n \"def fix_natural_language(name):\\n\\tfor ch in r\\\"\\\\`*{}[]()>#+-.!$\\\":\\n\\t\\tif ch in name:\\n\\t\\t\\tname = name.replace(ch,\\\"_\\\")\\n\\treturn name\",\n \"def sanitize_luxcore_name(string):\\r\\n return re.sub(\\\"[^_0-9a-zA-Z]+\\\", \\\"__\\\", string)\",\n \"def test_sanitize_name(self):\\n assert scrape_category.sanitize_name(\\\" foo \\\") == \\\"foo\\\"\\n assert scrape_category.sanitize_name(' foo\\\" ') == \\\"foo\\\"\\n assert scrape_category.sanitize_name(' foo...bar ') == \\\"foo.bar\\\"\",\n \"def _validate_names(mapping: Mapping[str, Any],\\n ref: str) -> Tuple[Set[str], List[SchemaError]]:\\n errs = [] # type: List[SchemaError]\\n\\n names = {mapping['name']}\\n\\n if 'classes' in mapping:\\n for i, obj in enumerate(mapping['classes']):\\n name = obj['name']\\n if name in names:\\n errs.append(\\n SchemaError(\\n message=\\\"Duplicate names: {!r}\\\".format(name),\\n ref=\\\"{}/classes/{}/name\\\".format(ref, i)))\\n\\n names.add(name)\\n\\n if 'embeds' in mapping:\\n for i, obj in enumerate(mapping['embeds']):\\n name = obj['name']\\n if name in names:\\n errs.append(\\n SchemaError(\\n message=\\\"Duplicate names: {!r}\\\".format(name),\\n ref=\\\"{}/embeds/{}/name\\\".format(ref, i)))\\n\\n names.add(name)\\n\\n return names, errs\",\n \"def _sanitize_to_identifer(name):\\n n = name.strip()\\n n = re.sub('/', ' ', n)\\n n = re.sub('-', ' ', n)\\n n = re.sub(' +', '_', n)\\n n = re.sub('[\\\\W]+', '', n)\\n return n\",\n \"def FilterName(namefilter, safechar='P', reserved_names=None):\\n # remove non accepted characters\\n for c in r' -[]/\\\\;,><&*:%=+@!#^|?^':\\n namefilter = namefilter.replace(c, '')\\n\\n # remove non english characters\\n char_list = (c for c in namefilter if 0 < ord(c) < 127)\\n namefilter = ''.join(char_list)\\n\\n # Make sure we have a non empty string\\n if len(namefilter) <= 0:\\n namefilter = safechar\\n\\n # Make sure we don't start with a number\\n if namefilter[0].isdigit():\\n print(namefilter)\\n namefilter = safechar + namefilter\\n\\n # Make sure we are not using a reserved name\\n if reserved_names is not None:\\n while namefilter.lower() in reserved_names:\\n namefilter = safechar + namefilter\\n\\n # Add the name to reserved names\\n reserved_names.append(namefilter)\\n\\n return namefilter\",\n \"def symbolize_sensorname(name):\\n return name.lower().replace(\\\" \\\", \\\"_\\\")\",\n \"def sanitize(name):\\n ## Disallowed characters in filenames\\n DISALLOWED_CHARS = \\\"\\\\\\\\/:<>?*|\\\"\\n if name == None:\\n name = \\\"Unknown\\\"\\n for character in DISALLOWED_CHARS:\\n name = name.replace(character,'_')\\n # Replace \\\" with '\\n name = name.replace('\\\"', \\\"'\\\")\\n\\n return name\",\n \"def test_normalize_name_bug_1762789(self):\\n name = u'Fu\\\\xdfball'\\n self.assertEqual(u'CUSTOM_FU_BALL', utils.normalize_rc_name(name))\",\n \"def normalize_name(cls, name):\\n\\t\\treturn ' '.join(name.lower().strip().split())\",\n \"def normalize_name(cls, name):\\n\\t\\treturn ' '.join(name.lower().strip().split())\",\n \"def normalize_name(cls, name):\\n\\t\\treturn ' '.join(name.lower().strip().split())\",\n \"def sanitize_name(self, value):\\n if self.sanitize_names:\\n new_value = re.sub('[^a-zA-Z0-9_]', '_', value[:127])\\n else:\\n new_value = value\\n return new_value\",\n \"def test_white_space(self):\\n with self.assertRaises(ValidationError):\\n db_name_validator('http log')\",\n \"def test_legal_names(self):\\n names = [prod.name for prod in generate_products()]\\n sep = [(name.split()[0], name.split()[1]) for name in names]\\n for name in sep:\\n self.assertIn(name[0], ADJS)\\n self.assertIn(name[1], NOUNS)\",\n \"def sanitize(name):\\n return re.sub(\\\"\\\\\\\\W|^(?=\\\\\\\\d)\\\", \\\"_\\\", name)\",\n \"def name_to_goodreads(name):\\n name = to_ascii(name.title())\\n for char in CHARS:\\n name = name.replace(*char)\\n return name\",\n \"def sanitize(name):\\n return re.sub('\\\\\\\\W|^(?=\\\\\\\\d)', '_', name)\",\n \"def python_safe_name(s):\\n no_punctuation = re.compile(r'[\\\\W_]', re.MULTILINE).sub\\n s = s.lower()\\n s = no_punctuation(' ', s)\\n s = '_'.join(s.split())\\n if py2 and isinstance(s, unicode):\\n s = s.encode('ascii', 'ignore')\\n return s\",\n \"def validName(varname):\\r\\n if (len(varname[0])>32):\\r\\n return False\\r\\n if not(varname[0][0].isalpha()):\\r\\n return False \\r\\n for ch in varname[0][1:]:\\r\\n if not(ch.isalpha() or ch.isdigit() or ch=='_'):\\r\\n return False\\r\\n \\r\\n return True\",\n \"def test_value_special_chars(self):\\n raw = [\\n 0x48,\\n 0x65,\\n 0x79,\\n 0x21,\\n 0x3F,\\n 0x24,\\n 0x20,\\n 0xC4,\\n 0xD6,\\n 0xDC,\\n 0xE4,\\n 0xF6,\\n 0xFC,\\n 0xDF,\\n ]\\n string = \\\"Hey!?$ ÄÖÜäöüß\\\"\\n self.assertEqual(DPTString.to_knx(string), raw)\\n self.assertEqual(DPTString.from_knx(raw), string)\",\n \"def isValidDataTypeName(name: unicode) -> bool:\\n ...\",\n \"def sanitize_name(name: str) -> str:\\n return re.sub(r\\\"[^A-Za-z0-9_-]\\\", \\\"-\\\", name)[0:128]\",\n \"def _convert_name(self, name):\\n if not self.re_name.match(name):\\n org_name = name\\n name = self.re_white.sub('_', name)\\n name = self.re_alpha.sub('_', name)\\n if not self.re_name.match(name):\\n name = 'x_' + name2\\n self.warn('Converting name <' + org_name + '> to <' + name + '>.')\\n return name\",\n \"def test_hyphen(self):\\n try:\\n db_name_validator('logstash-')\\n except ValidationError:\\n self.fail('Name raised ValidationError unexpectedly')\",\n \"def _database_username_validate(s):\\n if len(s) < 1 or len(s) > 63:\\n raise ValueError('Database user name must be 1 to 63 characters long')\\n if s[0] not in string.ascii_letters:\\n raise ValueError('Database user name must start with a letter')\\n allowed_characters = frozenset(string.ascii_letters + string.digits + '_')\\n if frozenset(s).issuperset(allowed_characters):\\n raise ValueError('Invalid character in database user name. Only '\\n 'numbers, letters, and _ are acceptable.')\",\n \"def normalize(s):\\n s = str(s.strip())\\n patt = re.compile(r'^\\\\?\\\\w+$')\\n if patt.match(s):\\n name = s[1:]\\n return Variable(name)\\n return s\",\n \"def __sanitize(name):\\n if name[-1] == \\\"/\\\":\\n return name[:-1]\\n return name\",\n \"def create_schema(self, schema: str):\\n return\",\n \"def clean_name(s):\\n return re.sub('[\\\\W_]+', '', s).lower()\",\n \"def normalize_reference_name(name):\\n return name.strip().lower().replace(\\\"-\\\", \\\"_\\\").replace(\\\" \\\", \\\"_\\\")\",\n \"def test_legal_names(self):\\n prods = generate_products()\\n for obj in prods:\\n self.assertRegexpMatches(\\n '(\\\\w{2,10} \\\\w{0,12}|\\\\?{0,3}){1}', obj.name)\",\n \"def validate_names(name):\\n return isinstance(name, str) and not re.search(r'[\\\\s]', name)\",\n \"def safe_formal_name(name):\\n return re.sub(r\\\"\\\\s+\\\", \\\" \\\", re.sub(r'[!/\\\\\\\\:<>\\\"\\\\?\\\\*\\\\|]', \\\"\\\", name)).strip()\",\n \"def test_special_characters_business_name(self):\\n user = \\\"chairman\\\"\\n msg = self.business_item_class.create_business(\\\"Ma@en_deleo\\\", user, \\\"soft*%ware\\\", \\\"nairo@&\\\")\\n print(msg)\\n self.assertEqual(msg, {\\\"message\\\":\\\"Business name should not contain special characters\\\"})\",\n \"def standardize_name_for_look_up(name: Any) -> str:\\n if not isinstance(name, str):\\n return name\\n\\n name = name.lower().strip()\\n name = \\\" \\\".join(name.split(\\\"_\\\"))\\n name = name.translate(\\n str.maketrans(\\\"\\\", \\\"\\\", string.punctuation)\\n ) # remove punctuation\\n name = \\\" \\\".join(\\n [part for part in name.split(\\\" \\\") if part]\\n ) # ensure there is only a single space between words\\n return name\",\n \"def test_instance_type_create_with_special_characters(self):\\n name = \\\"foo.bar!@#$%^-test_name\\\"\\n flavorid = \\\"flavor1\\\"\\n self.assertRaises(exception.InvalidInput, instance_types.create,\\n name, 256, 1, 120, 100, flavorid)\",\n \"def check_valid_key_name(name):\\n if type(name) not in [str]:\\n return False\\n bad_chars = [\\\"*\\\", \\\".\\\", \\\"&&&&\\\"]\\n for k in bad_chars:\\n if k in name:\\n return False\\n return True\",\n \"def to_safe_name(name: str) -> str:\\n return regex_replace(r'\\\\-|\\\\.|:', \\\"\\\", name.replace(' ', '_'))\",\n \"def sanitize_diagnoses(df):\\n df = df.str.replace(\\\"\\\\W\\\", \\\"\\\") # \\\"\\\\W\\\" regex represents ANY non-alphanumeric character\\n# assert (df.str.contains(\\\"\\\\W\\\")).any(), \\\"At least one diagnosis has a non-alphanumeric character in it\\\"\\n return df\",\n \"def test_nonreserved_name(self):\\n try:\\n field_name_validator('_identifier')\\n except ValidationError:\\n self.fail('Field name raised ValidationError unexpectedly')\",\n \"def normalizeName(fullName):\\n\\n fullName = fullName.lower()\\n\\n fullName = fullName.split('\\\\n')[0].strip()\\n fullName = re.sub(r'\\\\([^()]*\\\\)', '', fullName) # Remove parenthesis\\n fullName = re.sub(r\\\"\\\\'[^'']*\\\\'\\\", '', fullName) # Remove commas\\n fullName = unidecode.unidecode(fullName) # Remove diacritics\\n fullName = fullName.replace(' ', '_')\\n # Remove all non-alphanumerics characters (except _)\\n fullName = re.sub(r'\\\\W+', '', fullName)\\n fullName = re.sub(r\\\"[_]+\\\", '_', fullName)\\n return fullName\",\n \"def fromSSQL(s):\\n return s.replace('___', '.')\",\n \"def validVarConstructName(self,varname):\\r\\n if (len(varname[0])>32):\\r\\n return False, ''\\r\\n if not(varname[0][0].isalpha()):\\r\\n return False, '' \\r\\n for ch in varname[0][1:]:\\r\\n if not(ch.isalpha() or ch.isdigit() or ch=='_'):\\r\\n return False, ''\\r\\n \\r\\n return True, varname\",\n \"def _check_if_valid_dataset_name(dataset_name: str) -> str:\\n if not re.match(r\\\"^[A-Za-z0-9_]+$\\\", dataset_name):\\n raise ExecutionEngineError(\\n f\\\"dataset_name: {dataset_name} is not valid, because it contains non-alphanumeric and _ characters.\\\"\\n f\\\"Please check your configuration.\\\"\\n )\\n\\n if len(dataset_name) >= MAX_TABLE_NAME_LENGTH:\\n # starting from the end, so that we always get the index and sub_index\\n new_dataset_name = dataset_name[-MAX_TABLE_NAME_LENGTH:]\\n logger.info(\\n f\\\"dataset_name: '{dataset_name}' was truncated to '{new_dataset_name}' to keep within length limits.\\\"\\n )\\n dataset_name = new_dataset_name\\n\\n while not re.match(r\\\"^[A-Za-z]+$\\\", dataset_name[0]):\\n dataset_name = dataset_name[1:]\\n\\n return dataset_name\",\n \"def test_asterisk(self):\\n with self.assertRaises(ValidationError):\\n db_name_validator('logstash*')\",\n \"def _normalize_show_name(name):\\n\\tname = name.casefold()\\n\\tname = re.sub(\\\"[^a-z0-9]\\\", \\\" \\\", name)\\n\\tname = re.sub(\\\"_\\\", \\\" \\\", name)\\n\\tname = re.sub(\\\"season \\\\d( part \\\\d)?\\\", \\\" \\\", name)\\n\\tname = re.sub(\\\"\\\\s+\\\", \\\" \\\", name)\\n\\treturn name\",\n \"def normalize(name):\\n name = name.lower()\\n name = name.replace('-', '')\\n name = name.replace(' ', '')\\n return name\",\n \"def clean(name):\\n name = remove_extra(name)\\n name = unidecode.unidecode(name) # Remove diacritics\\n name = \\\"\\\".join(\\n list(filter(lambda c: c in (string.ascii_letters + string.digits + \\\" \\\"), name))\\n )\\n name = name.lower().strip()\\n return name\",\n \"def normalize_name(field_name):\\n fixes = (\\n (r\\\"/\\\", \\\"_per_\\\"),\\n (r\\\"%\\\", \\\"_pct_\\\"),\\n (r\\\"\\\\W\\\", \\\"_\\\"),\\n (r\\\"^_+\\\", \\\"\\\"), # remove '_' if field_name begins with '_'\\n (r\\\"_+$\\\", \\\"\\\"),\\n (r\\\"__+\\\", \\\"_\\\"),\\n )\\n result = field_name.strip().lower() or None\\n # result = field_name.strip().upper() or None\\n if result:\\n if result.endswith(\\\"?\\\"):\\n if not re.match(r\\\"is[_\\\\W]\\\", result):\\n result = \\\"is_\\\" + result\\n for pattern, replacement in fixes:\\n result = re.sub(pattern, replacement, result)\\n return result\",\n \"def clean_name(name: str) -> str:\\n if not re.match(\\\"[a-zA-Z_]\\\", name[0]):\\n name = \\\"_\\\" + name\\n name = re.sub(\\\"[^0-9a-zA-Z_]+\\\", \\\"_\\\", name)\\n if all(c == \\\"_\\\" for c in name):\\n name = \\\"v\\\"\\n return name\",\n \"def normalize_name(name):\\n return PUNCT_RE.sub('-', name.lower()).strip('-')\",\n \"def _bcl_scrub_name(name):\\n return re.sub('[^0-9a-zA-Z\\\\-\\\\_]+', '_', name)\",\n \"def adjust_name_for_printing(name):\\n if name is not None:\\n name2 = name\\n name = name.replace(\\\" \\\", \\\"_\\\").replace(\\\".\\\", \\\"_\\\").replace(\\\"-\\\", \\\"_m_\\\")\\n name = name.replace(\\\"+\\\", \\\"_p_\\\").replace(\\\"!\\\", \\\"_I_\\\")\\n name = name.replace(\\\"**\\\", \\\"_xx_\\\").replace(\\\"*\\\", \\\"_x_\\\")\\n name = name.replace(\\\"/\\\", \\\"_l_\\\").replace(\\\"@\\\", '_at_')\\n name = name.replace(\\\"(\\\", \\\"_of_\\\").replace(\\\")\\\", \\\"\\\")\\n if re.match(r'^[a-zA-Z_][a-zA-Z0-9-_]*$', name) is None:\\n raise NameError(\\\"name {} converted to {} cannot be further converted to valid python variable name!\\\".format(name2, name))\\n return name\\n return ''\",\n \"def resolver(schema):\\n name = schema.__name__\\n if name.endswith(\\\"Schema\\\"):\\n return name[:-6] or name\\n return name\",\n \"def validate_output_name(value):\\n internal_name_prefix = u'___'\\n if value.startswith(internal_name_prefix):\\n raise GraphQLCompilationError(\\n u'The prefix \\\"___\\\" (three underscores) for output names is reserved by the compiler.')\",\n \"def mangle_name(name):\\n import re\\n try:\\n return re.sub('_+','_',re.sub('[^\\\\w_]','_',name).lower()).rstrip('_')\\n except TypeError:\\n raise TypeError(\\n 'Trying to mangle name with invalid type of: ' + str(type(name)))\",\n \"def test_split_table_name(self):\\n\\n self.assertEqual(\\n {\\\"database\\\": \\\"database\\\", \\\"database_schema\\\": \\\"schema\\\", \\\"table\\\": \\\"table\\\"},\\n fqn.split_table_name(table_name=\\\"database.schema.table\\\"),\\n )\\n\\n self.assertEqual(\\n {\\\"database\\\": None, \\\"database_schema\\\": \\\"schema\\\", \\\"table\\\": \\\"table\\\"},\\n fqn.split_table_name(table_name=\\\"schema.table\\\"),\\n )\\n\\n self.assertEqual(\\n {\\\"database\\\": None, \\\"database_schema\\\": None, \\\"table\\\": \\\"table\\\"},\\n fqn.split_table_name(table_name=\\\"table\\\"),\\n )\\n\\n # We also clean quotes\\n self.assertEqual(\\n {\\\"database\\\": \\\"database\\\", \\\"database_schema\\\": \\\"schema\\\", \\\"table\\\": \\\"table\\\"},\\n fqn.split_table_name(table_name='database.\\\"schema\\\".table'),\\n )\",\n \"def to_safe(self, word):\\n return re.sub(\\\"[^A-Za-z0-9\\\\-]\\\", \\\"_\\\", word)\",\n \"def clean_strain_name(raw_name):\\n strain_name = clean_string(raw_name)\\n strain_name = strain_name.split(' Strain')[0]\\n return strain_name\",\n \"def normalize_symbol_name(symbol_name):\\n if symbol_name == \\\"\\\\\\\\frac\\\":\\n return \\\"\\\\\\\\frac{}{}\\\" # noqa\\n elif symbol_name == \\\"\\\\\\\\sqrt\\\":\\n return \\\"\\\\\\\\sqrt{}\\\" # noqa\\n elif symbol_name in [\\\"<\\\", r\\\"\\\\lt\\\"]:\\n return \\\"<\\\"\\n elif symbol_name in [\\\">\\\", r\\\"\\\\gt\\\"]:\\n return \\\">\\\"\\n elif symbol_name == \\\"{\\\":\\n return r\\\"\\\\{\\\"\\n elif symbol_name == \\\"}\\\":\\n return r\\\"\\\\}\\\"\\n return symbol_name\",\n \"def test_space_stripping(self):\\n descriptor = clone(SPECIES_OBSERVATION_SCHEMA)\\n species_name = 'Chubby Bat'\\n record = {\\n 'Observation Date': \\\"18/08/2016\\\",\\n 'Latitude': -32,\\n 'Longitude': 115,\\n 'Species Name': ' Chubby Bat '\\n }\\n schema = SpeciesObservationSchema(descriptor)\\n self.assertEqual(species_name, schema.cast_species_name(record))\",\n \"def clean_table_name(table_name):\\n path_underscore = table_name.translate(table_name.maketrans(\\\"-. \\\", \\\"___\\\"))\\n return \\\"_\\\".join(filter(None, path_underscore.split(\\\"_\\\")))\",\n \"def clean_schema(schema):\\n # type: (Dict) -> Dict\\n return {k: v for k, v in schema.items()\\n if k not in _SWAGGER_FIELDS and not k.lower().startswith(\\\"x-\\\")}\",\n \"def check_file_name_components(self):\\n illegal_characters = [\\\".\\\", \\\"-\\\", \\\" \\\"]\\n components_to_check = [self.location_id, self.dataset_name, self.qualifier, self.temporal]\\n valid = lambda component: sum([bad_char in component for bad_char in illegal_characters]) == 0\\n bad_components = [component for component in components_to_check if not valid(component)]\\n if bad_components:\\n message = f\\\"The following properties contained one or more illegal characters: \\\"\\n message += f\\\"{bad_components}\\\\n\\\"\\n message += f\\\"Illegal characters include: {illegal_characters}\\\"\\n raise DefinitionError(message)\",\n \"def _is_valid_keyspace_name(self, keyspace_name):\\n if keyspace_name == None or not keyspace_name:\\n return False\\n return re.match(r\\\"^[a-z_]*[^-]$\\\", keyspace_name)\",\n \"def normalize_const(var_name):\\n return var_name.lower().split('_')\",\n \"def alias(name):\\n name = name.strip().replace(\\\" \\\", \\\"_\\\").replace(\\\"-\\\", \\\"_\\\")\\n while \\\"__\\\" in name:\\n name = name.replace(\\\"__\\\", \\\"_\\\")\\n return \\\"\\\".join(x for x in name if x.isalnum() or x == \\\"_\\\").lower()\",\n \"def _slugify_columns(column_names):\\n\\n encoded_names = []\\n\\n for column_name in column_names:\\n slug = RE_ENCODED_COLUMN.sub('_', column_name).lower()\\n slug = make_unique(slug, encoded_names + Parser.reserved_words)\\n encoded_names.append(slug)\\n\\n return encoded_names\",\n \"def k8s_safe_name(name):\\n return name.lower().replace('_', '-')\",\n \"def _filter_hotkey_set_name(hotkey_set_name):\\n # Replace spaces with underscores\\n hotkey_set_name = hotkey_set_name.replace(' ', '_')\\n # Remove special characters\\n hotkey_set_name = ''.join(re.findall(r\\\"[_a-zA-Z0-9]+\\\", hotkey_set_name))\\n return hotkey_set_name\",\n \"def test_special_characters(self):\\n testString = sanitize('[-;]\\\\`{\\\\}')\\n self.assertEqual(testString, '_________')\",\n \"def testValidCastToStringAfterParse(self):\\n correct = 0\\n for example in VALID_EXAMPLES:\\n schema_data = schema.Parse(example.schema_string)\\n schema.Parse(str(schema_data))\\n correct += 1\\n\\n fail_msg = \\\"Cast to string success on %d out of %d schemas\\\" % \\\\\\n (correct, len(VALID_EXAMPLES))\\n self.assertEqual(correct, len(VALID_EXAMPLES), fail_msg)\",\n \"def get_names(view, sel):\\n word = view.word(sel)\\n schema = None\\n if view.substr(word.begin() - 1) == '.':\\n schema = view.substr(view.word(word.begin() - 2)).lower()\\n return schema, view.substr(word).lower()\",\n \"def standardize(self, name: str) -> str:\\n clean_name = name\\n for rule in rules.RULES:\\n clean_name = rule(clean_name)\\n return clean_name\",\n \"def test_normalize_separator(self):\\n sep = '-'\\n text = 'test'\\n expected = sep + text\\n name = self.t.normalize_name('\\\\\\\\\\\\\\\\' + text, separator=sep)\\n name2 = self.t.normalize_name('\\\\\\\\' + text, separator=sep)\\n name3 = self.t.normalize_name('/' + text, separator=sep)\\n name4 = self.t.normalize_name('//' + text, separator=sep)\\n\\n self.assertEqual(name, expected)\\n self.assertEqual(name2, expected)\\n self.assertEqual(name3, expected)\\n self.assertEqual(name4, expected)\",\n \"def cleanName(name):\\n return ''.join(char for char in name.lower() if char in (string.digits + string.ascii_lowercase))\",\n \"def sanitize_input(term: str) -> str:\\n return term.strip().replace(\\\"*\\\", \\\"\\\").replace(\\\"'\\\", \\\"\\\\\\\\'\\\").replace(\\\"~\\\", \\\"\\\")\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.61856335","0.6037464","0.6004261","0.58687896","0.58262765","0.5808754","0.5807647","0.57684666","0.5738535","0.5723603","0.57223094","0.57125217","0.56966615","0.56726086","0.5666764","0.5645181","0.56419724","0.5639399","0.5602806","0.55878466","0.55830765","0.5582149","0.5565719","0.5532494","0.55069286","0.54917175","0.5485123","0.54760677","0.5472531","0.54710674","0.54679537","0.5439834","0.5439834","0.5439834","0.5438098","0.54314345","0.5430122","0.54260045","0.5425268","0.5417487","0.5393531","0.5374802","0.5373346","0.5372704","0.53703976","0.53672147","0.5357513","0.53358257","0.5334971","0.5333481","0.5332844","0.532931","0.5328456","0.5324284","0.53228575","0.53152925","0.53136224","0.53034264","0.5301009","0.5300053","0.5279931","0.52775806","0.5276549","0.52633","0.52536327","0.5250966","0.5250361","0.5246375","0.5239893","0.52390885","0.5236872","0.52338606","0.52222997","0.52195513","0.5217444","0.52125597","0.5208949","0.52068055","0.5195162","0.5194463","0.5185539","0.5177966","0.5167446","0.51641953","0.5153396","0.5153255","0.5137325","0.5119143","0.51179844","0.5114004","0.51125866","0.5107707","0.5099931","0.50994086","0.5096194","0.5091087","0.5089908","0.5089897","0.50879693","0.507037"],"string":"[\n \"0.61856335\",\n \"0.6037464\",\n \"0.6004261\",\n \"0.58687896\",\n \"0.58262765\",\n \"0.5808754\",\n \"0.5807647\",\n \"0.57684666\",\n \"0.5738535\",\n \"0.5723603\",\n \"0.57223094\",\n \"0.57125217\",\n \"0.56966615\",\n \"0.56726086\",\n \"0.5666764\",\n \"0.5645181\",\n \"0.56419724\",\n \"0.5639399\",\n \"0.5602806\",\n \"0.55878466\",\n \"0.55830765\",\n \"0.5582149\",\n \"0.5565719\",\n \"0.5532494\",\n \"0.55069286\",\n \"0.54917175\",\n \"0.5485123\",\n \"0.54760677\",\n \"0.5472531\",\n \"0.54710674\",\n \"0.54679537\",\n \"0.5439834\",\n \"0.5439834\",\n \"0.5439834\",\n \"0.5438098\",\n \"0.54314345\",\n \"0.5430122\",\n \"0.54260045\",\n \"0.5425268\",\n \"0.5417487\",\n \"0.5393531\",\n \"0.5374802\",\n \"0.5373346\",\n \"0.5372704\",\n \"0.53703976\",\n \"0.53672147\",\n \"0.5357513\",\n \"0.53358257\",\n \"0.5334971\",\n \"0.5333481\",\n \"0.5332844\",\n \"0.532931\",\n \"0.5328456\",\n \"0.5324284\",\n \"0.53228575\",\n \"0.53152925\",\n \"0.53136224\",\n \"0.53034264\",\n \"0.5301009\",\n \"0.5300053\",\n \"0.5279931\",\n \"0.52775806\",\n \"0.5276549\",\n \"0.52633\",\n \"0.52536327\",\n \"0.5250966\",\n \"0.5250361\",\n \"0.5246375\",\n \"0.5239893\",\n \"0.52390885\",\n \"0.5236872\",\n \"0.52338606\",\n \"0.52222997\",\n \"0.52195513\",\n \"0.5217444\",\n \"0.52125597\",\n \"0.5208949\",\n \"0.52068055\",\n \"0.5195162\",\n \"0.5194463\",\n \"0.5185539\",\n \"0.5177966\",\n \"0.5167446\",\n \"0.51641953\",\n \"0.5153396\",\n \"0.5153255\",\n \"0.5137325\",\n \"0.5119143\",\n \"0.51179844\",\n \"0.5114004\",\n \"0.51125866\",\n \"0.5107707\",\n \"0.5099931\",\n \"0.50994086\",\n \"0.5096194\",\n \"0.5091087\",\n \"0.5089908\",\n \"0.5089897\",\n \"0.50879693\",\n \"0.507037\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.53094554"},"document_rank":{"kind":"string","value":"57"}}},{"rowIdx":3994,"cells":{"query":{"kind":"string","value":"Get learning rate scheduler."},"document":{"kind":"string","value":"def get_lr_scheduler(self):\n try:\n scheduler_name = self.configs.OPTIM.LR_SCHEDULER.SCHEDULER_NAME\n except AttributeError:\n scheduler_name = None\n\n if scheduler_name is None:\n lr_scheduler = None\n\n elif scheduler_name == 'plateau':\n factor = self.configs.OPTIM.LR_SCHEDULER.FACTOR\n patience = self.configs.OPTIM.LR_SCHEDULER.PATIENCE\n\n lr_scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(\n optimizer=self.optimizer,\n mode='min',\n factor=factor,\n patience=patience,\n verbose=False,\n threshold=1e-4,\n threshold_mode='rel',\n cooldown=0,\n min_lr=1e-6, # default min_lr is 0\n eps=1e-8,\n )\n\n elif scheduler_name == 'cyclic':\n base_lr = self.configs.OPTIM.LR_SCHEDULER.BASE_LR\n max_lr = self.configs.OPTIM.LR_SCHEDULER.MAX_LR\n\n lr_scheduler = torch.optim.lr_scheduler.CyclicLR(\n optimizer=self.optimizer,\n base_lr=base_lr,\n max_lr=max_lr,\n step_size_up=2000,\n step_size_down=None,\n mode='triangular',\n gamma=1.0,\n scale_fn=None,\n scale_mode='cycle',\n cycle_momentum=True,\n base_momentum=0.8,\n max_momentum=0.9,\n last_epoch=-1,\n )\n\n else:\n LOGGER.error('Invalid learning rate scheduler: %s', scheduler_name)\n raise NotImplementedError\n\n return lr_scheduler"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_scheduler(optimizer, opt):\n \n epochs_no_decay = opt.epochs - opt.lr_linear\n lr_policy = opt.lr_policy\n \n if lr_policy == 'linear':\n def lr_lambda(epoch):\n return 1. - max(0, epoch - epochs_no_decay) / float(opt.lr_linear + 1)\n scheduler = lr_scheduler.LambdaLR(optimizer, lr_lambda=lr_lambda)\n elif lr_policy == 'step':\n # multiply by gamma every lr_decay_steps\n # for example lr_decay_steps=50 and initial learning = .5\n # then we have \n # lr = .5 for 0 <= epoch < 50;\n # lr = .05 for 50 <= epoch < 100;\n # lr = .005 for 100 <= epoch < 150;\n scheduler = lr_scheduler.StepLR(optimizer, step_size=opt.lr_step, gamma=.1)\n elif lr_policy == 'plateau':\n # Reduce learning rate when a metric has stopped improving. \n # Models often benefit from reducing the learning rate by a factor of 2-10 once learning stagnates. \n # This scheduler reads a metrics quantity and if no improvement \n # is seen for a ‘patience’ number of epochs, \n # the learning rate is reduced.\n # Parameters\n # - mode (str, default=min): In `min` mode, lr will be reduced when the quantity monitored has stopped decreasing; \n # in `max` mode, lr will be reduced when the quantity monitored has stopped increasing.\n # - factor (float, default=.1): Factor by which the learning rate will be reduced. new_lr = lr * factor.\n # - patience (int, default=10): Number of epochs with no improvement after which learning rate will be reduced. \n # - threshold (float): only decrease lr if the change in the quantitiy monitored is smaller than threshold. \n # Say we have threshold=0.001, if loss is $18.0$ on epoch $n$ and loss is $17.9999$ on epoch $n+1$,\n # then multiply current learning rate by the factor.\n # On the contrary, if the loss is 17.99, lr doesn't have to be changed.\n scheduler = lr_scheduler.ReduceLROnPlateau(optimizer, mode='min', factor=.2, threshold=.01, patience=5)\n else:\n return NotImplementedError(f'learning rate policy {lr_policy} is not implemented')\n return scheduler","def get_lr(self):\n\n if self.opt is None:\n raise ValueError('No learning rate schedulers initialized')\n else:\n for pg in self.opt.param_groups:\n return pg['lr']","def get_lr(self) -> Tensor:\n\n return self.lr_scheduler.get_lr()","def get_lr_scheduler(self) -> Optional[pytorch.LRScheduler]:\n return self.lr_scheduler","def get_scheduler(optimizer, opt):\n def lambda_rule(epoch):\n lr_l = 1.0 - max(0, epoch + opt.epoch_count - opt.n_epochs) / float(opt.n_epochs_decay + 1)\n return lr_l\n scheduler = lr_scheduler.LambdaLR(optimizer, lr_lambda=lambda_rule)\n return scheduler","def init_scheduler(self):\n gamma = self.config_dict.get(\"gamma\")\n if gamma is None:\n return None\n else:\n return torch.optim.lr_scheduler.ExponentialLR(self.optimizer, gamma=gamma)","def __call__(self, epoch):\n # Compute the new dynamic learning rate, log in onto TensorBoard and\n # return the result for the training process\n learning_rate = self.schedule(epoch)\n tf.summary.scalar('learning rate', data=learning_rate, step=epoch)\n return learning_rate","def update_learning_rate(self) -> None:\n optimizer = list(self.optimizers.values())[0]\n old_lr = optimizer.param_groups[0]['lr']\n for name, scheduler in self.schedulers.items():\n if name == 'generator' and self.opt.generator_scheduler_name == 'plateau':\n scheduler.step(self.metric)\n elif name == 'discriminator' and self.opt.discriminator_scheduler_name == 'plateau':\n scheduler.step(self.metric)\n else:\n scheduler.step()\n\n lr = optimizer.param_groups[0]['lr']\n print('learning rate %.7f -> %.7f' % (old_lr, lr))\n return","def _create_learning_rate_scheduler(learning_rate_config, optimizer, last_step=-1):\n lr_scheduler = None\n learning_rate_type = learning_rate_config.name \n if learning_rate_type == 'constant_learning_rate': \n\n lr_scheduler = learning_schedules.Constant(\n optimizer, last_step=last_step)\n\n if learning_rate_type == 'exponential_decay_learning_rate':\n config = learning_rate_config \n lr_scheduler = learning_schedules.ExponentialDecay(\n optimizer, config.decay_steps, \n config.decay_factor, config.staircase, last_step=last_step)\n\n if learning_rate_type == 'manual_step_learning_rate':\n config = learning_rate_config\n if not config.schedule:\n raise ValueError('Empty learning rate schedule.')\n learning_rate_step_boundaries = [x.step for x in config.schedule]\n learning_rate_sequence = [config.initial_learning_rate]\n learning_rate_sequence += [x.learning_rate for x in config.schedule]\n lr_scheduler = learning_schedules.ManualStepping(\n optimizer, learning_rate_step_boundaries, learning_rate_sequence, \n last_step=last_step)\n\n if learning_rate_type == 'cosine_decay_learning_rate':\n config = learning_rate_config.cosine_decay_learning_rate\n lr_scheduler = learning_schedules.CosineDecayWithWarmup(\n optimizer, config.total_steps, \n config.warmup_learning_rate, config.warmup_steps, \n last_step=last_step)\n\n if lr_scheduler is None:\n raise ValueError('Learning_rate %s not supported.' % learning_rate_type)\n\n return lr_scheduler","def build_learning_rate(self):\n\n # TODO(arashwan): Explore if we want to only allow explicit const lr sched.\n if not self._lr_config:\n lr = self._optimizer_config.learning_rate\n else:\n lr = LR_CLS[self._lr_type](**self._lr_config.as_dict())\n\n if self._warmup_config:\n lr = WARMUP_CLS[self._warmup_type](lr, **self._warmup_config.as_dict())\n\n return lr","def update_learning_rate(self):\n for scheduler in self.schedulers:\n if self.opt.lr_policy == 'plateau':\n scheduler.step(self.metric)\n else:\n scheduler.step()\n\n lr = self.optimizers[0].param_groups[0]['lr']\n print('learning rate = %.7f' % lr)","def scheduler(epoch):\n return alpha / (1 + decay_rate * epoch)","def _get_lr_scheduler(project_parameters, optimizer):\n if project_parameters.lr_scheduler == 'StepLR':\n lr_scheduler = StepLR(optimizer=optimizer,\n step_size=project_parameters.step_size, gamma=project_parameters.gamma)\n elif project_parameters.lr_scheduler == 'CosineAnnealingLR':\n lr_scheduler = CosineAnnealingLR(\n optimizer=optimizer, T_max=project_parameters.step_size)\n return lr_scheduler","def _get_scheduler(\r\n self, optimizer, scheduler: str, warmup_steps: int, t_total: int):\r\n scheduler = scheduler.lower()\r\n if scheduler == 'constantlr':\r\n return transformers.get_constant_schedule(optimizer)\r\n elif scheduler == 'warmupconstant':\r\n # this uses warmup\r\n return transformers.get_constant_schedule_with_warmup(\r\n optimizer, num_warmup_steps=warmup_steps)\r\n elif scheduler == 'warmuplinear':\r\n # This uses warmup + lr-decay with t_total lr-decays\r\n # only this wrapper accepts num_trianing_steps\r\n # if you open the function get_linear_schedule_with_warmup\r\n # you will find that return\r\n # LambdaLR(optimizer, lr_lambda, last_epoch)\r\n # and last_epoch=-1. So it will end till\r\n # num_training_steps consume up\r\n # and you will see that each .step() consumes 1 training\r\n # step. You can see from\r\n # https://pytorch.org/docs/stable/optim.html\r\n # 'How to adjust Learning Rate'\r\n # When you call the step, the counter will reduce by 1,\r\n # and the learning rate will be adjusted accordingly.\r\n # Initial learning rate is given in the Optimiser.\r\n # Initially, at each step, the learning rate will be\r\n # adjusted by param_group in optimizer.param_groups:\r\n # param_group['lr'] = lr\r\n # Now it is implicitly adjusted by the scheduler\r\n return transformers.get_linear_schedule_with_warmup(\r\n optimizer, num_warmup_steps=warmup_steps,\r\n num_training_steps=t_total)\r\n elif scheduler == 'warmupcosine':\r\n return transformers.get_cosine_schedule_with_warmup(\r\n optimizer, num_warmup_steps=warmup_steps,\r\n num_training_steps=t_total)\r\n elif scheduler == 'warmupcosinewithhardrestarts':\r\n return transformers.get_cosine_with_hard_restarts_schedule_with_warmup(\r\n optimizer,\r\n num_warmup_steps=warmup_steps,\r\n num_training_steps=t_total)\r\n else:\r\n raise ValueError(\"Unknown scheduler {}\".format(scheduler))","def _create_learning_rate_scheduler(learning_rate_config, optimizer, total_step):\n lr_scheduler = None\n learning_rate_type = learning_rate_config.WhichOneof('learning_rate')\n if learning_rate_type == 'multi_phase':\n config = learning_rate_config.multi_phase\n lr_phases = []\n mom_phases = []\n for phase_cfg in config.phases:\n lr_phases.append((phase_cfg.start, phase_cfg.lambda_func))\n mom_phases.append((phase_cfg.start, phase_cfg.momentum_lambda_func))\n lr_scheduler = lsf.LRSchedulerStep(\n optimizer,total_step, lr_phases, mom_phases)\n\n if learning_rate_type == 'one_cycle':\n config = learning_rate_config.one_cycle\n lr_scheduler = lsf.OneCycle(\n optimizer, total_step, config.lr_max, list(config.moms), config.div_factor, config.pct_start)\n\n if lr_scheduler is None:\n raise ValueError('Learning_rate %s not supported.' % learning_rate_type)\n\n return lr_scheduler","def lr_schedule(epoch,lr):\r\n learning_rate = lr\r\n if epoch > 10:\r\n learning_rate *= 0.1\r\n if epoch > 20:\r\n learning_rate *= 0.1\r\n if epoch > 50:\r\n learning_rate *= 0.01\r\n\r\n # tf.summary.scalar('learning rate', data=learning_rate, step=epoch)\r\n return learning_rate","def learning_rate_fn():\n start_learning_rate = FLAGS.start_learning_rate\n step = tf.cast(tf.compat.v1.train.get_or_create_global_step(), 'float32')\n effective_step = tf.maximum(step - FLAGS.lr_decay_after_num_steps + 1, 0)\n lr_step_ratio = tf.cast(effective_step, 'float32') / float(\n FLAGS.lr_decay_steps)\n warm_up_factor = tf.cast(tf.minimum(step / float(FLAGS.warm_up_steps), 1.),\n 'float32')\n final_learning_rate = FLAGS.gpu_learning_rate\n # Ease in to final learning rate.\n lr = ((1. - warm_up_factor) * start_learning_rate) + (\n warm_up_factor * final_learning_rate)\n lr = tf.cast(lr, 'float32')\n if FLAGS.lr_decay_type == 'none' or FLAGS.lr_decay_steps <= 0:\n return lr\n elif FLAGS.lr_decay_type == 'exponential':\n return lr * 0.5**lr_step_ratio\n else:\n raise ValueError('Unknown lr_decay_type', FLAGS.lr_decay_type)","def reschedule_learning_rate(model, epoch, scheduler):\n if epoch == 7:\n optimizer = torch.optim.SGD(model.parameters(), lr=0.005)\n current_lr = next(iter(optimizer.param_groups))[\"lr\"]\n scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(\n optimizer, 6, eta_min=current_lr / 100, last_epoch=-1\n )\n if epoch == 13:\n optimizer = torch.optim.SGD(model.parameters(), lr=0.005)\n current_lr = next(iter(optimizer.param_groups))[\"lr\"]\n scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(\n optimizer, 6, eta_min=current_lr / 100, last_epoch=-1\n )\n if epoch == 19:\n optimizer = torch.optim.SGD(model.parameters(), lr=0.002)\n current_lr = next(iter(optimizer.param_groups))[\"lr\"]\n scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(\n optimizer, 6, eta_min=current_lr / 100, last_epoch=-1\n )\n if epoch == 25:\n optimizer = torch.optim.SGD(model.parameters(), lr=0.002)\n current_lr = next(iter(optimizer.param_groups))[\"lr\"]\n scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(\n optimizer, 6, eta_min=current_lr / 100, last_epoch=-1\n )\n\n return model, scheduler","def scheduler_creator(optimizer, config):\n return torch.optim.lr_scheduler.StepLR(optimizer, step_size=5, gamma=0.9)","def get_lr_scheduler(scheduler_type: str,\n updates_per_checkpoint: int,\n learning_rate_half_life: int,\n learning_rate_reduce_factor: float,\n learning_rate_reduce_num_not_improved: int) -> Optional[LearningRateScheduler]:\n if scheduler_type is None:\n return None\n if scheduler_type == \"fixed-rate-inv-sqrt-t\":\n return LearningRateSchedulerInvSqrtT(updates_per_checkpoint, learning_rate_half_life)\n elif scheduler_type == \"fixed-rate-inv-t\":\n return LearningRateSchedulerInvT(updates_per_checkpoint, learning_rate_half_life)\n elif scheduler_type == \"plateau-reduce\":\n check_condition(learning_rate_reduce_factor is not None,\n \"learning_rate_reduce_factor needed for plateau-reduce scheduler\")\n check_condition(learning_rate_reduce_num_not_improved is not None,\n \"learning_rate_reduce_num_not_improved needed for plateau-reduce scheduler\")\n if learning_rate_reduce_factor >= 1.0:\n logger.warning(\"Not using plateau-reduce learning rate scheduling: learning_rate_reduce_factor == 1.0\")\n return None\n return LearningRateSchedulerPlateauReduce(learning_rate_reduce_factor, learning_rate_reduce_num_not_improved)\n else:\n raise ValueError(\"Unknown learning rate scheduler type %s.\" % scheduler_type)","def lr_schedule(self, epoch):\n lr = self.params.learning_rate\n\n if epoch > int(self.params.num_epochs * 0.8):\n lr *= 1e-3\n elif epoch > int(self.params.num_epochs * 0.6):\n lr *= 1e-2\n elif epoch > int(self.params.num_epochs * 0.4):\n lr *= 1e-1\n print('Learning rate: ', lr)\n return lr","def scheduler(epoch_idx, lr):\n new_lr = lr\n if (epoch_idx == 60 or epoch_idx == 120 or epoch_idx == 160\n or epoch_idx == 260 or epoch_idx == 320 or epoch_idx == 360):\n new_lr *= 0.2\n \"\"\"\n if epoch_idx == 200:\n new_lr = 0.1\n \"\"\"\n return new_lr","def get_learning_rate(self):\n config = self.config\n cur_lr = Train_model_pipeline.adjust_learning_rate(\n self.optimizer,\n self.epoch,\n config[\"training\"][\"learning_rate\"],\n decay=config[\"training\"][\"lr_decay_rate\"],\n step=config[\"training\"][\"lr_decay_step\"],\n )\n self.cur_lr = cur_lr\n return cur_lr","def learning_rate_schedule(epoch):\n lr = 1.0\n\n if config[\"distributed_lr_warmup_epoch\"] > 0:\n warmup_epochs = config[\"distributed_lr_warmup_epoch\"]\n max_factor = config[\"distributed_lr_warmup_factor\"]\n factor = 1.0 + (max_factor - 1.0) * min(epoch / warmup_epochs, 1.0)\n lr *= factor\n\n for (milestone, factor) in config[\"lr_schedule_milestones\"]:\n if epoch >= milestone:\n lr *= factor\n else:\n return lr\n return lr","def create_lr_scheduler(\n self, optimizer: torch.optim.Optimizer # type: ignore\n ) -> Optional[LRScheduler]:\n pass","def learning_rate_schedule(current_epoch,\n current_batch,\n batches_per_epoch,\n batch_size):\n del current_batch, batches_per_epoch # not used\n initial_learning_rate = common.BASE_LEARNING_RATE * batch_size / 128\n learning_rate = initial_learning_rate\n for mult, start_epoch in LR_SCHEDULE:\n if current_epoch >= start_epoch:\n learning_rate = initial_learning_rate * mult\n else:\n break\n return learning_rate","def get_lr_scheduler(learning_rate, lr_refactor_step, lr_refactor_ratio,\n num_example, batch_size, begin_epoch):\n assert lr_refactor_ratio > 0\n iter_refactor = [int(r) for r in lr_refactor_step.split(',') if r.strip()]\n if lr_refactor_ratio >= 1:\n return (learning_rate, None)\n else:\n lr = learning_rate\n epoch_size = num_example // batch_size\n for s in iter_refactor:\n if begin_epoch >= s:\n lr *= lr_refactor_ratio\n if lr != learning_rate:\n pass\n # logging.getLogger().info(\"Adjusted learning rate to {} for epoch {}\".format(lr, begin_epoch))\n steps = [epoch_size * (x - begin_epoch) for x in iter_refactor if x > begin_epoch]\n if not steps:\n return (lr, None)\n lr_scheduler = mx.lr_scheduler.MultiFactorScheduler(step=steps, factor=lr_refactor_ratio)\n return (lr, lr_scheduler)","def get_scheduler(optimizer, recipe):\n\n # <optimizer>, \"stages__*__lr_scheduler\"\n return get_instance(optimizer, **recipe)","def learning_rate_scheduler(self, lr_decay_schedule, lr_decay_parameters):\n #Available learning rate decay schedules\n self.lr_decay_schedules = ['constant', 'multiplication', 'exponential', 'power']\n \n #Checks if asked schedule is implemented\n assert lr_decay_schedule in self.lr_decay_schedules, \\\n \"Learning rate schedule {0!r} not implemented. Choose one of the following: {1}\".format(\n lr_decay_schedule, self.lr_decay_schedules)\n\n assert type(lr_decay_parameters) is ListType or TupleType,\\\n \"Learning rate decay parameters must be a list or a tuple. Provided value: {0!r} and \\\n type {1!r}\".format(lr_decay_parameters, type(lr_decay_parameters))\n\n #Initial learning rate value for epoch 0.\n init_lr = lr_decay_parameters[0]\n\n assert type(init_lr) is FloatType or IntType,\\\n \"Initial learning_rate value must be float or int: {0!r}\".format(init_lr)\n\n assert init_lr >= 0, \"Initial learning_rate must be >=0: {0!r}\".format(init_lr)\n\n #Constant learning rate\n if lr_decay_schedule == self.lr_decay_schedules[0]:\n return lambda epoch: init_lr\n\n assert len(lr_decay_parameters) >= 2,\\\n \"If decay not constant at least two parameters [init learning_rate, decay rate] are\\\n expected for learning_rate_decay_parameters. Provided values: {0!r}\".format(lr_decay_parameters)\n\n #Parameter r\n decay_rate = lr_decay_parameters[1]\n\n assert type(decay_rate) is FloatType or IntType,\\\n \"Decay rate for learning rate value must be float or int: {0!r}\".format(decay_rate)\n\n assert decay_rate >= 0, \"Decay rate for learning rate must be >=0: {0!r}\".format(decay_rate)\n\n if lr_decay_schedule == self.lr_decay_schedules[1]:\n return lambda epoch: init_lr*decay_rate**epoch\n\n if lr_decay_schedule == self.lr_decay_schedules[2]:\n return lambda epoch: init_lr*10**(-epoch*1./decay_rate)\n\n if lr_decay_schedule == self.lr_decay_schedules[3]:\n assert len(lr_decay_parameters) == 3, \"For Power Scheduling 3 parameters are needed \\\n [init learning rate, r, c]: {0!r}\".format(lr_decay_parameters)\n\n c = lr_decay_parameters[2]\n assert type(c) is FloatType or IntType, \\\n \"c parameter in Power Schedule for lr must be float or int: {0!r}\".format(type(c)) \n\n assert c >=0, \"c in Power Schedule for lr must be >=0: {0!r}\".format(c)\n return lambda epoch: init_lr*(1+epoch*1./r)**-c","def GetLearnRate(DILr,Epochs):\n\n if(DILr.mode == 'poly'):\n ScheduelLr = PolynomialDecay(maxEpochs=DILr.StepSize,initAlpha=DILr.Lr,power=DILr.factor)\n ScheduelLr.plot(range(1,int(Epochs)+1))\n lrate = LearningRateScheduler(ScheduelLr)\n elif(DILr.mode == 'cycle'):\n lrate = CyclicLR(step_size=DILr.StepSize,mode=DILr.cycle,gamma=DILr.factor,base_lr=DILr.MinLr,max_lr=DILr.Lr)\n elif(DILr.mode == 'drop'):\n ScheduelLr = StepDecay(initAlpha=DILr.Lr, factor=DILr.factor, dropEvery=DILr.StepSize)\n ScheduelLr.plot(range(1,int(Epochs)+1))\n lrate = LearningRateScheduler(ScheduelLr)\n elif(DILr.mode == 'normal'):\n lrate = None\n\n return np.asarray(lrate)","def update_learning_rate(self):\n self.scheduler.step()\n lr = self.optimizer.param_groups[0]['lr']\n print('learning rate = %.7f' % lr)","def _get_scheduler(self):\n return self.__scheduler","def _get_scheduler(self):\n return self.__scheduler","def _get_scheduler(self):\n return self.__scheduler","def _get_scheduler(self):\n return self.__scheduler","def _get_scheduler(self):\n return self.__scheduler","def _get_scheduler(self):\n return self.__scheduler","def _get_scheduler(self):\n return self.__scheduler","def _get_scheduler(self):\n return self.__scheduler","def _get_scheduler(self):\n return self.__scheduler","def lr_schedule(epoch):\n lr = 1e-3\n if epoch > 30:\n lr *= 0.5e-3\n elif epoch > 25:\n lr *= 1e-3\n elif epoch > 20:\n lr *= 1e-2\n elif epoch > 10:\n lr *= 1e-1\n print('Learning rate: ', lr)\n return lr","def _learning_rate_scheduler(max_learning_rate, \n iteration, nb_iterations, nb_warmup_iterations, nb_warmdown_iterations, \n beta2):\n warmup_scaling = lax.max(0.5 * iteration * (1. - beta2), iteration / nb_warmup_iterations)\n warmdown_scaling = (nb_iterations - iteration) / nb_warmdown_iterations\n scaling = lax.min(1., lax.min(warmup_scaling, warmdown_scaling))\n return scaling * max_learning_rate","def __get_lr_at(self, epoch):\r\n if self.lr_schedule == '' or self.lr_schedule is None:\r\n return self.lr\r\n if self.lr_schedule == 'warmup':\r\n stop_epoch = max(3, int(0.03 * self.epochs))\r\n if epoch <= stop_epoch:\r\n return self.lr * (0.5 ** (stop_epoch - epoch))\r\n else:\r\n return self.lr\r\n else:\r\n return self.lr","def lr_schedule(epoch):\r\n lr = 1e-3\r\n if epoch > 180:\r\n lr *= 0.5e-3\r\n elif epoch > 160:\r\n lr *= 1e-3\r\n elif epoch > 120:\r\n lr *= 1e-2\r\n elif epoch > 80:\r\n lr *= 1e-1\r\n print('Learning rate: ', lr)\r\n return lr","def learning_rate(epoch):\n self.lr = self.lr / 1.00000001\n return self.lr","def scheduler(self):\n return self.__scheduler","def lr_schedule(epoch):\n lr = 1e-3\n if epoch > 500:\n lr *= 1e-1\n elif epoch > 800:\n lr *= 1e-2\n print('Learning rate: ', lr)\n return lr","def lr_schedule(epoch):\n lr = 0.0001\n if epoch > 40:\n lr *= 1e-2\n elif epoch > 30:\n lr *= 5e-2\n elif epoch > 20:\n lr *= 1e-1\n elif epoch > 10:\n lr *= 5e-1\n print ('Learning rate: ', lr)\n return lr","def lr_schedule(epoch):\n lr = 1e-3\n if epoch > 180:\n lr *= 0.5e-3\n elif epoch > 160:\n lr *= 1e-3\n elif epoch > 120:\n lr *= 1e-2\n elif epoch > 80:\n lr *= 1e-1\n print('Learning rate: ', lr)\n return lr","def lr_schedule(epoch):\n lr = 1e-3\n if epoch > 180:\n lr *= 0.5e-3\n elif epoch > 160:\n lr *= 1e-3\n elif epoch > 120:\n lr *= 1e-2\n elif epoch > 80:\n lr *= 1e-1\n print('Learning rate: ', lr)\n return lr","def lr_schedule(epoch):\n lr = 1e-3\n if epoch > 180:\n lr *= 0.5e-3\n elif epoch > 160:\n lr *= 1e-3\n elif epoch > 120:\n lr *= 1e-2\n elif epoch > 80:\n lr *= 1e-1\n print('Learning rate: ', lr)\n return lr","def lr_schedule(epoch):\n lr = 1e-3\n if epoch > 180:\n lr *= 0.5e-3\n elif epoch > 160:\n lr *= 1e-3\n elif epoch > 120:\n lr *= 1e-2\n elif epoch > 80:\n lr *= 1e-1\n print('Learning rate: ', lr)\n return lr","def update_learning_rate(self, validation_loss=None):\n if validation_loss is None:\n for scheduler in self.schedulers:\n scheduler.step()\n else:\n for scheduler in self.schedulers:\n scheduler.step(validation_loss)\n self.lr = self.optimizers[0].param_groups[0]['lr']\n print('learning rate = {0:.7f}'.format(self.lr))","def get_lr(self):\n # HACK: We need to check if this is the first time ``self.get_lr()`` was called,\n # since ``torch.optim.lr_scheduler._LRScheduler`` will call ``self.get_lr()``\n # when first initialized, but the learning rate should remain unchanged\n # for the first epoch.\n if not self._initialized:\n self._initialized = True\n return self.base_lrs\n\n step = self.last_epoch + 1\n self._cycle_counter = step - self._last_restart\n\n lrs = [\n self.eta_min + ((lr - self.eta_min) / 2) * (\n np.cos(\n np.pi *\n (self._cycle_counter % self._updated_cycle_len) /\n self._updated_cycle_len\n ) + 1\n )\n for lr in self.base_lrs\n ]\n\n if self._cycle_counter % self._updated_cycle_len == 0:\n # Adjust the cycle length.\n self._cycle_factor *= self.factor\n self._cycle_counter = 0\n self._updated_cycle_len = int(self._cycle_factor * self.t_max)\n self._last_restart = step\n\n return lrs","def create_lr_scheduler(lr_scheduler_name: str, optimizer: torch.optim.Optimizer,\n lr_gamma: float, max_epochs: int) -> torch.optim.lr_scheduler._LRScheduler:\n if lr_scheduler_name.lower() == \"exponential\":\n lr_scheduler = torch.optim.lr_scheduler.ExponentialLR(optimizer, lr_gamma)\n elif lr_scheduler_name.lower() == \"linear\":\n lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, lambda epoch: 1 - epoch / max_epochs)\n else:\n raise ValueError(\"SystemLog: Unknown learning rate scheduler {}\".format(lr_scheduler_name))\n\n return lr_scheduler","def get_lr(self):\n return self.optimizer.get_lr()","def get_lr(self):\n return self.optimizer.get_lr()","def scheduler(self):\n return self._scheduler","def get_lr_schedule(hparams, examples_per_epoch, replicas_to_aggregate=1):\n global_step = tf.train.get_or_create_global_step()\n steps_per_epoch = float(examples_per_epoch) / float(hparams.batch_size)\n if replicas_to_aggregate > 0:\n steps_per_epoch /= replicas_to_aggregate\n\n if hparams.lr_schedule == 'exp_decay':\n decay_steps = long(steps_per_epoch * hparams.lr_num_epochs_per_decay)\n learning_rate = tf.train.exponential_decay(\n hparams.learning_rate,\n global_step,\n decay_steps,\n hparams.lr_decay_factor,\n staircase=True)\n elif hparams.lr_schedule == 'step':\n lr_decay_steps = [long(epoch * steps_per_epoch)\n for epoch in hparams.lr_decay_epochs]\n learning_rate = tf.train.piecewise_constant(\n global_step, lr_decay_steps, hparams.lr_list)\n elif hparams.lr_schedule == 'fixed':\n learning_rate = hparams.learning_rate\n else:\n raise ValueError('Invalid value of lr_schedule: %s' % hparams.lr_schedule)\n\n if replicas_to_aggregate > 0:\n learning_rate *= replicas_to_aggregate\n\n return learning_rate, steps_per_epoch","def _initScheduler(self) -> torch.optim.lr_scheduler.ReduceLROnPlateau:\n\n return torch.optim.lr_scheduler.ReduceLROnPlateau(\n self.optimizer, \n mode=cfg.training.scheduler_mode,\n factor=cfg.training.scheduler_factor,\n patience=cfg.training.scheduler_patience,\n threshold=cfg.training.scheduler_threshold\n )","def make_lr_scheduler(lr: float, final_lr: float, n_epochs: int,\n verbose: int = 1) -> keras.callbacks.LearningRateScheduler:\n schedule = build_schedule(lr, final_lr, n_epochs)\n return LearningRateScheduler(schedule=schedule, verbose=verbose)","def get_learning_rate(training_params):\n\n initial_lr = training_params.initial_lr\n lr_decay_factor = training_params.lr_decay_factor\n lr_decay_steps_str = training_params.lr_decay_steps_str\n if lr_decay_steps_str:\n global_step = tf.train.get_or_create_global_step()\n lr_decay_steps = [int(s) for s in lr_decay_steps_str.split(\",\")]\n\n lr = tf.train.piecewise_constant(\n global_step,\n lr_decay_steps,\n [initial_lr * (lr_decay_factor ** i)\n for i in range(len(lr_decay_steps) + 1)]\n )\n else:\n lr = initial_lr\n return lr","def exp_lr_scheduler(optimizer, epoch, init_lr=0.01, lr_decay_epoch=10):\r\n lr = init_lr * (0.8**(epoch // lr_decay_epoch))\r\n print('LR is set to {}'.format(lr))\r\n for param_group in optimizer.param_groups:\r\n param_group['lr'] = lr\r\n\r\n return optimizer","def update_learning_rate(self):\r\n self.scheduler.step(self.clock.epoch)","def lr_schedule(num_epochs):\n return lambda epoch: 1.0","def get_lr(self):\n return self.call_async(0, '_async_get_lr').gen()","def exp_lr_scheduler(optimizer, epoch, init_lr=0.01, lr_decay_epoch=decay):\n lr = init_lr * (0.1**(epoch // lr_decay_epoch))\n\n if epoch % lr_decay_epoch == 0:\n print('LR is set to {}'.format(lr))\n\n for param_group in optimizer.param_groups:\n param_group['lr'] = lr\n\n return optimizer","def exp_lr_scheduler(optimizer, epoch, init_lr=0.01, lr_decay_epoch=10):\n lr = init_lr * (0.8**(epoch // lr_decay_epoch))\n print('LR is set to {}'.format(lr))\n for param_group in optimizer.param_groups:\n param_group['lr'] = lr\n\n return optimizer","def current_lr(\n self, optimizer_states: types.OptimizerStates\n ) -> tp.Optional[jnp.ndarray]:\n\n if self.lr_schedule is not None:\n step = optimizer_states[-1].count\n return self.lr_schedule(step)","def get_scheduler(optimizer: Optimizer,\n hparams: Optional[Union[HParams, Dict[str, Any]]] = None) -> \\\n Optional[_LRScheduler]:\n if hparams is None or isinstance(hparams, dict):\n hparams = HParams(hparams, default_optimization_hparams())\n\n hparams_scheduler = hparams[\"learning_rate_decay\"]\n\n scheduler_type = hparams_scheduler[\"type\"]\n if scheduler_type == \"\" or scheduler_type is None:\n scheduler = None\n else:\n if isinstance(scheduler_type, _LRScheduler):\n scheduler_class = scheduler_type\n else:\n scheduler_modules = ['torch.optim.lr_scheduler',\n 'texar.torch.custom']\n try:\n scheduler_class = utils.check_or_get_class( # type: ignore\n scheduler_type, scheduler_modules, _LRScheduler)\n except TypeError:\n raise ValueError(\n \"Unrecognized lr_scheduler. Must be string name of the \"\n \"lr_scheduler class, or the class which is a subclass of \"\n \"torch.optim._LRScheduler.\")\n\n scheduler_kwargs = hparams_scheduler[\"kwargs\"].todict()\n scheduler_kwargs.update({\"optimizer\": optimizer})\n scheduler = scheduler_class(**scheduler_kwargs) # type: ignore\n\n return scheduler","def build_lr_scheduler(optimizer: Optimizer, args: Namespace,\n total_epochs: List[int] = None) -> _LRScheduler:\n # Learning rate scheduler\n return NoamLR(\n optimizer=optimizer,\n warmup_epochs=[args.warmup_epochs],\n total_epochs=total_epochs or [args.epochs] * args.num_lrs,\n steps_per_epoch=args.train_data_size // args.batch_size,\n init_lr=[args.init_lr],\n max_lr=[args.max_lr],\n final_lr=[args.final_lr]\n )","def rnn_learning_rate_schedule(dataset):\n model, prefix = make_rnn(non_negative=True)\n # model.set_params(**{prefix + \"val\": 0.1})\n\n # base = no schedule\n print(\"Baseline RNN\")\n # model.set_params(**{prefix + \"history_file\": \"nn_default.csv\"})\n cross_validate(dataset, model)\n # model.fit(dataset.inputs, dataset.outputs)\n\n # higher init, decay set to reach the same at 40 epochs\n print(\"RNN with decay\")\n model.set_params(**{prefix + \"lr_decay\": \"DecreasingLearningRateScheduler\"})\n # model.fit(dataset.inputs, dataset.outputs)\n cross_validate(dataset, model)","def lr_scheduler(epochs):\n\n switch_points = [0, 99, 149]\n for i in [2, 1, 0]:\n if epochs >= switch_points[i]:\n return 0.001 * pow(0.1, i)","def lr_scheduler(self, lr_init, global_step):\n pass","def exp_lr_scheduler(optimizer, epoch, init_lr, lr_decay_epoch):\n\n lr = init_lr * (0.1**((epoch-1) // lr_decay_epoch))\n\n if (epoch-1) % lr_decay_epoch == 0:\n print('LR is set to {}'.format(lr))\n # log_value('lr',lr,epoch)\n\n for param_group in optimizer.param_groups:\n param_group['lr'] = lr\n\n return optimizer","def _get_scheduler_policy(self):\n return self.__scheduler_policy","def _get_scheduler_policy(self):\n return self.__scheduler_policy","def _get_scheduler_policy(self):\n return self.__scheduler_policy","def _get_scheduler_policy(self):\n return self.__scheduler_policy","def _get_scheduler_policy(self):\n return self.__scheduler_policy","def _get_scheduler_policy(self):\n return self.__scheduler_policy","def _get_scheduler_policy(self):\n return self.__scheduler_policy","def _get_scheduler_policy(self):\n return self.__scheduler_policy","def _get_scheduler_policy(self):\n return self.__scheduler_policy","def lr_scheduler(optimizer, epoch, init_lr=0.1, lr_decay_epoch=100):\r\n\r\n if epoch % lr_decay_epoch == 0 and epoch > 1:\r\n for param_group in optimizer.param_groups:\r\n param_group['lr'] = param_group['lr'] * 0.1\r\n\r\n return optimizer","def lr_scheduler(optimizer, lr_decay=0.001, epoch=None, step=1):\n if epoch is None or step == 1 or (epoch+1) % step == 0:\n for param_group in optimizer.param_groups:\n param_group['lr'] *= (1 - lr_decay)\n return optimizer","def get_last_lr(self) -> Tensor:\n\n return self.lr_scheduler.get_last_lr()","def lr_scheduler(optimizer, epoch, init_lr=0.1, lr_decay_epoch=50):\n if epoch % lr_decay_epoch == 0 and epoch > 1:\n for param_group in optimizer.param_groups:\n param_group['lr'] = param_group['lr'] * 0.1\n return optimizer","def lr_scheduler(optimizer, epoch, init_lr=0.1, lr_decay_epoch=50):\n if epoch % lr_decay_epoch == 0 and epoch > 1:\n for param_group in optimizer.param_groups:\n param_group['lr'] = param_group['lr'] * 0.1\n return optimizer","def lr(self):\n if self.T is None:\n return self.lr0\n else:\n return linear_decay(self.lr0, self.alpha, self.T, self.step)","def lr_scheduler(optimizer, epoch, init_lr=0.1, lr_decay_epoch=100):\n\n if epoch % lr_decay_epoch == 0 and epoch > 1:\n for param_group in optimizer.param_groups:\n param_group['lr'] = param_group['lr'] * 0.1\n\n return optimizer","def exp_lr_scheduler(optimizer, epoch, lr_decay_epoch=100,lr_decay_factor=0.5):\n init_lr = optimizer.param_groups[0]['lr']\n if epoch > 0 and (epoch % lr_decay_epoch == 0):\n lr = init_lr*lr_decay_factor\n print('\\n LR is set to {}'.format(lr))\n for param_group in optimizer.param_groups:\n param_group['lr'] = lr\n\n return optimizer","def lr_schedule(epoch, current_lr):\n lr = current_lr\n if epoch == 23: lr *= 0.5\n elif epoch == 21: lr *= 1e-1\n elif epoch == 16: lr *= 1e-1\n elif epoch == 11: lr *= 1e-1\n return lr","def lr_schedule(epoch):\n lr = 1e-3\n return lr","def get_learning_rate():\n return 0.00001","def build(optimizer_config, optimizer, total_step):\n optimizer_type = optimizer_config.WhichOneof('optimizer')\n\n if optimizer_type == 'rms_prop_optimizer':\n config = optimizer_config.rms_prop_optimizer\n lr_scheduler = _create_learning_rate_scheduler(\n config.learning_rate, optimizer, total_step=total_step)\n\n if optimizer_type == 'momentum_optimizer':\n config = optimizer_config.momentum_optimizer\n lr_scheduler = _create_learning_rate_scheduler(\n config.learning_rate, optimizer, total_step=total_step)\n\n if optimizer_type == 'adam_optimizer':\n config = optimizer_config.adam_optimizer\n lr_scheduler = _create_learning_rate_scheduler(\n config.learning_rate, optimizer, total_step=total_step)\n\n return lr_scheduler","def get_lr(self) -> Union[float, List[float]]:\n self._check_train_ready()\n lrs = []\n for param_group in self.optimizer.param_groups:\n lrs.append(param_group['lr'])\n if len(lrs) == 1:\n return lrs[0]\n return lrs","def adjust_learning_rate(self):\n out_base_lr = self.args.base_lr\n for param_group in self.optimizer.param_groups:\n in_lr = param_group[\"initial_lr\"]\n out_lr = in_lr\n if self.args.lr_decay_type == \"cos\": # cosine lr schedule\n out_lr *= 0.5 * (1.0 + np.cos(np.pi * self.epoch / self.args.epochs))\n else: # stepwise lr schedule\n for milestone in self.args.lr_step_schedule:\n out_lr *= 0.1 if self.epoch >= milestone else 1.0\n param_group[\"lr\"] = out_lr\n if in_lr == self.args.base_lr:\n out_base_lr = out_lr\n if self.train_logger is not None:\n self.train_logger.scalar_summary(\n \"metrics/%s/epoch\" % self.full_name, self.epoch, step=self.iteration, increment_counter=False\n )\n self.train_logger.scalar_summary(\n \"metrics/%s/lr\" % self.full_name, out_base_lr, step=self.iteration, increment_counter=False\n )\n print(\"Epoch\", self.epoch, \"Learning rate\", out_base_lr)\n return out_base_lr","def getActualLearnRate(self, epoch):\n raise NotImplementedError('getActualLearnRate')","def __learning_rate(self, lr0, epoch):\n \n \"\"\"\n Dan's Methos\n \"\"\"\n lrs = lr0 * 0.001\n c = np.power((lrs/lr0), 1.0/self.__maxEpoch)\n \n return lr0*np.power(c, epoch)"],"string":"[\n \"def get_scheduler(optimizer, opt):\\n \\n epochs_no_decay = opt.epochs - opt.lr_linear\\n lr_policy = opt.lr_policy\\n \\n if lr_policy == 'linear':\\n def lr_lambda(epoch):\\n return 1. - max(0, epoch - epochs_no_decay) / float(opt.lr_linear + 1)\\n scheduler = lr_scheduler.LambdaLR(optimizer, lr_lambda=lr_lambda)\\n elif lr_policy == 'step':\\n # multiply by gamma every lr_decay_steps\\n # for example lr_decay_steps=50 and initial learning = .5\\n # then we have \\n # lr = .5 for 0 <= epoch < 50;\\n # lr = .05 for 50 <= epoch < 100;\\n # lr = .005 for 100 <= epoch < 150;\\n scheduler = lr_scheduler.StepLR(optimizer, step_size=opt.lr_step, gamma=.1)\\n elif lr_policy == 'plateau':\\n # Reduce learning rate when a metric has stopped improving. \\n # Models often benefit from reducing the learning rate by a factor of 2-10 once learning stagnates. \\n # This scheduler reads a metrics quantity and if no improvement \\n # is seen for a ‘patience’ number of epochs, \\n # the learning rate is reduced.\\n # Parameters\\n # - mode (str, default=min): In `min` mode, lr will be reduced when the quantity monitored has stopped decreasing; \\n # in `max` mode, lr will be reduced when the quantity monitored has stopped increasing.\\n # - factor (float, default=.1): Factor by which the learning rate will be reduced. new_lr = lr * factor.\\n # - patience (int, default=10): Number of epochs with no improvement after which learning rate will be reduced. \\n # - threshold (float): only decrease lr if the change in the quantitiy monitored is smaller than threshold. \\n # Say we have threshold=0.001, if loss is $18.0$ on epoch $n$ and loss is $17.9999$ on epoch $n+1$,\\n # then multiply current learning rate by the factor.\\n # On the contrary, if the loss is 17.99, lr doesn't have to be changed.\\n scheduler = lr_scheduler.ReduceLROnPlateau(optimizer, mode='min', factor=.2, threshold=.01, patience=5)\\n else:\\n return NotImplementedError(f'learning rate policy {lr_policy} is not implemented')\\n return scheduler\",\n \"def get_lr(self):\\n\\n if self.opt is None:\\n raise ValueError('No learning rate schedulers initialized')\\n else:\\n for pg in self.opt.param_groups:\\n return pg['lr']\",\n \"def get_lr(self) -> Tensor:\\n\\n return self.lr_scheduler.get_lr()\",\n \"def get_lr_scheduler(self) -> Optional[pytorch.LRScheduler]:\\n return self.lr_scheduler\",\n \"def get_scheduler(optimizer, opt):\\n def lambda_rule(epoch):\\n lr_l = 1.0 - max(0, epoch + opt.epoch_count - opt.n_epochs) / float(opt.n_epochs_decay + 1)\\n return lr_l\\n scheduler = lr_scheduler.LambdaLR(optimizer, lr_lambda=lambda_rule)\\n return scheduler\",\n \"def init_scheduler(self):\\n gamma = self.config_dict.get(\\\"gamma\\\")\\n if gamma is None:\\n return None\\n else:\\n return torch.optim.lr_scheduler.ExponentialLR(self.optimizer, gamma=gamma)\",\n \"def __call__(self, epoch):\\n # Compute the new dynamic learning rate, log in onto TensorBoard and\\n # return the result for the training process\\n learning_rate = self.schedule(epoch)\\n tf.summary.scalar('learning rate', data=learning_rate, step=epoch)\\n return learning_rate\",\n \"def update_learning_rate(self) -> None:\\n optimizer = list(self.optimizers.values())[0]\\n old_lr = optimizer.param_groups[0]['lr']\\n for name, scheduler in self.schedulers.items():\\n if name == 'generator' and self.opt.generator_scheduler_name == 'plateau':\\n scheduler.step(self.metric)\\n elif name == 'discriminator' and self.opt.discriminator_scheduler_name == 'plateau':\\n scheduler.step(self.metric)\\n else:\\n scheduler.step()\\n\\n lr = optimizer.param_groups[0]['lr']\\n print('learning rate %.7f -> %.7f' % (old_lr, lr))\\n return\",\n \"def _create_learning_rate_scheduler(learning_rate_config, optimizer, last_step=-1):\\n lr_scheduler = None\\n learning_rate_type = learning_rate_config.name \\n if learning_rate_type == 'constant_learning_rate': \\n\\n lr_scheduler = learning_schedules.Constant(\\n optimizer, last_step=last_step)\\n\\n if learning_rate_type == 'exponential_decay_learning_rate':\\n config = learning_rate_config \\n lr_scheduler = learning_schedules.ExponentialDecay(\\n optimizer, config.decay_steps, \\n config.decay_factor, config.staircase, last_step=last_step)\\n\\n if learning_rate_type == 'manual_step_learning_rate':\\n config = learning_rate_config\\n if not config.schedule:\\n raise ValueError('Empty learning rate schedule.')\\n learning_rate_step_boundaries = [x.step for x in config.schedule]\\n learning_rate_sequence = [config.initial_learning_rate]\\n learning_rate_sequence += [x.learning_rate for x in config.schedule]\\n lr_scheduler = learning_schedules.ManualStepping(\\n optimizer, learning_rate_step_boundaries, learning_rate_sequence, \\n last_step=last_step)\\n\\n if learning_rate_type == 'cosine_decay_learning_rate':\\n config = learning_rate_config.cosine_decay_learning_rate\\n lr_scheduler = learning_schedules.CosineDecayWithWarmup(\\n optimizer, config.total_steps, \\n config.warmup_learning_rate, config.warmup_steps, \\n last_step=last_step)\\n\\n if lr_scheduler is None:\\n raise ValueError('Learning_rate %s not supported.' % learning_rate_type)\\n\\n return lr_scheduler\",\n \"def build_learning_rate(self):\\n\\n # TODO(arashwan): Explore if we want to only allow explicit const lr sched.\\n if not self._lr_config:\\n lr = self._optimizer_config.learning_rate\\n else:\\n lr = LR_CLS[self._lr_type](**self._lr_config.as_dict())\\n\\n if self._warmup_config:\\n lr = WARMUP_CLS[self._warmup_type](lr, **self._warmup_config.as_dict())\\n\\n return lr\",\n \"def update_learning_rate(self):\\n for scheduler in self.schedulers:\\n if self.opt.lr_policy == 'plateau':\\n scheduler.step(self.metric)\\n else:\\n scheduler.step()\\n\\n lr = self.optimizers[0].param_groups[0]['lr']\\n print('learning rate = %.7f' % lr)\",\n \"def scheduler(epoch):\\n return alpha / (1 + decay_rate * epoch)\",\n \"def _get_lr_scheduler(project_parameters, optimizer):\\n if project_parameters.lr_scheduler == 'StepLR':\\n lr_scheduler = StepLR(optimizer=optimizer,\\n step_size=project_parameters.step_size, gamma=project_parameters.gamma)\\n elif project_parameters.lr_scheduler == 'CosineAnnealingLR':\\n lr_scheduler = CosineAnnealingLR(\\n optimizer=optimizer, T_max=project_parameters.step_size)\\n return lr_scheduler\",\n \"def _get_scheduler(\\r\\n self, optimizer, scheduler: str, warmup_steps: int, t_total: int):\\r\\n scheduler = scheduler.lower()\\r\\n if scheduler == 'constantlr':\\r\\n return transformers.get_constant_schedule(optimizer)\\r\\n elif scheduler == 'warmupconstant':\\r\\n # this uses warmup\\r\\n return transformers.get_constant_schedule_with_warmup(\\r\\n optimizer, num_warmup_steps=warmup_steps)\\r\\n elif scheduler == 'warmuplinear':\\r\\n # This uses warmup + lr-decay with t_total lr-decays\\r\\n # only this wrapper accepts num_trianing_steps\\r\\n # if you open the function get_linear_schedule_with_warmup\\r\\n # you will find that return\\r\\n # LambdaLR(optimizer, lr_lambda, last_epoch)\\r\\n # and last_epoch=-1. So it will end till\\r\\n # num_training_steps consume up\\r\\n # and you will see that each .step() consumes 1 training\\r\\n # step. You can see from\\r\\n # https://pytorch.org/docs/stable/optim.html\\r\\n # 'How to adjust Learning Rate'\\r\\n # When you call the step, the counter will reduce by 1,\\r\\n # and the learning rate will be adjusted accordingly.\\r\\n # Initial learning rate is given in the Optimiser.\\r\\n # Initially, at each step, the learning rate will be\\r\\n # adjusted by param_group in optimizer.param_groups:\\r\\n # param_group['lr'] = lr\\r\\n # Now it is implicitly adjusted by the scheduler\\r\\n return transformers.get_linear_schedule_with_warmup(\\r\\n optimizer, num_warmup_steps=warmup_steps,\\r\\n num_training_steps=t_total)\\r\\n elif scheduler == 'warmupcosine':\\r\\n return transformers.get_cosine_schedule_with_warmup(\\r\\n optimizer, num_warmup_steps=warmup_steps,\\r\\n num_training_steps=t_total)\\r\\n elif scheduler == 'warmupcosinewithhardrestarts':\\r\\n return transformers.get_cosine_with_hard_restarts_schedule_with_warmup(\\r\\n optimizer,\\r\\n num_warmup_steps=warmup_steps,\\r\\n num_training_steps=t_total)\\r\\n else:\\r\\n raise ValueError(\\\"Unknown scheduler {}\\\".format(scheduler))\",\n \"def _create_learning_rate_scheduler(learning_rate_config, optimizer, total_step):\\n lr_scheduler = None\\n learning_rate_type = learning_rate_config.WhichOneof('learning_rate')\\n if learning_rate_type == 'multi_phase':\\n config = learning_rate_config.multi_phase\\n lr_phases = []\\n mom_phases = []\\n for phase_cfg in config.phases:\\n lr_phases.append((phase_cfg.start, phase_cfg.lambda_func))\\n mom_phases.append((phase_cfg.start, phase_cfg.momentum_lambda_func))\\n lr_scheduler = lsf.LRSchedulerStep(\\n optimizer,total_step, lr_phases, mom_phases)\\n\\n if learning_rate_type == 'one_cycle':\\n config = learning_rate_config.one_cycle\\n lr_scheduler = lsf.OneCycle(\\n optimizer, total_step, config.lr_max, list(config.moms), config.div_factor, config.pct_start)\\n\\n if lr_scheduler is None:\\n raise ValueError('Learning_rate %s not supported.' % learning_rate_type)\\n\\n return lr_scheduler\",\n \"def lr_schedule(epoch,lr):\\r\\n learning_rate = lr\\r\\n if epoch > 10:\\r\\n learning_rate *= 0.1\\r\\n if epoch > 20:\\r\\n learning_rate *= 0.1\\r\\n if epoch > 50:\\r\\n learning_rate *= 0.01\\r\\n\\r\\n # tf.summary.scalar('learning rate', data=learning_rate, step=epoch)\\r\\n return learning_rate\",\n \"def learning_rate_fn():\\n start_learning_rate = FLAGS.start_learning_rate\\n step = tf.cast(tf.compat.v1.train.get_or_create_global_step(), 'float32')\\n effective_step = tf.maximum(step - FLAGS.lr_decay_after_num_steps + 1, 0)\\n lr_step_ratio = tf.cast(effective_step, 'float32') / float(\\n FLAGS.lr_decay_steps)\\n warm_up_factor = tf.cast(tf.minimum(step / float(FLAGS.warm_up_steps), 1.),\\n 'float32')\\n final_learning_rate = FLAGS.gpu_learning_rate\\n # Ease in to final learning rate.\\n lr = ((1. - warm_up_factor) * start_learning_rate) + (\\n warm_up_factor * final_learning_rate)\\n lr = tf.cast(lr, 'float32')\\n if FLAGS.lr_decay_type == 'none' or FLAGS.lr_decay_steps <= 0:\\n return lr\\n elif FLAGS.lr_decay_type == 'exponential':\\n return lr * 0.5**lr_step_ratio\\n else:\\n raise ValueError('Unknown lr_decay_type', FLAGS.lr_decay_type)\",\n \"def reschedule_learning_rate(model, epoch, scheduler):\\n if epoch == 7:\\n optimizer = torch.optim.SGD(model.parameters(), lr=0.005)\\n current_lr = next(iter(optimizer.param_groups))[\\\"lr\\\"]\\n scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(\\n optimizer, 6, eta_min=current_lr / 100, last_epoch=-1\\n )\\n if epoch == 13:\\n optimizer = torch.optim.SGD(model.parameters(), lr=0.005)\\n current_lr = next(iter(optimizer.param_groups))[\\\"lr\\\"]\\n scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(\\n optimizer, 6, eta_min=current_lr / 100, last_epoch=-1\\n )\\n if epoch == 19:\\n optimizer = torch.optim.SGD(model.parameters(), lr=0.002)\\n current_lr = next(iter(optimizer.param_groups))[\\\"lr\\\"]\\n scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(\\n optimizer, 6, eta_min=current_lr / 100, last_epoch=-1\\n )\\n if epoch == 25:\\n optimizer = torch.optim.SGD(model.parameters(), lr=0.002)\\n current_lr = next(iter(optimizer.param_groups))[\\\"lr\\\"]\\n scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(\\n optimizer, 6, eta_min=current_lr / 100, last_epoch=-1\\n )\\n\\n return model, scheduler\",\n \"def scheduler_creator(optimizer, config):\\n return torch.optim.lr_scheduler.StepLR(optimizer, step_size=5, gamma=0.9)\",\n \"def get_lr_scheduler(scheduler_type: str,\\n updates_per_checkpoint: int,\\n learning_rate_half_life: int,\\n learning_rate_reduce_factor: float,\\n learning_rate_reduce_num_not_improved: int) -> Optional[LearningRateScheduler]:\\n if scheduler_type is None:\\n return None\\n if scheduler_type == \\\"fixed-rate-inv-sqrt-t\\\":\\n return LearningRateSchedulerInvSqrtT(updates_per_checkpoint, learning_rate_half_life)\\n elif scheduler_type == \\\"fixed-rate-inv-t\\\":\\n return LearningRateSchedulerInvT(updates_per_checkpoint, learning_rate_half_life)\\n elif scheduler_type == \\\"plateau-reduce\\\":\\n check_condition(learning_rate_reduce_factor is not None,\\n \\\"learning_rate_reduce_factor needed for plateau-reduce scheduler\\\")\\n check_condition(learning_rate_reduce_num_not_improved is not None,\\n \\\"learning_rate_reduce_num_not_improved needed for plateau-reduce scheduler\\\")\\n if learning_rate_reduce_factor >= 1.0:\\n logger.warning(\\\"Not using plateau-reduce learning rate scheduling: learning_rate_reduce_factor == 1.0\\\")\\n return None\\n return LearningRateSchedulerPlateauReduce(learning_rate_reduce_factor, learning_rate_reduce_num_not_improved)\\n else:\\n raise ValueError(\\\"Unknown learning rate scheduler type %s.\\\" % scheduler_type)\",\n \"def lr_schedule(self, epoch):\\n lr = self.params.learning_rate\\n\\n if epoch > int(self.params.num_epochs * 0.8):\\n lr *= 1e-3\\n elif epoch > int(self.params.num_epochs * 0.6):\\n lr *= 1e-2\\n elif epoch > int(self.params.num_epochs * 0.4):\\n lr *= 1e-1\\n print('Learning rate: ', lr)\\n return lr\",\n \"def scheduler(epoch_idx, lr):\\n new_lr = lr\\n if (epoch_idx == 60 or epoch_idx == 120 or epoch_idx == 160\\n or epoch_idx == 260 or epoch_idx == 320 or epoch_idx == 360):\\n new_lr *= 0.2\\n \\\"\\\"\\\"\\n if epoch_idx == 200:\\n new_lr = 0.1\\n \\\"\\\"\\\"\\n return new_lr\",\n \"def get_learning_rate(self):\\n config = self.config\\n cur_lr = Train_model_pipeline.adjust_learning_rate(\\n self.optimizer,\\n self.epoch,\\n config[\\\"training\\\"][\\\"learning_rate\\\"],\\n decay=config[\\\"training\\\"][\\\"lr_decay_rate\\\"],\\n step=config[\\\"training\\\"][\\\"lr_decay_step\\\"],\\n )\\n self.cur_lr = cur_lr\\n return cur_lr\",\n \"def learning_rate_schedule(epoch):\\n lr = 1.0\\n\\n if config[\\\"distributed_lr_warmup_epoch\\\"] > 0:\\n warmup_epochs = config[\\\"distributed_lr_warmup_epoch\\\"]\\n max_factor = config[\\\"distributed_lr_warmup_factor\\\"]\\n factor = 1.0 + (max_factor - 1.0) * min(epoch / warmup_epochs, 1.0)\\n lr *= factor\\n\\n for (milestone, factor) in config[\\\"lr_schedule_milestones\\\"]:\\n if epoch >= milestone:\\n lr *= factor\\n else:\\n return lr\\n return lr\",\n \"def create_lr_scheduler(\\n self, optimizer: torch.optim.Optimizer # type: ignore\\n ) -> Optional[LRScheduler]:\\n pass\",\n \"def learning_rate_schedule(current_epoch,\\n current_batch,\\n batches_per_epoch,\\n batch_size):\\n del current_batch, batches_per_epoch # not used\\n initial_learning_rate = common.BASE_LEARNING_RATE * batch_size / 128\\n learning_rate = initial_learning_rate\\n for mult, start_epoch in LR_SCHEDULE:\\n if current_epoch >= start_epoch:\\n learning_rate = initial_learning_rate * mult\\n else:\\n break\\n return learning_rate\",\n \"def get_lr_scheduler(learning_rate, lr_refactor_step, lr_refactor_ratio,\\n num_example, batch_size, begin_epoch):\\n assert lr_refactor_ratio > 0\\n iter_refactor = [int(r) for r in lr_refactor_step.split(',') if r.strip()]\\n if lr_refactor_ratio >= 1:\\n return (learning_rate, None)\\n else:\\n lr = learning_rate\\n epoch_size = num_example // batch_size\\n for s in iter_refactor:\\n if begin_epoch >= s:\\n lr *= lr_refactor_ratio\\n if lr != learning_rate:\\n pass\\n # logging.getLogger().info(\\\"Adjusted learning rate to {} for epoch {}\\\".format(lr, begin_epoch))\\n steps = [epoch_size * (x - begin_epoch) for x in iter_refactor if x > begin_epoch]\\n if not steps:\\n return (lr, None)\\n lr_scheduler = mx.lr_scheduler.MultiFactorScheduler(step=steps, factor=lr_refactor_ratio)\\n return (lr, lr_scheduler)\",\n \"def get_scheduler(optimizer, recipe):\\n\\n # <optimizer>, \\\"stages__*__lr_scheduler\\\"\\n return get_instance(optimizer, **recipe)\",\n \"def learning_rate_scheduler(self, lr_decay_schedule, lr_decay_parameters):\\n #Available learning rate decay schedules\\n self.lr_decay_schedules = ['constant', 'multiplication', 'exponential', 'power']\\n \\n #Checks if asked schedule is implemented\\n assert lr_decay_schedule in self.lr_decay_schedules, \\\\\\n \\\"Learning rate schedule {0!r} not implemented. Choose one of the following: {1}\\\".format(\\n lr_decay_schedule, self.lr_decay_schedules)\\n\\n assert type(lr_decay_parameters) is ListType or TupleType,\\\\\\n \\\"Learning rate decay parameters must be a list or a tuple. Provided value: {0!r} and \\\\\\n type {1!r}\\\".format(lr_decay_parameters, type(lr_decay_parameters))\\n\\n #Initial learning rate value for epoch 0.\\n init_lr = lr_decay_parameters[0]\\n\\n assert type(init_lr) is FloatType or IntType,\\\\\\n \\\"Initial learning_rate value must be float or int: {0!r}\\\".format(init_lr)\\n\\n assert init_lr >= 0, \\\"Initial learning_rate must be >=0: {0!r}\\\".format(init_lr)\\n\\n #Constant learning rate\\n if lr_decay_schedule == self.lr_decay_schedules[0]:\\n return lambda epoch: init_lr\\n\\n assert len(lr_decay_parameters) >= 2,\\\\\\n \\\"If decay not constant at least two parameters [init learning_rate, decay rate] are\\\\\\n expected for learning_rate_decay_parameters. Provided values: {0!r}\\\".format(lr_decay_parameters)\\n\\n #Parameter r\\n decay_rate = lr_decay_parameters[1]\\n\\n assert type(decay_rate) is FloatType or IntType,\\\\\\n \\\"Decay rate for learning rate value must be float or int: {0!r}\\\".format(decay_rate)\\n\\n assert decay_rate >= 0, \\\"Decay rate for learning rate must be >=0: {0!r}\\\".format(decay_rate)\\n\\n if lr_decay_schedule == self.lr_decay_schedules[1]:\\n return lambda epoch: init_lr*decay_rate**epoch\\n\\n if lr_decay_schedule == self.lr_decay_schedules[2]:\\n return lambda epoch: init_lr*10**(-epoch*1./decay_rate)\\n\\n if lr_decay_schedule == self.lr_decay_schedules[3]:\\n assert len(lr_decay_parameters) == 3, \\\"For Power Scheduling 3 parameters are needed \\\\\\n [init learning rate, r, c]: {0!r}\\\".format(lr_decay_parameters)\\n\\n c = lr_decay_parameters[2]\\n assert type(c) is FloatType or IntType, \\\\\\n \\\"c parameter in Power Schedule for lr must be float or int: {0!r}\\\".format(type(c)) \\n\\n assert c >=0, \\\"c in Power Schedule for lr must be >=0: {0!r}\\\".format(c)\\n return lambda epoch: init_lr*(1+epoch*1./r)**-c\",\n \"def GetLearnRate(DILr,Epochs):\\n\\n if(DILr.mode == 'poly'):\\n ScheduelLr = PolynomialDecay(maxEpochs=DILr.StepSize,initAlpha=DILr.Lr,power=DILr.factor)\\n ScheduelLr.plot(range(1,int(Epochs)+1))\\n lrate = LearningRateScheduler(ScheduelLr)\\n elif(DILr.mode == 'cycle'):\\n lrate = CyclicLR(step_size=DILr.StepSize,mode=DILr.cycle,gamma=DILr.factor,base_lr=DILr.MinLr,max_lr=DILr.Lr)\\n elif(DILr.mode == 'drop'):\\n ScheduelLr = StepDecay(initAlpha=DILr.Lr, factor=DILr.factor, dropEvery=DILr.StepSize)\\n ScheduelLr.plot(range(1,int(Epochs)+1))\\n lrate = LearningRateScheduler(ScheduelLr)\\n elif(DILr.mode == 'normal'):\\n lrate = None\\n\\n return np.asarray(lrate)\",\n \"def update_learning_rate(self):\\n self.scheduler.step()\\n lr = self.optimizer.param_groups[0]['lr']\\n print('learning rate = %.7f' % lr)\",\n \"def _get_scheduler(self):\\n return self.__scheduler\",\n \"def _get_scheduler(self):\\n return self.__scheduler\",\n \"def _get_scheduler(self):\\n return self.__scheduler\",\n \"def _get_scheduler(self):\\n return self.__scheduler\",\n \"def _get_scheduler(self):\\n return self.__scheduler\",\n \"def _get_scheduler(self):\\n return self.__scheduler\",\n \"def _get_scheduler(self):\\n return self.__scheduler\",\n \"def _get_scheduler(self):\\n return self.__scheduler\",\n \"def _get_scheduler(self):\\n return self.__scheduler\",\n \"def lr_schedule(epoch):\\n lr = 1e-3\\n if epoch > 30:\\n lr *= 0.5e-3\\n elif epoch > 25:\\n lr *= 1e-3\\n elif epoch > 20:\\n lr *= 1e-2\\n elif epoch > 10:\\n lr *= 1e-1\\n print('Learning rate: ', lr)\\n return lr\",\n \"def _learning_rate_scheduler(max_learning_rate, \\n iteration, nb_iterations, nb_warmup_iterations, nb_warmdown_iterations, \\n beta2):\\n warmup_scaling = lax.max(0.5 * iteration * (1. - beta2), iteration / nb_warmup_iterations)\\n warmdown_scaling = (nb_iterations - iteration) / nb_warmdown_iterations\\n scaling = lax.min(1., lax.min(warmup_scaling, warmdown_scaling))\\n return scaling * max_learning_rate\",\n \"def __get_lr_at(self, epoch):\\r\\n if self.lr_schedule == '' or self.lr_schedule is None:\\r\\n return self.lr\\r\\n if self.lr_schedule == 'warmup':\\r\\n stop_epoch = max(3, int(0.03 * self.epochs))\\r\\n if epoch <= stop_epoch:\\r\\n return self.lr * (0.5 ** (stop_epoch - epoch))\\r\\n else:\\r\\n return self.lr\\r\\n else:\\r\\n return self.lr\",\n \"def lr_schedule(epoch):\\r\\n lr = 1e-3\\r\\n if epoch > 180:\\r\\n lr *= 0.5e-3\\r\\n elif epoch > 160:\\r\\n lr *= 1e-3\\r\\n elif epoch > 120:\\r\\n lr *= 1e-2\\r\\n elif epoch > 80:\\r\\n lr *= 1e-1\\r\\n print('Learning rate: ', lr)\\r\\n return lr\",\n \"def learning_rate(epoch):\\n self.lr = self.lr / 1.00000001\\n return self.lr\",\n \"def scheduler(self):\\n return self.__scheduler\",\n \"def lr_schedule(epoch):\\n lr = 1e-3\\n if epoch > 500:\\n lr *= 1e-1\\n elif epoch > 800:\\n lr *= 1e-2\\n print('Learning rate: ', lr)\\n return lr\",\n \"def lr_schedule(epoch):\\n lr = 0.0001\\n if epoch > 40:\\n lr *= 1e-2\\n elif epoch > 30:\\n lr *= 5e-2\\n elif epoch > 20:\\n lr *= 1e-1\\n elif epoch > 10:\\n lr *= 5e-1\\n print ('Learning rate: ', lr)\\n return lr\",\n \"def lr_schedule(epoch):\\n lr = 1e-3\\n if epoch > 180:\\n lr *= 0.5e-3\\n elif epoch > 160:\\n lr *= 1e-3\\n elif epoch > 120:\\n lr *= 1e-2\\n elif epoch > 80:\\n lr *= 1e-1\\n print('Learning rate: ', lr)\\n return lr\",\n \"def lr_schedule(epoch):\\n lr = 1e-3\\n if epoch > 180:\\n lr *= 0.5e-3\\n elif epoch > 160:\\n lr *= 1e-3\\n elif epoch > 120:\\n lr *= 1e-2\\n elif epoch > 80:\\n lr *= 1e-1\\n print('Learning rate: ', lr)\\n return lr\",\n \"def lr_schedule(epoch):\\n lr = 1e-3\\n if epoch > 180:\\n lr *= 0.5e-3\\n elif epoch > 160:\\n lr *= 1e-3\\n elif epoch > 120:\\n lr *= 1e-2\\n elif epoch > 80:\\n lr *= 1e-1\\n print('Learning rate: ', lr)\\n return lr\",\n \"def lr_schedule(epoch):\\n lr = 1e-3\\n if epoch > 180:\\n lr *= 0.5e-3\\n elif epoch > 160:\\n lr *= 1e-3\\n elif epoch > 120:\\n lr *= 1e-2\\n elif epoch > 80:\\n lr *= 1e-1\\n print('Learning rate: ', lr)\\n return lr\",\n \"def update_learning_rate(self, validation_loss=None):\\n if validation_loss is None:\\n for scheduler in self.schedulers:\\n scheduler.step()\\n else:\\n for scheduler in self.schedulers:\\n scheduler.step(validation_loss)\\n self.lr = self.optimizers[0].param_groups[0]['lr']\\n print('learning rate = {0:.7f}'.format(self.lr))\",\n \"def get_lr(self):\\n # HACK: We need to check if this is the first time ``self.get_lr()`` was called,\\n # since ``torch.optim.lr_scheduler._LRScheduler`` will call ``self.get_lr()``\\n # when first initialized, but the learning rate should remain unchanged\\n # for the first epoch.\\n if not self._initialized:\\n self._initialized = True\\n return self.base_lrs\\n\\n step = self.last_epoch + 1\\n self._cycle_counter = step - self._last_restart\\n\\n lrs = [\\n self.eta_min + ((lr - self.eta_min) / 2) * (\\n np.cos(\\n np.pi *\\n (self._cycle_counter % self._updated_cycle_len) /\\n self._updated_cycle_len\\n ) + 1\\n )\\n for lr in self.base_lrs\\n ]\\n\\n if self._cycle_counter % self._updated_cycle_len == 0:\\n # Adjust the cycle length.\\n self._cycle_factor *= self.factor\\n self._cycle_counter = 0\\n self._updated_cycle_len = int(self._cycle_factor * self.t_max)\\n self._last_restart = step\\n\\n return lrs\",\n \"def create_lr_scheduler(lr_scheduler_name: str, optimizer: torch.optim.Optimizer,\\n lr_gamma: float, max_epochs: int) -> torch.optim.lr_scheduler._LRScheduler:\\n if lr_scheduler_name.lower() == \\\"exponential\\\":\\n lr_scheduler = torch.optim.lr_scheduler.ExponentialLR(optimizer, lr_gamma)\\n elif lr_scheduler_name.lower() == \\\"linear\\\":\\n lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer, lambda epoch: 1 - epoch / max_epochs)\\n else:\\n raise ValueError(\\\"SystemLog: Unknown learning rate scheduler {}\\\".format(lr_scheduler_name))\\n\\n return lr_scheduler\",\n \"def get_lr(self):\\n return self.optimizer.get_lr()\",\n \"def get_lr(self):\\n return self.optimizer.get_lr()\",\n \"def scheduler(self):\\n return self._scheduler\",\n \"def get_lr_schedule(hparams, examples_per_epoch, replicas_to_aggregate=1):\\n global_step = tf.train.get_or_create_global_step()\\n steps_per_epoch = float(examples_per_epoch) / float(hparams.batch_size)\\n if replicas_to_aggregate > 0:\\n steps_per_epoch /= replicas_to_aggregate\\n\\n if hparams.lr_schedule == 'exp_decay':\\n decay_steps = long(steps_per_epoch * hparams.lr_num_epochs_per_decay)\\n learning_rate = tf.train.exponential_decay(\\n hparams.learning_rate,\\n global_step,\\n decay_steps,\\n hparams.lr_decay_factor,\\n staircase=True)\\n elif hparams.lr_schedule == 'step':\\n lr_decay_steps = [long(epoch * steps_per_epoch)\\n for epoch in hparams.lr_decay_epochs]\\n learning_rate = tf.train.piecewise_constant(\\n global_step, lr_decay_steps, hparams.lr_list)\\n elif hparams.lr_schedule == 'fixed':\\n learning_rate = hparams.learning_rate\\n else:\\n raise ValueError('Invalid value of lr_schedule: %s' % hparams.lr_schedule)\\n\\n if replicas_to_aggregate > 0:\\n learning_rate *= replicas_to_aggregate\\n\\n return learning_rate, steps_per_epoch\",\n \"def _initScheduler(self) -> torch.optim.lr_scheduler.ReduceLROnPlateau:\\n\\n return torch.optim.lr_scheduler.ReduceLROnPlateau(\\n self.optimizer, \\n mode=cfg.training.scheduler_mode,\\n factor=cfg.training.scheduler_factor,\\n patience=cfg.training.scheduler_patience,\\n threshold=cfg.training.scheduler_threshold\\n )\",\n \"def make_lr_scheduler(lr: float, final_lr: float, n_epochs: int,\\n verbose: int = 1) -> keras.callbacks.LearningRateScheduler:\\n schedule = build_schedule(lr, final_lr, n_epochs)\\n return LearningRateScheduler(schedule=schedule, verbose=verbose)\",\n \"def get_learning_rate(training_params):\\n\\n initial_lr = training_params.initial_lr\\n lr_decay_factor = training_params.lr_decay_factor\\n lr_decay_steps_str = training_params.lr_decay_steps_str\\n if lr_decay_steps_str:\\n global_step = tf.train.get_or_create_global_step()\\n lr_decay_steps = [int(s) for s in lr_decay_steps_str.split(\\\",\\\")]\\n\\n lr = tf.train.piecewise_constant(\\n global_step,\\n lr_decay_steps,\\n [initial_lr * (lr_decay_factor ** i)\\n for i in range(len(lr_decay_steps) + 1)]\\n )\\n else:\\n lr = initial_lr\\n return lr\",\n \"def exp_lr_scheduler(optimizer, epoch, init_lr=0.01, lr_decay_epoch=10):\\r\\n lr = init_lr * (0.8**(epoch // lr_decay_epoch))\\r\\n print('LR is set to {}'.format(lr))\\r\\n for param_group in optimizer.param_groups:\\r\\n param_group['lr'] = lr\\r\\n\\r\\n return optimizer\",\n \"def update_learning_rate(self):\\r\\n self.scheduler.step(self.clock.epoch)\",\n \"def lr_schedule(num_epochs):\\n return lambda epoch: 1.0\",\n \"def get_lr(self):\\n return self.call_async(0, '_async_get_lr').gen()\",\n \"def exp_lr_scheduler(optimizer, epoch, init_lr=0.01, lr_decay_epoch=decay):\\n lr = init_lr * (0.1**(epoch // lr_decay_epoch))\\n\\n if epoch % lr_decay_epoch == 0:\\n print('LR is set to {}'.format(lr))\\n\\n for param_group in optimizer.param_groups:\\n param_group['lr'] = lr\\n\\n return optimizer\",\n \"def exp_lr_scheduler(optimizer, epoch, init_lr=0.01, lr_decay_epoch=10):\\n lr = init_lr * (0.8**(epoch // lr_decay_epoch))\\n print('LR is set to {}'.format(lr))\\n for param_group in optimizer.param_groups:\\n param_group['lr'] = lr\\n\\n return optimizer\",\n \"def current_lr(\\n self, optimizer_states: types.OptimizerStates\\n ) -> tp.Optional[jnp.ndarray]:\\n\\n if self.lr_schedule is not None:\\n step = optimizer_states[-1].count\\n return self.lr_schedule(step)\",\n \"def get_scheduler(optimizer: Optimizer,\\n hparams: Optional[Union[HParams, Dict[str, Any]]] = None) -> \\\\\\n Optional[_LRScheduler]:\\n if hparams is None or isinstance(hparams, dict):\\n hparams = HParams(hparams, default_optimization_hparams())\\n\\n hparams_scheduler = hparams[\\\"learning_rate_decay\\\"]\\n\\n scheduler_type = hparams_scheduler[\\\"type\\\"]\\n if scheduler_type == \\\"\\\" or scheduler_type is None:\\n scheduler = None\\n else:\\n if isinstance(scheduler_type, _LRScheduler):\\n scheduler_class = scheduler_type\\n else:\\n scheduler_modules = ['torch.optim.lr_scheduler',\\n 'texar.torch.custom']\\n try:\\n scheduler_class = utils.check_or_get_class( # type: ignore\\n scheduler_type, scheduler_modules, _LRScheduler)\\n except TypeError:\\n raise ValueError(\\n \\\"Unrecognized lr_scheduler. Must be string name of the \\\"\\n \\\"lr_scheduler class, or the class which is a subclass of \\\"\\n \\\"torch.optim._LRScheduler.\\\")\\n\\n scheduler_kwargs = hparams_scheduler[\\\"kwargs\\\"].todict()\\n scheduler_kwargs.update({\\\"optimizer\\\": optimizer})\\n scheduler = scheduler_class(**scheduler_kwargs) # type: ignore\\n\\n return scheduler\",\n \"def build_lr_scheduler(optimizer: Optimizer, args: Namespace,\\n total_epochs: List[int] = None) -> _LRScheduler:\\n # Learning rate scheduler\\n return NoamLR(\\n optimizer=optimizer,\\n warmup_epochs=[args.warmup_epochs],\\n total_epochs=total_epochs or [args.epochs] * args.num_lrs,\\n steps_per_epoch=args.train_data_size // args.batch_size,\\n init_lr=[args.init_lr],\\n max_lr=[args.max_lr],\\n final_lr=[args.final_lr]\\n )\",\n \"def rnn_learning_rate_schedule(dataset):\\n model, prefix = make_rnn(non_negative=True)\\n # model.set_params(**{prefix + \\\"val\\\": 0.1})\\n\\n # base = no schedule\\n print(\\\"Baseline RNN\\\")\\n # model.set_params(**{prefix + \\\"history_file\\\": \\\"nn_default.csv\\\"})\\n cross_validate(dataset, model)\\n # model.fit(dataset.inputs, dataset.outputs)\\n\\n # higher init, decay set to reach the same at 40 epochs\\n print(\\\"RNN with decay\\\")\\n model.set_params(**{prefix + \\\"lr_decay\\\": \\\"DecreasingLearningRateScheduler\\\"})\\n # model.fit(dataset.inputs, dataset.outputs)\\n cross_validate(dataset, model)\",\n \"def lr_scheduler(epochs):\\n\\n switch_points = [0, 99, 149]\\n for i in [2, 1, 0]:\\n if epochs >= switch_points[i]:\\n return 0.001 * pow(0.1, i)\",\n \"def lr_scheduler(self, lr_init, global_step):\\n pass\",\n \"def exp_lr_scheduler(optimizer, epoch, init_lr, lr_decay_epoch):\\n\\n lr = init_lr * (0.1**((epoch-1) // lr_decay_epoch))\\n\\n if (epoch-1) % lr_decay_epoch == 0:\\n print('LR is set to {}'.format(lr))\\n # log_value('lr',lr,epoch)\\n\\n for param_group in optimizer.param_groups:\\n param_group['lr'] = lr\\n\\n return optimizer\",\n \"def _get_scheduler_policy(self):\\n return self.__scheduler_policy\",\n \"def _get_scheduler_policy(self):\\n return self.__scheduler_policy\",\n \"def _get_scheduler_policy(self):\\n return self.__scheduler_policy\",\n \"def _get_scheduler_policy(self):\\n return self.__scheduler_policy\",\n \"def _get_scheduler_policy(self):\\n return self.__scheduler_policy\",\n \"def _get_scheduler_policy(self):\\n return self.__scheduler_policy\",\n \"def _get_scheduler_policy(self):\\n return self.__scheduler_policy\",\n \"def _get_scheduler_policy(self):\\n return self.__scheduler_policy\",\n \"def _get_scheduler_policy(self):\\n return self.__scheduler_policy\",\n \"def lr_scheduler(optimizer, epoch, init_lr=0.1, lr_decay_epoch=100):\\r\\n\\r\\n if epoch % lr_decay_epoch == 0 and epoch > 1:\\r\\n for param_group in optimizer.param_groups:\\r\\n param_group['lr'] = param_group['lr'] * 0.1\\r\\n\\r\\n return optimizer\",\n \"def lr_scheduler(optimizer, lr_decay=0.001, epoch=None, step=1):\\n if epoch is None or step == 1 or (epoch+1) % step == 0:\\n for param_group in optimizer.param_groups:\\n param_group['lr'] *= (1 - lr_decay)\\n return optimizer\",\n \"def get_last_lr(self) -> Tensor:\\n\\n return self.lr_scheduler.get_last_lr()\",\n \"def lr_scheduler(optimizer, epoch, init_lr=0.1, lr_decay_epoch=50):\\n if epoch % lr_decay_epoch == 0 and epoch > 1:\\n for param_group in optimizer.param_groups:\\n param_group['lr'] = param_group['lr'] * 0.1\\n return optimizer\",\n \"def lr_scheduler(optimizer, epoch, init_lr=0.1, lr_decay_epoch=50):\\n if epoch % lr_decay_epoch == 0 and epoch > 1:\\n for param_group in optimizer.param_groups:\\n param_group['lr'] = param_group['lr'] * 0.1\\n return optimizer\",\n \"def lr(self):\\n if self.T is None:\\n return self.lr0\\n else:\\n return linear_decay(self.lr0, self.alpha, self.T, self.step)\",\n \"def lr_scheduler(optimizer, epoch, init_lr=0.1, lr_decay_epoch=100):\\n\\n if epoch % lr_decay_epoch == 0 and epoch > 1:\\n for param_group in optimizer.param_groups:\\n param_group['lr'] = param_group['lr'] * 0.1\\n\\n return optimizer\",\n \"def exp_lr_scheduler(optimizer, epoch, lr_decay_epoch=100,lr_decay_factor=0.5):\\n init_lr = optimizer.param_groups[0]['lr']\\n if epoch > 0 and (epoch % lr_decay_epoch == 0):\\n lr = init_lr*lr_decay_factor\\n print('\\\\n LR is set to {}'.format(lr))\\n for param_group in optimizer.param_groups:\\n param_group['lr'] = lr\\n\\n return optimizer\",\n \"def lr_schedule(epoch, current_lr):\\n lr = current_lr\\n if epoch == 23: lr *= 0.5\\n elif epoch == 21: lr *= 1e-1\\n elif epoch == 16: lr *= 1e-1\\n elif epoch == 11: lr *= 1e-1\\n return lr\",\n \"def lr_schedule(epoch):\\n lr = 1e-3\\n return lr\",\n \"def get_learning_rate():\\n return 0.00001\",\n \"def build(optimizer_config, optimizer, total_step):\\n optimizer_type = optimizer_config.WhichOneof('optimizer')\\n\\n if optimizer_type == 'rms_prop_optimizer':\\n config = optimizer_config.rms_prop_optimizer\\n lr_scheduler = _create_learning_rate_scheduler(\\n config.learning_rate, optimizer, total_step=total_step)\\n\\n if optimizer_type == 'momentum_optimizer':\\n config = optimizer_config.momentum_optimizer\\n lr_scheduler = _create_learning_rate_scheduler(\\n config.learning_rate, optimizer, total_step=total_step)\\n\\n if optimizer_type == 'adam_optimizer':\\n config = optimizer_config.adam_optimizer\\n lr_scheduler = _create_learning_rate_scheduler(\\n config.learning_rate, optimizer, total_step=total_step)\\n\\n return lr_scheduler\",\n \"def get_lr(self) -> Union[float, List[float]]:\\n self._check_train_ready()\\n lrs = []\\n for param_group in self.optimizer.param_groups:\\n lrs.append(param_group['lr'])\\n if len(lrs) == 1:\\n return lrs[0]\\n return lrs\",\n \"def adjust_learning_rate(self):\\n out_base_lr = self.args.base_lr\\n for param_group in self.optimizer.param_groups:\\n in_lr = param_group[\\\"initial_lr\\\"]\\n out_lr = in_lr\\n if self.args.lr_decay_type == \\\"cos\\\": # cosine lr schedule\\n out_lr *= 0.5 * (1.0 + np.cos(np.pi * self.epoch / self.args.epochs))\\n else: # stepwise lr schedule\\n for milestone in self.args.lr_step_schedule:\\n out_lr *= 0.1 if self.epoch >= milestone else 1.0\\n param_group[\\\"lr\\\"] = out_lr\\n if in_lr == self.args.base_lr:\\n out_base_lr = out_lr\\n if self.train_logger is not None:\\n self.train_logger.scalar_summary(\\n \\\"metrics/%s/epoch\\\" % self.full_name, self.epoch, step=self.iteration, increment_counter=False\\n )\\n self.train_logger.scalar_summary(\\n \\\"metrics/%s/lr\\\" % self.full_name, out_base_lr, step=self.iteration, increment_counter=False\\n )\\n print(\\\"Epoch\\\", self.epoch, \\\"Learning rate\\\", out_base_lr)\\n return out_base_lr\",\n \"def getActualLearnRate(self, epoch):\\n raise NotImplementedError('getActualLearnRate')\",\n \"def __learning_rate(self, lr0, epoch):\\n \\n \\\"\\\"\\\"\\n Dan's Methos\\n \\\"\\\"\\\"\\n lrs = lr0 * 0.001\\n c = np.power((lrs/lr0), 1.0/self.__maxEpoch)\\n \\n return lr0*np.power(c, epoch)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7635437","0.75883573","0.75060844","0.7453083","0.73677176","0.7187605","0.7152048","0.71470124","0.7139361","0.70922357","0.7084877","0.7058236","0.70532143","0.70265824","0.70135325","0.70125854","0.69860375","0.6956636","0.6950861","0.6934655","0.69265467","0.6899729","0.6876515","0.6805529","0.67600197","0.673775","0.6707196","0.66615224","0.66552997","0.6638318","0.6632102","0.66309977","0.66309977","0.66309977","0.66309977","0.66309977","0.66309977","0.66309977","0.66309977","0.66309977","0.6614746","0.66104895","0.66040635","0.6588716","0.6588259","0.65722644","0.6571075","0.6568491","0.65462774","0.65462774","0.65462774","0.65462774","0.65375435","0.6526492","0.65107375","0.6490373","0.6490373","0.648999","0.64655733","0.6460565","0.64338493","0.6422422","0.64187086","0.6401879","0.6401489","0.6397217","0.63971174","0.6395142","0.6385191","0.6382054","0.6380572","0.63779163","0.6375288","0.6374936","0.63498634","0.6346249","0.6346249","0.6346249","0.6346249","0.6346249","0.6346249","0.6346249","0.6346249","0.6346249","0.6345868","0.63455296","0.63339454","0.6319677","0.6319677","0.6310527","0.6297556","0.62837756","0.62802786","0.6263751","0.6255777","0.6249011","0.6200415","0.61991906","0.61895823","0.6170722"],"string":"[\n \"0.7635437\",\n \"0.75883573\",\n \"0.75060844\",\n \"0.7453083\",\n \"0.73677176\",\n \"0.7187605\",\n \"0.7152048\",\n \"0.71470124\",\n \"0.7139361\",\n \"0.70922357\",\n \"0.7084877\",\n \"0.7058236\",\n \"0.70532143\",\n \"0.70265824\",\n \"0.70135325\",\n \"0.70125854\",\n \"0.69860375\",\n \"0.6956636\",\n \"0.6950861\",\n \"0.6934655\",\n \"0.69265467\",\n \"0.6899729\",\n \"0.6876515\",\n \"0.6805529\",\n \"0.67600197\",\n \"0.673775\",\n \"0.6707196\",\n \"0.66615224\",\n \"0.66552997\",\n \"0.6638318\",\n \"0.6632102\",\n \"0.66309977\",\n \"0.66309977\",\n \"0.66309977\",\n \"0.66309977\",\n \"0.66309977\",\n \"0.66309977\",\n \"0.66309977\",\n \"0.66309977\",\n \"0.66309977\",\n \"0.6614746\",\n \"0.66104895\",\n \"0.66040635\",\n \"0.6588716\",\n \"0.6588259\",\n \"0.65722644\",\n \"0.6571075\",\n \"0.6568491\",\n \"0.65462774\",\n \"0.65462774\",\n \"0.65462774\",\n \"0.65462774\",\n \"0.65375435\",\n \"0.6526492\",\n \"0.65107375\",\n \"0.6490373\",\n \"0.6490373\",\n \"0.648999\",\n \"0.64655733\",\n \"0.6460565\",\n \"0.64338493\",\n \"0.6422422\",\n \"0.64187086\",\n \"0.6401879\",\n \"0.6401489\",\n \"0.6397217\",\n \"0.63971174\",\n \"0.6395142\",\n \"0.6385191\",\n \"0.6382054\",\n \"0.6380572\",\n \"0.63779163\",\n \"0.6375288\",\n \"0.6374936\",\n \"0.63498634\",\n \"0.6346249\",\n \"0.6346249\",\n \"0.6346249\",\n \"0.6346249\",\n \"0.6346249\",\n \"0.6346249\",\n \"0.6346249\",\n \"0.6346249\",\n \"0.6346249\",\n \"0.6345868\",\n \"0.63455296\",\n \"0.63339454\",\n \"0.6319677\",\n \"0.6319677\",\n \"0.6310527\",\n \"0.6297556\",\n \"0.62837756\",\n \"0.62802786\",\n \"0.6263751\",\n \"0.6255777\",\n \"0.6249011\",\n \"0.6200415\",\n \"0.61991906\",\n \"0.61895823\",\n \"0.6170722\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7616563"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":3995,"cells":{"query":{"kind":"string","value":"Return list of unique values while preserving order. Values must be hashable."},"document":{"kind":"string","value":"def uniq(seq: Iterable):\n seen, result = {}, []\n for item in seq:\n if item in seen:\n continue\n seen[item] = None\n result.append(item)\n return result"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_unique_value_list(value):\n my_set = set(value)\n new_list = list(my_set)\n new_list.sort()\n return new_list","def unique(x):\n\n return list(set(x))","def find_remove_duplicates(list_of_values):\r\n output = []\r\n seen = set()\r\n for value in list_of_values:\r\n if value not in seen:\r\n output.append(value)\r\n seen.add(value)\r\n return output","def _unique(li):\n return list(set(li))","def delDoublon(values):\n\treturn list(set(values))","def nunique(self, values):\n return self.aggregate(values, \"nunique\")","def uniq(val, key=None):\n if not isinstance(val, list):\n return val\n if key is None:\n try:\n return list(set(val))\n except TypeError:\n pass\n keys = []\n values = []\n for value in val:\n try:\n thiskey = value[key]\n except:\n thiskey = repr(value)\n if thiskey not in keys:\n keys.append(thiskey)\n values.append(value)\n return values","def unique_values(array: Iterable[T], key: Callable[[T], Union[str, int, float]]=None) -> List[T]:\n values = set()\n unique_array = []\n\n if key is None:\n for v in array:\n if v not in values:\n unique_array.append(v)\n values.add(v)\n else:\n for v in array:\n v_key = key(v)\n if v_key not in values:\n unique_array.append(v)\n values.add(v_key)\n\n return unique_array","def unique_ordered(seq):\n\tvals = set()\n\treturn [x for x in seq if not (x in vals or vals.add(x))]","def distinct(x):\n return list(set(x))","def unique(li):\r\n seen = set()\r\n seen_add = seen.add\r\n return [x for x in li if not (x in seen or seen_add(x))]","def unique(self):\n return self.element_wise(lambda seqs: list(set(seqs)))","def unique(self, key, lst=None):\n d = self.find(key, lst)\n vals = set(d.values())\n return sorted(list(vals))","def unique(seq):\n return list(set(seq))","def unique(self) -> 'List':\n return List(sorted(set(self), key=self.index))","def unique(self):\n return frozenset(self)","def unique_values(self):\n for key in self.metadb.unique_values():\n yield key, self.datadb[key]","def unique(list_: List) -> List:\n return list(collections.OrderedDict.fromkeys(list_))","def list_unique_values(series: pd.Series) -> str:\n return \", \".join(set(str(v) for v in pd.Series.unique(series)))","def unique_list(src_list):\n return list(OrderedDict.fromkeys(src_list).keys())","def _unique(iterable):\n return list(dict.fromkeys(iterable))","def remove_duplicates(possible_vulns):\n return list(set(possible_vulns))","def _unique_sorted(seq):\n seen = set()\n seen_add = seen.add\n return [x for x in seq if not (x in seen or seen_add(x))]","def _uniq(self, lst):\n h = {}\n for e in lst:\n h[e] = 1\n return sorted(h.keys())","def uniq(elements):\n us = set()\n ret = []\n for e in elements:\n if e not in us:\n ret.append(e)\n us.add(e)\n return ret","def keys_sorted_by_value_unique(d, **sort_kwargs):\n values = d.values()\n values.sort(**sort_kwargs)\n i = inverse(d)\n return [i[val] for val in values]","def flat_unique(ls):\n return list(unique(chain.from_iterable(ls), key=id))","def unique(lis):\n seen = set()\n ret = []\n for elm in lis:\n if elm not in seen:\n ret.append(elm)\n seen.add(elm)\n return ret","def uniquify(seq):\n seen = set()\n seen_add = seen.add\n return [ x for x in seq if x not in seen and not seen_add(x)]","def uniq_stable(elems):\r\n unique = []\r\n unique_set = set()\r\n for nn in elems:\r\n if nn not in unique_set:\r\n unique.append(nn)\r\n unique_set.add(nn)\r\n return unique","def _findUniqueMappingValues(mapping):\n uniqueMappingValues = set()\n for entries in viewvalues(mapping):\n if len(entries) == 1:\n uniqueMappingValues.update(entries)\n return uniqueMappingValues","def unique(self):\n return self.d_series.map_partitions(\n lambda s: s.list.unique(), meta=self.d_series._meta\n )","def unique(self):\n seen = {}\n result = []\n for p in map(tuple, self):\n if p not in seen:\n seen[p] = True\n result.append(p)\n return Pairs(result)","def uniq(seq):\n return sorted(set(seq))","def potential_values(self) -> Set[Hashable]:\n\t\treturn set(self.iter_potential_values())","def unique(list_of_links):\n return list(set(list_of_links))","def _naive_unique(li):\n tmp = []\n for el in li:\n if el not in tmp:\n tmp.append(el)\n return tmp","def unique_elements_lists(list_in):\n return list(dict.fromkeys(list_in))","def unique(self, values: groupable): # type: ignore\n from arkouda import Categorical\n from arkouda.segarray import SegArray\n\n if isinstance(values, (Strings, Categorical)) or (\n isinstance(values, Sequence) and any([isinstance(v, (Strings, Categorical)) for v in values])\n ):\n raise TypeError(\"Groupby.unique not supported on Strings or Categorical\")\n\n togroup = self._nested_grouping_helper(values)\n # Group to unique (key, value) pairs\n g = GroupBy(togroup)\n ki, unique_values = g.unique_keys[0], g.unique_keys[1:]\n # Group pairs by key\n g2 = GroupBy(ki)\n # GroupBy should be stable with a single key array, but\n # if for some reason these unique keys are not in original\n # order, then permute them accordingly\n if not (g2.unique_keys == arange(self.ngroups)).all():\n perm = argsort(cast(pdarray, g2.unique_keys))\n reorder = True\n else:\n reorder = False\n # Form a SegArray for each value array\n # Segments are from grouping by key indices\n # Values are the unique elements of the values arg\n if len(unique_values) == 1:\n # Squeeze singleton results\n ret = SegArray(g2.segments, unique_values[0])\n if reorder:\n ret = ret[perm]\n else:\n ret = [SegArray(g2.segments, uv) for uv in unique_values] # type: ignore\n if reorder:\n ret = [r[perm] for r in ret] # type: ignore\n return self.unique_keys, ret # type: ignore","def unique_permutations(items):\n return set(permutations(items))","def uniq(seq):\r\n seen = set()\r\n seen_add = seen.add\r\n return [x for x in seq if x not in seen and not seen_add(x)]","def unique(temp_list):\n seen = set()\n return [x for x in temp_list if not (x in seen or seen.add(x))]","def unique(self, key: Callable[[T], Union[str, int, float]]=None) -> 'List[T]':\n return unique_values(self.array, key)","def unique_ordered(seq: Iterable) -> list:\n seen = set()\n seen_add = seen.add\n return [x for x in seq if not (x in seen or seen_add(x))]","def uniq(iterable, key=lambda x: x):\n keys = set()\n res = []\n for x in iterable:\n k = key(x)\n if k in keys:\n continue\n\n res.append(x)\n keys.add(k)\n return res\n\n # Enumerate the list to restore order lately; reduce the sorted list; restore order\n # def append_unique(acc, item):\n # return acc if key(acc[-1][1]) == key(item[1]) else acc.append(item) or acc\n # srt_enum = sorted(enumerate(iterable), key=lambda item: key(item[1]))\n # return [item[1] for item in sorted(reduce(append_unique, srt_enum, [srt_enum[0]]))]","def unique(iterable):\n seen = set()\n return [x for x in iterable if x not in seen and not seen.add(x)]","def get_unique_values(local_data, attr):\n\tvalues = []\n\tfor element in local_data:\n\t\tif element[attr] not in values:\n\t\t\tvalues.extend([element[attr]])\n\treturn values","def deduped(items):\n \n return list(set(items))","def values(self):\n return [_ for _ in self._dict.values()]","def unique_list(inlist):\n return set(inlist)","def uniq(seq):\n # Taken from https://stackoverflow.com/questions/480214\n seen = set()\n seen_add = seen.add\n return [x for x in seq if not (x in seen or seen_add(x))]","def unique_vals(rows, col):\n return set([row[col] for row in rows])","def unique(input_list):\n output = []\n for item in input_list:\n if item not in output:\n output.append(item)\n return output","def get_values(self):\n return set(self._table.keys())","def unique(x):\n try:\n tmp = x.flatten()\n if tmp.size == 0:\n return tmp\n tmp.sort()\n idx = concatenate(([True],tmp[1:]!=tmp[:-1]))\n return tmp[idx]\n except AttributeError:\n items = list(set(x))\n items.sort()\n return asarray(items)","def get_unique_users(self, users):\n users_without_duplicates = []\n for user in range(2, len(users)):\n if users[user] not in users_without_duplicates:\n users_without_duplicates.append(users[user])\n return users_without_duplicates","def _uniq( list ) : \r\n \r\n d = {} \r\n for e in list : \r\n d[e] = 1 \r\n \r\n return d.keys()","def unique(iterable):\n seen = set()\n return [i for i in iterable if not (i in seen or seen.add(i))]","def unique_names(names):\n return sorted(set(names))","def uniq(seq):\r\n #TODO: consider building a set out of seq so that the if condition\r\n #is constant time -JB\r\n return [x for i, x in enumerate(seq) if seq.index(x) == i]","def dedupe_list(input):\n return list(set(input))","def get_uniques(array):\n uniques = []\n for element in array:\n if element not in uniques:\n uniques.append(element)\n return uniques","def make_unique(lista):\n f = []\n for it in lista:\n if it not in f:\n f.append(it)\n return f","def unique_vals(client, proj, dataset, table, col_name):\n if not client.check_table(dataset, table):\n return []\n res = run_bq_query(client, \"SELECT %s FROM [%s:%s.%s] GROUP BY %s ORDER BY %s\" % (col_name, proj, dataset, table, col_name, col_name), 120)\n return [rec[col_name] for rec in res]","def find_uniq_preserve_order(orig_keys, orig_values=None):\n seen = {}\n keys = []\n values = []\n for i, item in enumerate(orig_keys):\n if item in seen:\n continue\n seen[item] = 1\n keys.append(item)\n if orig_values:\n values.append(orig_values[i])\n return keys, values","def unique(objects):\n uniques = []\n for obj in objects:\n if obj not in uniques:\n uniques.append(obj)\n return uniques","def duplicates(self, x):\n return list(dict.fromkeys(x))","def makeUnique(list):\n\tu = []\n\tfor l in list:\n\t\tif not l in u:\n\t\t\tu.append(l)\n\treturn u","def UniqueSequence(seq):\n seen = set()\n return [i for i in seq if i not in seen and not seen.add(i)]","def _remove_duplicates(input_list):\n return list(OrderedDict.fromkeys(input_list))","def values(cls):\n if not hasattr(cls, \"__values__\"):\n setattr(cls, \"__values__\", set(i.value for i in cls))\n return getattr(cls, \"__values__\")","def unique_list(\n l1: list,\n l2: list,\n ) -> list:\n\n l = list((set(l1) | set(l2)) - (set(l1) & set(l2)))\n\n return l","def unsorted_unique(a):\n\n indexes = np.unique(a, return_index = True)[1]\n a_unique = np.array(a)[sorted(indexes)]\n return a_unique","def values(self):\n return [i.value for i in self.value]","def unique(items, attribute=None):\n\n if attribute is not None:\n return list(\n collections.OrderedDict.fromkeys(\n [getattr(item, attribute) for item in items]))\n else:\n return list(collections.OrderedDict.fromkeys(items))","def get_unique_employees():\n unique_names = []\n\n for entry in Entry.select():\n if entry.employee_name not in unique_names:\n unique_names.append(entry.employee_name)\n\n clear()\n return unique_names","def listops_uniq(list_a):\r\n retlist = []\r\n for item in list_a:\r\n if item not in retlist:\r\n retlist.append(item)\r\n\r\n return retlist","def unique(list1):\n # insert the list to the set\n list_set = set(list1)\n # convert the set to the list\n unique_list = (list(list_set))\n for x in unique_list:\n return(x,)","def listUnique(self,permutations=True):\n ind,ok = self.testDuplicate(permutations)\n return ind[ok]","def remove_duplicates(mylist):\n return list(set(mylist))","def unique(list1):\n \n # intilize a null list \n unique_list = [] \n \n # traverse for all elements \n for x in list1: \n # check if exists in unique_list or not \n if x not in unique_list: \n unique_list.append(x)\n return unique_list","def unique(arr):\n seen = set()\n for elem in arr:\n if elem not in seen:\n yield elem\n seen.add(elem)","def unique_dicts_by_value(d, key):\n return list({v[key]: v for v in d}.values())","def keys(self):\n return sorted(self._local_unique_map.keys())","def values(self):\n x = []\n for k in list(self.keys()):\n x.append(self[k])\n return x","def get_values(self) -> list:\r\n values = []\r\n for key, value in self._items:\r\n values.append(value)\r\n return values","def unique(v):\r\n\r\n nstr = \"-,-\".join(v)\r\n capsstr = nstr.upper()\r\n s = capsstr.split(\"-,-\")\r\n\r\n\r\n n = len(s)\r\n if n == 0:\r\n return []\r\n\r\n # Try using a dict first, as that's the fastest and will usually\r\n # work. If it doesn't work, it will usually fail quickly, so it\r\n # usually doesn't cost much to *try* it. It requires that all the\r\n # sequence elements be hashable, and support equality comparison.\r\n u = {}\r\n try:\r\n for x in s:\r\n u[x] = 1\r\n except TypeError:\r\n del u # move on to the next method\r\n else:\r\n return u.keys()\r\n\r\n # We can't hash all the elements. Second fastest is to sort,\r\n # which brings the equal elements together; then duplicates are\r\n # easy to weed out in a single pass.\r\n # NOTE: Python's list.sort() was designed to be efficient in the\r\n # presence of many duplicate elements. This isn't true of all\r\n # sort functions in all languages or libraries, so this approach\r\n # is more effective in Python than it may be elsewhere.\r\n try:\r\n t = list(s)\r\n t.sort()\r\n except TypeError:\r\n del t # move on to the next method\r\n else:\r\n assert n > 0\r\n last = t[0]\r\n lasti = i = 1\r\n while i < n:\r\n if t[i] != last:\r\n t[lasti] = last = t[i]\r\n lasti += 1\r\n i += 1\r\n return t[:lasti]\r\n\r\n # Brute force is all that's left.\r\n u = []\r\n for x in s:\r\n if x not in u:\r\n u.append(x)\r\n\r\n\r\n nstr = \"-,-\".join(u)\r\n capsstr = nstr.capitalize()\r\n x = capsstr.split(\"-,-\")\r\n\r\n return x","def unique(iterable):\n seen_items = set()\n for item in iterable:\n if item not in seen_items:\n yield item\n seen_items.add(item)","def unique_list(duplicates_list):\n used = set()\n unique = [x for x in duplicates_list\n if x not in used and\n (used.add(x) or True)]\n return unique","def possible_values(self) -> Set[int]:\n return {x for x in SudokuTile.UNIVERSE_OF_TILE_VALUES if\n (x not in self._row) and\n (x not in self._column) and\n (x not in self._box)}","def copy_values(self) -> List[FixupValue]:\n return list(self._fixup.values())","def nunique(self, values: groupable) -> Tuple[groupable, pdarray]:\n # TO DO: defer to self.aggregate once logic is ported over to Chapel\n # return self.aggregate(values, \"nunique\")\n togroup = self._nested_grouping_helper(values)\n # Find unique pairs of (key, val)\n g = GroupBy(togroup)\n # Group unique pairs again by original key\n g2 = GroupBy(g.unique_keys[0], assume_sorted=False)\n # Count number of unique values per key\n keyorder, nuniq = g2.count()\n # The last GroupBy *should* result in sorted key indices, but in case it\n # doesn't, we need to permute the answer to match the original key order\n if not is_sorted(keyorder):\n perm = argsort(keyorder)\n nuniq = nuniq[perm]\n # Re-join unique counts with original keys (sorting guarantees same order)\n return self.unique_keys, nuniq","def unique(input_list): \n try:\n # intilize a null list \n unique_list = [] \n # traverse for all elements \n for x in input_list: \n # check if exists in unique_list or not \n if x not in unique_list: \n unique_list.append(x)\n return(unique_list)\n except TypeError as detail:\n return (\"int object is not iterable\")","def merge_uniq(*args):\n return list(set(merge(*args)))","def unique(my_list):\n return [x for x in my_list if x not in locals()['_[1]']]","def aslist(self):\n return sorted(list(self.fingerprints))","def get_arraysurdit(self,list_values):\n\n\t\tself.list_values = list_values\n\t\tset_values = set([x for x in self.list_values if self.list_values.count(x) > 1])\n\t\treturn list(set_values)[0]","def to_set(self):\n return set(self._items)","def to_set(self):\n return set(self._items)","def values(self) -> Iterable[U]:\n return self._store.values()"],"string":"[\n \"def create_unique_value_list(value):\\n my_set = set(value)\\n new_list = list(my_set)\\n new_list.sort()\\n return new_list\",\n \"def unique(x):\\n\\n return list(set(x))\",\n \"def find_remove_duplicates(list_of_values):\\r\\n output = []\\r\\n seen = set()\\r\\n for value in list_of_values:\\r\\n if value not in seen:\\r\\n output.append(value)\\r\\n seen.add(value)\\r\\n return output\",\n \"def _unique(li):\\n return list(set(li))\",\n \"def delDoublon(values):\\n\\treturn list(set(values))\",\n \"def nunique(self, values):\\n return self.aggregate(values, \\\"nunique\\\")\",\n \"def uniq(val, key=None):\\n if not isinstance(val, list):\\n return val\\n if key is None:\\n try:\\n return list(set(val))\\n except TypeError:\\n pass\\n keys = []\\n values = []\\n for value in val:\\n try:\\n thiskey = value[key]\\n except:\\n thiskey = repr(value)\\n if thiskey not in keys:\\n keys.append(thiskey)\\n values.append(value)\\n return values\",\n \"def unique_values(array: Iterable[T], key: Callable[[T], Union[str, int, float]]=None) -> List[T]:\\n values = set()\\n unique_array = []\\n\\n if key is None:\\n for v in array:\\n if v not in values:\\n unique_array.append(v)\\n values.add(v)\\n else:\\n for v in array:\\n v_key = key(v)\\n if v_key not in values:\\n unique_array.append(v)\\n values.add(v_key)\\n\\n return unique_array\",\n \"def unique_ordered(seq):\\n\\tvals = set()\\n\\treturn [x for x in seq if not (x in vals or vals.add(x))]\",\n \"def distinct(x):\\n return list(set(x))\",\n \"def unique(li):\\r\\n seen = set()\\r\\n seen_add = seen.add\\r\\n return [x for x in li if not (x in seen or seen_add(x))]\",\n \"def unique(self):\\n return self.element_wise(lambda seqs: list(set(seqs)))\",\n \"def unique(self, key, lst=None):\\n d = self.find(key, lst)\\n vals = set(d.values())\\n return sorted(list(vals))\",\n \"def unique(seq):\\n return list(set(seq))\",\n \"def unique(self) -> 'List':\\n return List(sorted(set(self), key=self.index))\",\n \"def unique(self):\\n return frozenset(self)\",\n \"def unique_values(self):\\n for key in self.metadb.unique_values():\\n yield key, self.datadb[key]\",\n \"def unique(list_: List) -> List:\\n return list(collections.OrderedDict.fromkeys(list_))\",\n \"def list_unique_values(series: pd.Series) -> str:\\n return \\\", \\\".join(set(str(v) for v in pd.Series.unique(series)))\",\n \"def unique_list(src_list):\\n return list(OrderedDict.fromkeys(src_list).keys())\",\n \"def _unique(iterable):\\n return list(dict.fromkeys(iterable))\",\n \"def remove_duplicates(possible_vulns):\\n return list(set(possible_vulns))\",\n \"def _unique_sorted(seq):\\n seen = set()\\n seen_add = seen.add\\n return [x for x in seq if not (x in seen or seen_add(x))]\",\n \"def _uniq(self, lst):\\n h = {}\\n for e in lst:\\n h[e] = 1\\n return sorted(h.keys())\",\n \"def uniq(elements):\\n us = set()\\n ret = []\\n for e in elements:\\n if e not in us:\\n ret.append(e)\\n us.add(e)\\n return ret\",\n \"def keys_sorted_by_value_unique(d, **sort_kwargs):\\n values = d.values()\\n values.sort(**sort_kwargs)\\n i = inverse(d)\\n return [i[val] for val in values]\",\n \"def flat_unique(ls):\\n return list(unique(chain.from_iterable(ls), key=id))\",\n \"def unique(lis):\\n seen = set()\\n ret = []\\n for elm in lis:\\n if elm not in seen:\\n ret.append(elm)\\n seen.add(elm)\\n return ret\",\n \"def uniquify(seq):\\n seen = set()\\n seen_add = seen.add\\n return [ x for x in seq if x not in seen and not seen_add(x)]\",\n \"def uniq_stable(elems):\\r\\n unique = []\\r\\n unique_set = set()\\r\\n for nn in elems:\\r\\n if nn not in unique_set:\\r\\n unique.append(nn)\\r\\n unique_set.add(nn)\\r\\n return unique\",\n \"def _findUniqueMappingValues(mapping):\\n uniqueMappingValues = set()\\n for entries in viewvalues(mapping):\\n if len(entries) == 1:\\n uniqueMappingValues.update(entries)\\n return uniqueMappingValues\",\n \"def unique(self):\\n return self.d_series.map_partitions(\\n lambda s: s.list.unique(), meta=self.d_series._meta\\n )\",\n \"def unique(self):\\n seen = {}\\n result = []\\n for p in map(tuple, self):\\n if p not in seen:\\n seen[p] = True\\n result.append(p)\\n return Pairs(result)\",\n \"def uniq(seq):\\n return sorted(set(seq))\",\n \"def potential_values(self) -> Set[Hashable]:\\n\\t\\treturn set(self.iter_potential_values())\",\n \"def unique(list_of_links):\\n return list(set(list_of_links))\",\n \"def _naive_unique(li):\\n tmp = []\\n for el in li:\\n if el not in tmp:\\n tmp.append(el)\\n return tmp\",\n \"def unique_elements_lists(list_in):\\n return list(dict.fromkeys(list_in))\",\n \"def unique(self, values: groupable): # type: ignore\\n from arkouda import Categorical\\n from arkouda.segarray import SegArray\\n\\n if isinstance(values, (Strings, Categorical)) or (\\n isinstance(values, Sequence) and any([isinstance(v, (Strings, Categorical)) for v in values])\\n ):\\n raise TypeError(\\\"Groupby.unique not supported on Strings or Categorical\\\")\\n\\n togroup = self._nested_grouping_helper(values)\\n # Group to unique (key, value) pairs\\n g = GroupBy(togroup)\\n ki, unique_values = g.unique_keys[0], g.unique_keys[1:]\\n # Group pairs by key\\n g2 = GroupBy(ki)\\n # GroupBy should be stable with a single key array, but\\n # if for some reason these unique keys are not in original\\n # order, then permute them accordingly\\n if not (g2.unique_keys == arange(self.ngroups)).all():\\n perm = argsort(cast(pdarray, g2.unique_keys))\\n reorder = True\\n else:\\n reorder = False\\n # Form a SegArray for each value array\\n # Segments are from grouping by key indices\\n # Values are the unique elements of the values arg\\n if len(unique_values) == 1:\\n # Squeeze singleton results\\n ret = SegArray(g2.segments, unique_values[0])\\n if reorder:\\n ret = ret[perm]\\n else:\\n ret = [SegArray(g2.segments, uv) for uv in unique_values] # type: ignore\\n if reorder:\\n ret = [r[perm] for r in ret] # type: ignore\\n return self.unique_keys, ret # type: ignore\",\n \"def unique_permutations(items):\\n return set(permutations(items))\",\n \"def uniq(seq):\\r\\n seen = set()\\r\\n seen_add = seen.add\\r\\n return [x for x in seq if x not in seen and not seen_add(x)]\",\n \"def unique(temp_list):\\n seen = set()\\n return [x for x in temp_list if not (x in seen or seen.add(x))]\",\n \"def unique(self, key: Callable[[T], Union[str, int, float]]=None) -> 'List[T]':\\n return unique_values(self.array, key)\",\n \"def unique_ordered(seq: Iterable) -> list:\\n seen = set()\\n seen_add = seen.add\\n return [x for x in seq if not (x in seen or seen_add(x))]\",\n \"def uniq(iterable, key=lambda x: x):\\n keys = set()\\n res = []\\n for x in iterable:\\n k = key(x)\\n if k in keys:\\n continue\\n\\n res.append(x)\\n keys.add(k)\\n return res\\n\\n # Enumerate the list to restore order lately; reduce the sorted list; restore order\\n # def append_unique(acc, item):\\n # return acc if key(acc[-1][1]) == key(item[1]) else acc.append(item) or acc\\n # srt_enum = sorted(enumerate(iterable), key=lambda item: key(item[1]))\\n # return [item[1] for item in sorted(reduce(append_unique, srt_enum, [srt_enum[0]]))]\",\n \"def unique(iterable):\\n seen = set()\\n return [x for x in iterable if x not in seen and not seen.add(x)]\",\n \"def get_unique_values(local_data, attr):\\n\\tvalues = []\\n\\tfor element in local_data:\\n\\t\\tif element[attr] not in values:\\n\\t\\t\\tvalues.extend([element[attr]])\\n\\treturn values\",\n \"def deduped(items):\\n \\n return list(set(items))\",\n \"def values(self):\\n return [_ for _ in self._dict.values()]\",\n \"def unique_list(inlist):\\n return set(inlist)\",\n \"def uniq(seq):\\n # Taken from https://stackoverflow.com/questions/480214\\n seen = set()\\n seen_add = seen.add\\n return [x for x in seq if not (x in seen or seen_add(x))]\",\n \"def unique_vals(rows, col):\\n return set([row[col] for row in rows])\",\n \"def unique(input_list):\\n output = []\\n for item in input_list:\\n if item not in output:\\n output.append(item)\\n return output\",\n \"def get_values(self):\\n return set(self._table.keys())\",\n \"def unique(x):\\n try:\\n tmp = x.flatten()\\n if tmp.size == 0:\\n return tmp\\n tmp.sort()\\n idx = concatenate(([True],tmp[1:]!=tmp[:-1]))\\n return tmp[idx]\\n except AttributeError:\\n items = list(set(x))\\n items.sort()\\n return asarray(items)\",\n \"def get_unique_users(self, users):\\n users_without_duplicates = []\\n for user in range(2, len(users)):\\n if users[user] not in users_without_duplicates:\\n users_without_duplicates.append(users[user])\\n return users_without_duplicates\",\n \"def _uniq( list ) : \\r\\n \\r\\n d = {} \\r\\n for e in list : \\r\\n d[e] = 1 \\r\\n \\r\\n return d.keys()\",\n \"def unique(iterable):\\n seen = set()\\n return [i for i in iterable if not (i in seen or seen.add(i))]\",\n \"def unique_names(names):\\n return sorted(set(names))\",\n \"def uniq(seq):\\r\\n #TODO: consider building a set out of seq so that the if condition\\r\\n #is constant time -JB\\r\\n return [x for i, x in enumerate(seq) if seq.index(x) == i]\",\n \"def dedupe_list(input):\\n return list(set(input))\",\n \"def get_uniques(array):\\n uniques = []\\n for element in array:\\n if element not in uniques:\\n uniques.append(element)\\n return uniques\",\n \"def make_unique(lista):\\n f = []\\n for it in lista:\\n if it not in f:\\n f.append(it)\\n return f\",\n \"def unique_vals(client, proj, dataset, table, col_name):\\n if not client.check_table(dataset, table):\\n return []\\n res = run_bq_query(client, \\\"SELECT %s FROM [%s:%s.%s] GROUP BY %s ORDER BY %s\\\" % (col_name, proj, dataset, table, col_name, col_name), 120)\\n return [rec[col_name] for rec in res]\",\n \"def find_uniq_preserve_order(orig_keys, orig_values=None):\\n seen = {}\\n keys = []\\n values = []\\n for i, item in enumerate(orig_keys):\\n if item in seen:\\n continue\\n seen[item] = 1\\n keys.append(item)\\n if orig_values:\\n values.append(orig_values[i])\\n return keys, values\",\n \"def unique(objects):\\n uniques = []\\n for obj in objects:\\n if obj not in uniques:\\n uniques.append(obj)\\n return uniques\",\n \"def duplicates(self, x):\\n return list(dict.fromkeys(x))\",\n \"def makeUnique(list):\\n\\tu = []\\n\\tfor l in list:\\n\\t\\tif not l in u:\\n\\t\\t\\tu.append(l)\\n\\treturn u\",\n \"def UniqueSequence(seq):\\n seen = set()\\n return [i for i in seq if i not in seen and not seen.add(i)]\",\n \"def _remove_duplicates(input_list):\\n return list(OrderedDict.fromkeys(input_list))\",\n \"def values(cls):\\n if not hasattr(cls, \\\"__values__\\\"):\\n setattr(cls, \\\"__values__\\\", set(i.value for i in cls))\\n return getattr(cls, \\\"__values__\\\")\",\n \"def unique_list(\\n l1: list,\\n l2: list,\\n ) -> list:\\n\\n l = list((set(l1) | set(l2)) - (set(l1) & set(l2)))\\n\\n return l\",\n \"def unsorted_unique(a):\\n\\n indexes = np.unique(a, return_index = True)[1]\\n a_unique = np.array(a)[sorted(indexes)]\\n return a_unique\",\n \"def values(self):\\n return [i.value for i in self.value]\",\n \"def unique(items, attribute=None):\\n\\n if attribute is not None:\\n return list(\\n collections.OrderedDict.fromkeys(\\n [getattr(item, attribute) for item in items]))\\n else:\\n return list(collections.OrderedDict.fromkeys(items))\",\n \"def get_unique_employees():\\n unique_names = []\\n\\n for entry in Entry.select():\\n if entry.employee_name not in unique_names:\\n unique_names.append(entry.employee_name)\\n\\n clear()\\n return unique_names\",\n \"def listops_uniq(list_a):\\r\\n retlist = []\\r\\n for item in list_a:\\r\\n if item not in retlist:\\r\\n retlist.append(item)\\r\\n\\r\\n return retlist\",\n \"def unique(list1):\\n # insert the list to the set\\n list_set = set(list1)\\n # convert the set to the list\\n unique_list = (list(list_set))\\n for x in unique_list:\\n return(x,)\",\n \"def listUnique(self,permutations=True):\\n ind,ok = self.testDuplicate(permutations)\\n return ind[ok]\",\n \"def remove_duplicates(mylist):\\n return list(set(mylist))\",\n \"def unique(list1):\\n \\n # intilize a null list \\n unique_list = [] \\n \\n # traverse for all elements \\n for x in list1: \\n # check if exists in unique_list or not \\n if x not in unique_list: \\n unique_list.append(x)\\n return unique_list\",\n \"def unique(arr):\\n seen = set()\\n for elem in arr:\\n if elem not in seen:\\n yield elem\\n seen.add(elem)\",\n \"def unique_dicts_by_value(d, key):\\n return list({v[key]: v for v in d}.values())\",\n \"def keys(self):\\n return sorted(self._local_unique_map.keys())\",\n \"def values(self):\\n x = []\\n for k in list(self.keys()):\\n x.append(self[k])\\n return x\",\n \"def get_values(self) -> list:\\r\\n values = []\\r\\n for key, value in self._items:\\r\\n values.append(value)\\r\\n return values\",\n \"def unique(v):\\r\\n\\r\\n nstr = \\\"-,-\\\".join(v)\\r\\n capsstr = nstr.upper()\\r\\n s = capsstr.split(\\\"-,-\\\")\\r\\n\\r\\n\\r\\n n = len(s)\\r\\n if n == 0:\\r\\n return []\\r\\n\\r\\n # Try using a dict first, as that's the fastest and will usually\\r\\n # work. If it doesn't work, it will usually fail quickly, so it\\r\\n # usually doesn't cost much to *try* it. It requires that all the\\r\\n # sequence elements be hashable, and support equality comparison.\\r\\n u = {}\\r\\n try:\\r\\n for x in s:\\r\\n u[x] = 1\\r\\n except TypeError:\\r\\n del u # move on to the next method\\r\\n else:\\r\\n return u.keys()\\r\\n\\r\\n # We can't hash all the elements. Second fastest is to sort,\\r\\n # which brings the equal elements together; then duplicates are\\r\\n # easy to weed out in a single pass.\\r\\n # NOTE: Python's list.sort() was designed to be efficient in the\\r\\n # presence of many duplicate elements. This isn't true of all\\r\\n # sort functions in all languages or libraries, so this approach\\r\\n # is more effective in Python than it may be elsewhere.\\r\\n try:\\r\\n t = list(s)\\r\\n t.sort()\\r\\n except TypeError:\\r\\n del t # move on to the next method\\r\\n else:\\r\\n assert n > 0\\r\\n last = t[0]\\r\\n lasti = i = 1\\r\\n while i < n:\\r\\n if t[i] != last:\\r\\n t[lasti] = last = t[i]\\r\\n lasti += 1\\r\\n i += 1\\r\\n return t[:lasti]\\r\\n\\r\\n # Brute force is all that's left.\\r\\n u = []\\r\\n for x in s:\\r\\n if x not in u:\\r\\n u.append(x)\\r\\n\\r\\n\\r\\n nstr = \\\"-,-\\\".join(u)\\r\\n capsstr = nstr.capitalize()\\r\\n x = capsstr.split(\\\"-,-\\\")\\r\\n\\r\\n return x\",\n \"def unique(iterable):\\n seen_items = set()\\n for item in iterable:\\n if item not in seen_items:\\n yield item\\n seen_items.add(item)\",\n \"def unique_list(duplicates_list):\\n used = set()\\n unique = [x for x in duplicates_list\\n if x not in used and\\n (used.add(x) or True)]\\n return unique\",\n \"def possible_values(self) -> Set[int]:\\n return {x for x in SudokuTile.UNIVERSE_OF_TILE_VALUES if\\n (x not in self._row) and\\n (x not in self._column) and\\n (x not in self._box)}\",\n \"def copy_values(self) -> List[FixupValue]:\\n return list(self._fixup.values())\",\n \"def nunique(self, values: groupable) -> Tuple[groupable, pdarray]:\\n # TO DO: defer to self.aggregate once logic is ported over to Chapel\\n # return self.aggregate(values, \\\"nunique\\\")\\n togroup = self._nested_grouping_helper(values)\\n # Find unique pairs of (key, val)\\n g = GroupBy(togroup)\\n # Group unique pairs again by original key\\n g2 = GroupBy(g.unique_keys[0], assume_sorted=False)\\n # Count number of unique values per key\\n keyorder, nuniq = g2.count()\\n # The last GroupBy *should* result in sorted key indices, but in case it\\n # doesn't, we need to permute the answer to match the original key order\\n if not is_sorted(keyorder):\\n perm = argsort(keyorder)\\n nuniq = nuniq[perm]\\n # Re-join unique counts with original keys (sorting guarantees same order)\\n return self.unique_keys, nuniq\",\n \"def unique(input_list): \\n try:\\n # intilize a null list \\n unique_list = [] \\n # traverse for all elements \\n for x in input_list: \\n # check if exists in unique_list or not \\n if x not in unique_list: \\n unique_list.append(x)\\n return(unique_list)\\n except TypeError as detail:\\n return (\\\"int object is not iterable\\\")\",\n \"def merge_uniq(*args):\\n return list(set(merge(*args)))\",\n \"def unique(my_list):\\n return [x for x in my_list if x not in locals()['_[1]']]\",\n \"def aslist(self):\\n return sorted(list(self.fingerprints))\",\n \"def get_arraysurdit(self,list_values):\\n\\n\\t\\tself.list_values = list_values\\n\\t\\tset_values = set([x for x in self.list_values if self.list_values.count(x) > 1])\\n\\t\\treturn list(set_values)[0]\",\n \"def to_set(self):\\n return set(self._items)\",\n \"def to_set(self):\\n return set(self._items)\",\n \"def values(self) -> Iterable[U]:\\n return self._store.values()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.77642304","0.73466635","0.72686464","0.70993155","0.7049732","0.7036178","0.6986363","0.69395584","0.69315803","0.6901696","0.6871331","0.6860619","0.68340397","0.68287754","0.68124825","0.67243654","0.6652985","0.66490304","0.66442025","0.6638174","0.66174823","0.6584867","0.65734386","0.65669256","0.653517","0.6526536","0.65219796","0.6503382","0.6503031","0.65001535","0.649318","0.64386886","0.6417277","0.6417182","0.6389918","0.63856685","0.6379408","0.6372535","0.6362301","0.63609016","0.63578516","0.6357335","0.6328045","0.6311632","0.628636","0.62795895","0.6266743","0.6264654","0.6252849","0.6246644","0.6234314","0.6231654","0.62154615","0.6214476","0.61879176","0.61827695","0.617336","0.6171362","0.6167807","0.6120054","0.6119802","0.61160815","0.60971874","0.6069118","0.6068945","0.60583115","0.6026956","0.60038877","0.5999766","0.5956348","0.59209627","0.5920662","0.5919336","0.59154135","0.59121406","0.591201","0.590997","0.5896444","0.5879732","0.5878972","0.5878025","0.586986","0.5864919","0.5857625","0.58538383","0.58517957","0.58396435","0.58394045","0.58301044","0.58297545","0.58217657","0.58169055","0.5810085","0.5807956","0.57978624","0.57922107","0.5788204","0.578559","0.578559","0.5783775"],"string":"[\n \"0.77642304\",\n \"0.73466635\",\n \"0.72686464\",\n \"0.70993155\",\n \"0.7049732\",\n \"0.7036178\",\n \"0.6986363\",\n \"0.69395584\",\n \"0.69315803\",\n \"0.6901696\",\n \"0.6871331\",\n \"0.6860619\",\n \"0.68340397\",\n \"0.68287754\",\n \"0.68124825\",\n \"0.67243654\",\n \"0.6652985\",\n \"0.66490304\",\n \"0.66442025\",\n \"0.6638174\",\n \"0.66174823\",\n \"0.6584867\",\n \"0.65734386\",\n \"0.65669256\",\n \"0.653517\",\n \"0.6526536\",\n \"0.65219796\",\n \"0.6503382\",\n \"0.6503031\",\n \"0.65001535\",\n \"0.649318\",\n \"0.64386886\",\n \"0.6417277\",\n \"0.6417182\",\n \"0.6389918\",\n \"0.63856685\",\n \"0.6379408\",\n \"0.6372535\",\n \"0.6362301\",\n \"0.63609016\",\n \"0.63578516\",\n \"0.6357335\",\n \"0.6328045\",\n \"0.6311632\",\n \"0.628636\",\n \"0.62795895\",\n \"0.6266743\",\n \"0.6264654\",\n \"0.6252849\",\n \"0.6246644\",\n \"0.6234314\",\n \"0.6231654\",\n \"0.62154615\",\n \"0.6214476\",\n \"0.61879176\",\n \"0.61827695\",\n \"0.617336\",\n \"0.6171362\",\n \"0.6167807\",\n \"0.6120054\",\n \"0.6119802\",\n \"0.61160815\",\n \"0.60971874\",\n \"0.6069118\",\n \"0.6068945\",\n \"0.60583115\",\n \"0.6026956\",\n \"0.60038877\",\n \"0.5999766\",\n \"0.5956348\",\n \"0.59209627\",\n \"0.5920662\",\n \"0.5919336\",\n \"0.59154135\",\n \"0.59121406\",\n \"0.591201\",\n \"0.590997\",\n \"0.5896444\",\n \"0.5879732\",\n \"0.5878972\",\n \"0.5878025\",\n \"0.586986\",\n \"0.5864919\",\n \"0.5857625\",\n \"0.58538383\",\n \"0.58517957\",\n \"0.58396435\",\n \"0.58394045\",\n \"0.58301044\",\n \"0.58297545\",\n \"0.58217657\",\n \"0.58169055\",\n \"0.5810085\",\n \"0.5807956\",\n \"0.57978624\",\n \"0.57922107\",\n \"0.5788204\",\n \"0.578559\",\n \"0.578559\",\n \"0.5783775\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6244349"},"document_rank":{"kind":"string","value":"50"}}},{"rowIdx":3996,"cells":{"query":{"kind":"string","value":"Initialize table from listlike container."},"document":{"kind":"string","value":"def _init_list(self, data: List[Any]):\n # Assume data is homogenous in regard to row type\n obj = data[0]\n column_names = self._column_name_getter(obj)\n column_values = self._column_value_getter(obj)\n\n # Map of source to destination column\n column_map = {}\n\n # Do not update columns if predefined\n add_columns = not bool(self._columns)\n\n for obj in data:\n row = [None] * len(self._columns)\n\n for column_src in column_names(obj):\n # Check if column has been added with different name\n column_dst = column_map.get(column_src, column_src)\n\n # Dictionaries and namedtuples can\n # contain unknown columns\n if column_dst not in self._columns:\n if not add_columns:\n continue\n\n col = self._add_column(column_dst)\n\n # Store map of source column name to created name\n column_dst = self._columns[col]\n column_map[column_src] = column_dst\n\n while len(row) < len(self._columns):\n row.append(None)\n\n col = self.column_location(column_dst)\n row[col] = column_values(obj, column_src)\n\n self._data.append(row)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _init_table(self, table: \"Table\"):\n if not self.columns:\n self.columns = table.columns\n self._data = table.data","def __init__(self):\n self.table = {}\n self.ls = []","def init_blank(self, T):\n self.headings = []\n self.table = {}\n self.rowcount = 0\n for e in T.entries:\n self.headings.append(e.name)\n self.table[e.name] = []","def __init__(self):\n\n self.table = []","def __init__(self):\n self.table = []","def __init__(self, *args):\n _table.Table_swiginit(self, _table.new_Table(*args))","def __init__(self, object_list, table_name, crowdcontext):\n self.cc = crowdcontext\n self.data = {'id': range(len(object_list)), 'object':object_list}\n self.start_id = len(object_list)\n self.cols = [\"id\", \"object\"]\n self.table_name = table_name\n self.presenter = None\n self.project_id = None\n self.project_short_name = None\n self.project_name = None\n\n if type(object_list) is not list:\n raise Exception(\"'object_list' should be a list\")\n if table_name not in self.cc.show_tables():\n try:\n exe_str = \"CREATE TABLE '%s' (id integer, col_name BLOB, value BLOB DEFAULT NULL, PRIMARY KEY(id, col_name))\" %(table_name)\n self.cc.cursor.execute(exe_str)\n except sqlite3.OperationalError:\n raise","def __init__(self, dim, connections_per_row=3):\n _table.STable_swiginit(self, _table.new_STable(dim, connections_per_row))","def __init__(self, rows=[]):\n self._rows, self._columns = Rows(self), Columns(self)\n self._m = 0 # Number of columns per row, see Table.insert().\n self.extend(rows)","def __init__(self, table, data: Iterator, columns: list,\n batch_size: int=BATCH_SIZE, header: bool=False):\n self.table = table\n self.data = data\n self.columns = columns\n self.batch_size = batch_size\n self.header = header\n\n if isinstance(self.data, list):\n self.data = iter(self.data)\n\n if not isinstance(self.data, Iterator):\n raise TypeError('Expected Iterator, got {}'.format(\n self.data.__class__))\n\n if not self.columns:\n raise ValueError('Columns cannot be empty')\n\n if isinstance(self.columns[0], tuple):\n self.columns = [Column(*c) for c in self.columns]","def from_list(self, lst: List[Tuple[keyType, valueType]]) -> None:\n key_size, value_size = self.size()\n if key_size > 0:\n # Clear the content of the existing custom dictionary object to the initial state.\n self.length = 10\n self.hashTable = [HeadNode() for i in range(self.length)]\n self.iter_head_node_index = 0\n self.iter_chain_node_index = -1\n self.iter_value_index = -1\n self.iter_values = []\n for element in lst:\n key = element[0]\n value = element[1]\n self.add(key, value)","def __init__(self, db_connection, table):\r\n self.elements = []\r\n self.db = db_connection\r\n self.table = table","def __init__(self, *args):\n _snap.TTable_swiginit(self, _snap.new_TTable(*args))","def from_list(cls, rowslist, shape, domain):\n return cls(rowslist, shape, domain)","def __init__(self):\n self.capacity = 10000\n self.table = [[] for _ in range(self.capacity)]","def __init__(self):\n _snap.TTableRow_swiginit(self, _snap.new_TTableRow())","def _load_table(self, field_list):\n for i, patterns in enumerate(field_list):\n self.ui.tableFields.insertRow(i)\n for j, item in enumerate(patterns):\n self.ui.tableFields.setItem(i, j, QTableWidgetItem(item))","def __init__(self, slots):\n self.slots = slots\n self.table = []\n for i in range(slots):\n self.table.append([])","def __init__(self, slots):\n self.slots = slots\n self.table = []\n for i in range(slots):\n self.table.append([])","def __init__(self, plantsim, table_name):\n self._rows = []\n self._rows_coldict = []\n\n row_count = plantsim.get_value(f'{table_name}.YDim')\n col_count = plantsim.get_value(f'{table_name}.XDim')\n if row_count > 0 and col_count > 0:\n for row_idx in range(row_count + 1):\n row = []\n row_coldict = {}\n for col_idx in range(col_count + 1):\n cell_value = plantsim.get_value(f'{table_name}[{col_idx}, {row_idx}]')\n row.append(cell_value)\n if row_idx > 0:\n col_header = self.rows[0][col_idx]\n row_coldict[col_header] = cell_value\n self._rows.append(row)\n if row_idx > 0:\n self._rows_coldict.append(row_coldict)","def from_tabular(cls, *args, **kwargs):\n return cls().add_tabular(*args, **kwargs)","def init_table(row_num):\n # Initialize the number of rows in table\n table = []\n for i in range(row_num):\n row = []\n table.append(row)\n\n # Append the default first cell to the table\n table[0].append(\"Curreny Type\")\n\n return table","def __init__(self, initial_data=[]):\n hdict.__init__(self)\n\n for elt in initial_data:\n self.add(elt)","def __init__(self, size):\n self.table = [set() for x in range(size)]","def __init__(self, rows=()):\n self.rows = list(rows)","def __init__(self, table_capacity=101, hash_base=31):\n\n self.table_capacity = table_capacity\n self.hash_base = hash_base\n self.array = [None] * self.table_capacity # Array initialized with 'None\" in each element.\n self.count = 0 # the number of items in the table, initially set to '0'\n self.rehash_count = 0\n self.probe_array = []","def __init__(self, nrows):\n _table.DSTable_swiginit(self, _table.new_DSTable(nrows))","def __init__(\n self,\n table: \"Table\",\n use_header: bool = True,\n template: Optional[Template] = None,\n escape: bool = True,\n ):\n self.table = table\n self.escape = escape\n self.use_header = use_header\n self.template = self.get_template()\n self.context = self.get_context(table, self.use_header)","def from_list(cls, l):\n max_cols = max([len(r) for r in l])\n output = cls(len(l), max_cols)\n\n for i, r in enumerate(l):\n for j, c in enumerate(r):\n output[i, j] = c\n\n return output","def from_rows(cls, rows, column_labels=None):\n return Table(list(zip(*rows)), column_labels)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, table, j):\n self._table = table\n self._j = j","def __init__(self,L):\n list.__init__(self,L)\n self.list = L\n i,j = LTMatrix.getRowColumn(len(L) - 1)\n assert i == j, \"Not a LTMatrix\"\n self.dimension = i + 1","def __init__(self, data):\n self.data = data\n self.columns = Columns(data)\n self.rows = Rows(data)","def __init__(self, PTableV):\n _snap.TTableIterator_swiginit(self, _snap.new_TTableIterator(PTableV))","def __init__(self):\n self.buckets = 1009\n self.table = [[] for _ in range(self.buckets)]","def __init__(self, table):\r\n self.table = table\r\n KaoTableColumn.__init__(self)","def __init__(self, inputlist):\n\n # Verify if the inputlist is a iterable but the first element isn't\n # it means is a single dimensional iterable\n try:\n self.n = len(inputlist)\n except TypeError:\n raise(VetorError, \"Parametro de entrada nao possui tamanho\")\n\n if hasattr(inputlist[0], \"__iter__\"):\n raise(VetorError, \"Elementos nao sao escalares\")\n\n self.elem = inputlist","def __init__(self, title=\"\", scaling=\"\", column_list=None):\n if column_list is None:\n column_list = []\n\n self.__title = title\n self.__column_list = column_list\n self.__scaling = scaling\n if self.__title:\n self.__nonzero = True\n else:\n self.__nonzero = False\n # Store a reference to the parent table\n self.__parent_table = None","def __init__(self, py_dict=None):\n super(ListFilesSchema, self).__init__()\n self.table = [ListFilesEntrySchema()]\n if py_dict is not None:\n self.get_object_from_py_dict(py_dict)","def __init__(self, container_type, datasource=sybase.NULL_SOURCE):\n super(sytable, self).__init__(container_type,\n datasource or sybase.NULL_SOURCE)\n columns = datasource.columns()\n self._name = datasource.read_name()\n self._attributes = datasource.read_table_attributes() or {}\n self._number_of_rows = datasource.number_of_rows()\n self._columns = OrderedDict(\n (column, _column_factory(datasource, column, self._number_of_rows))\n for column in columns)\n\n self._column_attributes = dict.fromkeys(columns)\n self._dirty = False","def new(headings: Optional[List[Any]] = None,\n data: Optional[List[List[Any]]] = None,\n style: Text = 'default',\n align: Text = None,\n device: Text = 'stdout',\n dataframe=None) -> TableD: # mypy: ignore\n\n if dataframe is not None:\n headings = list(dataframe.columns)\n data = dataframe.values.tolist()\n\n return TableD(headings or [], data or [], style, align, device)","def _populate(self, table):\n # Repopulating the listboxes will reset the scroll.\n self._curr_scroll_row = 0\n # Repopulating the listboxes will reset the selection, so make sure the entry defaults to disabled.\n self._disable_entry()\n self._clear()\n # Initialize the _last_table_idx to -1 because the listbox rows are zero-indexed and each table added to the\n # listboxes will increment _last_table_idx.\n self._last_table_idx = -1\n # Add a parent table row to the listboxes if the given table is not the root table.\n if table is not self.root_table:\n self._append_row(self.PARENT_DIR, self.BLANK, None)\n self._last_table_idx += 1\n # Iterate through the given table's subtables and add each one to the listboxes.\n for subtable in table.getSubTables():\n self._append_row(self.TABLE_FORMAT.format(subtable), self.BLANK, table.getSubTable(subtable))\n self._last_table_idx += 1\n # Iterate through the given table's entries and add each one to the listboxes.\n for key in table.getKeys():\n entry = table.getEntry(key)\n self._append_row(self.ENTRY_FORMAT.format(key), str(entry.value), entry)","def __init__(self, table):\n\n self.table = table\n\n ## Lots of shortcutting\n # \"Connection\"\n self.client = self.table.db.client\n\n # Table object\n self.worksheet = self.table.worksheet\n self.worksheet_id = self.table.worksheet_id\n\n # Addressing\n self.fields = self.table.fields\n\n ## And something to come later\n self.row = None\n self.data = {}","def list_to_table(data, col_count):\r\n\r\n if len(data) % col_count != 0:\r\n message = \"Cannot convert list to table. \" \\\r\n \"The total number of cells ({0}) is not compatible with the number of columns ({1})\"\\\r\n .format(len(data), col_count)\r\n raise ValueError(message)\r\n\r\n row_count = len(data) // col_count\r\n # cpp way\r\n tabled_data = []\r\n for row_i in range(row_count):\r\n row = []\r\n for col_i in range(col_count):\r\n row.append(data[row_i * col_count + col_i])\r\n tabled_data.append(row)\r\n return tabled_data","def __init__(self, tree):\n connector = db\n if isinstance(tree, list):\n for collection in tree:\n connector = connector[collection]\n else:\n connector = connector[tree]\n self.table = connector\n self.attributs = {}","def __init__(self, s=None):\n self._index_map = {}\n self._list = []\n\n if s is not None:\n for item in s:\n self.add(item)","def __init__(self):\n self.table = {}","def __init__(self, maybe_an_iterable=None):\n try:\n self._container = DblLinkedList(maybe_an_iterable[::-1])\n except TypeError:\n self._container = DblLinkedList(maybe_an_iterable)","def table(self, list_or_name):\n if not isinstance(list_or_name, basestring):\n for c in list_or_name:\n self.table(c)\n else:\n self._table_names.append(list_or_name)\n\n return self","def _initChoiceTable(self):\n\n t = self.tableWidget_choice_list # shorthand notation\n\n ### Header popluation & properties\n '''\n for (i, col_name) in enumerate(self.data.col_name_list):\n # Order the column labels as in the order of the definition\n # of the dictionary for the element property names and the\n # column names\n t.horizontalHeaderItem(i).setText(col_name)\n '''\n # or\n t.setHorizontalHeaderLabels(self.data.col_name_list)\n\n t.horizontalHeader().setMovable(True)","def __init__(self, nestedList):\n self.idx = -1\n self.elements = []\n self.unNest(nestedList)","def __init__(self, record_list=[[]]) -> None:\n self.record_list = record_list\n self.all_item = []\n # all items in the record to build the n*n matrix\n for record in record_list:\n if record[0] not in self.all_item:\n self.all_item.append(record[0])\n if record[1] not in self.all_item:\n self.all_item.append(record[1])\n self.item_num = len(self.all_item)\n # number od unique items\n self.item_mat = np.zeros(shape=(self.item_num, self.item_num))\n # The matrix, considered as the Massey matrix in MasseyRanking, fo example.\n self.ranking = []\n # A copy of list to return.","def __init__(self, *args, **kwargs):\n \n self.dense = True\n\n # Create table\n super().__init__(*args, **kwargs)","def test_query_simple_list(self):\n tab = 'query_test'\n cols = ['col1', 'col2']\n rows_in = [[1, 2], [2, 4], [3, 6]]\n\n with self.dbh.table_recreate(tab, cols, 'integer'):\n self.dbh.insert_many(tab, cols, rows_in)\n rows_out = self.dbh.query_simple(tab, cols, orderby=cols,\n rowtype=list)\n self.assertEqual(rows_in, rows_out)","def __init__(self):\n self.buckets = 1009\n self.table = [{} for _ in range(self.buckets)]","def from_list(cls, lst):\n return cls(lst[0], lst[1], lst[2])","def _read_table(hdulist, extname, **kwargs):\n t = _read_ext(Table, hdulist, extname, **kwargs)\n h = hdulist[extname].header\n for i in range(h['TFIELDS']):\n try:\n t.columns[i].unit = h['TUNIT%d' % (i + 1)]\n except Exception:\n pass\n return t","def __init__(self, m, d):\n if not m or not d:\n raise ValueError(\"Table size (m) and amount of hash functions (d)\"\n \" must be non-zero\")\n self.m = m\n self.d = d\n self.n = 0\n self.tables = []\n \n \n for _ in xrange(d):\n table = array.array(\"l\", (0 for _ in xrange(m)))\n self.tables.append(table)","def _populate_table(self):\n self._table.setSortingEnabled(False)\n self._table.setRowCount(len(self._module_names))\n for i, module_name in enumerate(self._module_names, 0):\n self._table.setItem(i, 0, QtWidgets.QTableWidgetItem(module_name))\n self._table.resizeRowsToContents()\n self._table.setSortingEnabled(True)","def __init__(self):\n self._data = PositionalList() # list of Item instances","def __init__(self, caption, tag, header, flip=False):\n super(LatexTable, self).__init__(caption, tag)\n self._header = header\n self._content = []\n self._flip = flip","def __init__(self,items,caption=None,parent=None,tab=False):\n warnings.warn('warn_old_table_dialog')\n \n GenericDialog.__init__(self,[],title=caption,parent=parent)\n if tab:\n contents = Tabs(\n [ (item[0], Table(data=item[2],chead=item[1],parent=None))\n for item in items ], parent=parent)\n else:\n contents = Table(data=items[1],chead=items[0],parent=None)\n\n self.add(contents)\n self.show()","def __init__(self):\n self._data = PositionalList() # list of _Item instances","def _initFilterTable(self):\n\n t = self.tableWidget_filter # shorthand notation\n\n ### Header population & properties\n t.setHorizontalHeaderLabels(self.data.filter_col_name_list)\n t.horizontalHeader().setMovable(True)\n\n ### Item population\n nRows = len(self.data.filter_spec)\n t.setRowCount(nRows)\n for (j, spec) in enumerate(self.data.filter_spec):\n for (i, filter_prop) in enumerate(self.data.filter_property_list):\n if filter_prop is not 'exclude':\n if filter_prop in spec[0]:\n item_string = spec[0][filter_prop]\n else:\n item_string = ''\n t.setItem(j,i,\n Qt.QTableWidgetItem(item_string))\n\n t.item(j,i).setFlags(Qt.Qt.ItemIsSelectable|\n Qt.Qt.ItemIsEditable|\n Qt.Qt.ItemIsDragEnabled|\n Qt.Qt.ItemIsEnabled) # Make it editable\n else:\n t.setItem(j,i,Qt.QTableWidgetItem(''))\n\n t.item(j,i).setFlags(Qt.Qt.ItemIsSelectable|\n Qt.Qt.ItemIsEditable|\n Qt.Qt.ItemIsDragEnabled|\n Qt.Qt.ItemIsUserCheckable|\n Qt.Qt.ItemIsEnabled) # Make it checkable\n if spec[1]: # exclusion flag\n t.item(j,i).setCheckState(Qt.Qt.Checked)\n else:\n t.item(j,i).setCheckState(Qt.Qt.Unchecked)\n\n\n\n ### Presentation formatting\n t.resizeColumnsToContents()\n for i in range(t.columnCount()):\n if t.columnWidth(i) > self.max_auto_adjust_column_width:\n t.setColumnWidth(i,self.max_auto_adjust_column_width)","def __init__(self, items=None):\n if items is None:\n self.items = []\n elif isinstance(items, list):\n self.items = items\n elif isinstance(items, SQLParam):\n self.items = [items]\n elif isinstance(items, SQLQuery):\n self.items = list(items.items)\n else:\n self.items = [items]\n \n # Take care of SQLLiterals\n for i, item in enumerate(self.items):\n if isinstance(item, SQLParam) and isinstance(item.value, SQLLiteral):\n self.items[i] = item.value.v","def __init__(self, *records: ScalarSequence):\n self._records = [r for r in records if r]","def _ui_init_table(self):\n self._table = QtWidgets.QTableWidget()\n self._table.verticalHeader().setVisible(False)\n self._table.setHorizontalScrollMode(QtWidgets.QAbstractItemView.ScrollPerPixel)\n self._table.horizontalHeader().setFont(self._font)\n self._table.setFont(self._font)\n\n # Create a simple table / list\n self._table.setColumnCount(1)\n self._table.setHorizontalHeaderLabels([\"Module Name\"])\n\n # left align text in column headers\n self._table.horizontalHeaderItem(0).setTextAlignment(QtCore.Qt.AlignLeft)\n\n # disable bolding of column headers when selected\n self._table.horizontalHeader().setHighlightSections(False)\n\n # stretch the last column of the table (aesthetics)\n self._table.horizontalHeader().setStretchLastSection(True)\n\n # make table read only, select a full row by default\n self._table.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers)\n self._table.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows)\n\n # catch double click events on table rows\n self._table.cellDoubleClicked.connect(self._ui_cell_double_click)","def __init__(self, values=[]):\n self.values = values\n self.head = None\n for i in values:\n self.insert(i)","def __init__(self, nestedList):\n\n self.nestedList = nestedList","def __init__(self):\n list.__init__([])\n self.name = ''\n self.ideal_value = None","def __init__(self, table_id='', columns=(),\n file_name='', table_data=(), verbose=True):\n self.table_id = table_id\n self.columns = list(columns)\n self.file_name = file_name\n self.table_data = list(table_data)\n self.verbose = verbose","def init_from(cls, matrix: list) -> object:\n return cls(tool.flatten(matrix))","def __init__(self, columns, values=[], row_number=None, source_row_number=None):\n self.columns = columns\n self.values = copy.copy(values)\n self.row_number = row_number\n self.source_row_number = source_row_number","def from_list(cls, rep, lev, ord, dom):\n return cls(dmp_from_dict(rep, lev, dom), dom, lev)","def load_list(self, last=False):\n\n self.SetItemCount(len(self.itemDataMap))\n if not self.resize_complete:\n for i in range(0, self.column_count):\n real = self.get_real_col(i)\n if real not in self.hidden_columns:\n self.SetColumnWidth(i, self.widest_cell[i])\n else:\n self.SetColumnWidth(i, 0)\n if not self.size_sample:\n self.resize_complete = True\n if last:\n if self.sort_init:\n listmix.ColumnSorterMixin.__init__(self, self.column_count)\n self.sort_init = False\n self.resize_last_column()\n self.size_sample = 0\n self.complete = True","def load(self, dct):\n self.items = list()\n if dct[\"type\"] == \"sep\":\n self.type = dct[\"type\"]\n for i in range(0, len(dct[\"items\"])):\n if dct[\"items\"][i] is None:\n self.items.append(LinkedChainTable())\n else:\n k = list()\n for j in range(0, len(dct[\"items\"][i])):\n k.append(createTableItem(dct[\"items\"][i][j], dct[\"items\"][i][j]))\n l = LinkedChainTable()\n l.load(k)\n self.items.append(l)\n self.n = len(dct[\"items\"])\n\n else:\n self.type = dct[\"type\"]\n for i in range(0, len(dct[\"items\"])):\n if dct[\"items\"][i] is None:\n self.items.append(None)\n else:\n self.items.append(createTableItem(dct[\"items\"][i], dct[\"items\"][i]))\n self.n = len(dct[\"items\"])","def __init__(self, header=None, rows=None, fromfile=None, delimiter=','):\n\t\tif fromfile:\n\t\t\trs = Csv(fromfile,delimiter=delimiter).getRows()\t\n\t\t\tself.header=rs[0]\n\t\t\tself.data = [] #a list of dictionaries\n\t\t\tfor r in rs[1:]:\n\t\t\t\tacc= dict()\n\t\t\t\tfor h in self.header:\n\t\t\t\t\tacc[h]=r[self.header.index(h)]\t\n\t\t\t\tself.data.append(acc) \n\t\telif header:\n\t\t\tself.header = header\t\n\t\t\tself.data = []\n\t\t\tif rows:\n\t\t\t\tif isinstance(rows[0],dict):\n\t\t\t\t\tself.data = rows\n\t\t\t\telif isinstance(rows[0],list):\t\n\t\t\t\t\tfor r in rows:\n\t\t\t\t\t\tacc= dict()\n\t\t\t\t\t\tfor h in self.header:\n\t\t\t\t\t\t\tacc[h]=r[self.header.index(h)]\n\t\t\t\t\t\tself.data.append(acc) \n\t\telse:\n\t\t\tself.header = []\t\n\t\t\tself.data = []","def __init__(self):\n self.data = SortedList()","def make_one_table(data, data_list, key, first_key):\n if key == first_key:\n data_list.append(data)\n else:\n data_list.append(data)\n return data_list","def from_(self, table):\n self.from__ = table\n\n return self","def cria_de_lista(lista, tamanho):\n tabuleiro = []\n for x in range(tamanho):\n tabuleiro.append([])\n for y in range(tamanho):\n tabuleiro[x].append(lista[x][y])\n wumpus = Wumpus(tamanho)\n wumpus.tabuleiro = tabuleiro\n return wumpus","def __init__(self, width, height):\n self.width = width\n self.height = height\n self.table = [False] * (width * height)","def __init__(self, lst):\n\n if not isinstance(lst, list):\n raise ValueError(\"Wrong parameter type\")\n self.values = copy.copy(lst)\n # self.values = lst","def patch_table(cls, mount_table: ty.List[ty.Tuple[str, str]]):\n orig_table = cls._mount_table\n cls._mount_table = list(mount_table)\n try:\n yield\n finally:\n cls._mount_table = orig_table","def table_head(\n self, table: Table, count: int = 5, as_list: bool = False\n ) -> Union[Table, List[List]]:\n self._requires_table(table)\n return table.head(count, as_list)","def __init__(self, lines):\n self.table = OrderedDict()\n\n # Load bp file, put lines in table, where the key is the key\n # and the value is the list of values on that bp line\n for line in lines:\n elements = line.split(';')\n self.table[elements[0]] = elements[1:]","def __init__(self, columns=()):\n self.columns = list(columns)\n\n # Create internal dictionary for faster access\n self.column_dict = {}\n\n for column in self.columns:\n self.column_dict[column.column_id] = column","def __init__(self, schema_row):\n self.schema = []\n for field in schema_row['fields']:\n self.schema.append(field['type'])","def visit_list(self, sylist):\n def index(sytable):\n try:\n return sytable.get_column(self.input_index)\n except:\n return np.array([0] * sytable.number_of_rows(), dtype=int)\n\n def column_or_nan(sytable, column, length):\n try:\n return sytable.get_column(column)\n except:\n return int(length)\n\n def fill(columns):\n test = []\n for column in columns:\n try:\n if column.size:\n test.append(column[:0])\n except:\n pass\n test = [[]] if not test else test\n dtype = np.hstack(test).dtype\n kind = dtype.kind\n\n if kind in ['S', 'U']:\n filler = lambda x: np.zeros(x, dtype='S1')\n else:\n filler = lambda x: np.zeros(x, dtype='f4') * np.nan\n\n result = [filler(column)\n if isinstance(column, int)\n else column for column in columns]\n if not result:\n result.append([])\n\n return result\n\n common_columns = set()\n all_columns = []\n order = OrderedDict()\n offset = 0\n indices = [[]]\n lengths = []\n\n # Pre-compute columns etc.\n for item in sylist:\n item_columns = item.columns()\n all_columns.append(item_columns)\n order.update(OrderedDict.fromkeys(item_columns))\n current_index = index(item)\n length = item.number_of_rows()\n minimum = np.min(current_index) if length else 0\n indices.append(current_index + (offset - minimum))\n\n offset += (np.max(current_index) - minimum + 1\n if length else\n self.minimum_increment)\n\n lengths.append(length)\n\n # Keep only common columns except when in fill mode.\n if not self.fill:\n try:\n common_columns.update(order.keys())\n for current_columns in all_columns:\n if current_columns:\n common_columns = common_columns.intersection(\n current_columns)\n except:\n pass\n order = OrderedDict.fromkeys(\n [key for key in order.keys() if key in common_columns])\n\n # VJoin columns and attributes.\n for column in order:\n data = []\n attrs = {}\n\n if self.fill:\n for i, item in enumerate(sylist):\n data.append(column_or_nan(item, column, lengths[i]))\n if column in all_columns[i]:\n attrs.update(item.get_column_attributes(column).get())\n else:\n for length, item in izip(lengths, sylist):\n if length:\n data.append(item.get_column(column))\n try:\n attrs.update(item.get_column_attributes(column).get())\n except KeyError:\n pass\n self.current.set_column(column, np.hstack(fill(data)))\n self.current.get_column_attributes(column).set(attrs)\n\n # VJoin index column.\n if self.current.number_of_columns() and self.output_index:\n self.current.set_column(self.output_index, np.hstack(indices))"],"string":"[\n \"def _init_table(self, table: \\\"Table\\\"):\\n if not self.columns:\\n self.columns = table.columns\\n self._data = table.data\",\n \"def __init__(self):\\n self.table = {}\\n self.ls = []\",\n \"def init_blank(self, T):\\n self.headings = []\\n self.table = {}\\n self.rowcount = 0\\n for e in T.entries:\\n self.headings.append(e.name)\\n self.table[e.name] = []\",\n \"def __init__(self):\\n\\n self.table = []\",\n \"def __init__(self):\\n self.table = []\",\n \"def __init__(self, *args):\\n _table.Table_swiginit(self, _table.new_Table(*args))\",\n \"def __init__(self, object_list, table_name, crowdcontext):\\n self.cc = crowdcontext\\n self.data = {'id': range(len(object_list)), 'object':object_list}\\n self.start_id = len(object_list)\\n self.cols = [\\\"id\\\", \\\"object\\\"]\\n self.table_name = table_name\\n self.presenter = None\\n self.project_id = None\\n self.project_short_name = None\\n self.project_name = None\\n\\n if type(object_list) is not list:\\n raise Exception(\\\"'object_list' should be a list\\\")\\n if table_name not in self.cc.show_tables():\\n try:\\n exe_str = \\\"CREATE TABLE '%s' (id integer, col_name BLOB, value BLOB DEFAULT NULL, PRIMARY KEY(id, col_name))\\\" %(table_name)\\n self.cc.cursor.execute(exe_str)\\n except sqlite3.OperationalError:\\n raise\",\n \"def __init__(self, dim, connections_per_row=3):\\n _table.STable_swiginit(self, _table.new_STable(dim, connections_per_row))\",\n \"def __init__(self, rows=[]):\\n self._rows, self._columns = Rows(self), Columns(self)\\n self._m = 0 # Number of columns per row, see Table.insert().\\n self.extend(rows)\",\n \"def __init__(self, table, data: Iterator, columns: list,\\n batch_size: int=BATCH_SIZE, header: bool=False):\\n self.table = table\\n self.data = data\\n self.columns = columns\\n self.batch_size = batch_size\\n self.header = header\\n\\n if isinstance(self.data, list):\\n self.data = iter(self.data)\\n\\n if not isinstance(self.data, Iterator):\\n raise TypeError('Expected Iterator, got {}'.format(\\n self.data.__class__))\\n\\n if not self.columns:\\n raise ValueError('Columns cannot be empty')\\n\\n if isinstance(self.columns[0], tuple):\\n self.columns = [Column(*c) for c in self.columns]\",\n \"def from_list(self, lst: List[Tuple[keyType, valueType]]) -> None:\\n key_size, value_size = self.size()\\n if key_size > 0:\\n # Clear the content of the existing custom dictionary object to the initial state.\\n self.length = 10\\n self.hashTable = [HeadNode() for i in range(self.length)]\\n self.iter_head_node_index = 0\\n self.iter_chain_node_index = -1\\n self.iter_value_index = -1\\n self.iter_values = []\\n for element in lst:\\n key = element[0]\\n value = element[1]\\n self.add(key, value)\",\n \"def __init__(self, db_connection, table):\\r\\n self.elements = []\\r\\n self.db = db_connection\\r\\n self.table = table\",\n \"def __init__(self, *args):\\n _snap.TTable_swiginit(self, _snap.new_TTable(*args))\",\n \"def from_list(cls, rowslist, shape, domain):\\n return cls(rowslist, shape, domain)\",\n \"def __init__(self):\\n self.capacity = 10000\\n self.table = [[] for _ in range(self.capacity)]\",\n \"def __init__(self):\\n _snap.TTableRow_swiginit(self, _snap.new_TTableRow())\",\n \"def _load_table(self, field_list):\\n for i, patterns in enumerate(field_list):\\n self.ui.tableFields.insertRow(i)\\n for j, item in enumerate(patterns):\\n self.ui.tableFields.setItem(i, j, QTableWidgetItem(item))\",\n \"def __init__(self, slots):\\n self.slots = slots\\n self.table = []\\n for i in range(slots):\\n self.table.append([])\",\n \"def __init__(self, slots):\\n self.slots = slots\\n self.table = []\\n for i in range(slots):\\n self.table.append([])\",\n \"def __init__(self, plantsim, table_name):\\n self._rows = []\\n self._rows_coldict = []\\n\\n row_count = plantsim.get_value(f'{table_name}.YDim')\\n col_count = plantsim.get_value(f'{table_name}.XDim')\\n if row_count > 0 and col_count > 0:\\n for row_idx in range(row_count + 1):\\n row = []\\n row_coldict = {}\\n for col_idx in range(col_count + 1):\\n cell_value = plantsim.get_value(f'{table_name}[{col_idx}, {row_idx}]')\\n row.append(cell_value)\\n if row_idx > 0:\\n col_header = self.rows[0][col_idx]\\n row_coldict[col_header] = cell_value\\n self._rows.append(row)\\n if row_idx > 0:\\n self._rows_coldict.append(row_coldict)\",\n \"def from_tabular(cls, *args, **kwargs):\\n return cls().add_tabular(*args, **kwargs)\",\n \"def init_table(row_num):\\n # Initialize the number of rows in table\\n table = []\\n for i in range(row_num):\\n row = []\\n table.append(row)\\n\\n # Append the default first cell to the table\\n table[0].append(\\\"Curreny Type\\\")\\n\\n return table\",\n \"def __init__(self, initial_data=[]):\\n hdict.__init__(self)\\n\\n for elt in initial_data:\\n self.add(elt)\",\n \"def __init__(self, size):\\n self.table = [set() for x in range(size)]\",\n \"def __init__(self, rows=()):\\n self.rows = list(rows)\",\n \"def __init__(self, table_capacity=101, hash_base=31):\\n\\n self.table_capacity = table_capacity\\n self.hash_base = hash_base\\n self.array = [None] * self.table_capacity # Array initialized with 'None\\\" in each element.\\n self.count = 0 # the number of items in the table, initially set to '0'\\n self.rehash_count = 0\\n self.probe_array = []\",\n \"def __init__(self, nrows):\\n _table.DSTable_swiginit(self, _table.new_DSTable(nrows))\",\n \"def __init__(\\n self,\\n table: \\\"Table\\\",\\n use_header: bool = True,\\n template: Optional[Template] = None,\\n escape: bool = True,\\n ):\\n self.table = table\\n self.escape = escape\\n self.use_header = use_header\\n self.template = self.get_template()\\n self.context = self.get_context(table, self.use_header)\",\n \"def from_list(cls, l):\\n max_cols = max([len(r) for r in l])\\n output = cls(len(l), max_cols)\\n\\n for i, r in enumerate(l):\\n for j, c in enumerate(r):\\n output[i, j] = c\\n\\n return output\",\n \"def from_rows(cls, rows, column_labels=None):\\n return Table(list(zip(*rows)), column_labels)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, table, j):\\n self._table = table\\n self._j = j\",\n \"def __init__(self,L):\\n list.__init__(self,L)\\n self.list = L\\n i,j = LTMatrix.getRowColumn(len(L) - 1)\\n assert i == j, \\\"Not a LTMatrix\\\"\\n self.dimension = i + 1\",\n \"def __init__(self, data):\\n self.data = data\\n self.columns = Columns(data)\\n self.rows = Rows(data)\",\n \"def __init__(self, PTableV):\\n _snap.TTableIterator_swiginit(self, _snap.new_TTableIterator(PTableV))\",\n \"def __init__(self):\\n self.buckets = 1009\\n self.table = [[] for _ in range(self.buckets)]\",\n \"def __init__(self, table):\\r\\n self.table = table\\r\\n KaoTableColumn.__init__(self)\",\n \"def __init__(self, inputlist):\\n\\n # Verify if the inputlist is a iterable but the first element isn't\\n # it means is a single dimensional iterable\\n try:\\n self.n = len(inputlist)\\n except TypeError:\\n raise(VetorError, \\\"Parametro de entrada nao possui tamanho\\\")\\n\\n if hasattr(inputlist[0], \\\"__iter__\\\"):\\n raise(VetorError, \\\"Elementos nao sao escalares\\\")\\n\\n self.elem = inputlist\",\n \"def __init__(self, title=\\\"\\\", scaling=\\\"\\\", column_list=None):\\n if column_list is None:\\n column_list = []\\n\\n self.__title = title\\n self.__column_list = column_list\\n self.__scaling = scaling\\n if self.__title:\\n self.__nonzero = True\\n else:\\n self.__nonzero = False\\n # Store a reference to the parent table\\n self.__parent_table = None\",\n \"def __init__(self, py_dict=None):\\n super(ListFilesSchema, self).__init__()\\n self.table = [ListFilesEntrySchema()]\\n if py_dict is not None:\\n self.get_object_from_py_dict(py_dict)\",\n \"def __init__(self, container_type, datasource=sybase.NULL_SOURCE):\\n super(sytable, self).__init__(container_type,\\n datasource or sybase.NULL_SOURCE)\\n columns = datasource.columns()\\n self._name = datasource.read_name()\\n self._attributes = datasource.read_table_attributes() or {}\\n self._number_of_rows = datasource.number_of_rows()\\n self._columns = OrderedDict(\\n (column, _column_factory(datasource, column, self._number_of_rows))\\n for column in columns)\\n\\n self._column_attributes = dict.fromkeys(columns)\\n self._dirty = False\",\n \"def new(headings: Optional[List[Any]] = None,\\n data: Optional[List[List[Any]]] = None,\\n style: Text = 'default',\\n align: Text = None,\\n device: Text = 'stdout',\\n dataframe=None) -> TableD: # mypy: ignore\\n\\n if dataframe is not None:\\n headings = list(dataframe.columns)\\n data = dataframe.values.tolist()\\n\\n return TableD(headings or [], data or [], style, align, device)\",\n \"def _populate(self, table):\\n # Repopulating the listboxes will reset the scroll.\\n self._curr_scroll_row = 0\\n # Repopulating the listboxes will reset the selection, so make sure the entry defaults to disabled.\\n self._disable_entry()\\n self._clear()\\n # Initialize the _last_table_idx to -1 because the listbox rows are zero-indexed and each table added to the\\n # listboxes will increment _last_table_idx.\\n self._last_table_idx = -1\\n # Add a parent table row to the listboxes if the given table is not the root table.\\n if table is not self.root_table:\\n self._append_row(self.PARENT_DIR, self.BLANK, None)\\n self._last_table_idx += 1\\n # Iterate through the given table's subtables and add each one to the listboxes.\\n for subtable in table.getSubTables():\\n self._append_row(self.TABLE_FORMAT.format(subtable), self.BLANK, table.getSubTable(subtable))\\n self._last_table_idx += 1\\n # Iterate through the given table's entries and add each one to the listboxes.\\n for key in table.getKeys():\\n entry = table.getEntry(key)\\n self._append_row(self.ENTRY_FORMAT.format(key), str(entry.value), entry)\",\n \"def __init__(self, table):\\n\\n self.table = table\\n\\n ## Lots of shortcutting\\n # \\\"Connection\\\"\\n self.client = self.table.db.client\\n\\n # Table object\\n self.worksheet = self.table.worksheet\\n self.worksheet_id = self.table.worksheet_id\\n\\n # Addressing\\n self.fields = self.table.fields\\n\\n ## And something to come later\\n self.row = None\\n self.data = {}\",\n \"def list_to_table(data, col_count):\\r\\n\\r\\n if len(data) % col_count != 0:\\r\\n message = \\\"Cannot convert list to table. \\\" \\\\\\r\\n \\\"The total number of cells ({0}) is not compatible with the number of columns ({1})\\\"\\\\\\r\\n .format(len(data), col_count)\\r\\n raise ValueError(message)\\r\\n\\r\\n row_count = len(data) // col_count\\r\\n # cpp way\\r\\n tabled_data = []\\r\\n for row_i in range(row_count):\\r\\n row = []\\r\\n for col_i in range(col_count):\\r\\n row.append(data[row_i * col_count + col_i])\\r\\n tabled_data.append(row)\\r\\n return tabled_data\",\n \"def __init__(self, tree):\\n connector = db\\n if isinstance(tree, list):\\n for collection in tree:\\n connector = connector[collection]\\n else:\\n connector = connector[tree]\\n self.table = connector\\n self.attributs = {}\",\n \"def __init__(self, s=None):\\n self._index_map = {}\\n self._list = []\\n\\n if s is not None:\\n for item in s:\\n self.add(item)\",\n \"def __init__(self):\\n self.table = {}\",\n \"def __init__(self, maybe_an_iterable=None):\\n try:\\n self._container = DblLinkedList(maybe_an_iterable[::-1])\\n except TypeError:\\n self._container = DblLinkedList(maybe_an_iterable)\",\n \"def table(self, list_or_name):\\n if not isinstance(list_or_name, basestring):\\n for c in list_or_name:\\n self.table(c)\\n else:\\n self._table_names.append(list_or_name)\\n\\n return self\",\n \"def _initChoiceTable(self):\\n\\n t = self.tableWidget_choice_list # shorthand notation\\n\\n ### Header popluation & properties\\n '''\\n for (i, col_name) in enumerate(self.data.col_name_list):\\n # Order the column labels as in the order of the definition\\n # of the dictionary for the element property names and the\\n # column names\\n t.horizontalHeaderItem(i).setText(col_name)\\n '''\\n # or\\n t.setHorizontalHeaderLabels(self.data.col_name_list)\\n\\n t.horizontalHeader().setMovable(True)\",\n \"def __init__(self, nestedList):\\n self.idx = -1\\n self.elements = []\\n self.unNest(nestedList)\",\n \"def __init__(self, record_list=[[]]) -> None:\\n self.record_list = record_list\\n self.all_item = []\\n # all items in the record to build the n*n matrix\\n for record in record_list:\\n if record[0] not in self.all_item:\\n self.all_item.append(record[0])\\n if record[1] not in self.all_item:\\n self.all_item.append(record[1])\\n self.item_num = len(self.all_item)\\n # number od unique items\\n self.item_mat = np.zeros(shape=(self.item_num, self.item_num))\\n # The matrix, considered as the Massey matrix in MasseyRanking, fo example.\\n self.ranking = []\\n # A copy of list to return.\",\n \"def __init__(self, *args, **kwargs):\\n \\n self.dense = True\\n\\n # Create table\\n super().__init__(*args, **kwargs)\",\n \"def test_query_simple_list(self):\\n tab = 'query_test'\\n cols = ['col1', 'col2']\\n rows_in = [[1, 2], [2, 4], [3, 6]]\\n\\n with self.dbh.table_recreate(tab, cols, 'integer'):\\n self.dbh.insert_many(tab, cols, rows_in)\\n rows_out = self.dbh.query_simple(tab, cols, orderby=cols,\\n rowtype=list)\\n self.assertEqual(rows_in, rows_out)\",\n \"def __init__(self):\\n self.buckets = 1009\\n self.table = [{} for _ in range(self.buckets)]\",\n \"def from_list(cls, lst):\\n return cls(lst[0], lst[1], lst[2])\",\n \"def _read_table(hdulist, extname, **kwargs):\\n t = _read_ext(Table, hdulist, extname, **kwargs)\\n h = hdulist[extname].header\\n for i in range(h['TFIELDS']):\\n try:\\n t.columns[i].unit = h['TUNIT%d' % (i + 1)]\\n except Exception:\\n pass\\n return t\",\n \"def __init__(self, m, d):\\n if not m or not d:\\n raise ValueError(\\\"Table size (m) and amount of hash functions (d)\\\"\\n \\\" must be non-zero\\\")\\n self.m = m\\n self.d = d\\n self.n = 0\\n self.tables = []\\n \\n \\n for _ in xrange(d):\\n table = array.array(\\\"l\\\", (0 for _ in xrange(m)))\\n self.tables.append(table)\",\n \"def _populate_table(self):\\n self._table.setSortingEnabled(False)\\n self._table.setRowCount(len(self._module_names))\\n for i, module_name in enumerate(self._module_names, 0):\\n self._table.setItem(i, 0, QtWidgets.QTableWidgetItem(module_name))\\n self._table.resizeRowsToContents()\\n self._table.setSortingEnabled(True)\",\n \"def __init__(self):\\n self._data = PositionalList() # list of Item instances\",\n \"def __init__(self, caption, tag, header, flip=False):\\n super(LatexTable, self).__init__(caption, tag)\\n self._header = header\\n self._content = []\\n self._flip = flip\",\n \"def __init__(self,items,caption=None,parent=None,tab=False):\\n warnings.warn('warn_old_table_dialog')\\n \\n GenericDialog.__init__(self,[],title=caption,parent=parent)\\n if tab:\\n contents = Tabs(\\n [ (item[0], Table(data=item[2],chead=item[1],parent=None))\\n for item in items ], parent=parent)\\n else:\\n contents = Table(data=items[1],chead=items[0],parent=None)\\n\\n self.add(contents)\\n self.show()\",\n \"def __init__(self):\\n self._data = PositionalList() # list of _Item instances\",\n \"def _initFilterTable(self):\\n\\n t = self.tableWidget_filter # shorthand notation\\n\\n ### Header population & properties\\n t.setHorizontalHeaderLabels(self.data.filter_col_name_list)\\n t.horizontalHeader().setMovable(True)\\n\\n ### Item population\\n nRows = len(self.data.filter_spec)\\n t.setRowCount(nRows)\\n for (j, spec) in enumerate(self.data.filter_spec):\\n for (i, filter_prop) in enumerate(self.data.filter_property_list):\\n if filter_prop is not 'exclude':\\n if filter_prop in spec[0]:\\n item_string = spec[0][filter_prop]\\n else:\\n item_string = ''\\n t.setItem(j,i,\\n Qt.QTableWidgetItem(item_string))\\n\\n t.item(j,i).setFlags(Qt.Qt.ItemIsSelectable|\\n Qt.Qt.ItemIsEditable|\\n Qt.Qt.ItemIsDragEnabled|\\n Qt.Qt.ItemIsEnabled) # Make it editable\\n else:\\n t.setItem(j,i,Qt.QTableWidgetItem(''))\\n\\n t.item(j,i).setFlags(Qt.Qt.ItemIsSelectable|\\n Qt.Qt.ItemIsEditable|\\n Qt.Qt.ItemIsDragEnabled|\\n Qt.Qt.ItemIsUserCheckable|\\n Qt.Qt.ItemIsEnabled) # Make it checkable\\n if spec[1]: # exclusion flag\\n t.item(j,i).setCheckState(Qt.Qt.Checked)\\n else:\\n t.item(j,i).setCheckState(Qt.Qt.Unchecked)\\n\\n\\n\\n ### Presentation formatting\\n t.resizeColumnsToContents()\\n for i in range(t.columnCount()):\\n if t.columnWidth(i) > self.max_auto_adjust_column_width:\\n t.setColumnWidth(i,self.max_auto_adjust_column_width)\",\n \"def __init__(self, items=None):\\n if items is None:\\n self.items = []\\n elif isinstance(items, list):\\n self.items = items\\n elif isinstance(items, SQLParam):\\n self.items = [items]\\n elif isinstance(items, SQLQuery):\\n self.items = list(items.items)\\n else:\\n self.items = [items]\\n \\n # Take care of SQLLiterals\\n for i, item in enumerate(self.items):\\n if isinstance(item, SQLParam) and isinstance(item.value, SQLLiteral):\\n self.items[i] = item.value.v\",\n \"def __init__(self, *records: ScalarSequence):\\n self._records = [r for r in records if r]\",\n \"def _ui_init_table(self):\\n self._table = QtWidgets.QTableWidget()\\n self._table.verticalHeader().setVisible(False)\\n self._table.setHorizontalScrollMode(QtWidgets.QAbstractItemView.ScrollPerPixel)\\n self._table.horizontalHeader().setFont(self._font)\\n self._table.setFont(self._font)\\n\\n # Create a simple table / list\\n self._table.setColumnCount(1)\\n self._table.setHorizontalHeaderLabels([\\\"Module Name\\\"])\\n\\n # left align text in column headers\\n self._table.horizontalHeaderItem(0).setTextAlignment(QtCore.Qt.AlignLeft)\\n\\n # disable bolding of column headers when selected\\n self._table.horizontalHeader().setHighlightSections(False)\\n\\n # stretch the last column of the table (aesthetics)\\n self._table.horizontalHeader().setStretchLastSection(True)\\n\\n # make table read only, select a full row by default\\n self._table.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers)\\n self._table.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows)\\n\\n # catch double click events on table rows\\n self._table.cellDoubleClicked.connect(self._ui_cell_double_click)\",\n \"def __init__(self, values=[]):\\n self.values = values\\n self.head = None\\n for i in values:\\n self.insert(i)\",\n \"def __init__(self, nestedList):\\n\\n self.nestedList = nestedList\",\n \"def __init__(self):\\n list.__init__([])\\n self.name = ''\\n self.ideal_value = None\",\n \"def __init__(self, table_id='', columns=(),\\n file_name='', table_data=(), verbose=True):\\n self.table_id = table_id\\n self.columns = list(columns)\\n self.file_name = file_name\\n self.table_data = list(table_data)\\n self.verbose = verbose\",\n \"def init_from(cls, matrix: list) -> object:\\n return cls(tool.flatten(matrix))\",\n \"def __init__(self, columns, values=[], row_number=None, source_row_number=None):\\n self.columns = columns\\n self.values = copy.copy(values)\\n self.row_number = row_number\\n self.source_row_number = source_row_number\",\n \"def from_list(cls, rep, lev, ord, dom):\\n return cls(dmp_from_dict(rep, lev, dom), dom, lev)\",\n \"def load_list(self, last=False):\\n\\n self.SetItemCount(len(self.itemDataMap))\\n if not self.resize_complete:\\n for i in range(0, self.column_count):\\n real = self.get_real_col(i)\\n if real not in self.hidden_columns:\\n self.SetColumnWidth(i, self.widest_cell[i])\\n else:\\n self.SetColumnWidth(i, 0)\\n if not self.size_sample:\\n self.resize_complete = True\\n if last:\\n if self.sort_init:\\n listmix.ColumnSorterMixin.__init__(self, self.column_count)\\n self.sort_init = False\\n self.resize_last_column()\\n self.size_sample = 0\\n self.complete = True\",\n \"def load(self, dct):\\n self.items = list()\\n if dct[\\\"type\\\"] == \\\"sep\\\":\\n self.type = dct[\\\"type\\\"]\\n for i in range(0, len(dct[\\\"items\\\"])):\\n if dct[\\\"items\\\"][i] is None:\\n self.items.append(LinkedChainTable())\\n else:\\n k = list()\\n for j in range(0, len(dct[\\\"items\\\"][i])):\\n k.append(createTableItem(dct[\\\"items\\\"][i][j], dct[\\\"items\\\"][i][j]))\\n l = LinkedChainTable()\\n l.load(k)\\n self.items.append(l)\\n self.n = len(dct[\\\"items\\\"])\\n\\n else:\\n self.type = dct[\\\"type\\\"]\\n for i in range(0, len(dct[\\\"items\\\"])):\\n if dct[\\\"items\\\"][i] is None:\\n self.items.append(None)\\n else:\\n self.items.append(createTableItem(dct[\\\"items\\\"][i], dct[\\\"items\\\"][i]))\\n self.n = len(dct[\\\"items\\\"])\",\n \"def __init__(self, header=None, rows=None, fromfile=None, delimiter=','):\\n\\t\\tif fromfile:\\n\\t\\t\\trs = Csv(fromfile,delimiter=delimiter).getRows()\\t\\n\\t\\t\\tself.header=rs[0]\\n\\t\\t\\tself.data = [] #a list of dictionaries\\n\\t\\t\\tfor r in rs[1:]:\\n\\t\\t\\t\\tacc= dict()\\n\\t\\t\\t\\tfor h in self.header:\\n\\t\\t\\t\\t\\tacc[h]=r[self.header.index(h)]\\t\\n\\t\\t\\t\\tself.data.append(acc) \\n\\t\\telif header:\\n\\t\\t\\tself.header = header\\t\\n\\t\\t\\tself.data = []\\n\\t\\t\\tif rows:\\n\\t\\t\\t\\tif isinstance(rows[0],dict):\\n\\t\\t\\t\\t\\tself.data = rows\\n\\t\\t\\t\\telif isinstance(rows[0],list):\\t\\n\\t\\t\\t\\t\\tfor r in rows:\\n\\t\\t\\t\\t\\t\\tacc= dict()\\n\\t\\t\\t\\t\\t\\tfor h in self.header:\\n\\t\\t\\t\\t\\t\\t\\tacc[h]=r[self.header.index(h)]\\n\\t\\t\\t\\t\\t\\tself.data.append(acc) \\n\\t\\telse:\\n\\t\\t\\tself.header = []\\t\\n\\t\\t\\tself.data = []\",\n \"def __init__(self):\\n self.data = SortedList()\",\n \"def make_one_table(data, data_list, key, first_key):\\n if key == first_key:\\n data_list.append(data)\\n else:\\n data_list.append(data)\\n return data_list\",\n \"def from_(self, table):\\n self.from__ = table\\n\\n return self\",\n \"def cria_de_lista(lista, tamanho):\\n tabuleiro = []\\n for x in range(tamanho):\\n tabuleiro.append([])\\n for y in range(tamanho):\\n tabuleiro[x].append(lista[x][y])\\n wumpus = Wumpus(tamanho)\\n wumpus.tabuleiro = tabuleiro\\n return wumpus\",\n \"def __init__(self, width, height):\\n self.width = width\\n self.height = height\\n self.table = [False] * (width * height)\",\n \"def __init__(self, lst):\\n\\n if not isinstance(lst, list):\\n raise ValueError(\\\"Wrong parameter type\\\")\\n self.values = copy.copy(lst)\\n # self.values = lst\",\n \"def patch_table(cls, mount_table: ty.List[ty.Tuple[str, str]]):\\n orig_table = cls._mount_table\\n cls._mount_table = list(mount_table)\\n try:\\n yield\\n finally:\\n cls._mount_table = orig_table\",\n \"def table_head(\\n self, table: Table, count: int = 5, as_list: bool = False\\n ) -> Union[Table, List[List]]:\\n self._requires_table(table)\\n return table.head(count, as_list)\",\n \"def __init__(self, lines):\\n self.table = OrderedDict()\\n\\n # Load bp file, put lines in table, where the key is the key\\n # and the value is the list of values on that bp line\\n for line in lines:\\n elements = line.split(';')\\n self.table[elements[0]] = elements[1:]\",\n \"def __init__(self, columns=()):\\n self.columns = list(columns)\\n\\n # Create internal dictionary for faster access\\n self.column_dict = {}\\n\\n for column in self.columns:\\n self.column_dict[column.column_id] = column\",\n \"def __init__(self, schema_row):\\n self.schema = []\\n for field in schema_row['fields']:\\n self.schema.append(field['type'])\",\n \"def visit_list(self, sylist):\\n def index(sytable):\\n try:\\n return sytable.get_column(self.input_index)\\n except:\\n return np.array([0] * sytable.number_of_rows(), dtype=int)\\n\\n def column_or_nan(sytable, column, length):\\n try:\\n return sytable.get_column(column)\\n except:\\n return int(length)\\n\\n def fill(columns):\\n test = []\\n for column in columns:\\n try:\\n if column.size:\\n test.append(column[:0])\\n except:\\n pass\\n test = [[]] if not test else test\\n dtype = np.hstack(test).dtype\\n kind = dtype.kind\\n\\n if kind in ['S', 'U']:\\n filler = lambda x: np.zeros(x, dtype='S1')\\n else:\\n filler = lambda x: np.zeros(x, dtype='f4') * np.nan\\n\\n result = [filler(column)\\n if isinstance(column, int)\\n else column for column in columns]\\n if not result:\\n result.append([])\\n\\n return result\\n\\n common_columns = set()\\n all_columns = []\\n order = OrderedDict()\\n offset = 0\\n indices = [[]]\\n lengths = []\\n\\n # Pre-compute columns etc.\\n for item in sylist:\\n item_columns = item.columns()\\n all_columns.append(item_columns)\\n order.update(OrderedDict.fromkeys(item_columns))\\n current_index = index(item)\\n length = item.number_of_rows()\\n minimum = np.min(current_index) if length else 0\\n indices.append(current_index + (offset - minimum))\\n\\n offset += (np.max(current_index) - minimum + 1\\n if length else\\n self.minimum_increment)\\n\\n lengths.append(length)\\n\\n # Keep only common columns except when in fill mode.\\n if not self.fill:\\n try:\\n common_columns.update(order.keys())\\n for current_columns in all_columns:\\n if current_columns:\\n common_columns = common_columns.intersection(\\n current_columns)\\n except:\\n pass\\n order = OrderedDict.fromkeys(\\n [key for key in order.keys() if key in common_columns])\\n\\n # VJoin columns and attributes.\\n for column in order:\\n data = []\\n attrs = {}\\n\\n if self.fill:\\n for i, item in enumerate(sylist):\\n data.append(column_or_nan(item, column, lengths[i]))\\n if column in all_columns[i]:\\n attrs.update(item.get_column_attributes(column).get())\\n else:\\n for length, item in izip(lengths, sylist):\\n if length:\\n data.append(item.get_column(column))\\n try:\\n attrs.update(item.get_column_attributes(column).get())\\n except KeyError:\\n pass\\n self.current.set_column(column, np.hstack(fill(data)))\\n self.current.get_column_attributes(column).set(attrs)\\n\\n # VJoin index column.\\n if self.current.number_of_columns() and self.output_index:\\n self.current.set_column(self.output_index, np.hstack(indices))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6741247","0.65784097","0.6445998","0.6421057","0.6410227","0.62771124","0.62656546","0.6222653","0.62108904","0.6183416","0.6157158","0.61253923","0.6124469","0.6088853","0.60814494","0.598742","0.59580296","0.5902306","0.5902306","0.5886963","0.58821136","0.5854922","0.584919","0.5848905","0.58385813","0.5798223","0.57853174","0.57699424","0.5769668","0.57684904","0.5766405","0.5766405","0.5766405","0.5766405","0.5766405","0.5766405","0.5766405","0.5766405","0.5766405","0.5766405","0.5766405","0.57588226","0.5758165","0.5754839","0.5744732","0.572496","0.5721325","0.5668699","0.56612015","0.56567246","0.5651656","0.56469274","0.56462014","0.5635604","0.5626479","0.5594912","0.5581895","0.5568192","0.5539676","0.5532435","0.55173546","0.5512957","0.55023426","0.54942334","0.54919267","0.5489311","0.54613936","0.5456735","0.54439795","0.54354966","0.5434893","0.5432826","0.54259205","0.5410654","0.54048747","0.5402011","0.5400154","0.5399531","0.5394812","0.53904504","0.538513","0.5373492","0.5373325","0.53728193","0.53713846","0.53677875","0.53601414","0.5359357","0.5343865","0.5332384","0.5331745","0.5326313","0.53257996","0.5324845","0.5323245","0.53224015","0.5316896","0.52953404","0.5292831","0.5280328"],"string":"[\n \"0.6741247\",\n \"0.65784097\",\n \"0.6445998\",\n \"0.6421057\",\n \"0.6410227\",\n \"0.62771124\",\n \"0.62656546\",\n \"0.6222653\",\n \"0.62108904\",\n \"0.6183416\",\n \"0.6157158\",\n \"0.61253923\",\n \"0.6124469\",\n \"0.6088853\",\n \"0.60814494\",\n \"0.598742\",\n \"0.59580296\",\n \"0.5902306\",\n \"0.5902306\",\n \"0.5886963\",\n \"0.58821136\",\n \"0.5854922\",\n \"0.584919\",\n \"0.5848905\",\n \"0.58385813\",\n \"0.5798223\",\n \"0.57853174\",\n \"0.57699424\",\n \"0.5769668\",\n \"0.57684904\",\n \"0.5766405\",\n \"0.5766405\",\n \"0.5766405\",\n \"0.5766405\",\n \"0.5766405\",\n \"0.5766405\",\n \"0.5766405\",\n \"0.5766405\",\n \"0.5766405\",\n \"0.5766405\",\n \"0.5766405\",\n \"0.57588226\",\n \"0.5758165\",\n \"0.5754839\",\n \"0.5744732\",\n \"0.572496\",\n \"0.5721325\",\n \"0.5668699\",\n \"0.56612015\",\n \"0.56567246\",\n \"0.5651656\",\n \"0.56469274\",\n \"0.56462014\",\n \"0.5635604\",\n \"0.5626479\",\n \"0.5594912\",\n \"0.5581895\",\n \"0.5568192\",\n \"0.5539676\",\n \"0.5532435\",\n \"0.55173546\",\n \"0.5512957\",\n \"0.55023426\",\n \"0.54942334\",\n \"0.54919267\",\n \"0.5489311\",\n \"0.54613936\",\n \"0.5456735\",\n \"0.54439795\",\n \"0.54354966\",\n \"0.5434893\",\n \"0.5432826\",\n \"0.54259205\",\n \"0.5410654\",\n \"0.54048747\",\n \"0.5402011\",\n \"0.5400154\",\n \"0.5399531\",\n \"0.5394812\",\n \"0.53904504\",\n \"0.538513\",\n \"0.5373492\",\n \"0.5373325\",\n \"0.53728193\",\n \"0.53713846\",\n \"0.53677875\",\n \"0.53601414\",\n \"0.5359357\",\n \"0.5343865\",\n \"0.5332384\",\n \"0.5331745\",\n \"0.5326313\",\n \"0.53257996\",\n \"0.5324845\",\n \"0.5323245\",\n \"0.53224015\",\n \"0.5316896\",\n \"0.52953404\",\n \"0.5292831\",\n \"0.5280328\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6464922"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":3997,"cells":{"query":{"kind":"string","value":"Initialize table from dictlike container."},"document":{"kind":"string","value":"def _init_dict(self, data: Dict[Column, Row]):\n if not self._columns:\n self._columns = list(data.keys())\n\n # Filter values by defined columns\n columns = (\n to_list(values)\n for column, values in data.items()\n if column in self._columns\n )\n\n # Convert columns to rows\n self._data = [list(row) for row in zip_longest(*columns)]"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _init_table(self, table: \"Table\"):\n if not self.columns:\n self.columns = table.columns\n self._data = table.data","def test_create_from_dicts(self):\n cols = list(zip(*self.dtypes))[0]\n dicts = [dict([(cols[i], d[i]) for i in xrange(len(d))])\n for d in self.idata]\n\n tbl = Table.create(\n ':memory:', \"Bar\", dicts, verbose=True,\n primary_key='id', autoincrement=True)\n\n self.check_index(self.idata, tbl.select())\n for idx, col in enumerate(cols):\n if col == 'id':\n continue\n self.check_data(self.idata[:, [0, idx]], tbl[col])","def from_dict(self, dictionary):\n for column in self.__table__.columns.keys():\n value = dictionary.get(column, None)\n if value:\n setattr(self, column, value)","def __init__(self):\n self.table = {}","def from_dict(self, data: dict):\n super().from_dict(data)\n if self.data is not None:\n try:\n self.data[\"columns\"] = np.array(\n [int(col) for col in self.data[\"columns\"]]\n )\n except:\n pass\n self.data = pd.DataFrame(\n data=self.data[\"data\"],\n columns=self.data[\"columns\"],\n index=self.data[\"index\"],\n )","def from_dict(self, dictionary: dict):\n raise NotImplementedError()","def from_dict(cls, odic):\n return dacite.from_dict(data_class=cls, data=odic)","def init_blank(self, T):\n self.headings = []\n self.table = {}\n self.rowcount = 0\n for e in T.entries:\n self.headings.append(e.name)\n self.table[e.name] = []","def __init__(self):\n self.table = {}\n self.ls = []","def from_dict(cls, data: 'collections.OrderedDict[str, Sequence]') \\\n -> 'PlainFrame':\n\n typed_columns, values = zip(*data.items())\n columns, dtypes = cls._parse_typed_columns(typed_columns)\n\n return cls.from_plain(data=values, columns=columns, dtypes=dtypes,\n row_wise=False)","def __init__(self, py_dict=None):\n super(VNIStatsTableEntrySchema, self).__init__()\n self.update_arp = None\n self.query_arp = None\n\n if py_dict is not None:\n self.get_object_from_py_dict(py_dict)","def __init__(self, *args):\n _table.Table_swiginit(self, _table.new_Table(*args))","def initializeFromDict(self, inputDict):\n pass","def __init__(self, *args):\n _snap.TTable_swiginit(self, _snap.new_TTable(*args))","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def _from_dict(cls, _dict):\n return cls.from_dict(_dict)","def init_from_dict(self, d):\n for k, v in d.items():\n # First, keys must be strings, not ints\n if isinstance(k, int):\n k = str(k)\n # Now, assign to the key, handling nested AttrDicts properly\n if isinstance(v, dict):\n self.set_key(k, AttrDict(v))\n elif isinstance(v, list):\n self.set_key(k, [i if not isinstance(i, dict) else AttrDict(i)\n for i in v])\n else:\n self.set_key(k, v)","def __init__(self, dim, connections_per_row=3):\n _table.STable_swiginit(self, _table.new_STable(dim, connections_per_row))","def from_dict(self, d):\n return Grid(**d)","def from_dict(cls, dct):\n pass","def from_dict(cls, d):\n d = d.copy()\n if \"length\" in d:\n # length argument removed in version 1.1.0\n del d[\"length\"]\n return cls(**d)","def __init__(self):\n self.buckets = 1009\n self.table = [{} for _ in range(self.buckets)]","def init_dict(self, train_data, dict_ord=None):\n raise NotImplementedError()","def from_dict(cls, copula_dict):\n raise NotImplementedError","def constructTable(table, records, columns, colNames):\n tableObject = {\n \"title\": table.name,\n \"records\": records,\n \"columns\": columns,\n \"colNames\": colNames,\n \"id\" : str(table.id),\n \"searchTerm\":table.searchTerm,\n \"sortBy\":table.sortBy,\n \"maxRows\":table.maxRows,\n \"isHereByDefault\":table.isDefaultOnDashboard,\n \"sizex\": table.sizex,\n \"sizey\": table.sizey,\n \"row\": table.row,\n \"col\": table.col\n }\n if table.objType:\n tableObject[\"objType\"] = table.objType\n tableObject[\"url\"] = reverse(\"crits.dashboards.views.load_data\",\n kwargs={\"obj\":table.objType})\n return tableObject","def from_dict(cls, d):\n return loadd(d, cls)","def _from_dict(cls, _dict: dict) -> 'BaseDataConnection':\n pass","def from_dict(self, dict_=None):\n for key in dict_.keys():\n if key == \"data\":\n self.data = dict_[key]\n elif key == \"axes\":\n for number, axis in enumerate(dict_[key]):\n self.axes[number].from_dict(axis)","def from_dict(cls, dictionary):\n normalised = cls.normalise_dict(dictionary)\n return cls.from_normalised_dict(normalised)","def __init__(self, dict):\n self.dict = dict","def __init__(self, dict):\n self.dict = dict","def __init__(self, plantsim, table_name):\n self._rows = []\n self._rows_coldict = []\n\n row_count = plantsim.get_value(f'{table_name}.YDim')\n col_count = plantsim.get_value(f'{table_name}.XDim')\n if row_count > 0 and col_count > 0:\n for row_idx in range(row_count + 1):\n row = []\n row_coldict = {}\n for col_idx in range(col_count + 1):\n cell_value = plantsim.get_value(f'{table_name}[{col_idx}, {row_idx}]')\n row.append(cell_value)\n if row_idx > 0:\n col_header = self.rows[0][col_idx]\n row_coldict[col_header] = cell_value\n self._rows.append(row)\n if row_idx > 0:\n self._rows_coldict.append(row_coldict)","def from_dict(cls, input_dict):\n expected_keys = set([\"row_start\", \"row_end\", \"col_start\", \"col_end\"])\n VERIFICATION.verify_type(input_dict, dict, \"input must be dict\")\n VERIFICATION.verify_value(set(input_dict.keys()) == expected_keys,\n \"expected keys: {0}\".format(expected_keys))\n\n return cls(input_dict[\"row_start\"],\n input_dict[\"row_end\"],\n input_dict[\"col_start\"],\n input_dict[\"col_end\"])","def from_dict(self, route_table):\n self._route_table = route_table\n return self","def __init__(self):\n _snap.TTableRow_swiginit(self, _snap.new_TTableRow())","def __init__(self, table):\n\n self.table = table\n\n ## Lots of shortcutting\n # \"Connection\"\n self.client = self.table.db.client\n\n # Table object\n self.worksheet = self.table.worksheet\n self.worksheet_id = self.table.worksheet_id\n\n # Addressing\n self.fields = self.table.fields\n\n ## And something to come later\n self.row = None\n self.data = {}","def __init__(self, **values):\r\n self.eid = values.get('_id')\r\n self._values = {}\r\n for name, column in self._columns.items():\r\n value = values.get(name, None)\r\n if value is not None:\r\n value = column.to_python(value)\r\n value_mngr = column.value_manager(self, column, value)\r\n self._values[name] = value_mngr","def from_dict(cls, data):\n return cls(**data)","def from_dict(cls, obj):\r\n raise NotImplementedError","def from_dict(self, dict_=None):\n for key in dict_:\n if hasattr(self, key):\n setattr(self, key, dict_[key])","def __init__(self, initial_data=[]):\n hdict.__init__(self)\n\n for elt in initial_data:\n self.add(elt)","def table_from_row_data(rows, **kwargs):\n table = Table(**kwargs)\n\n if len(rows) == 0:\n return table\n\n colnames = list(rows[0].keys())\n\n for name in colnames:\n coldata = [_[name] for _ in rows]\n if isinstance(rows[0][name], Quantity):\n coldata = Quantity(coldata, unit=rows[0][name].unit)\n table[name] = coldata\n\n return table","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def __init__(self, **kwargs):\n TableLoader.__init__(self, **kwargs)","def load(self, dct):\n self.items = list()\n if dct[\"type\"] == \"sep\":\n self.type = dct[\"type\"]\n for i in range(0, len(dct[\"items\"])):\n if dct[\"items\"][i] is None:\n self.items.append(LinkedChainTable())\n else:\n k = list()\n for j in range(0, len(dct[\"items\"][i])):\n k.append(createTableItem(dct[\"items\"][i][j], dct[\"items\"][i][j]))\n l = LinkedChainTable()\n l.load(k)\n self.items.append(l)\n self.n = len(dct[\"items\"])\n\n else:\n self.type = dct[\"type\"]\n for i in range(0, len(dct[\"items\"])):\n if dct[\"items\"][i] is None:\n self.items.append(None)\n else:\n self.items.append(createTableItem(dct[\"items\"][i], dct[\"items\"][i]))\n self.n = len(dct[\"items\"])","def from_dict(cls, dictionary: Dict[str, Any]):\n return cls(**dictionary)","def __init__(self):\n\n self._dict = OrderedDict(zip(const.BFHCOLS, [0] * 111))","def create_data_from_dict(storage, d, df):\n data = DataFactory.factories[storage].from_dict(d, df)\n return data"],"string":"[\n \"def _init_table(self, table: \\\"Table\\\"):\\n if not self.columns:\\n self.columns = table.columns\\n self._data = table.data\",\n \"def test_create_from_dicts(self):\\n cols = list(zip(*self.dtypes))[0]\\n dicts = [dict([(cols[i], d[i]) for i in xrange(len(d))])\\n for d in self.idata]\\n\\n tbl = Table.create(\\n ':memory:', \\\"Bar\\\", dicts, verbose=True,\\n primary_key='id', autoincrement=True)\\n\\n self.check_index(self.idata, tbl.select())\\n for idx, col in enumerate(cols):\\n if col == 'id':\\n continue\\n self.check_data(self.idata[:, [0, idx]], tbl[col])\",\n \"def from_dict(self, dictionary):\\n for column in self.__table__.columns.keys():\\n value = dictionary.get(column, None)\\n if value:\\n setattr(self, column, value)\",\n \"def __init__(self):\\n self.table = {}\",\n \"def from_dict(self, data: dict):\\n super().from_dict(data)\\n if self.data is not None:\\n try:\\n self.data[\\\"columns\\\"] = np.array(\\n [int(col) for col in self.data[\\\"columns\\\"]]\\n )\\n except:\\n pass\\n self.data = pd.DataFrame(\\n data=self.data[\\\"data\\\"],\\n columns=self.data[\\\"columns\\\"],\\n index=self.data[\\\"index\\\"],\\n )\",\n \"def from_dict(self, dictionary: dict):\\n raise NotImplementedError()\",\n \"def from_dict(cls, odic):\\n return dacite.from_dict(data_class=cls, data=odic)\",\n \"def init_blank(self, T):\\n self.headings = []\\n self.table = {}\\n self.rowcount = 0\\n for e in T.entries:\\n self.headings.append(e.name)\\n self.table[e.name] = []\",\n \"def __init__(self):\\n self.table = {}\\n self.ls = []\",\n \"def from_dict(cls, data: 'collections.OrderedDict[str, Sequence]') \\\\\\n -> 'PlainFrame':\\n\\n typed_columns, values = zip(*data.items())\\n columns, dtypes = cls._parse_typed_columns(typed_columns)\\n\\n return cls.from_plain(data=values, columns=columns, dtypes=dtypes,\\n row_wise=False)\",\n \"def __init__(self, py_dict=None):\\n super(VNIStatsTableEntrySchema, self).__init__()\\n self.update_arp = None\\n self.query_arp = None\\n\\n if py_dict is not None:\\n self.get_object_from_py_dict(py_dict)\",\n \"def __init__(self, *args):\\n _table.Table_swiginit(self, _table.new_Table(*args))\",\n \"def initializeFromDict(self, inputDict):\\n pass\",\n \"def __init__(self, *args):\\n _snap.TTable_swiginit(self, _snap.new_TTable(*args))\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def _from_dict(cls, _dict):\\n return cls.from_dict(_dict)\",\n \"def init_from_dict(self, d):\\n for k, v in d.items():\\n # First, keys must be strings, not ints\\n if isinstance(k, int):\\n k = str(k)\\n # Now, assign to the key, handling nested AttrDicts properly\\n if isinstance(v, dict):\\n self.set_key(k, AttrDict(v))\\n elif isinstance(v, list):\\n self.set_key(k, [i if not isinstance(i, dict) else AttrDict(i)\\n for i in v])\\n else:\\n self.set_key(k, v)\",\n \"def __init__(self, dim, connections_per_row=3):\\n _table.STable_swiginit(self, _table.new_STable(dim, connections_per_row))\",\n \"def from_dict(self, d):\\n return Grid(**d)\",\n \"def from_dict(cls, dct):\\n pass\",\n \"def from_dict(cls, d):\\n d = d.copy()\\n if \\\"length\\\" in d:\\n # length argument removed in version 1.1.0\\n del d[\\\"length\\\"]\\n return cls(**d)\",\n \"def __init__(self):\\n self.buckets = 1009\\n self.table = [{} for _ in range(self.buckets)]\",\n \"def init_dict(self, train_data, dict_ord=None):\\n raise NotImplementedError()\",\n \"def from_dict(cls, copula_dict):\\n raise NotImplementedError\",\n \"def constructTable(table, records, columns, colNames):\\n tableObject = {\\n \\\"title\\\": table.name,\\n \\\"records\\\": records,\\n \\\"columns\\\": columns,\\n \\\"colNames\\\": colNames,\\n \\\"id\\\" : str(table.id),\\n \\\"searchTerm\\\":table.searchTerm,\\n \\\"sortBy\\\":table.sortBy,\\n \\\"maxRows\\\":table.maxRows,\\n \\\"isHereByDefault\\\":table.isDefaultOnDashboard,\\n \\\"sizex\\\": table.sizex,\\n \\\"sizey\\\": table.sizey,\\n \\\"row\\\": table.row,\\n \\\"col\\\": table.col\\n }\\n if table.objType:\\n tableObject[\\\"objType\\\"] = table.objType\\n tableObject[\\\"url\\\"] = reverse(\\\"crits.dashboards.views.load_data\\\",\\n kwargs={\\\"obj\\\":table.objType})\\n return tableObject\",\n \"def from_dict(cls, d):\\n return loadd(d, cls)\",\n \"def _from_dict(cls, _dict: dict) -> 'BaseDataConnection':\\n pass\",\n \"def from_dict(self, dict_=None):\\n for key in dict_.keys():\\n if key == \\\"data\\\":\\n self.data = dict_[key]\\n elif key == \\\"axes\\\":\\n for number, axis in enumerate(dict_[key]):\\n self.axes[number].from_dict(axis)\",\n \"def from_dict(cls, dictionary):\\n normalised = cls.normalise_dict(dictionary)\\n return cls.from_normalised_dict(normalised)\",\n \"def __init__(self, dict):\\n self.dict = dict\",\n \"def __init__(self, dict):\\n self.dict = dict\",\n \"def __init__(self, plantsim, table_name):\\n self._rows = []\\n self._rows_coldict = []\\n\\n row_count = plantsim.get_value(f'{table_name}.YDim')\\n col_count = plantsim.get_value(f'{table_name}.XDim')\\n if row_count > 0 and col_count > 0:\\n for row_idx in range(row_count + 1):\\n row = []\\n row_coldict = {}\\n for col_idx in range(col_count + 1):\\n cell_value = plantsim.get_value(f'{table_name}[{col_idx}, {row_idx}]')\\n row.append(cell_value)\\n if row_idx > 0:\\n col_header = self.rows[0][col_idx]\\n row_coldict[col_header] = cell_value\\n self._rows.append(row)\\n if row_idx > 0:\\n self._rows_coldict.append(row_coldict)\",\n \"def from_dict(cls, input_dict):\\n expected_keys = set([\\\"row_start\\\", \\\"row_end\\\", \\\"col_start\\\", \\\"col_end\\\"])\\n VERIFICATION.verify_type(input_dict, dict, \\\"input must be dict\\\")\\n VERIFICATION.verify_value(set(input_dict.keys()) == expected_keys,\\n \\\"expected keys: {0}\\\".format(expected_keys))\\n\\n return cls(input_dict[\\\"row_start\\\"],\\n input_dict[\\\"row_end\\\"],\\n input_dict[\\\"col_start\\\"],\\n input_dict[\\\"col_end\\\"])\",\n \"def from_dict(self, route_table):\\n self._route_table = route_table\\n return self\",\n \"def __init__(self):\\n _snap.TTableRow_swiginit(self, _snap.new_TTableRow())\",\n \"def __init__(self, table):\\n\\n self.table = table\\n\\n ## Lots of shortcutting\\n # \\\"Connection\\\"\\n self.client = self.table.db.client\\n\\n # Table object\\n self.worksheet = self.table.worksheet\\n self.worksheet_id = self.table.worksheet_id\\n\\n # Addressing\\n self.fields = self.table.fields\\n\\n ## And something to come later\\n self.row = None\\n self.data = {}\",\n \"def __init__(self, **values):\\r\\n self.eid = values.get('_id')\\r\\n self._values = {}\\r\\n for name, column in self._columns.items():\\r\\n value = values.get(name, None)\\r\\n if value is not None:\\r\\n value = column.to_python(value)\\r\\n value_mngr = column.value_manager(self, column, value)\\r\\n self._values[name] = value_mngr\",\n \"def from_dict(cls, data):\\n return cls(**data)\",\n \"def from_dict(cls, obj):\\r\\n raise NotImplementedError\",\n \"def from_dict(self, dict_=None):\\n for key in dict_:\\n if hasattr(self, key):\\n setattr(self, key, dict_[key])\",\n \"def __init__(self, initial_data=[]):\\n hdict.__init__(self)\\n\\n for elt in initial_data:\\n self.add(elt)\",\n \"def table_from_row_data(rows, **kwargs):\\n table = Table(**kwargs)\\n\\n if len(rows) == 0:\\n return table\\n\\n colnames = list(rows[0].keys())\\n\\n for name in colnames:\\n coldata = [_[name] for _ in rows]\\n if isinstance(rows[0][name], Quantity):\\n coldata = Quantity(coldata, unit=rows[0][name].unit)\\n table[name] = coldata\\n\\n return table\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def __init__(self, **kwargs):\\n TableLoader.__init__(self, **kwargs)\",\n \"def load(self, dct):\\n self.items = list()\\n if dct[\\\"type\\\"] == \\\"sep\\\":\\n self.type = dct[\\\"type\\\"]\\n for i in range(0, len(dct[\\\"items\\\"])):\\n if dct[\\\"items\\\"][i] is None:\\n self.items.append(LinkedChainTable())\\n else:\\n k = list()\\n for j in range(0, len(dct[\\\"items\\\"][i])):\\n k.append(createTableItem(dct[\\\"items\\\"][i][j], dct[\\\"items\\\"][i][j]))\\n l = LinkedChainTable()\\n l.load(k)\\n self.items.append(l)\\n self.n = len(dct[\\\"items\\\"])\\n\\n else:\\n self.type = dct[\\\"type\\\"]\\n for i in range(0, len(dct[\\\"items\\\"])):\\n if dct[\\\"items\\\"][i] is None:\\n self.items.append(None)\\n else:\\n self.items.append(createTableItem(dct[\\\"items\\\"][i], dct[\\\"items\\\"][i]))\\n self.n = len(dct[\\\"items\\\"])\",\n \"def from_dict(cls, dictionary: Dict[str, Any]):\\n return cls(**dictionary)\",\n \"def __init__(self):\\n\\n self._dict = OrderedDict(zip(const.BFHCOLS, [0] * 111))\",\n \"def create_data_from_dict(storage, d, df):\\n data = DataFactory.factories[storage].from_dict(d, df)\\n return data\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7078723","0.69768757","0.6741791","0.6514259","0.6489797","0.6371205","0.63667476","0.6355663","0.63450754","0.6337645","0.63217604","0.63029504","0.6181961","0.61749095","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.61712486","0.6170315","0.61622685","0.6157969","0.61442095","0.6125456","0.60789865","0.607398","0.60734284","0.604024","0.6039682","0.6022634","0.60183686","0.60101426","0.59899193","0.59899193","0.5967622","0.59669363","0.59654844","0.59602726","0.5950385","0.5943936","0.5943624","0.5925885","0.59219617","0.58955","0.58846927","0.5883674","0.5883674","0.5883674","0.5883674","0.5883674","0.5883674","0.5883674","0.5883674","0.5883674","0.5883674","0.5883674","0.5880213","0.58513474","0.5837635","0.5837272"],"string":"[\n \"0.7078723\",\n \"0.69768757\",\n \"0.6741791\",\n \"0.6514259\",\n \"0.6489797\",\n \"0.6371205\",\n \"0.63667476\",\n \"0.6355663\",\n \"0.63450754\",\n \"0.6337645\",\n \"0.63217604\",\n \"0.63029504\",\n \"0.6181961\",\n \"0.61749095\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.61712486\",\n \"0.6170315\",\n \"0.61622685\",\n \"0.6157969\",\n \"0.61442095\",\n \"0.6125456\",\n \"0.60789865\",\n \"0.607398\",\n \"0.60734284\",\n \"0.604024\",\n \"0.6039682\",\n \"0.6022634\",\n \"0.60183686\",\n \"0.60101426\",\n \"0.59899193\",\n \"0.59899193\",\n \"0.5967622\",\n \"0.59669363\",\n \"0.59654844\",\n \"0.59602726\",\n \"0.5950385\",\n \"0.5943936\",\n \"0.5943624\",\n \"0.5925885\",\n \"0.59219617\",\n \"0.58955\",\n \"0.58846927\",\n \"0.5883674\",\n \"0.5883674\",\n \"0.5883674\",\n \"0.5883674\",\n \"0.5883674\",\n \"0.5883674\",\n \"0.5883674\",\n \"0.5883674\",\n \"0.5883674\",\n \"0.5883674\",\n \"0.5883674\",\n \"0.5880213\",\n \"0.58513474\",\n \"0.5837635\",\n \"0.5837272\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6601733"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":3998,"cells":{"query":{"kind":"string","value":"Validate that given column names can be used."},"document":{"kind":"string","value":"def _validate_columns(self, names):\n if not is_list_like(names):\n raise ValueError(\"Columns should be list-like\")\n\n if len(set(names)) != len(names):\n raise ValueError(\"Duplicate column names\")\n\n if self._data and len(names) != len(self._data[0]):\n raise ValueError(\"Invalid columns length\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _check_columns(df: pd.DataFrame, names: typing.Sequence[str]) -> None:\n for expected in names:\n if expected not in df.columns:\n raise ValueError(f\"'{expected}' column not found in input\")\n return","def _validate_columns(data, ip_column, lat_column, long_column, other_columns):\n if not ip_column and not (lat_column and long_column):\n raise ValueError(\n \"Data must have either an IpAddress ('ip_column')\",\n \"or latitude ('lat_column') and longitude ('long_column')\",\n )\n param_cols: List[str] = []\n for param in other_columns:\n if not param:\n continue\n if isinstance(param, list):\n param_cols.extend(param)\n else:\n param_cols.append(param)\n missing_columns = {col for col in param_cols if col not in data.columns}\n if missing_columns:\n raise LookupError(\n \"The following columns are not in the supplied DataFrame\",\n \",\".join(f\"'{col}'\" for col in missing_columns),\n )","def validate_column_names(self, cols):\n self.stdout.write('Verifying CSV header')\n csv_cols = set(cols)\n if self.required_csv_columns <= csv_cols:\n return True\n else:\n missing_cols = set(self.required_csv_columns).difference(csv_cols)\n raise ValidationError(\n \"These columns '{0}' are required, but missing in the CSV \"\n \"file.\".format(\n ', '.join(missing_cols)\n )\n )","def validate_columns(self, fieldnames, dao):\n unstored_columns = ['blank']\n expected_columns = dao.model_type.__table__.columns.keys() + unstored_columns\n for column_name in fieldnames:\n if column_name not in expected_columns:\n raise AttributeError(f\"{self.file_path}: {column_name} column mismatch for \"\n f\"expected file type: {self.file_type.name}\")","def checkcolumnstest(chosen_columns, chosen_df):\n if not all([item in chosen_columns for item in chosen_df.columns]):\n raise ValueError('Columns do not match')","def _validate_cols(cols):\n\n\tif cols is not None and len(cols) < 2:\n\t\traise ValueError('too few features')","def _check_columns_with_table(table: Table, columns: Sequence[str]) -> Optional[bool]:\n for column in columns:\n if column not in table.c.keys():\n raise TypeError(f\"Specified column {column} did not exist on table {table}\")\n return True","def verify_columns_in_dataset(self, columns):\n all_cols = self.dataset.columns\n for col in columns:\n if not col in all_cols:\n raise KeyError(\"column '%s' not in dataset\" % col)","def is_cols_valid(bd):\n for col in cols:\n seen = []\n for num in nums:\n if bd[col[num]] == \" \":\n continue\n elif bd[col[num]] not in seen:\n seen += [bd[col[num]]]\n else:\n return False\n else:\n continue\n return True","def cols_valid(self,\n df: pd.DataFrame,\n req_cols: set) -> bool:\n missing_cols = req_cols.difference(df.columns)\n\n if len(missing_cols) > 0:\n logging.error(f\"{missing_cols} columns required but missing\")\n return False\n\n return True","def _check_headers(cursor, headers):\n all_columns = set(chain.from_iterable(_columns(cursor, table) for table in DATA_TABLES))\n for header in headers:\n if header not in all_columns:\n raise ValueError('column {} not recognized'.format(header))","def verify_columns_in_dataset(self, columns):\n all_cols = self.train.columns\n for col in columns:\n if not col in all_cols:\n raise KeyError(\"column '%s' not in dataset\" % col)","def _check_missing_columns(self, df: pd.DataFrame) -> None:\n if any([c not in df.columns for c in REQUIRED_COLUMNS]):\n raise ValueError(\"Missing columns in dataset.\"\n f\"Columns: {df.columns}\"\n f\"Required: {REQUIRED_COLUMNS}\")","def validate_col_lst(self, df, columns_lst):\n if columns_lst == []:\n raise ValueError(\"column_lst is empty\")\n col_set = set(columns_lst)\n df_col_set = set(list(df))\n if col_set - df_col_set != set():\n msg = \"col_lst has columns name that does not exists in the DataFrame columns:{}\".format(\n str(col_set - df_col_set))\n print(msg)\n raise ValueError(msg)\n return True","def check_ingress_required_columns(self, col_names):\n if not set(col_names).issuperset(REQUIRED_COLUMNS):\n if not set(col_names).issuperset(REQUIRED_ALT_COLUMNS):\n missing_columns = [x for x in REQUIRED_ALT_COLUMNS if x not in col_names]\n return missing_columns\n return None","def check_columns_in_dataframe(df: pd.DataFrame, columns: Tuple[str]) -> None:\n\n for col in columns:\n if col not in df.columns:\n raise ValueError(f\"Column {col} is not in the dataframe.\")","def _dataframe_column_check(df: DataFrame, compulsory_columns: Sequence) -> None:\n if not set(compulsory_columns).issubset(df.columns):\n diff = set(compulsory_columns).difference(df.columns)\n msg = (\n \"The following compulsory column(s) are missing from the \"\n f\"DataFrame: {diff}\"\n )\n raise ValueError(msg)","def verify_columns_in_dataframe(df, columns):\n\n if not isinstance(columns, list):\n columns = [columns]\n return set(columns).issubset(df.columns)","def _check_columns(\n schema_errors: set[str],\n stored: Mapping,\n expected: Mapping,\n columns: Iterable[str],\n table_name: str,\n supports: str,\n) -> None:\n for column in columns:\n if stored[column] == expected[column]:\n continue\n schema_errors.add(f\"{table_name}.{supports}\")\n _LOGGER.error(\n \"Column %s in database table %s does not support %s (stored=%s != expected=%s)\",\n column,\n table_name,\n supports,\n stored[column],\n expected[column],\n )","def _check_columns(cdm_column_names, csv_columns, result):\n columns_valid = True\n\n # if len(csv_columns) != len(cdm_column_names):\n\n # check all column headers in the file\n for col in csv_columns:\n if col not in cdm_column_names:\n e = dict(message=MSG_INCORRECT_HEADER, column_name=col, actual=col)\n result['errors'].append(e)\n columns_valid = False\n\n # check cdm table headers against headers in file\n for col in cdm_column_names:\n if col not in csv_columns:\n e = dict(message=MSG_MISSING_HEADER, column_name=col, expected=col)\n result['errors'].append(e)\n columns_valid = False\n\n # check order of cdm table headers against headers in file\n for idx, col in enumerate(cdm_column_names):\n if idx < len(csv_columns) and csv_columns[idx] != col:\n e = dict(message=MSG_INCORRECT_ORDER,\n column_name=csv_columns[idx],\n actual=csv_columns[idx],\n expected=col)\n result['errors'].append(e)\n columns_valid = False\n break\n\n return columns_valid","def check_cols_methane(name):\n return True if name in ['SampleDay', 'SampleHour', 'Decimal Year',\n 'Peak Area 1', 'Peak Area 2', 'Run median', 'Daily Median'] else False","def validate_match_columns(import_log, field_names, model_class, header_row):\n errors = []\n column_matches = import_log.import_setting.columnmatch_set.all()\n for field_name in field_names:\n field_object, model, direct, m2m = model_class._meta.get_field_by_name(field_name)\n if (direct and\n model and\n not field_object.blank):\n field_matches = column_matches.filter(field_name=field_name)\n if field_matches:\n if field_matches[0].column_name not in header_row:\n errors += [\"{0} is required but is not in your spreadsheet. \".format(field_object.verbose_name)]\n else:\n errors += [\"{0} is required but has no match.\".format(field_object.verbose_name)]\n \n return errors","def _assert_columns_exist(self, columns):\n if not nonstringiter(columns):\n columns = (columns,)\n self_cols = self.columns()\n is_missing = lambda col: col not in self_cols\n missing = [c for c in columns if is_missing(c)]\n if missing:\n missing = ', '.join(repr(x) for x in missing)\n msg = '{0} not in {1}'.format(missing, self.__repr__())\n raise LookupError(msg)","def check_column(self, columns):\n for i in columns:\n if i.name == self.name:\n raise ColumnNameAlreadyInTableException(f'Column \"{self.name}\" is already in the table!')\n return True","def check_df_col(df, column, name=None):\n if column is not None:\n\n if type(column) != list:\n\n column = [column]\n\n for col in column:\n if name is None:\n error_message = f\"The value '{col}' is not present in any of the columns of your DataFrame.\"\n else:\n error_message = f\"Your {name} value '{col}' is not present in any of the columns of your DataFrame.\"\n error_message += \"\\nYou may be looking for:\\n \" + str(list(df.columns))\n\n assert col in df.columns, error_message","def check_dataframe_columns(df):\r\n if len(set(df.columns).intersection(\r\n set([constants.CASE_CONCEPT_NAME, xes_constants.DEFAULT_NAME_KEY,\r\n xes_constants.DEFAULT_TIMESTAMP_KEY]))) < 3:\r\n raise Exception(\r\n \"please format your dataframe accordingly! df = pm4py.format_dataframe(df, case_id='<name of the case ID column>', activity_key='<name of the activity column>', timestamp_key='<name of the timestamp column>')\")","def verify(self):\n for col in self.columns:\n if col not in self.table_obj.columns.keys():\n raise Exception('{} column not found in {}'.format(\n col, self.table_obj))","def _validate_data(df):\n if constants.IMAGE_URI_KEY not in df.columns:\n # or label_col not in df.columns:\n raise AttributeError(\n 'DataFrame must contain image_uri column {}.')\n if constants.LABEL_KEY not in df.columns:\n raise AttributeError(\n 'DataFrame must contain label column.')\n if constants.SPLIT_KEY not in df.columns:\n raise AttributeError(\n 'DataFrame must contain split column.')\n if list(df.columns) != constants.IMAGE_CSV_COLUMNS:\n raise AttributeError(\n 'DataFrame column order must be {}'.format(\n constants.IMAGE_CSV_COLUMNS))","def check_column_values(self, values):\n none_keys = sorted(list(self._necessary_input_columns.intersection(set([elem for elem in self._columns if values[self.column_id[elem]] in [None, 'None']]))))\n if len(none_keys) > 0:\n raise Exception('missing_keys in ForcingOnMesh_DBManager add function parameter file_info:\\n%s\\n'%('\\n'.join([' - %s'%elem for elem in none_keys])))","def check_column_names(expected_headings, found_headings):\n column_missing = False\n column_additional = False\n\n # Check if column headings exist\n logging.info(\"Checking column headers are correct.\")\n diff_columns = set(expected_headings) - set(found_headings)\n if len(diff_columns) > 0:\n column_missing = True\n\n # Check whether there are any additional columns (could need renaming)\n extra_columns = set(found_headings) - set(expected_headings)\n if len(extra_columns) > 0:\n column_additional = True\n\n # Check for duplicate headings\n # NOTE: As mangle_dupe_cols=True, any duplicate columns will be stored in the form column.1.... column.N\n # We use this to avoid overwriting data. However, to identify duplicate original columns, we need to remove\n # these prior to checking for dups\n main_column_names = [i.split(\".\")[0] for i in found_headings]\n duplicate_headings = len(main_column_names) > len(set(main_column_names))\n if duplicate_headings:\n logging.error(\"Duplicate headings identified.\")\n if column_missing:\n logging.error(\"Missing headers identified:\")\n print(diff_columns)\n if column_additional:\n logging.error(\"Additional headers identified:\")\n print(extra_columns)\n if column_missing or column_additional or duplicate_headings:\n logging.info(\n \"File will not pass checks as I am unable to tell \"\n \"what to do with the columns on my own.\"\n )\n return False\n return True","def validate(self):\n super().validate()\n frame = getattr(self, 'frame', None)\n if frame is None:\n raise ValueError('Missing columns %s since no frame' % ', '.join(\n self.required_cols))\n cols = set(list(self.frame))\n missing = sorted(self.required_cols - cols)\n if missing:\n raise ValueError('Missing columns: [%s]' % ', '.join(missing))","def test_column_presence(self):\n\n columns = [\n \"assay_ontology_term_id\",\n \"development_stage_ontology_term_id\",\n \"disease_ontology_term_id\",\n \"ethnicity_ontology_term_id\",\n \"is_primary_data\",\n \"sex_ontology_term_id\",\n \"tissue_ontology_term_id\",\n ]\n\n for column in columns:\n with self.subTest(column=column):\n self.validator.errors = []\n self.validator.adata = examples.adata.copy()\n\n self.validator.adata.obs.drop(column, axis=1, inplace=True)\n # Remove batch condition because it has a dependency with is_primary_data\n self.validator.adata.uns.pop(\"batch_condition\")\n\n self.validator.validate_adata()\n self.assertEqual(\n self.validator.errors,\n [f\"ERROR: Dataframe 'obs' is missing \" f\"column '{column}'.\"],\n )","def validate(self):\r\n for name, col in self._columns.items():\r\n val = col.validate(getattr(self, name))\r\n setattr(self, name, val)","def setRequiredColumns(self, colnames):\n # Make sure all column names are lower case so comparisons in _TableRow\n # are not case sensitive. From a modularity standpoint, this should be\n # done in _TableRow, but it is more efficient to do it here, since the\n # conversion need be done only once.\n self.required_cols = [colname.lower() for colname in colnames]","def validate_custom_columns(record_custom_columns):\n\n\tcustom_column_name_errors = []\n\n\tfor k, v in record_custom_columns.items():\n\t\tfield_name = \"Custom Column: \" + k\n\t\tfield_desc = \"Column Description: \" + v\n\n\t\tif not re.match(character_regex_with_space, k):\n\t\t\tmessage = get_regex_mismatch_error_text(field_name, character_regex)\n\t\t\tcustom_column_name_errors.append(message)\n\n\t\tif not re.match(character_regex_with_space, v):\n\t\t\tmessage = get_regex_mismatch_error_text(field_desc, character_regex_with_space)\n\t\t\tcustom_column_name_errors.append(message)\n\n\t\tif (len(k) > field_length_limit):\n\t\t\tmessage = get_field_length_error_text(field_name)\n\t\t\tcustom_column_name_errors.append(message)\n\n\t\tif (len(v) > field_length_limit):\n\t\t\tmessage = get_field_length_error_text(field_desc)\n\t\t\tcustom_column_name_errors.append(message)\n\n\treturn custom_column_name_errors","def verify(self):\n for col in self._columns:\n if col not in self._table_obj.columns.keys():\n raise GaiaException('{} column not found in {}'.format(\n col, self._table_obj))","def _validate_optional_columns(data, optional_columns: Iterable[str]) -> List[str]:\n return [col for col in optional_columns if col in data.columns]","def test_set_col_names_exception(self):\n with self.assertRaises(ValueError) as ctx:\n self.dboard.set_col_names([\"A\", \"B\", \"C\"])\n\n self.assertEqual(\"'names' list size does not match the number of columns allocated\", str(ctx.exception))","def __validate_col_prefix(col, prefixes, input_name):\n\n missing = [not col.startswith(p) for p in prefixes]\n if all(missing):\n msg = (\"Input {0} column {1!r} does not start with a valid \"\n \"prefix: {2!r}. Please ensure that the {0} column \"\n \"names specify the correct resource prefix.\")\n e = msg.format(input_name, col, prefixes)\n logger.error(e)\n raise InputError(e)","def test_columns_str_error(self):\n\n df = d.create_df_1()\n\n x = BaseTransformer(columns=None)\n\n x.columns = \"a\"\n\n with pytest.raises(ValueError):\n\n x.columns_check(X=df)","def test_invalid_columns():\n train = ((\"Lorem ipsum dolor sit amet\", 3),\n (\"Sed ut perspiciatis unde\", 5.5))\n with pytest.raises(ValueError):\n TabularDataset(train, named_columns=['some_random_col'])","def validate(self):\n super().validate()\n frame = getattr(self, 'frame', None)\n if frame is None:\n raise ValueError('Missing columns %s since no frame' % ', '.join(\n [c[0] for c in self.col_regexps]))\n for col_name, c_re in self.col_regexps:\n if col_name not in self.frame:\n raise ValueError('Missing required column %s' % col_name)\n if c_re is None:\n continue # Just verified that column is present\n c_re_c = re.compile(c_re)\n for date, item in self.frame[col_name].iteritems():\n if not c_re_c.match(item):\n raise ValueError(\n 'In column %s, index %s, item %s fails regexp %s' % (\n col_name, date, item, c_re))","def test_clean_columns():\n assert clean_columns('Id, AdCampaignId, CampaignId') == ['id', 'adCampaignId', 'campaignId']","def _check_required_columns(self, param_df, var_name='param_mean'):\n\n if param_df is None:\n return pd.DataFrame()\n\n try:\n if param_df.shape[0] == 0:\n return pd.DataFrame(columns=list(set(self.required_columns[var_name])|set(param_df.columns)))\n\n if self.required_columns[var_name] - set(param_df.columns) == set([]): # df has required cols.\n return param_df\n else:\n note = \"'{}' must be a pd.DataFrame with the following column names: \".format(var_name) + \\\n _list_the_errors(self.required_columns[var_name] - set(param_df.columns)) + \".\"\n raise ValueError(note)\n except KeyError:\n raise KeyError(\"'{}' is not supported\".format(var_name))","def check_schema_definition(schema_definition: pd.DataFrame) -> bool:\n\n if required_headers.issubset(set(list(schema_definition.columns))):\n return\n elif \"Requires\" in list(schema_definition.columns) or \"Requires Component\" in list(\n schema_definition.columns\n ):\n raise ValueError(\n \"The input CSV schema file contains the 'Requires' and/or the 'Requires \"\n \"Component' column headers. These columns were renamed to 'DependsOn' and \"\n \"'DependsOn Component', respectively. Switch to the new column names.\"\n )","def check_cols(self):\n if self.ad_tab is not None and 'date' not in self.ad_cols:\n raise DataException(\"\"\"date column not found in adServer table.\"\"\")\n if self.ad_tab is not None and 'impressions' not in self.ad_cols:\n raise DataException(\"\"\"impressions column not found in adServer table.\"\"\")\n if 'timestamp' not in self.log_cols and 'date' not in self.log_cols:\n raise DataException(\"\"\"Both timestamp and date column missing from {t}\nCannot do dailyQA\"\"\".format(t=self.log_tab))\n if self.configs['hourshift'] != 0 or 'date' not in self.log_cols:\n if 'timestamp' not in self.log_cols:\n raise DataException(\"\"\"Time shift requested \\\nbut no timestamp column in {t}.\"\"\".format(t=self.log_tab))\n else:\n check_timestamp(self.configs['schema'], self.log_tab)","def test_columns_not_in_X_error(self):\n\n df = d.create_df_1()\n\n x = BaseTransformer(columns=[\"a\", \"z\"])\n\n with pytest.raises(ValueError):\n\n x.columns_check(X=df)","def validate_dataframe(\n df: pd.DataFrame, settings: Settings = DefaultSettings()\n) -> None:\n if df.columns.dtype != object or not (df.columns.map(type) == str).all():\n raise ValueError(\"column names must all be str\")\n\n for colname, uccolname in zip(\n list(df.columns), gen_unique_clean_colnames(list(df.columns), settings=settings)\n ):\n if uccolname.is_ascii_cleaned:\n raise ValueError(\n 'column name \"%s\" must not contain ASCII control characters' % colname\n )\n if uccolname.is_unicode_fixed:\n # `str(\"x \\ud800 x\")` doesn't crash, so this ValueError should be safe to print\n raise ValueError(\n 'column name \"%s\" must not contain invalid Unicode surrogates'\n % colname,\n )\n if uccolname.is_default:\n raise ValueError('column name \"%s\" must not be empty' % colname)\n if uccolname.is_truncated:\n raise ValueError(\n 'column name \"%s\" must contain %d bytes or fewer'\n % (\n colname,\n settings.MAX_BYTES_PER_COLUMN_NAME,\n )\n )\n if uccolname.is_numbered:\n raise ValueError(\n 'column name \"%s\" must not appear more than once' % colname\n )\n\n if not df.index.equals(pd.RangeIndex(0, len(df))):\n raise ValueError(\n \"must use the default RangeIndex — \"\n \"try table.reset_index(drop=True, inplace=True)\"\n )\n\n for column in df.columns:\n validate_series(df[column])","def _valid_column(column_name):\n return str(column_name)","def _validate_ratio_cols_exist(self):\n\n for col in self._ratio_cols:\n no_prefix_name = \"_\".join(col.split('_')[1:])\n if not self.data.contains_col(no_prefix_name):\n msg = (\"Input ratios column {!r} not found in either meta \"\n \"data! Please check the input files {!r} and {!r}\")\n e = msg.format(no_prefix_name, self.data.solar_fpath,\n self.data.wind_fpath)\n logger.error(e)\n raise FileInputError(e)","def table_is_keyed_by_columns(self, table, *, column_names: Iterable[str]) -> bool:\n # get rid of some corner cases\n if table.shape[0] < 2:\n return True\n if (column_names is None):\n return False\n # check for ill-condition\n if isinstance(column_names, str):\n column_names = [column_names]\n else:\n column_names = list(column_names)\n missing_columns = set(column_names) - set(table.columns)\n if len(missing_columns) > 0:\n return False\n # get rid of some corner cases\n if len(column_names) < 1:\n return False\n mx = (\n table\n .select(column_names)\n .with_columns([pl.lit(1, pl.Int64).alias(\"_da_count_tmp\")])\n .groupby(column_names)\n .sum()[\"_da_count_tmp\"]\n .max()\n )\n return mx <= 1","def test_extract_multiple_invalid_columns(self):\n keywords = [\"invalid\", \"another_invalid_col\"]\n self.dicom.extract_keywords(keywords)\n\n # test that columns were added\n columns = self.dicom.metadata.column_names\n if u'invalid' not in columns:\n raise Exception(\"invalid column not added to columns\")\n if u'another_invalid_col' not in columns:\n raise Exception(\"another_invalid_col not added to columns\")\n\n # compare actual with expected result\n invalid_columns = self.dicom.metadata.take(self.count, columns=keywords)\n expected_result = [[None, None] for x in range(0, self.count)]\n self.assertEqual(invalid_columns, expected_result)","def validate_required_fields(dataframe):\n\n if dataframe is None:\n raise ValueError(\"It was not provided a valid Dataframe.\")","def test_column_presence(self):\n\n columns = [\"feature_is_filtered\", \"feature_biotype\"]\n\n for component_name in [\"var\", \"raw.var\"]:\n for column in columns:\n if column == \"feature_is_filtered\" and component_name == \"raw.var\":\n continue\n with self.subTest(component_name=component_name, column=column):\n\n # Resetting validator\n self.validator.errors = []\n self.validator.adata = examples.adata.copy()\n\n component = Validator.getattr_anndata(\n self.validator.adata, component_name\n )\n component.drop(column, axis=1, inplace=True)\n\n self.validator.validate_adata()\n self.assertEqual(\n self.validator.errors,\n [\n f\"ERROR: Dataframe '{component_name}' is missing \"\n f\"column '{column}'.\"\n ],\n )","def validate(self):\r\n for name in self._columns.keys():\r\n func_name = 'validate_{}'.format(name)\r\n val = getattr(self, name)\r\n if hasattr(self, func_name):\r\n val = getattr(self, func_name)(val)\r\n else:\r\n val = self.validate_field(name, val)\r\n setattr(self, name, val)","def test_quoted_column_names_reading_specify_names(self):\n self.quoted_column_names_reading_template(specify_column_names=True)","def _validate_column_name(col_name : str) -> str:\n\n if col_name[0].isdigit():\n return f'\"{col_name}\"'\n return col_name","def check_column(self, table_name: str, column_name: str) -> bool:\n try:\n insp = reflection.Inspector.from_engine(self.engine)\n for col in insp.get_columns(table_name):\n if column_name in col[\"name\"]:\n return True\n return False\n except Exception as err:\n logger.error(\"check_column [error] -> %s\" % err)\n return False","def check_column(data, functions, threshold):\n\n # Apply the functions to the column to return True/False values\n data = data.map(lambda x: any(f(x) for f in functions)).copy()\n # Identify the number of incorrect values\n data_invalid = data.sum()\n # Identify the number of values in the column\n data_total = data.count()\n\n if data_total == 0 or data_invalid == data_total:\n # If entire column is invalid or empty\n logging.error(\"Header supplied, but all data invalid or missing.\")\n return False\n else:\n # Find the percentage of invalid values\n data_perc = data_invalid / data_total\n\n # Check whether the % invalid values is above or below the threshold\n if data_perc > threshold:\n logging.error(f\"{data_perc*100 : .2f}% of values are blank or invalid\")\n return False\n\n return True","def check_column(rule, column):\n for value in column:\n if not check_ranges(rule, value):\n return False\n return True","def _validate_plaincolumns(self):\n\n # assert tuples for plaincolumns and plaincolumns to be PlainColumn\n if not isinstance(self.plaincolumns, tuple):\n raise ValueError(\"PlainFrame was instantiated incorrectly. \"\n \"`plaincolumns` needs to be of type `tuple`. \"\n \"However, {} was encountered. Please use \"\n \"`PlainFrame.from_plain` instead for convenient \"\n \"instantiation and proper type casts.\"\n .format(type(self.plaincolumns)))\n\n not_plaincolumn = [type(column)\n for column in self.plaincolumns\n if not isinstance(column, PlainColumn)]\n\n if not_plaincolumn:\n raise ValueError(\"PlainFrame was instantiated incorrectly. \"\n \"Elements of `plaincolumns` needs to be of type \"\n \"`PlainColumn`. However, {} was encountered. \"\n \"Please use `PlainFrame.from_plain` instead for \"\n \"convenient instantiation and proper type casts.\"\n .format(not_plaincolumn))\n\n # assert equal number of values per column\n row_lenghts = {len(column.values) for column in self.plaincolumns}\n if len(row_lenghts) > 1:\n raise ValueError(\"Input data has varying number of values per \"\n \"column. Please check provided input data.\")\n\n # assert unique column names\n duplicates = {x for x in self.columns if self.columns.count(x) > 1}\n if duplicates:\n raise ValueError(\"Duplicated column names encountered: {}. \"\n \"Please use unique column names.\"\n .format(duplicates))","def columns(self, names):\n self._validate_columns(names)\n self._columns = list(names)","def validate_parameters(\n data: pd.DataFrame,\n key_columns: Union[List[str], Tuple[str]],\n parameter_columns: Union[List[str], Tuple],\n value_columns: Union[List[str], Tuple[str]],\n):\n if (\n data is None\n or (isinstance(data, pd.DataFrame) and data.empty)\n or (isinstance(data, (list, tuple)) and not data)\n ):\n raise ValueError(\"Must supply some data\")\n\n if not isinstance(data, (Number, datetime, timedelta, list, tuple, pd.DataFrame)):\n raise TypeError(\n f\"The only allowable types for data are number, datetime, timedelta, \"\n f\"list, tuple, or pandas.DataFrame. You passed {type(data)}.\"\n )\n\n if isinstance(data, (list, tuple)):\n if not value_columns:\n raise ValueError(\n f\"To invoke scalar view with multiple values, you must supply value_columns\"\n )\n if len(value_columns) != len(data):\n raise ValueError(\n f\"The number of value columns must match the number of values.\"\n f\"You supplied values: {data} and value_columns: {value_columns}\"\n )\n\n if isinstance(data, pd.DataFrame):\n all_parameter_columns = []\n for p in parameter_columns:\n all_parameter_columns += [p, f\"{p}_start\", f\"{p}_end\"]\n if set(key_columns).intersection(set(all_parameter_columns)):\n raise ValueError(\n f\"There should be no overlap between key columns: {key_columns} \"\n f\"and parameter columns: {parameter_columns}.\"\n )\n\n if value_columns:\n data_value_columns = data.columns.difference(\n set(key_columns) | set(all_parameter_columns)\n )\n if set(value_columns) != set(data_value_columns):\n raise ValueError(\n f\"The value columns you supplied: {value_columns} do not match \"\n f\"the non-parameter columns in the passed data: {data_value_columns}\"\n )","def validate_dataset(columns, rows):\n # Ensure that all column identifier are zero or greater, unique, and smaller\n # than the column counter (if given)\n col_ids = set()\n for col in columns:\n if col.identifier < 0:\n raise ValueError('negative column identifier \\'' + str(col.identifier) + '\\'')\n elif col.identifier in col_ids:\n raise ValueError('duplicate column identifier \\'' + str(col.identifier) + '\\'')\n col_ids.add(col.identifier)\n # Ensure that all row identifier are zero or greater, unique, smaller than\n # the row counter (if given), and contain exactly one value for each column\n row_ids = set()\n for row in rows:\n if len(row.values) != len(columns):\n raise ValueError('schema violation for row \\'' + str(row.identifier) + '\\'')\n elif row.identifier < 0:\n raise ValueError('negative row identifier \\'' + str(row.identifier) + '\\'')\n elif row.identifier in row_ids:\n raise ValueError('duplicate row identifier \\'' + str(row.identifier) + '\\'')\n row_ids.add(row.identifier)\n return max(col_ids) if len(col_ids) > 0 else -1, max(row_ids) if len(row_ids) > 0 else -1","def validate_csv(filename, header, cols, rows):\n\n # open file\n data = pd.read_csv(filename, delimiter='|')\n\n # validate header\n assert header == '|'.join(list(data.columns.values))\n\n # validate column count\n assert data.shape[1] == cols\n\n # validate row count\n assert data.shape[0] == rows\n\n # return (header_result == column_result == row_result) is True","def _column_exists(self, tbname, colname):\n self._check_file(tbname)\n tb = tbtool()\n tb.open(tbname)\n cols = tb.colnames()\n tb.close()\n return (colname in cols)","def __checkcolumns(self, lista: List[str]) -> True:\r\n\r\n if isinstance(lista, list) is False:\r\n raise TypeError(f\"{lista} has to be a list.\")\r\n if len(lista) != 10:\r\n raise ValueError(f\"{lista} must have 10 columns\")\r\n\r\n errorlista = []\r\n\r\n # Regarding 'self.tiposDisponiveis',\r\n # Layer and Marked happens on the same column.\r\n # if there is 'layer', 'marked' won't show up, and viceversa.\r\n # Therefore 'self.tiposDisponiveis' is a list with 11 elements. While 'lista' is a list with 10 elements.\r\n\r\n for _ in lista:\r\n # searching for 'Layer'\r\n if self.tiposDisponiveis[0].lower() == _.lower():\r\n break\r\n else:\r\n # if 'Layer' wasn't found, searching for 'Marked'\r\n for _ in lista:\r\n if self.tiposDisponiveis[1].lower() == _.lower():\r\n break\r\n else:\r\n # If none of the two are present on the line, add to the error list\r\n errorlista.append(\"Layer Or Marked\")\r\n \r\n # repeat the search for all the remaining required values\"\"\"\r\n for _ in range(2, len(self.tiposDisponiveis)-1):\r\n for x in lista:\r\n if x.lower() == self.tiposDisponiveis[_].lower():\r\n break\r\n else:\r\n # Didn't find this column in the list\r\n errorlista.append(f\"{self.tiposDisponiveis[_]}\")\r\n\r\n # Raising the errors, if any occurred.\r\n if len(errorlista) > 0:\r\n raise ValueError(f\"{errorlista} <- These columns are missing from format.\")\r\n\r\n # Last column has to be 'Text'\r\n if lista[9].lower() != self.tiposDisponiveis[10].lower():\r\n raise ValueError(f\"{lista[9]} last element has to be 'Text'.\")\r\n \r\n return True","def test_attempting_to_make_duplicate_column_names_fails(self):\r\n\r\n with self.assertRaises(ModelException):\r\n class BadNames(Model):\r\n words = columns.Text()\r\n content = columns.Text(db_field='words')","def test_daal_pca_bad_column_type(self):\n with self.assertRaisesRegexp(Exception, \"columns must be a list of strings\"):\n self.context.daaltk.models.dimreduction.pca.train(self.frame, 10, k=10)","def _validate_limits_cols_prefixed(self):\n for col in self._limits:\n self.__validate_col_prefix(\n col, (SOLAR_PREFIX, WIND_PREFIX), input_name='limits'\n )","def _parse_cols(kwargs):\n\n # Get col or cols from kwargs\n try:\n cols = kwargs.pop(\"cols\")\n except KeyError:\n try:\n cols = [kwargs.pop(\"col\")]\n except KeyError:\n raise KeyError(f\"Need 'col' or 'cols' field in {kwargs}\")\n\n # Make sure cols is now a list of strings\n if not all(\n isinstance(element, str) for element in cols\n ) or not isinstance(cols, list):\n raise TypeError(\n f\"col should be string or cols should be list of strings. \"\n f\"Now parsed cols is '{cols}'\"\n )\n return cols","def text_rename_column_errors(dupcols):\n # Incompatible column and name lists\n with pytest.raises(ValueError):\n rename(dupcols, columns='Name', names=['Person', 'Age'])\n # Unknown column name\n with pytest.raises(ValueError):\n rename(dupcols, columns='Names', names='Persons')\n # Column index out of range\n with pytest.raises(ValueError):\n rename(dupcols, columns=100, names='Persons')","def test_quoted_column_names_reading_dont_specify_names(self):\n self.quoted_column_names_reading_template(specify_column_names=False)","def _validate_data(self, table_definition, data):\n if len(data) == 0:\n # Length zero columns get converted on write.\n return\n\n columns_checked = set()\n\n for column_name, column_definition in table_definition.c.items():\n if column_name in data:\n expected_type = self._expected_type(column_definition)\n is_nullable_numeric = (column_definition.nullable and\n expected_type in [int, float])\n if is_nullable_numeric:\n data[column_name] = data[column_name].fillna(value=np.nan)\n actual_type = data[column_name].dtype\n is_pandas_extension = isinstance(actual_type, ExtensionDtype)\n if expected_type is int:\n self._check_int_type(actual_type, column_name,\n is_pandas_extension, table_definition)\n elif expected_type is float:\n self._check_float_type(actual_type, column_name,\n table_definition)\n elif expected_type is str:\n self._check_str_type(actual_type, column_name, data,\n table_definition)\n else:\n raise RuntimeError(f\"Unexpected type from column \"\n f\"definitions: {expected_type}.\")\n elif not (column_definition.primary_key or\n column_definition.nullable):\n raise DismodFileError(f\"Missing column in data for table \"\n f\"'{table_definition.name}': \"\n f\"'{column_name}'\")\n columns_checked.add(column_name)\n\n extra_columns = set(data.columns).difference(table_definition.c.keys())\n if extra_columns:\n raise DismodFileError(f\"extra columns in data for table \"\n f\"'{table_definition.name}': {extra_columns}\"\n )","def ensure_column_exists(df, col_name, col_alt = False):\n if col_name not in df.columns:\n renamed = False\n if col_alt:\n for dta in col_alt:\n if dta in df.columns:\n df.rename(columns={dta:col_name}, inplace = True)\n renamed = True\n else:\n pass\n if not renamed:\n txt = 'Column %s not found.'%col_name\n if col_alt:\n txt += 'Neither one of the alternatives: %s'(col_alt)\n raise AttributeError(txt)\n return","def check_col(self):\n return (set(map(lambda x: x.lower(),\n self.config['dtypes'])) -\n set(self.metadata.name.values))","def test_batch_condition_is_column_from_obs(self):\n\n self.validator.adata.uns[\"batch_condition\"] = [\"NO_COLUMN\"]\n self.validator.validate_adata()\n self.assertEqual(\n self.validator.errors,\n [\n \"ERROR: Value 'NO_COLUMN' of list 'batch_condition' is not a \"\n \"column in 'adata.obs'.\"\n ],\n )","def has_columns(df, columns):\n result = True\n for column in columns:\n if column not in df.columns:\n print(\"Missing column: {} in DataFrame\".format(column))\n result = False\n\n return result","def test_read_wrong_column_names(self):\n self.prepare()\n self.session.execute(\"\"\"\n CREATE TABLE testwrongcolumns (\n a int,\n b int,\n c int,\n PRIMARY KEY(a, b)\n )\"\"\")\n\n tempfile = self.get_temp_file()\n logger.debug('Writing {}'.format(tempfile.name))\n write_rows_to_csv(tempfile.name, [[1, 1, 1]])\n\n cmd = \"\"\"COPY ks.testwrongcolumns (a, b, d) FROM '{}'\"\"\".format(tempfile.name)\n out, err, _ = self.run_cqlsh(cmd)\n logger.debug(out)\n logger.debug(err)\n results = list(self.session.execute(\"SELECT * FROM testwrongcolumns\"))\n\n assert 'Invalid column name d' in err\n assert 'child process(es) died unexpectedly' not in err\n assert not results","def validate_data_format(\n Xs: List[Tensor], Ys: List[Tensor], Yvars: List[Tensor], metric_names: List[str]\n) -> None:\n if len({len(Xs), len(Ys), len(Yvars), len(metric_names)}) > 1:\n raise ValueError( # pragma: no cover\n \"Lengths of Xs, Ys, Yvars, and metric_names must match. Your \"\n f\"inputs have lengths {len(Xs)}, {len(Ys)}, {len(Yvars)}, and \"\n f\"{len(metric_names)}, respectively.\"\n )","def isValidDataTypeName(name: unicode) -> bool:\n ...","def test_is_valid_manifest_format_using_column_names_to_enums(caplog):\n column_names_to_enums = {\n \"md5_with_underscores\": Columns.MD5,\n \"file size with spaces\": Columns.SIZE,\n \"Urls With Caps\": Columns.URL,\n \"authz with special chars!@*&\": Columns.AUTHZ,\n }\n result = is_valid_manifest_format(\n \"tests/validate_manifest_format/manifests/manifest_with_custom_column_names.tsv\",\n column_names_to_enums=column_names_to_enums,\n )\n error_log = caplog.text\n manifest_with_many_types_of_errors_helper(error_log)\n assert result == False","def validate_input(self):\n self._validate_limits_cols_prefixed()\n self._validate_fillna_cols_prefixed()\n self._validate_ratio_input()","def valid_col_tester(self, state):\n vert_state = self.cols(state)\n for line in vert_state:\n line_index = vert_state.index(line)\n vert_word = self.check_word(vert_state[line_index])\n if not(vert_word):\n return False\n return True","def require(self, **names):\n for cut, v in names.items():\n if not isinstance(cut, str) or cut not in self._names:\n raise ValueError(\n \"All arguments must be strings that refer to the names of existing selections\"\n )\n\n consider = 0\n require = 0\n for name, val in names.items():\n val = bool(val)\n idx = self._names.index(name)\n consider |= 1 << idx\n require |= int(val) << idx\n return (self._data & self._dtype.type(consider)) == require","def test_daal_pca_bad_column_name(self):\n with self.assertRaisesRegexp(Exception, \"column ERR was not found\"):\n self.context.daaltk.models.dimreduction.pca.train(self.frame,\n [\"ERR\", \"X2\", \"X3\", \"X4\", \"X5\",\n \"X6\", \"X7\", \"X8\", \"X9\", \"X10\"],\n k=10)","def valid_type_in_col(arch, **kwargs):\n return all(\n attrib.isdigit()\n for attrib in arch.xpath('//@col')\n )","def check_for_column(self, column_name):\n if column_name not in self.data.columns:\n raise RuntimeError(\"Source {} has no '{}' column\".format(\n self.name, column_name))","def test_columns_non_string_error(self):\n\n with pytest.raises(ValueError):\n\n BaseTransformer(columns=1)","def check_null_columns(spark, df, cols):\n null_cols_list = []\n # this assumes the col list matches the original schema\n # df = df.toDF(*cols)\n try:\n df = df.select(*cols)\n col_null_count = df.select([F.count(F.when(F.isnan(col) | F.col(col).isNull(), col)).alias(col) for col in cols]).toPandas().to_dict()\n null_cols_list = [k for k, v in col_null_count.items() if v[0] > 0]\n except Exception as e:\n logger.error('Probably and invalid column(s) was passed...')\n return ['failed']\n return null_cols_list","def test_no_column(self):\n\n self.assertRaises(ValueError, self.table.where, 'True')","def test_from_formula_bad_cols_names():\n bad_df = pd.DataFrame(columns=['Systolic-BP', 'is_smoker', 'Over+wt'])\n\n with pytest.raises(AssertionError):\n from_formula('Systolic-BP ~ *', bad_df, coerce=False)\n\n assert from_formula('Systolic_BP ~ *', bad_df)","def check_column_count(cls, line):\n\n # MAGIC n_cols = n_delim + 1 (no trailing delimiter)\n cols = line.count(cls.DELIMITER) + 1\n expected = 7 # MAGIC USAA convention, not all are populated though\n return cols == expected","def _validate_merge_col_exists(self):\n msg = (\"Cannot hybridize: merge column {!r} missing from the \"\n \"{} meta data! ({!r})\")\n\n mc = ColNameFormatter.fmt(MERGE_COLUMN)\n for cols, fp, res in zip([self.__solar_cols, self.__wind_cols],\n [self.solar_fpath, self.wind_fpath],\n ['solar', 'wind']):\n if mc not in cols:\n e = msg.format(MERGE_COLUMN, res, fp)\n logger.error(e)\n raise FileInputError(e)","def get_columns_for(self, column_names, row, dbrow=None):\n if dbrow:\n candidates = filter(lambda col: col not in self.insert_only_fields, column_names)\n else:\n candidates = column_names\n\n return set(candidates).intersection(row._fields)","def test_extract_invalid_column(self):\n self.dicom.extract_keywords([\"invalid\"])\n\n # ensure column was added\n columns = self.dicom.metadata.column_names\n if u'invalid' not in columns:\n raise Exception(\"Invalid column not added\")\n\n # compare expected and actual result\n invalid_column = self.dicom.metadata.take(self.count, columns=[u'invalid'])\n expected_result = [[None] for x in range(0, self.count)]\n self.assertEqual(invalid_column, expected_result)","def testColumnsNotListWrapped(self):\n with self.assertRaises(TypeError):\n Table(self.base_case[\"name\"], Column(\"col1\", str))","def _check_availability(self, names: Iterable) -> None:\n unavailable = [x for x in names if x not in self.__by_name.keys()]\n if unavailable:\n raise ValueError(f'datasets: {unavailable} not available in the {self.region} region.')","def test_wrong_number_of_columns(self):\n self.prepare()\n self.session.execute(\"\"\"\n CREATE TABLE testcolumns (\n a int PRIMARY KEY,\n b int\n )\"\"\")\n\n data = [[1, 2, 3]]\n tempfile = self.get_temp_file()\n write_rows_to_csv(tempfile.name, data)\n\n logger.debug('Importing from csv file: {name}'.format(name=tempfile.name))\n out, err, _ = self.run_cqlsh(\"COPY ks.testcolumns FROM '{name}'\".format(name=tempfile.name))\n\n assert not self.session.execute(\"SELECT * FROM testcolumns\")\n assert 'Failed to import' in err","def validate(self):\n regexp = re.compile(self.raw_pattern)\n missing = regexp.findall(self.sql)\n if missing:\n raise NameError(\"Value not provided for placeholder {}\".format(missing))"],"string":"[\n \"def _check_columns(df: pd.DataFrame, names: typing.Sequence[str]) -> None:\\n for expected in names:\\n if expected not in df.columns:\\n raise ValueError(f\\\"'{expected}' column not found in input\\\")\\n return\",\n \"def _validate_columns(data, ip_column, lat_column, long_column, other_columns):\\n if not ip_column and not (lat_column and long_column):\\n raise ValueError(\\n \\\"Data must have either an IpAddress ('ip_column')\\\",\\n \\\"or latitude ('lat_column') and longitude ('long_column')\\\",\\n )\\n param_cols: List[str] = []\\n for param in other_columns:\\n if not param:\\n continue\\n if isinstance(param, list):\\n param_cols.extend(param)\\n else:\\n param_cols.append(param)\\n missing_columns = {col for col in param_cols if col not in data.columns}\\n if missing_columns:\\n raise LookupError(\\n \\\"The following columns are not in the supplied DataFrame\\\",\\n \\\",\\\".join(f\\\"'{col}'\\\" for col in missing_columns),\\n )\",\n \"def validate_column_names(self, cols):\\n self.stdout.write('Verifying CSV header')\\n csv_cols = set(cols)\\n if self.required_csv_columns <= csv_cols:\\n return True\\n else:\\n missing_cols = set(self.required_csv_columns).difference(csv_cols)\\n raise ValidationError(\\n \\\"These columns '{0}' are required, but missing in the CSV \\\"\\n \\\"file.\\\".format(\\n ', '.join(missing_cols)\\n )\\n )\",\n \"def validate_columns(self, fieldnames, dao):\\n unstored_columns = ['blank']\\n expected_columns = dao.model_type.__table__.columns.keys() + unstored_columns\\n for column_name in fieldnames:\\n if column_name not in expected_columns:\\n raise AttributeError(f\\\"{self.file_path}: {column_name} column mismatch for \\\"\\n f\\\"expected file type: {self.file_type.name}\\\")\",\n \"def checkcolumnstest(chosen_columns, chosen_df):\\n if not all([item in chosen_columns for item in chosen_df.columns]):\\n raise ValueError('Columns do not match')\",\n \"def _validate_cols(cols):\\n\\n\\tif cols is not None and len(cols) < 2:\\n\\t\\traise ValueError('too few features')\",\n \"def _check_columns_with_table(table: Table, columns: Sequence[str]) -> Optional[bool]:\\n for column in columns:\\n if column not in table.c.keys():\\n raise TypeError(f\\\"Specified column {column} did not exist on table {table}\\\")\\n return True\",\n \"def verify_columns_in_dataset(self, columns):\\n all_cols = self.dataset.columns\\n for col in columns:\\n if not col in all_cols:\\n raise KeyError(\\\"column '%s' not in dataset\\\" % col)\",\n \"def is_cols_valid(bd):\\n for col in cols:\\n seen = []\\n for num in nums:\\n if bd[col[num]] == \\\" \\\":\\n continue\\n elif bd[col[num]] not in seen:\\n seen += [bd[col[num]]]\\n else:\\n return False\\n else:\\n continue\\n return True\",\n \"def cols_valid(self,\\n df: pd.DataFrame,\\n req_cols: set) -> bool:\\n missing_cols = req_cols.difference(df.columns)\\n\\n if len(missing_cols) > 0:\\n logging.error(f\\\"{missing_cols} columns required but missing\\\")\\n return False\\n\\n return True\",\n \"def _check_headers(cursor, headers):\\n all_columns = set(chain.from_iterable(_columns(cursor, table) for table in DATA_TABLES))\\n for header in headers:\\n if header not in all_columns:\\n raise ValueError('column {} not recognized'.format(header))\",\n \"def verify_columns_in_dataset(self, columns):\\n all_cols = self.train.columns\\n for col in columns:\\n if not col in all_cols:\\n raise KeyError(\\\"column '%s' not in dataset\\\" % col)\",\n \"def _check_missing_columns(self, df: pd.DataFrame) -> None:\\n if any([c not in df.columns for c in REQUIRED_COLUMNS]):\\n raise ValueError(\\\"Missing columns in dataset.\\\"\\n f\\\"Columns: {df.columns}\\\"\\n f\\\"Required: {REQUIRED_COLUMNS}\\\")\",\n \"def validate_col_lst(self, df, columns_lst):\\n if columns_lst == []:\\n raise ValueError(\\\"column_lst is empty\\\")\\n col_set = set(columns_lst)\\n df_col_set = set(list(df))\\n if col_set - df_col_set != set():\\n msg = \\\"col_lst has columns name that does not exists in the DataFrame columns:{}\\\".format(\\n str(col_set - df_col_set))\\n print(msg)\\n raise ValueError(msg)\\n return True\",\n \"def check_ingress_required_columns(self, col_names):\\n if not set(col_names).issuperset(REQUIRED_COLUMNS):\\n if not set(col_names).issuperset(REQUIRED_ALT_COLUMNS):\\n missing_columns = [x for x in REQUIRED_ALT_COLUMNS if x not in col_names]\\n return missing_columns\\n return None\",\n \"def check_columns_in_dataframe(df: pd.DataFrame, columns: Tuple[str]) -> None:\\n\\n for col in columns:\\n if col not in df.columns:\\n raise ValueError(f\\\"Column {col} is not in the dataframe.\\\")\",\n \"def _dataframe_column_check(df: DataFrame, compulsory_columns: Sequence) -> None:\\n if not set(compulsory_columns).issubset(df.columns):\\n diff = set(compulsory_columns).difference(df.columns)\\n msg = (\\n \\\"The following compulsory column(s) are missing from the \\\"\\n f\\\"DataFrame: {diff}\\\"\\n )\\n raise ValueError(msg)\",\n \"def verify_columns_in_dataframe(df, columns):\\n\\n if not isinstance(columns, list):\\n columns = [columns]\\n return set(columns).issubset(df.columns)\",\n \"def _check_columns(\\n schema_errors: set[str],\\n stored: Mapping,\\n expected: Mapping,\\n columns: Iterable[str],\\n table_name: str,\\n supports: str,\\n) -> None:\\n for column in columns:\\n if stored[column] == expected[column]:\\n continue\\n schema_errors.add(f\\\"{table_name}.{supports}\\\")\\n _LOGGER.error(\\n \\\"Column %s in database table %s does not support %s (stored=%s != expected=%s)\\\",\\n column,\\n table_name,\\n supports,\\n stored[column],\\n expected[column],\\n )\",\n \"def _check_columns(cdm_column_names, csv_columns, result):\\n columns_valid = True\\n\\n # if len(csv_columns) != len(cdm_column_names):\\n\\n # check all column headers in the file\\n for col in csv_columns:\\n if col not in cdm_column_names:\\n e = dict(message=MSG_INCORRECT_HEADER, column_name=col, actual=col)\\n result['errors'].append(e)\\n columns_valid = False\\n\\n # check cdm table headers against headers in file\\n for col in cdm_column_names:\\n if col not in csv_columns:\\n e = dict(message=MSG_MISSING_HEADER, column_name=col, expected=col)\\n result['errors'].append(e)\\n columns_valid = False\\n\\n # check order of cdm table headers against headers in file\\n for idx, col in enumerate(cdm_column_names):\\n if idx < len(csv_columns) and csv_columns[idx] != col:\\n e = dict(message=MSG_INCORRECT_ORDER,\\n column_name=csv_columns[idx],\\n actual=csv_columns[idx],\\n expected=col)\\n result['errors'].append(e)\\n columns_valid = False\\n break\\n\\n return columns_valid\",\n \"def check_cols_methane(name):\\n return True if name in ['SampleDay', 'SampleHour', 'Decimal Year',\\n 'Peak Area 1', 'Peak Area 2', 'Run median', 'Daily Median'] else False\",\n \"def validate_match_columns(import_log, field_names, model_class, header_row):\\n errors = []\\n column_matches = import_log.import_setting.columnmatch_set.all()\\n for field_name in field_names:\\n field_object, model, direct, m2m = model_class._meta.get_field_by_name(field_name)\\n if (direct and\\n model and\\n not field_object.blank):\\n field_matches = column_matches.filter(field_name=field_name)\\n if field_matches:\\n if field_matches[0].column_name not in header_row:\\n errors += [\\\"{0} is required but is not in your spreadsheet. \\\".format(field_object.verbose_name)]\\n else:\\n errors += [\\\"{0} is required but has no match.\\\".format(field_object.verbose_name)]\\n \\n return errors\",\n \"def _assert_columns_exist(self, columns):\\n if not nonstringiter(columns):\\n columns = (columns,)\\n self_cols = self.columns()\\n is_missing = lambda col: col not in self_cols\\n missing = [c for c in columns if is_missing(c)]\\n if missing:\\n missing = ', '.join(repr(x) for x in missing)\\n msg = '{0} not in {1}'.format(missing, self.__repr__())\\n raise LookupError(msg)\",\n \"def check_column(self, columns):\\n for i in columns:\\n if i.name == self.name:\\n raise ColumnNameAlreadyInTableException(f'Column \\\"{self.name}\\\" is already in the table!')\\n return True\",\n \"def check_df_col(df, column, name=None):\\n if column is not None:\\n\\n if type(column) != list:\\n\\n column = [column]\\n\\n for col in column:\\n if name is None:\\n error_message = f\\\"The value '{col}' is not present in any of the columns of your DataFrame.\\\"\\n else:\\n error_message = f\\\"Your {name} value '{col}' is not present in any of the columns of your DataFrame.\\\"\\n error_message += \\\"\\\\nYou may be looking for:\\\\n \\\" + str(list(df.columns))\\n\\n assert col in df.columns, error_message\",\n \"def check_dataframe_columns(df):\\r\\n if len(set(df.columns).intersection(\\r\\n set([constants.CASE_CONCEPT_NAME, xes_constants.DEFAULT_NAME_KEY,\\r\\n xes_constants.DEFAULT_TIMESTAMP_KEY]))) < 3:\\r\\n raise Exception(\\r\\n \\\"please format your dataframe accordingly! df = pm4py.format_dataframe(df, case_id='<name of the case ID column>', activity_key='<name of the activity column>', timestamp_key='<name of the timestamp column>')\\\")\",\n \"def verify(self):\\n for col in self.columns:\\n if col not in self.table_obj.columns.keys():\\n raise Exception('{} column not found in {}'.format(\\n col, self.table_obj))\",\n \"def _validate_data(df):\\n if constants.IMAGE_URI_KEY not in df.columns:\\n # or label_col not in df.columns:\\n raise AttributeError(\\n 'DataFrame must contain image_uri column {}.')\\n if constants.LABEL_KEY not in df.columns:\\n raise AttributeError(\\n 'DataFrame must contain label column.')\\n if constants.SPLIT_KEY not in df.columns:\\n raise AttributeError(\\n 'DataFrame must contain split column.')\\n if list(df.columns) != constants.IMAGE_CSV_COLUMNS:\\n raise AttributeError(\\n 'DataFrame column order must be {}'.format(\\n constants.IMAGE_CSV_COLUMNS))\",\n \"def check_column_values(self, values):\\n none_keys = sorted(list(self._necessary_input_columns.intersection(set([elem for elem in self._columns if values[self.column_id[elem]] in [None, 'None']]))))\\n if len(none_keys) > 0:\\n raise Exception('missing_keys in ForcingOnMesh_DBManager add function parameter file_info:\\\\n%s\\\\n'%('\\\\n'.join([' - %s'%elem for elem in none_keys])))\",\n \"def check_column_names(expected_headings, found_headings):\\n column_missing = False\\n column_additional = False\\n\\n # Check if column headings exist\\n logging.info(\\\"Checking column headers are correct.\\\")\\n diff_columns = set(expected_headings) - set(found_headings)\\n if len(diff_columns) > 0:\\n column_missing = True\\n\\n # Check whether there are any additional columns (could need renaming)\\n extra_columns = set(found_headings) - set(expected_headings)\\n if len(extra_columns) > 0:\\n column_additional = True\\n\\n # Check for duplicate headings\\n # NOTE: As mangle_dupe_cols=True, any duplicate columns will be stored in the form column.1.... column.N\\n # We use this to avoid overwriting data. However, to identify duplicate original columns, we need to remove\\n # these prior to checking for dups\\n main_column_names = [i.split(\\\".\\\")[0] for i in found_headings]\\n duplicate_headings = len(main_column_names) > len(set(main_column_names))\\n if duplicate_headings:\\n logging.error(\\\"Duplicate headings identified.\\\")\\n if column_missing:\\n logging.error(\\\"Missing headers identified:\\\")\\n print(diff_columns)\\n if column_additional:\\n logging.error(\\\"Additional headers identified:\\\")\\n print(extra_columns)\\n if column_missing or column_additional or duplicate_headings:\\n logging.info(\\n \\\"File will not pass checks as I am unable to tell \\\"\\n \\\"what to do with the columns on my own.\\\"\\n )\\n return False\\n return True\",\n \"def validate(self):\\n super().validate()\\n frame = getattr(self, 'frame', None)\\n if frame is None:\\n raise ValueError('Missing columns %s since no frame' % ', '.join(\\n self.required_cols))\\n cols = set(list(self.frame))\\n missing = sorted(self.required_cols - cols)\\n if missing:\\n raise ValueError('Missing columns: [%s]' % ', '.join(missing))\",\n \"def test_column_presence(self):\\n\\n columns = [\\n \\\"assay_ontology_term_id\\\",\\n \\\"development_stage_ontology_term_id\\\",\\n \\\"disease_ontology_term_id\\\",\\n \\\"ethnicity_ontology_term_id\\\",\\n \\\"is_primary_data\\\",\\n \\\"sex_ontology_term_id\\\",\\n \\\"tissue_ontology_term_id\\\",\\n ]\\n\\n for column in columns:\\n with self.subTest(column=column):\\n self.validator.errors = []\\n self.validator.adata = examples.adata.copy()\\n\\n self.validator.adata.obs.drop(column, axis=1, inplace=True)\\n # Remove batch condition because it has a dependency with is_primary_data\\n self.validator.adata.uns.pop(\\\"batch_condition\\\")\\n\\n self.validator.validate_adata()\\n self.assertEqual(\\n self.validator.errors,\\n [f\\\"ERROR: Dataframe 'obs' is missing \\\" f\\\"column '{column}'.\\\"],\\n )\",\n \"def validate(self):\\r\\n for name, col in self._columns.items():\\r\\n val = col.validate(getattr(self, name))\\r\\n setattr(self, name, val)\",\n \"def setRequiredColumns(self, colnames):\\n # Make sure all column names are lower case so comparisons in _TableRow\\n # are not case sensitive. From a modularity standpoint, this should be\\n # done in _TableRow, but it is more efficient to do it here, since the\\n # conversion need be done only once.\\n self.required_cols = [colname.lower() for colname in colnames]\",\n \"def validate_custom_columns(record_custom_columns):\\n\\n\\tcustom_column_name_errors = []\\n\\n\\tfor k, v in record_custom_columns.items():\\n\\t\\tfield_name = \\\"Custom Column: \\\" + k\\n\\t\\tfield_desc = \\\"Column Description: \\\" + v\\n\\n\\t\\tif not re.match(character_regex_with_space, k):\\n\\t\\t\\tmessage = get_regex_mismatch_error_text(field_name, character_regex)\\n\\t\\t\\tcustom_column_name_errors.append(message)\\n\\n\\t\\tif not re.match(character_regex_with_space, v):\\n\\t\\t\\tmessage = get_regex_mismatch_error_text(field_desc, character_regex_with_space)\\n\\t\\t\\tcustom_column_name_errors.append(message)\\n\\n\\t\\tif (len(k) > field_length_limit):\\n\\t\\t\\tmessage = get_field_length_error_text(field_name)\\n\\t\\t\\tcustom_column_name_errors.append(message)\\n\\n\\t\\tif (len(v) > field_length_limit):\\n\\t\\t\\tmessage = get_field_length_error_text(field_desc)\\n\\t\\t\\tcustom_column_name_errors.append(message)\\n\\n\\treturn custom_column_name_errors\",\n \"def verify(self):\\n for col in self._columns:\\n if col not in self._table_obj.columns.keys():\\n raise GaiaException('{} column not found in {}'.format(\\n col, self._table_obj))\",\n \"def _validate_optional_columns(data, optional_columns: Iterable[str]) -> List[str]:\\n return [col for col in optional_columns if col in data.columns]\",\n \"def test_set_col_names_exception(self):\\n with self.assertRaises(ValueError) as ctx:\\n self.dboard.set_col_names([\\\"A\\\", \\\"B\\\", \\\"C\\\"])\\n\\n self.assertEqual(\\\"'names' list size does not match the number of columns allocated\\\", str(ctx.exception))\",\n \"def __validate_col_prefix(col, prefixes, input_name):\\n\\n missing = [not col.startswith(p) for p in prefixes]\\n if all(missing):\\n msg = (\\\"Input {0} column {1!r} does not start with a valid \\\"\\n \\\"prefix: {2!r}. Please ensure that the {0} column \\\"\\n \\\"names specify the correct resource prefix.\\\")\\n e = msg.format(input_name, col, prefixes)\\n logger.error(e)\\n raise InputError(e)\",\n \"def test_columns_str_error(self):\\n\\n df = d.create_df_1()\\n\\n x = BaseTransformer(columns=None)\\n\\n x.columns = \\\"a\\\"\\n\\n with pytest.raises(ValueError):\\n\\n x.columns_check(X=df)\",\n \"def test_invalid_columns():\\n train = ((\\\"Lorem ipsum dolor sit amet\\\", 3),\\n (\\\"Sed ut perspiciatis unde\\\", 5.5))\\n with pytest.raises(ValueError):\\n TabularDataset(train, named_columns=['some_random_col'])\",\n \"def validate(self):\\n super().validate()\\n frame = getattr(self, 'frame', None)\\n if frame is None:\\n raise ValueError('Missing columns %s since no frame' % ', '.join(\\n [c[0] for c in self.col_regexps]))\\n for col_name, c_re in self.col_regexps:\\n if col_name not in self.frame:\\n raise ValueError('Missing required column %s' % col_name)\\n if c_re is None:\\n continue # Just verified that column is present\\n c_re_c = re.compile(c_re)\\n for date, item in self.frame[col_name].iteritems():\\n if not c_re_c.match(item):\\n raise ValueError(\\n 'In column %s, index %s, item %s fails regexp %s' % (\\n col_name, date, item, c_re))\",\n \"def test_clean_columns():\\n assert clean_columns('Id, AdCampaignId, CampaignId') == ['id', 'adCampaignId', 'campaignId']\",\n \"def _check_required_columns(self, param_df, var_name='param_mean'):\\n\\n if param_df is None:\\n return pd.DataFrame()\\n\\n try:\\n if param_df.shape[0] == 0:\\n return pd.DataFrame(columns=list(set(self.required_columns[var_name])|set(param_df.columns)))\\n\\n if self.required_columns[var_name] - set(param_df.columns) == set([]): # df has required cols.\\n return param_df\\n else:\\n note = \\\"'{}' must be a pd.DataFrame with the following column names: \\\".format(var_name) + \\\\\\n _list_the_errors(self.required_columns[var_name] - set(param_df.columns)) + \\\".\\\"\\n raise ValueError(note)\\n except KeyError:\\n raise KeyError(\\\"'{}' is not supported\\\".format(var_name))\",\n \"def check_schema_definition(schema_definition: pd.DataFrame) -> bool:\\n\\n if required_headers.issubset(set(list(schema_definition.columns))):\\n return\\n elif \\\"Requires\\\" in list(schema_definition.columns) or \\\"Requires Component\\\" in list(\\n schema_definition.columns\\n ):\\n raise ValueError(\\n \\\"The input CSV schema file contains the 'Requires' and/or the 'Requires \\\"\\n \\\"Component' column headers. These columns were renamed to 'DependsOn' and \\\"\\n \\\"'DependsOn Component', respectively. Switch to the new column names.\\\"\\n )\",\n \"def check_cols(self):\\n if self.ad_tab is not None and 'date' not in self.ad_cols:\\n raise DataException(\\\"\\\"\\\"date column not found in adServer table.\\\"\\\"\\\")\\n if self.ad_tab is not None and 'impressions' not in self.ad_cols:\\n raise DataException(\\\"\\\"\\\"impressions column not found in adServer table.\\\"\\\"\\\")\\n if 'timestamp' not in self.log_cols and 'date' not in self.log_cols:\\n raise DataException(\\\"\\\"\\\"Both timestamp and date column missing from {t}\\nCannot do dailyQA\\\"\\\"\\\".format(t=self.log_tab))\\n if self.configs['hourshift'] != 0 or 'date' not in self.log_cols:\\n if 'timestamp' not in self.log_cols:\\n raise DataException(\\\"\\\"\\\"Time shift requested \\\\\\nbut no timestamp column in {t}.\\\"\\\"\\\".format(t=self.log_tab))\\n else:\\n check_timestamp(self.configs['schema'], self.log_tab)\",\n \"def test_columns_not_in_X_error(self):\\n\\n df = d.create_df_1()\\n\\n x = BaseTransformer(columns=[\\\"a\\\", \\\"z\\\"])\\n\\n with pytest.raises(ValueError):\\n\\n x.columns_check(X=df)\",\n \"def validate_dataframe(\\n df: pd.DataFrame, settings: Settings = DefaultSettings()\\n) -> None:\\n if df.columns.dtype != object or not (df.columns.map(type) == str).all():\\n raise ValueError(\\\"column names must all be str\\\")\\n\\n for colname, uccolname in zip(\\n list(df.columns), gen_unique_clean_colnames(list(df.columns), settings=settings)\\n ):\\n if uccolname.is_ascii_cleaned:\\n raise ValueError(\\n 'column name \\\"%s\\\" must not contain ASCII control characters' % colname\\n )\\n if uccolname.is_unicode_fixed:\\n # `str(\\\"x \\\\ud800 x\\\")` doesn't crash, so this ValueError should be safe to print\\n raise ValueError(\\n 'column name \\\"%s\\\" must not contain invalid Unicode surrogates'\\n % colname,\\n )\\n if uccolname.is_default:\\n raise ValueError('column name \\\"%s\\\" must not be empty' % colname)\\n if uccolname.is_truncated:\\n raise ValueError(\\n 'column name \\\"%s\\\" must contain %d bytes or fewer'\\n % (\\n colname,\\n settings.MAX_BYTES_PER_COLUMN_NAME,\\n )\\n )\\n if uccolname.is_numbered:\\n raise ValueError(\\n 'column name \\\"%s\\\" must not appear more than once' % colname\\n )\\n\\n if not df.index.equals(pd.RangeIndex(0, len(df))):\\n raise ValueError(\\n \\\"must use the default RangeIndex — \\\"\\n \\\"try table.reset_index(drop=True, inplace=True)\\\"\\n )\\n\\n for column in df.columns:\\n validate_series(df[column])\",\n \"def _valid_column(column_name):\\n return str(column_name)\",\n \"def _validate_ratio_cols_exist(self):\\n\\n for col in self._ratio_cols:\\n no_prefix_name = \\\"_\\\".join(col.split('_')[1:])\\n if not self.data.contains_col(no_prefix_name):\\n msg = (\\\"Input ratios column {!r} not found in either meta \\\"\\n \\\"data! Please check the input files {!r} and {!r}\\\")\\n e = msg.format(no_prefix_name, self.data.solar_fpath,\\n self.data.wind_fpath)\\n logger.error(e)\\n raise FileInputError(e)\",\n \"def table_is_keyed_by_columns(self, table, *, column_names: Iterable[str]) -> bool:\\n # get rid of some corner cases\\n if table.shape[0] < 2:\\n return True\\n if (column_names is None):\\n return False\\n # check for ill-condition\\n if isinstance(column_names, str):\\n column_names = [column_names]\\n else:\\n column_names = list(column_names)\\n missing_columns = set(column_names) - set(table.columns)\\n if len(missing_columns) > 0:\\n return False\\n # get rid of some corner cases\\n if len(column_names) < 1:\\n return False\\n mx = (\\n table\\n .select(column_names)\\n .with_columns([pl.lit(1, pl.Int64).alias(\\\"_da_count_tmp\\\")])\\n .groupby(column_names)\\n .sum()[\\\"_da_count_tmp\\\"]\\n .max()\\n )\\n return mx <= 1\",\n \"def test_extract_multiple_invalid_columns(self):\\n keywords = [\\\"invalid\\\", \\\"another_invalid_col\\\"]\\n self.dicom.extract_keywords(keywords)\\n\\n # test that columns were added\\n columns = self.dicom.metadata.column_names\\n if u'invalid' not in columns:\\n raise Exception(\\\"invalid column not added to columns\\\")\\n if u'another_invalid_col' not in columns:\\n raise Exception(\\\"another_invalid_col not added to columns\\\")\\n\\n # compare actual with expected result\\n invalid_columns = self.dicom.metadata.take(self.count, columns=keywords)\\n expected_result = [[None, None] for x in range(0, self.count)]\\n self.assertEqual(invalid_columns, expected_result)\",\n \"def validate_required_fields(dataframe):\\n\\n if dataframe is None:\\n raise ValueError(\\\"It was not provided a valid Dataframe.\\\")\",\n \"def test_column_presence(self):\\n\\n columns = [\\\"feature_is_filtered\\\", \\\"feature_biotype\\\"]\\n\\n for component_name in [\\\"var\\\", \\\"raw.var\\\"]:\\n for column in columns:\\n if column == \\\"feature_is_filtered\\\" and component_name == \\\"raw.var\\\":\\n continue\\n with self.subTest(component_name=component_name, column=column):\\n\\n # Resetting validator\\n self.validator.errors = []\\n self.validator.adata = examples.adata.copy()\\n\\n component = Validator.getattr_anndata(\\n self.validator.adata, component_name\\n )\\n component.drop(column, axis=1, inplace=True)\\n\\n self.validator.validate_adata()\\n self.assertEqual(\\n self.validator.errors,\\n [\\n f\\\"ERROR: Dataframe '{component_name}' is missing \\\"\\n f\\\"column '{column}'.\\\"\\n ],\\n )\",\n \"def validate(self):\\r\\n for name in self._columns.keys():\\r\\n func_name = 'validate_{}'.format(name)\\r\\n val = getattr(self, name)\\r\\n if hasattr(self, func_name):\\r\\n val = getattr(self, func_name)(val)\\r\\n else:\\r\\n val = self.validate_field(name, val)\\r\\n setattr(self, name, val)\",\n \"def test_quoted_column_names_reading_specify_names(self):\\n self.quoted_column_names_reading_template(specify_column_names=True)\",\n \"def _validate_column_name(col_name : str) -> str:\\n\\n if col_name[0].isdigit():\\n return f'\\\"{col_name}\\\"'\\n return col_name\",\n \"def check_column(self, table_name: str, column_name: str) -> bool:\\n try:\\n insp = reflection.Inspector.from_engine(self.engine)\\n for col in insp.get_columns(table_name):\\n if column_name in col[\\\"name\\\"]:\\n return True\\n return False\\n except Exception as err:\\n logger.error(\\\"check_column [error] -> %s\\\" % err)\\n return False\",\n \"def check_column(data, functions, threshold):\\n\\n # Apply the functions to the column to return True/False values\\n data = data.map(lambda x: any(f(x) for f in functions)).copy()\\n # Identify the number of incorrect values\\n data_invalid = data.sum()\\n # Identify the number of values in the column\\n data_total = data.count()\\n\\n if data_total == 0 or data_invalid == data_total:\\n # If entire column is invalid or empty\\n logging.error(\\\"Header supplied, but all data invalid or missing.\\\")\\n return False\\n else:\\n # Find the percentage of invalid values\\n data_perc = data_invalid / data_total\\n\\n # Check whether the % invalid values is above or below the threshold\\n if data_perc > threshold:\\n logging.error(f\\\"{data_perc*100 : .2f}% of values are blank or invalid\\\")\\n return False\\n\\n return True\",\n \"def check_column(rule, column):\\n for value in column:\\n if not check_ranges(rule, value):\\n return False\\n return True\",\n \"def _validate_plaincolumns(self):\\n\\n # assert tuples for plaincolumns and plaincolumns to be PlainColumn\\n if not isinstance(self.plaincolumns, tuple):\\n raise ValueError(\\\"PlainFrame was instantiated incorrectly. \\\"\\n \\\"`plaincolumns` needs to be of type `tuple`. \\\"\\n \\\"However, {} was encountered. Please use \\\"\\n \\\"`PlainFrame.from_plain` instead for convenient \\\"\\n \\\"instantiation and proper type casts.\\\"\\n .format(type(self.plaincolumns)))\\n\\n not_plaincolumn = [type(column)\\n for column in self.plaincolumns\\n if not isinstance(column, PlainColumn)]\\n\\n if not_plaincolumn:\\n raise ValueError(\\\"PlainFrame was instantiated incorrectly. \\\"\\n \\\"Elements of `plaincolumns` needs to be of type \\\"\\n \\\"`PlainColumn`. However, {} was encountered. \\\"\\n \\\"Please use `PlainFrame.from_plain` instead for \\\"\\n \\\"convenient instantiation and proper type casts.\\\"\\n .format(not_plaincolumn))\\n\\n # assert equal number of values per column\\n row_lenghts = {len(column.values) for column in self.plaincolumns}\\n if len(row_lenghts) > 1:\\n raise ValueError(\\\"Input data has varying number of values per \\\"\\n \\\"column. Please check provided input data.\\\")\\n\\n # assert unique column names\\n duplicates = {x for x in self.columns if self.columns.count(x) > 1}\\n if duplicates:\\n raise ValueError(\\\"Duplicated column names encountered: {}. \\\"\\n \\\"Please use unique column names.\\\"\\n .format(duplicates))\",\n \"def columns(self, names):\\n self._validate_columns(names)\\n self._columns = list(names)\",\n \"def validate_parameters(\\n data: pd.DataFrame,\\n key_columns: Union[List[str], Tuple[str]],\\n parameter_columns: Union[List[str], Tuple],\\n value_columns: Union[List[str], Tuple[str]],\\n):\\n if (\\n data is None\\n or (isinstance(data, pd.DataFrame) and data.empty)\\n or (isinstance(data, (list, tuple)) and not data)\\n ):\\n raise ValueError(\\\"Must supply some data\\\")\\n\\n if not isinstance(data, (Number, datetime, timedelta, list, tuple, pd.DataFrame)):\\n raise TypeError(\\n f\\\"The only allowable types for data are number, datetime, timedelta, \\\"\\n f\\\"list, tuple, or pandas.DataFrame. You passed {type(data)}.\\\"\\n )\\n\\n if isinstance(data, (list, tuple)):\\n if not value_columns:\\n raise ValueError(\\n f\\\"To invoke scalar view with multiple values, you must supply value_columns\\\"\\n )\\n if len(value_columns) != len(data):\\n raise ValueError(\\n f\\\"The number of value columns must match the number of values.\\\"\\n f\\\"You supplied values: {data} and value_columns: {value_columns}\\\"\\n )\\n\\n if isinstance(data, pd.DataFrame):\\n all_parameter_columns = []\\n for p in parameter_columns:\\n all_parameter_columns += [p, f\\\"{p}_start\\\", f\\\"{p}_end\\\"]\\n if set(key_columns).intersection(set(all_parameter_columns)):\\n raise ValueError(\\n f\\\"There should be no overlap between key columns: {key_columns} \\\"\\n f\\\"and parameter columns: {parameter_columns}.\\\"\\n )\\n\\n if value_columns:\\n data_value_columns = data.columns.difference(\\n set(key_columns) | set(all_parameter_columns)\\n )\\n if set(value_columns) != set(data_value_columns):\\n raise ValueError(\\n f\\\"The value columns you supplied: {value_columns} do not match \\\"\\n f\\\"the non-parameter columns in the passed data: {data_value_columns}\\\"\\n )\",\n \"def validate_dataset(columns, rows):\\n # Ensure that all column identifier are zero or greater, unique, and smaller\\n # than the column counter (if given)\\n col_ids = set()\\n for col in columns:\\n if col.identifier < 0:\\n raise ValueError('negative column identifier \\\\'' + str(col.identifier) + '\\\\'')\\n elif col.identifier in col_ids:\\n raise ValueError('duplicate column identifier \\\\'' + str(col.identifier) + '\\\\'')\\n col_ids.add(col.identifier)\\n # Ensure that all row identifier are zero or greater, unique, smaller than\\n # the row counter (if given), and contain exactly one value for each column\\n row_ids = set()\\n for row in rows:\\n if len(row.values) != len(columns):\\n raise ValueError('schema violation for row \\\\'' + str(row.identifier) + '\\\\'')\\n elif row.identifier < 0:\\n raise ValueError('negative row identifier \\\\'' + str(row.identifier) + '\\\\'')\\n elif row.identifier in row_ids:\\n raise ValueError('duplicate row identifier \\\\'' + str(row.identifier) + '\\\\'')\\n row_ids.add(row.identifier)\\n return max(col_ids) if len(col_ids) > 0 else -1, max(row_ids) if len(row_ids) > 0 else -1\",\n \"def validate_csv(filename, header, cols, rows):\\n\\n # open file\\n data = pd.read_csv(filename, delimiter='|')\\n\\n # validate header\\n assert header == '|'.join(list(data.columns.values))\\n\\n # validate column count\\n assert data.shape[1] == cols\\n\\n # validate row count\\n assert data.shape[0] == rows\\n\\n # return (header_result == column_result == row_result) is True\",\n \"def _column_exists(self, tbname, colname):\\n self._check_file(tbname)\\n tb = tbtool()\\n tb.open(tbname)\\n cols = tb.colnames()\\n tb.close()\\n return (colname in cols)\",\n \"def __checkcolumns(self, lista: List[str]) -> True:\\r\\n\\r\\n if isinstance(lista, list) is False:\\r\\n raise TypeError(f\\\"{lista} has to be a list.\\\")\\r\\n if len(lista) != 10:\\r\\n raise ValueError(f\\\"{lista} must have 10 columns\\\")\\r\\n\\r\\n errorlista = []\\r\\n\\r\\n # Regarding 'self.tiposDisponiveis',\\r\\n # Layer and Marked happens on the same column.\\r\\n # if there is 'layer', 'marked' won't show up, and viceversa.\\r\\n # Therefore 'self.tiposDisponiveis' is a list with 11 elements. While 'lista' is a list with 10 elements.\\r\\n\\r\\n for _ in lista:\\r\\n # searching for 'Layer'\\r\\n if self.tiposDisponiveis[0].lower() == _.lower():\\r\\n break\\r\\n else:\\r\\n # if 'Layer' wasn't found, searching for 'Marked'\\r\\n for _ in lista:\\r\\n if self.tiposDisponiveis[1].lower() == _.lower():\\r\\n break\\r\\n else:\\r\\n # If none of the two are present on the line, add to the error list\\r\\n errorlista.append(\\\"Layer Or Marked\\\")\\r\\n \\r\\n # repeat the search for all the remaining required values\\\"\\\"\\\"\\r\\n for _ in range(2, len(self.tiposDisponiveis)-1):\\r\\n for x in lista:\\r\\n if x.lower() == self.tiposDisponiveis[_].lower():\\r\\n break\\r\\n else:\\r\\n # Didn't find this column in the list\\r\\n errorlista.append(f\\\"{self.tiposDisponiveis[_]}\\\")\\r\\n\\r\\n # Raising the errors, if any occurred.\\r\\n if len(errorlista) > 0:\\r\\n raise ValueError(f\\\"{errorlista} <- These columns are missing from format.\\\")\\r\\n\\r\\n # Last column has to be 'Text'\\r\\n if lista[9].lower() != self.tiposDisponiveis[10].lower():\\r\\n raise ValueError(f\\\"{lista[9]} last element has to be 'Text'.\\\")\\r\\n \\r\\n return True\",\n \"def test_attempting_to_make_duplicate_column_names_fails(self):\\r\\n\\r\\n with self.assertRaises(ModelException):\\r\\n class BadNames(Model):\\r\\n words = columns.Text()\\r\\n content = columns.Text(db_field='words')\",\n \"def test_daal_pca_bad_column_type(self):\\n with self.assertRaisesRegexp(Exception, \\\"columns must be a list of strings\\\"):\\n self.context.daaltk.models.dimreduction.pca.train(self.frame, 10, k=10)\",\n \"def _validate_limits_cols_prefixed(self):\\n for col in self._limits:\\n self.__validate_col_prefix(\\n col, (SOLAR_PREFIX, WIND_PREFIX), input_name='limits'\\n )\",\n \"def _parse_cols(kwargs):\\n\\n # Get col or cols from kwargs\\n try:\\n cols = kwargs.pop(\\\"cols\\\")\\n except KeyError:\\n try:\\n cols = [kwargs.pop(\\\"col\\\")]\\n except KeyError:\\n raise KeyError(f\\\"Need 'col' or 'cols' field in {kwargs}\\\")\\n\\n # Make sure cols is now a list of strings\\n if not all(\\n isinstance(element, str) for element in cols\\n ) or not isinstance(cols, list):\\n raise TypeError(\\n f\\\"col should be string or cols should be list of strings. \\\"\\n f\\\"Now parsed cols is '{cols}'\\\"\\n )\\n return cols\",\n \"def text_rename_column_errors(dupcols):\\n # Incompatible column and name lists\\n with pytest.raises(ValueError):\\n rename(dupcols, columns='Name', names=['Person', 'Age'])\\n # Unknown column name\\n with pytest.raises(ValueError):\\n rename(dupcols, columns='Names', names='Persons')\\n # Column index out of range\\n with pytest.raises(ValueError):\\n rename(dupcols, columns=100, names='Persons')\",\n \"def test_quoted_column_names_reading_dont_specify_names(self):\\n self.quoted_column_names_reading_template(specify_column_names=False)\",\n \"def _validate_data(self, table_definition, data):\\n if len(data) == 0:\\n # Length zero columns get converted on write.\\n return\\n\\n columns_checked = set()\\n\\n for column_name, column_definition in table_definition.c.items():\\n if column_name in data:\\n expected_type = self._expected_type(column_definition)\\n is_nullable_numeric = (column_definition.nullable and\\n expected_type in [int, float])\\n if is_nullable_numeric:\\n data[column_name] = data[column_name].fillna(value=np.nan)\\n actual_type = data[column_name].dtype\\n is_pandas_extension = isinstance(actual_type, ExtensionDtype)\\n if expected_type is int:\\n self._check_int_type(actual_type, column_name,\\n is_pandas_extension, table_definition)\\n elif expected_type is float:\\n self._check_float_type(actual_type, column_name,\\n table_definition)\\n elif expected_type is str:\\n self._check_str_type(actual_type, column_name, data,\\n table_definition)\\n else:\\n raise RuntimeError(f\\\"Unexpected type from column \\\"\\n f\\\"definitions: {expected_type}.\\\")\\n elif not (column_definition.primary_key or\\n column_definition.nullable):\\n raise DismodFileError(f\\\"Missing column in data for table \\\"\\n f\\\"'{table_definition.name}': \\\"\\n f\\\"'{column_name}'\\\")\\n columns_checked.add(column_name)\\n\\n extra_columns = set(data.columns).difference(table_definition.c.keys())\\n if extra_columns:\\n raise DismodFileError(f\\\"extra columns in data for table \\\"\\n f\\\"'{table_definition.name}': {extra_columns}\\\"\\n )\",\n \"def ensure_column_exists(df, col_name, col_alt = False):\\n if col_name not in df.columns:\\n renamed = False\\n if col_alt:\\n for dta in col_alt:\\n if dta in df.columns:\\n df.rename(columns={dta:col_name}, inplace = True)\\n renamed = True\\n else:\\n pass\\n if not renamed:\\n txt = 'Column %s not found.'%col_name\\n if col_alt:\\n txt += 'Neither one of the alternatives: %s'(col_alt)\\n raise AttributeError(txt)\\n return\",\n \"def check_col(self):\\n return (set(map(lambda x: x.lower(),\\n self.config['dtypes'])) -\\n set(self.metadata.name.values))\",\n \"def test_batch_condition_is_column_from_obs(self):\\n\\n self.validator.adata.uns[\\\"batch_condition\\\"] = [\\\"NO_COLUMN\\\"]\\n self.validator.validate_adata()\\n self.assertEqual(\\n self.validator.errors,\\n [\\n \\\"ERROR: Value 'NO_COLUMN' of list 'batch_condition' is not a \\\"\\n \\\"column in 'adata.obs'.\\\"\\n ],\\n )\",\n \"def has_columns(df, columns):\\n result = True\\n for column in columns:\\n if column not in df.columns:\\n print(\\\"Missing column: {} in DataFrame\\\".format(column))\\n result = False\\n\\n return result\",\n \"def test_read_wrong_column_names(self):\\n self.prepare()\\n self.session.execute(\\\"\\\"\\\"\\n CREATE TABLE testwrongcolumns (\\n a int,\\n b int,\\n c int,\\n PRIMARY KEY(a, b)\\n )\\\"\\\"\\\")\\n\\n tempfile = self.get_temp_file()\\n logger.debug('Writing {}'.format(tempfile.name))\\n write_rows_to_csv(tempfile.name, [[1, 1, 1]])\\n\\n cmd = \\\"\\\"\\\"COPY ks.testwrongcolumns (a, b, d) FROM '{}'\\\"\\\"\\\".format(tempfile.name)\\n out, err, _ = self.run_cqlsh(cmd)\\n logger.debug(out)\\n logger.debug(err)\\n results = list(self.session.execute(\\\"SELECT * FROM testwrongcolumns\\\"))\\n\\n assert 'Invalid column name d' in err\\n assert 'child process(es) died unexpectedly' not in err\\n assert not results\",\n \"def validate_data_format(\\n Xs: List[Tensor], Ys: List[Tensor], Yvars: List[Tensor], metric_names: List[str]\\n) -> None:\\n if len({len(Xs), len(Ys), len(Yvars), len(metric_names)}) > 1:\\n raise ValueError( # pragma: no cover\\n \\\"Lengths of Xs, Ys, Yvars, and metric_names must match. Your \\\"\\n f\\\"inputs have lengths {len(Xs)}, {len(Ys)}, {len(Yvars)}, and \\\"\\n f\\\"{len(metric_names)}, respectively.\\\"\\n )\",\n \"def isValidDataTypeName(name: unicode) -> bool:\\n ...\",\n \"def test_is_valid_manifest_format_using_column_names_to_enums(caplog):\\n column_names_to_enums = {\\n \\\"md5_with_underscores\\\": Columns.MD5,\\n \\\"file size with spaces\\\": Columns.SIZE,\\n \\\"Urls With Caps\\\": Columns.URL,\\n \\\"authz with special chars!@*&\\\": Columns.AUTHZ,\\n }\\n result = is_valid_manifest_format(\\n \\\"tests/validate_manifest_format/manifests/manifest_with_custom_column_names.tsv\\\",\\n column_names_to_enums=column_names_to_enums,\\n )\\n error_log = caplog.text\\n manifest_with_many_types_of_errors_helper(error_log)\\n assert result == False\",\n \"def validate_input(self):\\n self._validate_limits_cols_prefixed()\\n self._validate_fillna_cols_prefixed()\\n self._validate_ratio_input()\",\n \"def valid_col_tester(self, state):\\n vert_state = self.cols(state)\\n for line in vert_state:\\n line_index = vert_state.index(line)\\n vert_word = self.check_word(vert_state[line_index])\\n if not(vert_word):\\n return False\\n return True\",\n \"def require(self, **names):\\n for cut, v in names.items():\\n if not isinstance(cut, str) or cut not in self._names:\\n raise ValueError(\\n \\\"All arguments must be strings that refer to the names of existing selections\\\"\\n )\\n\\n consider = 0\\n require = 0\\n for name, val in names.items():\\n val = bool(val)\\n idx = self._names.index(name)\\n consider |= 1 << idx\\n require |= int(val) << idx\\n return (self._data & self._dtype.type(consider)) == require\",\n \"def test_daal_pca_bad_column_name(self):\\n with self.assertRaisesRegexp(Exception, \\\"column ERR was not found\\\"):\\n self.context.daaltk.models.dimreduction.pca.train(self.frame,\\n [\\\"ERR\\\", \\\"X2\\\", \\\"X3\\\", \\\"X4\\\", \\\"X5\\\",\\n \\\"X6\\\", \\\"X7\\\", \\\"X8\\\", \\\"X9\\\", \\\"X10\\\"],\\n k=10)\",\n \"def valid_type_in_col(arch, **kwargs):\\n return all(\\n attrib.isdigit()\\n for attrib in arch.xpath('//@col')\\n )\",\n \"def check_for_column(self, column_name):\\n if column_name not in self.data.columns:\\n raise RuntimeError(\\\"Source {} has no '{}' column\\\".format(\\n self.name, column_name))\",\n \"def test_columns_non_string_error(self):\\n\\n with pytest.raises(ValueError):\\n\\n BaseTransformer(columns=1)\",\n \"def check_null_columns(spark, df, cols):\\n null_cols_list = []\\n # this assumes the col list matches the original schema\\n # df = df.toDF(*cols)\\n try:\\n df = df.select(*cols)\\n col_null_count = df.select([F.count(F.when(F.isnan(col) | F.col(col).isNull(), col)).alias(col) for col in cols]).toPandas().to_dict()\\n null_cols_list = [k for k, v in col_null_count.items() if v[0] > 0]\\n except Exception as e:\\n logger.error('Probably and invalid column(s) was passed...')\\n return ['failed']\\n return null_cols_list\",\n \"def test_no_column(self):\\n\\n self.assertRaises(ValueError, self.table.where, 'True')\",\n \"def test_from_formula_bad_cols_names():\\n bad_df = pd.DataFrame(columns=['Systolic-BP', 'is_smoker', 'Over+wt'])\\n\\n with pytest.raises(AssertionError):\\n from_formula('Systolic-BP ~ *', bad_df, coerce=False)\\n\\n assert from_formula('Systolic_BP ~ *', bad_df)\",\n \"def check_column_count(cls, line):\\n\\n # MAGIC n_cols = n_delim + 1 (no trailing delimiter)\\n cols = line.count(cls.DELIMITER) + 1\\n expected = 7 # MAGIC USAA convention, not all are populated though\\n return cols == expected\",\n \"def _validate_merge_col_exists(self):\\n msg = (\\\"Cannot hybridize: merge column {!r} missing from the \\\"\\n \\\"{} meta data! ({!r})\\\")\\n\\n mc = ColNameFormatter.fmt(MERGE_COLUMN)\\n for cols, fp, res in zip([self.__solar_cols, self.__wind_cols],\\n [self.solar_fpath, self.wind_fpath],\\n ['solar', 'wind']):\\n if mc not in cols:\\n e = msg.format(MERGE_COLUMN, res, fp)\\n logger.error(e)\\n raise FileInputError(e)\",\n \"def get_columns_for(self, column_names, row, dbrow=None):\\n if dbrow:\\n candidates = filter(lambda col: col not in self.insert_only_fields, column_names)\\n else:\\n candidates = column_names\\n\\n return set(candidates).intersection(row._fields)\",\n \"def test_extract_invalid_column(self):\\n self.dicom.extract_keywords([\\\"invalid\\\"])\\n\\n # ensure column was added\\n columns = self.dicom.metadata.column_names\\n if u'invalid' not in columns:\\n raise Exception(\\\"Invalid column not added\\\")\\n\\n # compare expected and actual result\\n invalid_column = self.dicom.metadata.take(self.count, columns=[u'invalid'])\\n expected_result = [[None] for x in range(0, self.count)]\\n self.assertEqual(invalid_column, expected_result)\",\n \"def testColumnsNotListWrapped(self):\\n with self.assertRaises(TypeError):\\n Table(self.base_case[\\\"name\\\"], Column(\\\"col1\\\", str))\",\n \"def _check_availability(self, names: Iterable) -> None:\\n unavailable = [x for x in names if x not in self.__by_name.keys()]\\n if unavailable:\\n raise ValueError(f'datasets: {unavailable} not available in the {self.region} region.')\",\n \"def test_wrong_number_of_columns(self):\\n self.prepare()\\n self.session.execute(\\\"\\\"\\\"\\n CREATE TABLE testcolumns (\\n a int PRIMARY KEY,\\n b int\\n )\\\"\\\"\\\")\\n\\n data = [[1, 2, 3]]\\n tempfile = self.get_temp_file()\\n write_rows_to_csv(tempfile.name, data)\\n\\n logger.debug('Importing from csv file: {name}'.format(name=tempfile.name))\\n out, err, _ = self.run_cqlsh(\\\"COPY ks.testcolumns FROM '{name}'\\\".format(name=tempfile.name))\\n\\n assert not self.session.execute(\\\"SELECT * FROM testcolumns\\\")\\n assert 'Failed to import' in err\",\n \"def validate(self):\\n regexp = re.compile(self.raw_pattern)\\n missing = regexp.findall(self.sql)\\n if missing:\\n raise NameError(\\\"Value not provided for placeholder {}\\\".format(missing))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8195807","0.7515005","0.74477583","0.73584527","0.72443414","0.72358197","0.7166061","0.7122262","0.7121349","0.711966","0.7089864","0.708901","0.69831634","0.6980481","0.6958175","0.6949049","0.692618","0.6905489","0.6900764","0.6798847","0.6783542","0.67330474","0.6715883","0.6705759","0.66049206","0.65741473","0.6572069","0.65707684","0.65682274","0.6429215","0.63614476","0.63590336","0.63539344","0.6342669","0.6340701","0.63285786","0.63234776","0.6278749","0.6272669","0.62638825","0.6258839","0.6257768","0.6252311","0.6251879","0.6242469","0.6216212","0.6185083","0.61503834","0.61422026","0.61311364","0.61254764","0.6112051","0.6111085","0.60400295","0.60373324","0.60243326","0.601591","0.6012524","0.6001097","0.5979872","0.59586906","0.593003","0.59170794","0.5905363","0.58988976","0.5896816","0.587319","0.58684033","0.5866659","0.5864814","0.5853242","0.58384067","0.5833028","0.58205634","0.5808726","0.58062154","0.58030957","0.5802793","0.57942003","0.57867885","0.57778835","0.5762041","0.57612824","0.5752824","0.5748606","0.5718909","0.570704","0.5703594","0.5692021","0.5691629","0.5688113","0.5678081","0.56740993","0.56724846","0.5661312","0.5658886","0.5641835","0.5638078","0.56225085","0.56143105"],"string":"[\n \"0.8195807\",\n \"0.7515005\",\n \"0.74477583\",\n \"0.73584527\",\n \"0.72443414\",\n \"0.72358197\",\n \"0.7166061\",\n \"0.7122262\",\n \"0.7121349\",\n \"0.711966\",\n \"0.7089864\",\n \"0.708901\",\n \"0.69831634\",\n \"0.6980481\",\n \"0.6958175\",\n \"0.6949049\",\n \"0.692618\",\n \"0.6905489\",\n \"0.6900764\",\n \"0.6798847\",\n \"0.6783542\",\n \"0.67330474\",\n \"0.6715883\",\n \"0.6705759\",\n \"0.66049206\",\n \"0.65741473\",\n \"0.6572069\",\n \"0.65707684\",\n \"0.65682274\",\n \"0.6429215\",\n \"0.63614476\",\n \"0.63590336\",\n \"0.63539344\",\n \"0.6342669\",\n \"0.6340701\",\n \"0.63285786\",\n \"0.63234776\",\n \"0.6278749\",\n \"0.6272669\",\n \"0.62638825\",\n \"0.6258839\",\n \"0.6257768\",\n \"0.6252311\",\n \"0.6251879\",\n \"0.6242469\",\n \"0.6216212\",\n \"0.6185083\",\n \"0.61503834\",\n \"0.61422026\",\n \"0.61311364\",\n \"0.61254764\",\n \"0.6112051\",\n \"0.6111085\",\n \"0.60400295\",\n \"0.60373324\",\n \"0.60243326\",\n \"0.601591\",\n \"0.6012524\",\n \"0.6001097\",\n \"0.5979872\",\n \"0.59586906\",\n \"0.593003\",\n \"0.59170794\",\n \"0.5905363\",\n \"0.58988976\",\n \"0.5896816\",\n \"0.587319\",\n \"0.58684033\",\n \"0.5866659\",\n \"0.5864814\",\n \"0.5853242\",\n \"0.58384067\",\n \"0.5833028\",\n \"0.58205634\",\n \"0.5808726\",\n \"0.58062154\",\n \"0.58030957\",\n \"0.5802793\",\n \"0.57942003\",\n \"0.57867885\",\n \"0.57778835\",\n \"0.5762041\",\n \"0.57612824\",\n \"0.5752824\",\n \"0.5748606\",\n \"0.5718909\",\n \"0.570704\",\n \"0.5703594\",\n \"0.5692021\",\n \"0.5691629\",\n \"0.5688113\",\n \"0.5678081\",\n \"0.56740993\",\n \"0.56724846\",\n \"0.5661312\",\n \"0.5658886\",\n \"0.5641835\",\n \"0.5638078\",\n \"0.56225085\",\n \"0.56143105\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8290189"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":3999,"cells":{"query":{"kind":"string","value":"Find location for column value."},"document":{"kind":"string","value":"def column_location(self, value):\n\n # Try to use as-is\n try:\n return self._columns.index(value)\n except ValueError:\n pass\n\n # Try as integer index\n try:\n value = int(value)\n\n if value in self._columns:\n location = self._columns.index(value)\n elif value < 0:\n location = value + len(self._columns)\n else:\n location = value\n\n size = len(self._columns)\n if size == 0:\n raise IndexError(\"No columns in table\")\n\n if location >= size:\n raise IndexError(f\"Column ({location}) out of range (0..{size - 1})\")\n\n return location\n except ValueError:\n pass\n\n # No matches\n options = \", \".join(str(col) for col in self._columns)\n raise ValueError(f\"Unknown column name: {value}, current columns: {options}\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _col_match(sheet, row, value):\r\n for cell in sheet[row]:\r\n if cell.value == value:\r\n return cell.column","def _value_column(self, field):\n for field_dict in self.schema['idx_fields']:\n if field_dict['field_name'] == field:\n return field_dict['column']\n return 0","def loc_value(self):\n return self._loc_value[1]","def find_col(table, col):\n return table[0].index(col)","def find(self, value):\n for row in range(self.getHeight()):\n for column in range(self.getWidth()):\n if self[row][column] == value:\n return (row, column)\n return None","def col(self):\n return self.address.col","def find_value(self, x, y):\n for cell in self.cells:\n if cell.coordinates == (x,y):\n return cell.value\n else:\n return None","def get_position(self, row, column):\n position_key = \"{}{}\".format(row, column)\n return self.positions[position_key]","def find_offset(self,value):\n return self.header.find_offset(value)","def find_in_column(self, column, value):\n values = [cell[column - 1] for cell in self._op.values]\n try:\n return values.index(value) + 1\n except ValueError:\n return 0","def find_position(self, element):\n for row in range(self.rows):\n for col in range(self.cols):\n if self.data[row][col] == element:\n return row, col\n return None, None","def find_position(self, element):\n for row in range(self.rows):\n for col in range(self.cols):\n if self.data[row][col] == element:\n return row, col\n return None, None","def get_source_column(self, column):\n return self._source.columns.get_loc(self._dataframe.columns[column])","def _get_value(self, value_column):\n pass","def getColumnPosition(sheetData, columnName, defaultPosition):\n headerRow = getHeaderRowPosition(sheetData)\n columnRow = sheetData[headerRow]\n try:\n return columnRow.index(columnName)\n except ValueError:\n return defaultPosition","def get_location(line):\n line = line.split('\\t')\n for char in line:\n if ',' in char and line.index(char) != 0:\n char_index = line.index(char)\n return line[char_index]","def extract_location(x):\n if not pd.isna(x):\n x = ast.literal_eval(x)\n location = x['name']\n return location\n else:\n return np.nan","def current_position(self, solved_row, solved_col):\n solved_value = (solved_col + self._width * solved_row)\n\n for row in range(self._height):\n for col in range(self._width):\n if self._grid[row][col] == solved_value:\n return (row, col)\n assert False, \"Value \" + str(solved_value) + \" not found\"","def current_position(self, solved_row, solved_col):\n solved_value = (solved_col + self._width * solved_row)\n\n for row in range(self._height):\n for col in range(self._width):\n if self._grid[row][col] == solved_value:\n return (row, col)\n assert False, \"Value \" + str(solved_value) + \" not found\"","def current_position(self, solved_row, solved_col):\n solved_value = (solved_col + self._width * solved_row)\n\n for row in range(self._height):\n for col in range(self._width):\n if self._grid[row][col] == solved_value:\n return (row, col)\n assert False, \"Value \" + str(solved_value) + \" not found\"","def current_position(self, solved_row, solved_col):\n solved_value = (solved_col + self._width * solved_row)\n\n for row in range(self._height):\n for col in range(self._width):\n if self._grid[row][col] == solved_value:\n return (row, col)\n assert False, \"Value \" + str(solved_value) + \" not found\"","def _get_col(self, idx):\n return self.line[self._fwf.column_slices[idx]]","def find_coordinates(self, value):\n cells = {v.coordinates for v in self.cells if v.value == value}\n return cells if len(cells) > 0 else None","def current_position(self, solved_row, solved_col):\r\n solved_value = (solved_col + self._width * solved_row)\r\n\r\n for row in range(self._height):\r\n for col in range(self._width):\r\n if self._grid[row][col] == solved_value:\r\n return (row, col)\r\n assert False, \"Value \" + str(solved_value) + \" not found\"","def current_position(self, solved_row, solved_col):\r\n solved_value = (solved_col + self._width * solved_row)\r\n\r\n for row in range(self._height):\r\n for col in range(self._width):\r\n if self._grid[row][col] == solved_value:\r\n return (row, col)\r\n assert False, \"Value \" + str(solved_value) + \" not found\"","def current_position(self, solved_row, solved_col):\r\n solved_value = (solved_col + self._width * solved_row)\r\n\r\n for row in range(self._height):\r\n for col in range(self._width):\r\n if self._grid[row][col] == solved_value:\r\n return (row, col)\r\n assert False, \"Value \" + str(solved_value) + \" not found\"","def column(self):\n return self[\"column\"]","def column(self): \r\n\r\n return self._column","def find_value(self, value_to_find):\n pos = np.where(self.board == value_to_find)\n # convert pos to tuple of ints\n return tuple(ax[0] for ax in pos)","def loc(self):\n return self._loc","def loc(self):\n return self._loc","def getCellValue_quick(self, row, column):\n\n\t\t\t\treturn self.thing[f\"{column}{row}\"].value","def get_column(self):\n return self._column_number","def _get_column(self, column_or_label):\n c = column_or_label\n if isinstance(c, collections.Hashable) and c in self.column_labels:\n return self[c]\n else:\n assert len(c) == self.num_rows, 'column length mismatch'\n return c","def find(self, value):\n for position in range(self.get_size()):\n if self.table[position] == value:\n return position","def get_value(self, col, i) :\n\n if col not in self.cols :\n raise Exception('Column %s not in data' % col)\n if len(self.rows) <= i :\n raise Exception('Table has fewer than %d rows' % i)\n return self.rows[i][self.col_indices[col]]","def getColIdx(self, col):\n try: \n return int(col)\n except:\n return ord(col)-ord('a')","def _get_col(self, idx):\n return self.text[self._fwf.column_slices[idx]]","def column(self) -> int:\n return self._column","def location_of(self, c: str) -> tuple:\n\n c = c.upper()\n if c == 'J': c = 'I'\n\n row = 0\n while row < 5:\n col = self.key[row].find(c)\n\n if col != -1:\n return (row, col)\n\n row += 1\n\n raise ValueError(\"couldn't find letter %r in matrix %r\" % (c, self.key))","def get_column(self, pos, **opts):\n lnum, cnum = self._get_column(pos, **opts)\n return lnum + self.LINE_NUM_BASE, cnum + self.COLUMN_NUM_BASE","def getColIdx(self, col):\n try:\n return int(col)\n except:\n return ord(col)-ord('a')","def _get_header_position(header_row: List[str], column_title: str) -> int:\n for pos, column in enumerate(header_row):\n if column_title.lower() in column.lower():\n return pos\n\n raise Exception(\"Expected column header not found for {}\".format(column_title))","def find_column_index(self, columns):\n for i in range(len(columns)):\n if self.match(columns[i]):\n return i\n return None","def get_position(self, number):\n for rowidx, row in enumerate(self.numbers):\n for colidx, num in enumerate(row):\n if num == number:\n return rowidx, colidx","def _get_column(self, pos, **opts):\n lnum, cpos = self._get_linepos(pos)\n start, end = self._get_linespan(lnum)\n return lnum, self._pos2col(start, cpos, **opts)","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def column(self) -> pulumi.Input[int]:\n return pulumi.get(self, \"column\")","def GetActualValue(self, row, col):\r\n try:\r\n return self.data[row][col]\r\n except IndexError:\r\n return None","def search_col(sheet, start, value, limit=200):\n # first, split column letter from row number in start variable\n re_str = re.compile('[^a-zA-Z]') # will identify all non letters\n col = re_str.sub('', start) # get our column\n\n re_int = re.compile('[^0-9]') # will identify all non integers\n row = int(re_int.sub('', start)) # get our row\n\n # start iterating through upto limit or when we find the value\n for _ in range(limit):\n if sheet[col+str(row)].value == value:\n # if we find the value, return where we found it\n return (col, row)\n # if we don't find the value, move onto the next row\n row += 1\n # if we iterate over the limit number, we assume the value cannot be found\n # and raise an error\n raise KeyError(f'{value} not found in column {col} of workbook.')","def locate(self, column, cond_inp):\n\n try:\n return self.df_input.loc[self.df_input[column] == cond_inp]\n except Exception as e:\n print(e)","def find_column(self, columns):\n for column in columns:\n if self.match(column):\n return column\n return None","def _get_position_grid_column(position, grid_row):\n \n for (box, grid_col_index) in zip(grid_row, range(len(grid_row))):\n if box.contains_point((position.x, position.y)):\n return grid_col_index\n return None","def get_index(self, column):\r\n\r\n\t\treturn self.columns.index(column)","def cellval(row, col):\n key = 'R'+str(row)+'C'+str(col)\n if key not in DATA:\n return None\n return DATA[key]","def where(self, column_or_label, value=None):\n column = self._get_column(column_or_label)\n if value is not None:\n column = column == value\n return self.take(np.nonzero(column)[0])","def find_position(self, val):\n edges = np.array(self.cell_edges)\n if val in edges:\n index = np.searchsorted(edges, val)\n return index, index\n else:\n edges -= val\n if edges[0] > 0:\n return -1, 0\n if edges[-1] < 0:\n return 0, -1\n index = 0\n for i, e in enumerate(edges):\n if e > 0:\n index = i\n break\n return index - 1, index","def cell_value(self, row, col):\n if col > 1:\n raise Exception(\"Only two columns available in a Table.\")\n elif row >= self.rows:\n raise Exception(\"Maximum row index is %d\" % len(self.headings)-1)\n elif col == 0:\n return self.headings[row]\n else:\n heading = self.headings[row]\n return self.data[heading]","def get_colnumber(self, header):\n for i in range(0, len(self.data)):\n if self.data[i][0] == header:\n return i\n return None","def pos(self):\n return self.info['value']","def col(self):\n\t\treturn self.__col","def GetColumn(self, column):\r\n \r\n return self._header_win.GetColumn(column)","def get_index_in_table_column(self, table_locator, col, expected, loglevel='INFO'):\n has_head=0\n element = self._table_element_finder.find_by_header(self._current_browser(), table_locator, None)\n if element is not None:\n has_head = 1\n index = self._table_element_finder.find_in_col(self._current_browser(), table_locator, col, expected)\n if index <= 0:\n self.log_source(loglevel)\n raise AssertionError(\"Column #%s in table identified by '%s' \"\n \"should have contained text '%s'.\"\n % (col, table_locator, expected))\n return index+has_head","def column(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"column\")","def location_to_pos(self,row, col):\r\n\r\n pos_row = str(row + 1)\r\n pos_col = chr(col + 97)\r\n return pos_col + pos_row","def where_is(barcode: str):\n try:\n cell = sheet.find(barcode)\n location = sheet.cell(cell.row, cell.col + 1).value\n return str(location)\n\n except:\n return str(\"nowhere. NO CURRENT LOCATION FOR \" + barcode)","def _get_column_offset(self, lnum, colnum, **opts):\n start, end = self._get_linespan(lnum)\n length = end - start\n cpos = self._col2pos(start, colnum, **opts)\n if cpos < 0 or cpos >= length:\n raise IndexError(\"column out of bounds\")\n\n return start + cpos","def get_value( self, header, rowIndex ):\n return self.data[rowIndex, self.header2col[header]]","def _get_column(self, index):\n left, right = self._get_columns()\n return left if index < left.count else right","def _value(self, row):\n return row[\"_source\"][self.name]","def _get_column_values(self, col: str) -> ndarray:\n dtype, loc = self._get_col_dtype_loc(col) # type: str, int\n return self._data[dtype][:, loc]","def target_location(self):\n lst = self.cell_list()\n return lst[-1]","def get_coord_by_value(self, value):\n pos = self._state.index(value)+1\n row = pos // self._size\n col = pos % self._size\n return [row, col]","def _check_column(self):\n for column in np.transpose(self._board):\n col_string = ''.join(column)\n match = re.search(WIN_REGEX, col_string)\n if match:\n return match.group()[0]\n return None","def getCoordinateAt(self,colIndex,rowIndex):\n gridval = self.grid.get(self.createKey(colIndex,rowIndex),self.defaultVal)\n retvals = [self.currentCol,self.currentRow,gridval]\n return retvals","def table_column(self, i):\n return self.__column_list[i]","def get_column(filename, column_name):\n with open(filename) as f:\n for header in f:\n columns = header.rstrip().split(\"\\t\")\n return columns.index(column_name)","def column_marker(column):\n if (column)//7 == 0:\n marker = 'x'\n elif (column)//7 == 1:\n marker = '+'\n else:\n marker = 'd'\n return marker","def column_index(self, column_label):\n return self.column_labels.index(column_label)","def indexToPosition(self, col, row):\n columns = \"ABCDEFGH\"\n return columns[col] + str(row + 1)","def get_index(self, row, col):\n return (row * self.cols) + col","def which_cell(loc_x, loc_y):\n column = int(math.ceil((loc_x - LEFT_MARGIN) / CELL_SIZE))\n row = int(math.ceil((loc_y - TOP_MARGIN) / CELL_SIZE))\n cell_id = (row - 1) * CELL_COLUMN + column\n return cell_id","def locate_point(self, coord):\n lowest_lat = self.lower_left[0]\n leftmost_lng = self.lower_left[1]\n dist_lat = utils.haversine((coord[0], leftmost_lng), self.lower_left)*1000 # in meters\n dist_lng = utils.haversine((lowest_lat, coord[1]), self.lower_left)*1000 # in meters\n grid_coord = (floor(dist_lng/self.distance), floor(dist_lat/self.distance))\n if grid_coord in self.cells:\n return grid_coord\n return None","def col(self, name):\n # Identify the column corresponding to the\n # supplied name and return a copy of the data\n for i in range(0, self.ncolumns()):\n if self.table_column(i).title() == name:\n return copy.copy(self.table_column(i).data())\n # Column not found\n raise LookupError(\"Column called '\" + str(name) + \"' not found\")","def get_column(col_to_search, value_to_match, col_to_get, table, db_file):\n \n try:\n conn, c = connect_to_db(db_file) \n c.execute('SELECT {cg} FROM {t} WHERE {col}=\"{value}\"'.format(t=safe(table), \n cg=safe(col_to_get), col=safe(col_to_search), value=safe(value_to_match)))\n column = c.fetchone()\n conn.close()\n return column\n except Exception as e:\n print(\"Error when trying to fetch row in table\", table, \"in database file\", db_file)\n print(e)\n return None","def __get_position(self, value, state):\n coords = np.argwhere(state == value).flatten()\n return coords","def position(self) -> Tuple[int, int]:\n return self.row, self.col"],"string":"[\n \"def _col_match(sheet, row, value):\\r\\n for cell in sheet[row]:\\r\\n if cell.value == value:\\r\\n return cell.column\",\n \"def _value_column(self, field):\\n for field_dict in self.schema['idx_fields']:\\n if field_dict['field_name'] == field:\\n return field_dict['column']\\n return 0\",\n \"def loc_value(self):\\n return self._loc_value[1]\",\n \"def find_col(table, col):\\n return table[0].index(col)\",\n \"def find(self, value):\\n for row in range(self.getHeight()):\\n for column in range(self.getWidth()):\\n if self[row][column] == value:\\n return (row, column)\\n return None\",\n \"def col(self):\\n return self.address.col\",\n \"def find_value(self, x, y):\\n for cell in self.cells:\\n if cell.coordinates == (x,y):\\n return cell.value\\n else:\\n return None\",\n \"def get_position(self, row, column):\\n position_key = \\\"{}{}\\\".format(row, column)\\n return self.positions[position_key]\",\n \"def find_offset(self,value):\\n return self.header.find_offset(value)\",\n \"def find_in_column(self, column, value):\\n values = [cell[column - 1] for cell in self._op.values]\\n try:\\n return values.index(value) + 1\\n except ValueError:\\n return 0\",\n \"def find_position(self, element):\\n for row in range(self.rows):\\n for col in range(self.cols):\\n if self.data[row][col] == element:\\n return row, col\\n return None, None\",\n \"def find_position(self, element):\\n for row in range(self.rows):\\n for col in range(self.cols):\\n if self.data[row][col] == element:\\n return row, col\\n return None, None\",\n \"def get_source_column(self, column):\\n return self._source.columns.get_loc(self._dataframe.columns[column])\",\n \"def _get_value(self, value_column):\\n pass\",\n \"def getColumnPosition(sheetData, columnName, defaultPosition):\\n headerRow = getHeaderRowPosition(sheetData)\\n columnRow = sheetData[headerRow]\\n try:\\n return columnRow.index(columnName)\\n except ValueError:\\n return defaultPosition\",\n \"def get_location(line):\\n line = line.split('\\\\t')\\n for char in line:\\n if ',' in char and line.index(char) != 0:\\n char_index = line.index(char)\\n return line[char_index]\",\n \"def extract_location(x):\\n if not pd.isna(x):\\n x = ast.literal_eval(x)\\n location = x['name']\\n return location\\n else:\\n return np.nan\",\n \"def current_position(self, solved_row, solved_col):\\n solved_value = (solved_col + self._width * solved_row)\\n\\n for row in range(self._height):\\n for col in range(self._width):\\n if self._grid[row][col] == solved_value:\\n return (row, col)\\n assert False, \\\"Value \\\" + str(solved_value) + \\\" not found\\\"\",\n \"def current_position(self, solved_row, solved_col):\\n solved_value = (solved_col + self._width * solved_row)\\n\\n for row in range(self._height):\\n for col in range(self._width):\\n if self._grid[row][col] == solved_value:\\n return (row, col)\\n assert False, \\\"Value \\\" + str(solved_value) + \\\" not found\\\"\",\n \"def current_position(self, solved_row, solved_col):\\n solved_value = (solved_col + self._width * solved_row)\\n\\n for row in range(self._height):\\n for col in range(self._width):\\n if self._grid[row][col] == solved_value:\\n return (row, col)\\n assert False, \\\"Value \\\" + str(solved_value) + \\\" not found\\\"\",\n \"def current_position(self, solved_row, solved_col):\\n solved_value = (solved_col + self._width * solved_row)\\n\\n for row in range(self._height):\\n for col in range(self._width):\\n if self._grid[row][col] == solved_value:\\n return (row, col)\\n assert False, \\\"Value \\\" + str(solved_value) + \\\" not found\\\"\",\n \"def _get_col(self, idx):\\n return self.line[self._fwf.column_slices[idx]]\",\n \"def find_coordinates(self, value):\\n cells = {v.coordinates for v in self.cells if v.value == value}\\n return cells if len(cells) > 0 else None\",\n \"def current_position(self, solved_row, solved_col):\\r\\n solved_value = (solved_col + self._width * solved_row)\\r\\n\\r\\n for row in range(self._height):\\r\\n for col in range(self._width):\\r\\n if self._grid[row][col] == solved_value:\\r\\n return (row, col)\\r\\n assert False, \\\"Value \\\" + str(solved_value) + \\\" not found\\\"\",\n \"def current_position(self, solved_row, solved_col):\\r\\n solved_value = (solved_col + self._width * solved_row)\\r\\n\\r\\n for row in range(self._height):\\r\\n for col in range(self._width):\\r\\n if self._grid[row][col] == solved_value:\\r\\n return (row, col)\\r\\n assert False, \\\"Value \\\" + str(solved_value) + \\\" not found\\\"\",\n \"def current_position(self, solved_row, solved_col):\\r\\n solved_value = (solved_col + self._width * solved_row)\\r\\n\\r\\n for row in range(self._height):\\r\\n for col in range(self._width):\\r\\n if self._grid[row][col] == solved_value:\\r\\n return (row, col)\\r\\n assert False, \\\"Value \\\" + str(solved_value) + \\\" not found\\\"\",\n \"def column(self):\\n return self[\\\"column\\\"]\",\n \"def column(self): \\r\\n\\r\\n return self._column\",\n \"def find_value(self, value_to_find):\\n pos = np.where(self.board == value_to_find)\\n # convert pos to tuple of ints\\n return tuple(ax[0] for ax in pos)\",\n \"def loc(self):\\n return self._loc\",\n \"def loc(self):\\n return self._loc\",\n \"def getCellValue_quick(self, row, column):\\n\\n\\t\\t\\t\\treturn self.thing[f\\\"{column}{row}\\\"].value\",\n \"def get_column(self):\\n return self._column_number\",\n \"def _get_column(self, column_or_label):\\n c = column_or_label\\n if isinstance(c, collections.Hashable) and c in self.column_labels:\\n return self[c]\\n else:\\n assert len(c) == self.num_rows, 'column length mismatch'\\n return c\",\n \"def find(self, value):\\n for position in range(self.get_size()):\\n if self.table[position] == value:\\n return position\",\n \"def get_value(self, col, i) :\\n\\n if col not in self.cols :\\n raise Exception('Column %s not in data' % col)\\n if len(self.rows) <= i :\\n raise Exception('Table has fewer than %d rows' % i)\\n return self.rows[i][self.col_indices[col]]\",\n \"def getColIdx(self, col):\\n try: \\n return int(col)\\n except:\\n return ord(col)-ord('a')\",\n \"def _get_col(self, idx):\\n return self.text[self._fwf.column_slices[idx]]\",\n \"def column(self) -> int:\\n return self._column\",\n \"def location_of(self, c: str) -> tuple:\\n\\n c = c.upper()\\n if c == 'J': c = 'I'\\n\\n row = 0\\n while row < 5:\\n col = self.key[row].find(c)\\n\\n if col != -1:\\n return (row, col)\\n\\n row += 1\\n\\n raise ValueError(\\\"couldn't find letter %r in matrix %r\\\" % (c, self.key))\",\n \"def get_column(self, pos, **opts):\\n lnum, cnum = self._get_column(pos, **opts)\\n return lnum + self.LINE_NUM_BASE, cnum + self.COLUMN_NUM_BASE\",\n \"def getColIdx(self, col):\\n try:\\n return int(col)\\n except:\\n return ord(col)-ord('a')\",\n \"def _get_header_position(header_row: List[str], column_title: str) -> int:\\n for pos, column in enumerate(header_row):\\n if column_title.lower() in column.lower():\\n return pos\\n\\n raise Exception(\\\"Expected column header not found for {}\\\".format(column_title))\",\n \"def find_column_index(self, columns):\\n for i in range(len(columns)):\\n if self.match(columns[i]):\\n return i\\n return None\",\n \"def get_position(self, number):\\n for rowidx, row in enumerate(self.numbers):\\n for colidx, num in enumerate(row):\\n if num == number:\\n return rowidx, colidx\",\n \"def _get_column(self, pos, **opts):\\n lnum, cpos = self._get_linepos(pos)\\n start, end = self._get_linespan(lnum)\\n return lnum, self._pos2col(start, cpos, **opts)\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def column(self) -> pulumi.Input[int]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def GetActualValue(self, row, col):\\r\\n try:\\r\\n return self.data[row][col]\\r\\n except IndexError:\\r\\n return None\",\n \"def search_col(sheet, start, value, limit=200):\\n # first, split column letter from row number in start variable\\n re_str = re.compile('[^a-zA-Z]') # will identify all non letters\\n col = re_str.sub('', start) # get our column\\n\\n re_int = re.compile('[^0-9]') # will identify all non integers\\n row = int(re_int.sub('', start)) # get our row\\n\\n # start iterating through upto limit or when we find the value\\n for _ in range(limit):\\n if sheet[col+str(row)].value == value:\\n # if we find the value, return where we found it\\n return (col, row)\\n # if we don't find the value, move onto the next row\\n row += 1\\n # if we iterate over the limit number, we assume the value cannot be found\\n # and raise an error\\n raise KeyError(f'{value} not found in column {col} of workbook.')\",\n \"def locate(self, column, cond_inp):\\n\\n try:\\n return self.df_input.loc[self.df_input[column] == cond_inp]\\n except Exception as e:\\n print(e)\",\n \"def find_column(self, columns):\\n for column in columns:\\n if self.match(column):\\n return column\\n return None\",\n \"def _get_position_grid_column(position, grid_row):\\n \\n for (box, grid_col_index) in zip(grid_row, range(len(grid_row))):\\n if box.contains_point((position.x, position.y)):\\n return grid_col_index\\n return None\",\n \"def get_index(self, column):\\r\\n\\r\\n\\t\\treturn self.columns.index(column)\",\n \"def cellval(row, col):\\n key = 'R'+str(row)+'C'+str(col)\\n if key not in DATA:\\n return None\\n return DATA[key]\",\n \"def where(self, column_or_label, value=None):\\n column = self._get_column(column_or_label)\\n if value is not None:\\n column = column == value\\n return self.take(np.nonzero(column)[0])\",\n \"def find_position(self, val):\\n edges = np.array(self.cell_edges)\\n if val in edges:\\n index = np.searchsorted(edges, val)\\n return index, index\\n else:\\n edges -= val\\n if edges[0] > 0:\\n return -1, 0\\n if edges[-1] < 0:\\n return 0, -1\\n index = 0\\n for i, e in enumerate(edges):\\n if e > 0:\\n index = i\\n break\\n return index - 1, index\",\n \"def cell_value(self, row, col):\\n if col > 1:\\n raise Exception(\\\"Only two columns available in a Table.\\\")\\n elif row >= self.rows:\\n raise Exception(\\\"Maximum row index is %d\\\" % len(self.headings)-1)\\n elif col == 0:\\n return self.headings[row]\\n else:\\n heading = self.headings[row]\\n return self.data[heading]\",\n \"def get_colnumber(self, header):\\n for i in range(0, len(self.data)):\\n if self.data[i][0] == header:\\n return i\\n return None\",\n \"def pos(self):\\n return self.info['value']\",\n \"def col(self):\\n\\t\\treturn self.__col\",\n \"def GetColumn(self, column):\\r\\n \\r\\n return self._header_win.GetColumn(column)\",\n \"def get_index_in_table_column(self, table_locator, col, expected, loglevel='INFO'):\\n has_head=0\\n element = self._table_element_finder.find_by_header(self._current_browser(), table_locator, None)\\n if element is not None:\\n has_head = 1\\n index = self._table_element_finder.find_in_col(self._current_browser(), table_locator, col, expected)\\n if index <= 0:\\n self.log_source(loglevel)\\n raise AssertionError(\\\"Column #%s in table identified by '%s' \\\"\\n \\\"should have contained text '%s'.\\\"\\n % (col, table_locator, expected))\\n return index+has_head\",\n \"def column(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"column\\\")\",\n \"def location_to_pos(self,row, col):\\r\\n\\r\\n pos_row = str(row + 1)\\r\\n pos_col = chr(col + 97)\\r\\n return pos_col + pos_row\",\n \"def where_is(barcode: str):\\n try:\\n cell = sheet.find(barcode)\\n location = sheet.cell(cell.row, cell.col + 1).value\\n return str(location)\\n\\n except:\\n return str(\\\"nowhere. NO CURRENT LOCATION FOR \\\" + barcode)\",\n \"def _get_column_offset(self, lnum, colnum, **opts):\\n start, end = self._get_linespan(lnum)\\n length = end - start\\n cpos = self._col2pos(start, colnum, **opts)\\n if cpos < 0 or cpos >= length:\\n raise IndexError(\\\"column out of bounds\\\")\\n\\n return start + cpos\",\n \"def get_value( self, header, rowIndex ):\\n return self.data[rowIndex, self.header2col[header]]\",\n \"def _get_column(self, index):\\n left, right = self._get_columns()\\n return left if index < left.count else right\",\n \"def _value(self, row):\\n return row[\\\"_source\\\"][self.name]\",\n \"def _get_column_values(self, col: str) -> ndarray:\\n dtype, loc = self._get_col_dtype_loc(col) # type: str, int\\n return self._data[dtype][:, loc]\",\n \"def target_location(self):\\n lst = self.cell_list()\\n return lst[-1]\",\n \"def get_coord_by_value(self, value):\\n pos = self._state.index(value)+1\\n row = pos // self._size\\n col = pos % self._size\\n return [row, col]\",\n \"def _check_column(self):\\n for column in np.transpose(self._board):\\n col_string = ''.join(column)\\n match = re.search(WIN_REGEX, col_string)\\n if match:\\n return match.group()[0]\\n return None\",\n \"def getCoordinateAt(self,colIndex,rowIndex):\\n gridval = self.grid.get(self.createKey(colIndex,rowIndex),self.defaultVal)\\n retvals = [self.currentCol,self.currentRow,gridval]\\n return retvals\",\n \"def table_column(self, i):\\n return self.__column_list[i]\",\n \"def get_column(filename, column_name):\\n with open(filename) as f:\\n for header in f:\\n columns = header.rstrip().split(\\\"\\\\t\\\")\\n return columns.index(column_name)\",\n \"def column_marker(column):\\n if (column)//7 == 0:\\n marker = 'x'\\n elif (column)//7 == 1:\\n marker = '+'\\n else:\\n marker = 'd'\\n return marker\",\n \"def column_index(self, column_label):\\n return self.column_labels.index(column_label)\",\n \"def indexToPosition(self, col, row):\\n columns = \\\"ABCDEFGH\\\"\\n return columns[col] + str(row + 1)\",\n \"def get_index(self, row, col):\\n return (row * self.cols) + col\",\n \"def which_cell(loc_x, loc_y):\\n column = int(math.ceil((loc_x - LEFT_MARGIN) / CELL_SIZE))\\n row = int(math.ceil((loc_y - TOP_MARGIN) / CELL_SIZE))\\n cell_id = (row - 1) * CELL_COLUMN + column\\n return cell_id\",\n \"def locate_point(self, coord):\\n lowest_lat = self.lower_left[0]\\n leftmost_lng = self.lower_left[1]\\n dist_lat = utils.haversine((coord[0], leftmost_lng), self.lower_left)*1000 # in meters\\n dist_lng = utils.haversine((lowest_lat, coord[1]), self.lower_left)*1000 # in meters\\n grid_coord = (floor(dist_lng/self.distance), floor(dist_lat/self.distance))\\n if grid_coord in self.cells:\\n return grid_coord\\n return None\",\n \"def col(self, name):\\n # Identify the column corresponding to the\\n # supplied name and return a copy of the data\\n for i in range(0, self.ncolumns()):\\n if self.table_column(i).title() == name:\\n return copy.copy(self.table_column(i).data())\\n # Column not found\\n raise LookupError(\\\"Column called '\\\" + str(name) + \\\"' not found\\\")\",\n \"def get_column(col_to_search, value_to_match, col_to_get, table, db_file):\\n \\n try:\\n conn, c = connect_to_db(db_file) \\n c.execute('SELECT {cg} FROM {t} WHERE {col}=\\\"{value}\\\"'.format(t=safe(table), \\n cg=safe(col_to_get), col=safe(col_to_search), value=safe(value_to_match)))\\n column = c.fetchone()\\n conn.close()\\n return column\\n except Exception as e:\\n print(\\\"Error when trying to fetch row in table\\\", table, \\\"in database file\\\", db_file)\\n print(e)\\n return None\",\n \"def __get_position(self, value, state):\\n coords = np.argwhere(state == value).flatten()\\n return coords\",\n \"def position(self) -> Tuple[int, int]:\\n return self.row, self.col\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6948674","0.6942318","0.68900645","0.6643696","0.6632486","0.6617296","0.66054964","0.6541255","0.65210915","0.65178216","0.64717984","0.64717984","0.64595383","0.63534844","0.63455355","0.6333555","0.6323215","0.63208455","0.63208455","0.63208455","0.63208455","0.63181925","0.631676","0.62960905","0.62960905","0.62960905","0.6270586","0.6267135","0.62428635","0.6240275","0.6240275","0.62396896","0.62316686","0.619563","0.6194041","0.61934406","0.61562794","0.6154769","0.6134953","0.61309993","0.6129811","0.61231667","0.60589224","0.60518587","0.60394305","0.60265136","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60264367","0.60214084","0.60091764","0.6007434","0.60060537","0.60020757","0.6000247","0.5995318","0.5988479","0.59841555","0.59752995","0.59666914","0.5952466","0.5948354","0.59187484","0.5905249","0.59026223","0.58943146","0.5890112","0.5874364","0.58543503","0.58483005","0.5832879","0.5826033","0.581103","0.5804417","0.58003956","0.5798561","0.579571","0.578423","0.57825077","0.5774495","0.57708526","0.57550144","0.5753893","0.5742057","0.57409966","0.5738807","0.5736641","0.5735593"],"string":"[\n \"0.6948674\",\n \"0.6942318\",\n \"0.68900645\",\n \"0.6643696\",\n \"0.6632486\",\n \"0.6617296\",\n \"0.66054964\",\n \"0.6541255\",\n \"0.65210915\",\n \"0.65178216\",\n \"0.64717984\",\n \"0.64717984\",\n \"0.64595383\",\n \"0.63534844\",\n \"0.63455355\",\n \"0.6333555\",\n \"0.6323215\",\n \"0.63208455\",\n \"0.63208455\",\n \"0.63208455\",\n \"0.63208455\",\n \"0.63181925\",\n \"0.631676\",\n \"0.62960905\",\n \"0.62960905\",\n \"0.62960905\",\n \"0.6270586\",\n \"0.6267135\",\n \"0.62428635\",\n \"0.6240275\",\n \"0.6240275\",\n \"0.62396896\",\n \"0.62316686\",\n \"0.619563\",\n \"0.6194041\",\n \"0.61934406\",\n \"0.61562794\",\n \"0.6154769\",\n \"0.6134953\",\n \"0.61309993\",\n \"0.6129811\",\n \"0.61231667\",\n \"0.60589224\",\n \"0.60518587\",\n \"0.60394305\",\n \"0.60265136\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60264367\",\n \"0.60214084\",\n \"0.60091764\",\n \"0.6007434\",\n \"0.60060537\",\n \"0.60020757\",\n \"0.6000247\",\n \"0.5995318\",\n \"0.5988479\",\n \"0.59841555\",\n \"0.59752995\",\n \"0.59666914\",\n \"0.5952466\",\n \"0.5948354\",\n \"0.59187484\",\n \"0.5905249\",\n \"0.59026223\",\n \"0.58943146\",\n \"0.5890112\",\n \"0.5874364\",\n \"0.58543503\",\n \"0.58483005\",\n \"0.5832879\",\n \"0.5826033\",\n \"0.581103\",\n \"0.5804417\",\n \"0.58003956\",\n \"0.5798561\",\n \"0.579571\",\n \"0.578423\",\n \"0.57825077\",\n \"0.5774495\",\n \"0.57708526\",\n \"0.57550144\",\n \"0.5753893\",\n \"0.5742057\",\n \"0.57409966\",\n \"0.5738807\",\n \"0.5736641\",\n \"0.5735593\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.81713206"},"document_rank":{"kind":"string","value":"0"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":39,"numItemsPerPage":100,"numTotalItems":140256,"offset":3900,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sInJlcG9JZHMiOlsiNmFlNWFmZGU5YjYwZTdiMTIyZmRmMTNlIl0sImlhdCI6MTc5NDA3NzAxMywianRpIjoiY2RmN2IxOTQtYzJjNS00NzYyLWIwZjctYjE2MDhhM2NlYzg0Iiwic3ViIjoiL2RhdGFzZXRzL2hhcnZleXoxL2Nvcm5zdGFjay1weXRob24zIiwiZXhwIjoxNzk0MDgwNjEzLCJpc3MiOiJodHRwczovL2h1Z2dpbmdmYWNlLmNvIn0.i8rVFb1LXWso2Emd79hUG613pazVFq6DZ52Dd9VnHWVMqHL-2a0T80Tt3SnKNZBqWkG29Tl8S-Qz1r8NdY9qCw","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":140256,"numBytesParquet":1753816410}]},"discussionsStats":{"closed":0,"open":1,"total":1},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 10 2k | document stringlengths 20 51.2k | metadata dict | negatives listlengths 0 101 | negative_scores listlengths 0 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Set up OIDC issuer profile for the ManagedCluster object. | def set_up_oidc_issuer_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
oidc_issuer_profile = self.context.get_oidc_issuer_profile()
if oidc_issuer_profile is not None:
mc.oidc_issuer_profile = oidc_issuer_profile
return mc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_oidc_issuer_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n oidc_issuer_profile = self.context.get_oidc_issuer_profile()\n if oidc_issuer_profile is not None:\n mc.oidc_issuer_profile = oidc_issuer_profile\n\n return mc",
"def set_up_... | [
"0.68949056",
"0.6509729",
"0.59140515",
"0.58743733",
"0.58665264",
"0.5851112",
"0.5786927",
"0.573488",
"0.56927",
"0.5686523",
"0.56630516",
"0.5605314",
"0.5597112",
"0.5546473",
"0.5518196",
"0.5349327",
"0.53285",
"0.52434665",
"0.5205877",
"0.5151916",
"0.5124305",
... | 0.77052444 | 0 |
Set up workload autoscaler profile for the ManagedCluster object. | def set_up_workload_auto_scaler_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
if self.context.get_enable_keda():
if mc.workload_auto_scaler_profile is None:
mc.workload_auto_scaler_profile = self.models.ManagedClusterWorkloadAutoScalerProfile()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_auto_scaler_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n cluster_autoscaler_profile = self.context.get_cluster_autoscaler_profile()\n mc.auto_scaler_profile = cluster_autoscaler_profile\n return mc",
"def update_workload_auto_scaler_profile... | [
"0.8076214",
"0.7491031",
"0.7352861",
"0.6414039",
"0.63400394",
"0.63381267",
"0.61320627",
"0.6118087",
"0.5994238",
"0.59813344",
"0.5911872",
"0.58884025",
"0.5853951",
"0.58003074",
"0.57358766",
"0.57021785",
"0.56957954",
"0.56529593",
"0.5541374",
"0.55400974",
"0.55... | 0.8073404 | 1 |
Set up autoscaler profile for the ManagedCluster object. | def set_up_auto_scaler_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
cluster_autoscaler_profile = self.context.get_cluster_autoscaler_profile()
mc.auto_scaler_profile = cluster_autoscaler_profile
return mc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_workload_auto_scaler_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n if self.context.get_enable_keda():\n if mc.workload_auto_scaler_profile is None:\n mc.workload_auto_scaler_profile = self.models.ManagedClusterWorkloadAutoScalerPro... | [
"0.78787524",
"0.7584544",
"0.72677207",
"0.65111727",
"0.6414405",
"0.6131129",
"0.61158025",
"0.6072033",
"0.6016049",
"0.5991844",
"0.59358615",
"0.59160423",
"0.586377",
"0.58514345",
"0.5827458",
"0.57397324",
"0.5728022",
"0.5689652",
"0.5640538",
"0.5614725",
"0.555527... | 0.8339926 | 0 |
Set up azure monitor profile for the ManagedCluster object. | def set_up_azure_monitor_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
# read the original value passed by the command
ksm_metric_labels_allow_list = self.context.raw_param.get("ksm_metric_labels_allow_list")
ksm_metric_annotations_allow_list = self.context.raw... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_azure_monitor_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n # read the original value passed by the command\n ksm_metric_labels_allow_list = self.context.raw_param.get(\"ksm_metric_labels_allow_list\")\n ksm_metric_annotations_allow_list = sel... | [
"0.72846806",
"0.71346223",
"0.64711446",
"0.6104006",
"0.60403425",
"0.59842443",
"0.5969809",
"0.59013",
"0.5852365",
"0.5829357",
"0.5784714",
"0.5775937",
"0.5744401",
"0.570182",
"0.57013726",
"0.5676068",
"0.56605566",
"0.5610358",
"0.5585451",
"0.5560262",
"0.55012053"... | 0.7944016 | 0 |
Helper function to check if postprocessing is required after sending a PUT request to create the cluster. | def check_is_postprocessing_required(self, mc: ManagedCluster) -> bool:
# some addons require post cluster creation role assigment
monitoring_addon_enabled = self.context.get_intermediate("monitoring_addon_enabled", default_value=False)
ingress_appgw_addon_enabled = self.context.get_intermediate... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_is_postprocessing_required(self, mc: ManagedCluster) -> bool:\n # some addons require post cluster creation role assigment\n monitoring_addon_enabled = self.context.get_intermediate(\"monitoring_addon_enabled\", default_value=False)\n ingress_appgw_addon_enabled = self.context.get_in... | [
"0.65956247",
"0.6160552",
"0.5965819",
"0.5765838",
"0.54389656",
"0.52548474",
"0.5172896",
"0.51714987",
"0.5161744",
"0.5144229",
"0.50794834",
"0.50763243",
"0.50758445",
"0.5068631",
"0.506405",
"0.50525963",
"0.5025663",
"0.50229084",
"0.50158024",
"0.49857804",
"0.498... | 0.6787382 | 0 |
Initialize an AKSAgentPoolAddDecorator object to assemble the AgentPool profile. | def init_agentpool_decorator_context(self) -> None:
self.agentpool_decorator = AKSAgentPoolUpdateDecorator(
self.cmd, self.client, self.__raw_parameters, self.resource_type, self.agentpool_decorator_mode
)
self.agentpool_context = self.agentpool_decorator.context
self.context... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def init_agentpool_decorator_context(self) -> None:\n self.agentpool_decorator = AKSAgentPoolAddDecorator(\n self.cmd, self.client, self.__raw_parameters, self.resource_type, self.agentpool_decorator_mode\n )\n self.agentpool_context = self.agentpool_decorator.context\n self.... | [
"0.82316643",
"0.61094487",
"0.58690387",
"0.58118975",
"0.5642255",
"0.5622449",
"0.5469193",
"0.5461134",
"0.5350976",
"0.5324465",
"0.5300219",
"0.52914625",
"0.5236859",
"0.5222781",
"0.51754194",
"0.51687443",
"0.51389706",
"0.51012224",
"0.5097092",
"0.50748473",
"0.505... | 0.7490148 | 1 |
Get the ManagedCluster object currently in use and attach it to internal context. Internally send request using ContainerServiceClient and parameters name (cluster) and resource group name. | def fetch_mc(self) -> ManagedCluster:
mc = self.client.get(self.context.get_resource_group_name(), self.context.get_name())
# attach mc to AKSContext
self.context.attach_mc(mc)
return mc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def init_mc(self) -> ManagedCluster:\n # Initialize a ManagedCluster object with mandatory parameter location.\n mc = self.models.ManagedCluster(\n location=self.context.get_location(),\n )\n\n # attach mc to AKSContext\n self.context.attach_mc(mc)\n return mc",... | [
"0.63290817",
"0.5981959",
"0.5886816",
"0.58823264",
"0.5875958",
"0.5780633",
"0.5742241",
"0.5623842",
"0.56223327",
"0.5598198",
"0.5598198",
"0.55960774",
"0.5590564",
"0.5503874",
"0.54916924",
"0.54552215",
"0.5428519",
"0.5419511",
"0.5408951",
"0.53970474",
"0.539554... | 0.6626831 | 0 |
Update agentpool profile for the ManagedCluster object. | def update_agentpool_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
if not mc.agent_pool_profiles:
raise UnknownError(
"Encounter an unexpected error while getting agent pool profiles from the cluster in the process of "
"updating ag... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_agentpool_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n agentpool_profile = self.agentpool_decorator.construct_agentpool_profile_default()\n mc.agent_pool_profiles = [agentpool_profile]\n return mc",
"def update_mc_profile_default(self) -> M... | [
"0.69000655",
"0.64854956",
"0.63575286",
"0.58744913",
"0.5846469",
"0.58256614",
"0.58208615",
"0.571694",
"0.56969243",
"0.5597279",
"0.55756265",
"0.5568938",
"0.55441463",
"0.55437326",
"0.54608375",
"0.5429033",
"0.5364649",
"0.5275306",
"0.5205076",
"0.5190666",
"0.517... | 0.8161614 | 0 |
Update autoscaler profile for the ManagedCluster object. | def update_auto_scaler_profile(self, mc):
self._ensure_mc(mc)
cluster_autoscaler_profile = self.context.get_cluster_autoscaler_profile()
if cluster_autoscaler_profile is not None:
# update profile (may clear profile with empty dictionary)
mc.auto_scaler_profile = cluster... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_auto_scaler_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n cluster_autoscaler_profile = self.context.get_cluster_autoscaler_profile()\n mc.auto_scaler_profile = cluster_autoscaler_profile\n return mc",
"def update_workload_auto_scaler_profile... | [
"0.77689654",
"0.77025795",
"0.70554644",
"0.6538188",
"0.62741613",
"0.62367916",
"0.61821556",
"0.60954934",
"0.6095449",
"0.5962787",
"0.5960805",
"0.58981574",
"0.58537835",
"0.582746",
"0.5796772",
"0.57472837",
"0.5672821",
"0.5601652",
"0.5588318",
"0.5538377",
"0.5453... | 0.8491165 | 0 |
Update tags for the ManagedCluster object. | def update_tags(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
tags = self.context.get_tags()
if tags is not None:
mc.tags = tags
return mc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def AddClusterTags(self, tags, dry_run=False, reason=None):\n query = [(\"tag\", t) for t in tags]\n _AppendDryRunIf(query, dry_run)\n _AppendReason(query, reason)\n\n return self._SendRequest(HTTP_PUT, \"/%s/tags\" % GANETI_RAPI_VERSION,\n query, None)",
"def update_clust... | [
"0.5990642",
"0.59193057",
"0.5559754",
"0.55428",
"0.54464996",
"0.5432885",
"0.5410724",
"0.54037637",
"0.54037637",
"0.54037637",
"0.5357456",
"0.5332834",
"0.53129476",
"0.52917403",
"0.5266721",
"0.5208107",
"0.5159976",
"0.513104",
"0.51148003",
"0.5085101",
"0.50813633... | 0.74483514 | 0 |
Update sku (uptime sla) for the ManagedCluster object. | def update_sku(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
# Premium without LTS is ok (not vice versa)
if self.context.get_tier() == CONST_MANAGED_CLUSTER_SKU_TIER_PREMIUM:
mc.sku = self.models.ManagedClusterSKU(
name="Base",
tie... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_sku(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n if self.context.get_uptime_sla() or self.context.get_tier() == CONST_MANAGED_CLUSTER_SKU_TIER_STANDARD:\n mc.sku = self.models.ManagedClusterSKU(\n name=\"Base\",\n tier=\"St... | [
"0.71179074",
"0.5984935",
"0.53230107",
"0.5303793",
"0.5204448",
"0.5096391",
"0.5087994",
"0.5086891",
"0.502062",
"0.49859262",
"0.4938367",
"0.49240932",
"0.48839968",
"0.48643538",
"0.48471776",
"0.48239538",
"0.47839066",
"0.47805685",
"0.47805685",
"0.4759781",
"0.475... | 0.7960321 | 0 |
Update load balancer profile for the ManagedCluster object. | def update_load_balancer_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
if not mc.network_profile:
raise UnknownError(
"Encounter an unexpected error while getting network profile from the cluster in the process of "
"updating its lo... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_agentpool_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n if not mc.agent_pool_profiles:\n raise UnknownError(\n \"Encounter an unexpected error while getting agent pool profiles from the cluster in the process of \"\n ... | [
"0.65942985",
"0.63839215",
"0.6343197",
"0.62864435",
"0.61292905",
"0.61204284",
"0.6031443",
"0.57443124",
"0.5726644",
"0.5723703",
"0.5628799",
"0.5628109",
"0.5623104",
"0.56101996",
"0.56002855",
"0.5590744",
"0.5588446",
"0.55560887",
"0.55289423",
"0.55235827",
"0.55... | 0.75255644 | 0 |
Update nat gateway profile for the ManagedCluster object. | def update_nat_gateway_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
if not mc.network_profile:
raise UnknownError(
"Unexpectedly get an empty network profile in the process of updating nat gateway profile."
)
outbound_type = se... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_mc_profile_default(self) -> ManagedCluster:\n # check raw parameters\n # promt y/n if no options are specified to ask user whether to perform a reconcile operation\n self.check_raw_parameters()\n # fetch the ManagedCluster object\n mc = self.fetch_mc()\n # updat... | [
"0.6426489",
"0.63450545",
"0.62319547",
"0.60947186",
"0.60823864",
"0.59361637",
"0.5891273",
"0.5854507",
"0.5761657",
"0.57524437",
"0.5678059",
"0.56612414",
"0.5579701",
"0.53702694",
"0.5347543",
"0.53397816",
"0.5326909",
"0.52681994",
"0.5237096",
"0.5205934",
"0.518... | 0.7545268 | 0 |
Update api server access profile and fqdn subdomain for the ManagedCluster object. | def update_api_server_access_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
if mc.api_server_access_profile is None:
profile_holder = self.models.ManagedClusterAPIServerAccessProfile()
else:
profile_holder = mc.api_server_access_profile
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_api_server_access_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n api_server_access_profile = None\n api_server_authorized_ip_ranges = self.context.get_api_server_authorized_ip_ranges()\n enable_private_cluster = self.context.get_enable_private_... | [
"0.6785518",
"0.62549794",
"0.56788695",
"0.5587446",
"0.55768114",
"0.5548693",
"0.5440958",
"0.523388",
"0.5209735",
"0.5204637",
"0.5203941",
"0.5169459",
"0.5154716",
"0.51498365",
"0.5145779",
"0.50799966",
"0.50749654",
"0.50468695",
"0.5043714",
"0.50179535",
"0.500715... | 0.72265285 | 0 |
Update windows profile for the ManagedCluster object. | def update_windows_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
enable_ahub = self.context.get_enable_ahub()
disable_ahub = self.context.get_disable_ahub()
windows_admin_password = self.context.get_windows_admin_password()
enable_windows_gmsa = self.c... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_windows_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n (\n windows_admin_username,\n windows_admin_password,\n ) = self.context.get_windows_admin_username_and_password()\n if windows_admin_username or windows_admin_passwor... | [
"0.6615214",
"0.6559488",
"0.6554667",
"0.6302969",
"0.62154424",
"0.6039585",
"0.60123307",
"0.5999623",
"0.5888613",
"0.58799297",
"0.5857495",
"0.57862186",
"0.575272",
"0.55814606",
"0.5574849",
"0.5490474",
"0.54602957",
"0.5456462",
"0.54487735",
"0.5445578",
"0.5434550... | 0.79302394 | 0 |
Update OIDC issuer profile for the ManagedCluster object. | def update_oidc_issuer_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
oidc_issuer_profile = self.context.get_oidc_issuer_profile()
if oidc_issuer_profile is not None:
mc.oidc_issuer_profile = oidc_issuer_profile
return mc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_oidc_issuer_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n oidc_issuer_profile = self.context.get_oidc_issuer_profile()\n if oidc_issuer_profile is not None:\n mc.oidc_issuer_profile = oidc_issuer_profile\n\n return mc",
"def update_... | [
"0.7138633",
"0.6434838",
"0.6359209",
"0.6091803",
"0.5943593",
"0.5936524",
"0.5852094",
"0.5840535",
"0.58331877",
"0.56902266",
"0.56145376",
"0.55521697",
"0.5457869",
"0.53420657",
"0.5270344",
"0.52316934",
"0.51749843",
"0.5146125",
"0.5134343",
"0.5117193",
"0.509305... | 0.79235494 | 0 |
Update network plugin settings of network profile for the ManagedCluster object. | def update_network_plugin_settings(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
network_plugin_mode = self.context.get_network_plugin_mode()
if network_plugin_mode:
mc.network_profile.network_plugin_mode = network_plugin_mode
(
pod_cidr,
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_mc_profile_default(self) -> ManagedCluster:\n # check raw parameters\n # promt y/n if no options are specified to ask user whether to perform a reconcile operation\n self.check_raw_parameters()\n # fetch the ManagedCluster object\n mc = self.fetch_mc()\n # updat... | [
"0.6287261",
"0.62562764",
"0.6206155",
"0.5919854",
"0.5832747",
"0.5745208",
"0.5725939",
"0.5664839",
"0.5643876",
"0.56297773",
"0.5584582",
"0.54472065",
"0.5360767",
"0.53581583",
"0.534671",
"0.53357637",
"0.53113896",
"0.52554923",
"0.5243599",
"0.51855236",
"0.518398... | 0.8056863 | 0 |
Update storage profile for the ManagedCluster object. | def update_storage_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
mc.storage_profile = self.context.get_storage_profile()
return mc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_storage_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n if hasattr(self.models, \"ManagedClusterStorageProfile\"):\n mc.storage_profile = self.context.get_storage_profile()\n\n return mc",
"def update_mc_profile_default(self) -> ManagedClu... | [
"0.7120557",
"0.6314157",
"0.6202867",
"0.58940035",
"0.5887002",
"0.5872036",
"0.5859722",
"0.5836123",
"0.57843363",
"0.5757808",
"0.5714045",
"0.5625429",
"0.55987877",
"0.54697853",
"0.54638046",
"0.5455607",
"0.54530305",
"0.53886455",
"0.53717756",
"0.5316751",
"0.52893... | 0.81250465 | 0 |
Update security profile imageCleaner for the ManagedCluster object. | def update_image_cleaner(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
enable_image_cleaner = self.context.get_enable_image_cleaner()
disable_image_cleaner = self.context.get_disable_image_cleaner()
interval_hours = self.context.get_image_cleaner_interval_hours()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_image_cleaner(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n interval_hours = self.context.get_image_cleaner_interval_hours()\n\n if self.context.get_enable_image_cleaner():\n\n if mc.security_profile is None:\n mc.security_profile =... | [
"0.6851309",
"0.67022616",
"0.5652698",
"0.555268",
"0.54567385",
"0.5302302",
"0.52607596",
"0.50487584",
"0.50180537",
"0.5011092",
"0.5008191",
"0.5006725",
"0.49423403",
"0.48312888",
"0.47744167",
"0.47587383",
"0.47480166",
"0.47262153",
"0.47243848",
"0.47189918",
"0.4... | 0.73032594 | 0 |
Update workload autoscaler profile for the ManagedCluster object. | def update_workload_auto_scaler_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
if self.context.get_enable_keda():
if mc.workload_auto_scaler_profile is None:
mc.workload_auto_scaler_profile = self.models.ManagedClusterWorkloadAutoScalerProfile()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_auto_scaler_profile(self, mc):\n self._ensure_mc(mc)\n\n cluster_autoscaler_profile = self.context.get_cluster_autoscaler_profile()\n if cluster_autoscaler_profile is not None:\n # update profile (may clear profile with empty dictionary)\n mc.auto_scaler_profil... | [
"0.82561743",
"0.75433207",
"0.7293663",
"0.6517002",
"0.6411876",
"0.6182385",
"0.61311543",
"0.59943694",
"0.5993539",
"0.59688723",
"0.59505665",
"0.59278333",
"0.5866863",
"0.5812482",
"0.56214845",
"0.5597126",
"0.5546318",
"0.5526554",
"0.5516587",
"0.550821",
"0.548046... | 0.7946528 | 1 |
Update azure monitor profile for the ManagedCluster object. | def update_azure_monitor_profile(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
# read the original value passed by the command
ksm_metric_labels_allow_list = self.context.raw_param.get("ksm_metric_labels_allow_list")
ksm_metric_annotations_allow_list = self.context.ra... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_up_azure_monitor_profile(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n # read the original value passed by the command\n ksm_metric_labels_allow_list = self.context.raw_param.get(\"ksm_metric_labels_allow_list\")\n ksm_metric_annotations_allow_list = self.... | [
"0.7277104",
"0.63934505",
"0.61648846",
"0.614551",
"0.61402935",
"0.6066223",
"0.5994208",
"0.5984191",
"0.5957272",
"0.5943673",
"0.5894648",
"0.5878133",
"0.5850033",
"0.57665926",
"0.57402784",
"0.5631679",
"0.5623526",
"0.5593438",
"0.55433184",
"0.54727024",
"0.5458814... | 0.7853511 | 0 |
Helper function to check if postprocessing is required after sending a PUT request to create the cluster. | def check_is_postprocessing_required(self, mc: ManagedCluster) -> bool:
# some addons require post cluster creation role assigment
monitoring_addon_enabled = self.context.get_intermediate("monitoring_addon_enabled", default_value=False)
ingress_appgw_addon_enabled = self.context.get_intermediate... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_is_postprocessing_required(self, mc: ManagedCluster) -> bool:\n # some addons require post cluster creation role assigment\n monitoring_addon_enabled = self.context.get_intermediate(\"monitoring_addon_enabled\", default_value=False)\n ingress_appgw_addon_enabled = self.context.get_in... | [
"0.6787382",
"0.6160552",
"0.5965819",
"0.5765838",
"0.54389656",
"0.52548474",
"0.5172896",
"0.51714987",
"0.5161744",
"0.5144229",
"0.50794834",
"0.50763243",
"0.50758445",
"0.5068631",
"0.506405",
"0.50525963",
"0.5025663",
"0.50229084",
"0.50158024",
"0.49857804",
"0.4980... | 0.65956247 | 1 |
Send request to update the existing managed cluster. | def update_mc(self, mc: ManagedCluster) -> ManagedCluster:
self._ensure_mc(mc)
return self.put_mc(mc) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_cluster(self, cluster, params, *args, **kwargs):\n raise NotImplementedError",
"def update(id, body: Body):\n\n cluster = clusters.get_by_id(id)\n\n if cluster is None:\n raise HTTPException(status_code=404, detail=\"Cluster not found for ID: {0}\".format(id))\n\n cluster.update... | [
"0.7191971",
"0.7066755",
"0.7005855",
"0.67756027",
"0.6429547",
"0.6165414",
"0.6147759",
"0.61359227",
"0.60395795",
"0.6039569",
"0.59164023",
"0.58718383",
"0.58608097",
"0.58484197",
"0.58156073",
"0.5783585",
"0.5762689",
"0.575575",
"0.5751597",
"0.57309073",
"0.57024... | 0.52261937 | 56 |
Replaces u'celsius' with 'fahrenheit' in the provided string. | def replace_celcius(string):
return string.replace(u'celsius', u'fahrenheit') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convert_celsius_to_fahrenheit(celsius):\n return celsius * 9.0 / 5 + 32",
"def _celsius_to_fahrenheit(self) -> None:\n if self.units == \"celsius\":\n self.value = (((self.value / 5) * 9) + 32).__round__(2)\n self.units = \"fahrenheit\"\n else:\n msg = (\n ... | [
"0.66244715",
"0.6384214",
"0.6268346",
"0.6167058",
"0.61540127",
"0.61191595",
"0.6103219",
"0.60855544",
"0.6050967",
"0.60101855",
"0.5962116",
"0.59152514",
"0.5893281",
"0.58617944",
"0.5766658",
"0.5766658",
"0.5739406",
"0.5734028",
"0.57056034",
"0.5679949",
"0.56359... | 0.8532337 | 0 |
convnet inference block by block. The block coordinates should be aligned with cloud storage. | def create_inference_tasks(task_queue, image_layer_path, convnet_path,
mask_layer_path, output_layer_path, output_block_start, output_block_size,
grid_size, patch_size, patch_overlap, cropping_margin_size,
output_key='output', num_output_channels=3,
image_mip=1, output_mip=1, mask_mip... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def block_inception_c(blk, net):\n # By default use stride=1 and SAME padding\n s = net.add(Split('%s/Split' % blk, 4))\n br0 = conv2d(net, '%s/Branch_0/Conv2d_0a_1x1' % blk, 256, 1, src=s)\n\n br1 = conv2d(net, '%s/Branch_1/Conv2d_0a_1x1' % blk, 384, 1, src=s)\n br1 = net.add(Split('%s/Branch_1/Spl... | [
"0.66582626",
"0.6451007",
"0.64135444",
"0.63718015",
"0.63372326",
"0.62998694",
"0.62323284",
"0.6195406",
"0.6167625",
"0.6156127",
"0.61436325",
"0.61318815",
"0.6110937",
"0.6108192",
"0.61076534",
"0.6093889",
"0.60925573",
"0.6086378",
"0.60754573",
"0.60693055",
"0.6... | 0.0 | -1 |
Convert degrees to quaternions | def to_quaternion(roll = 0.0, pitch = 0.0, yaw = 0.0):
t0 = math.cos(math.radians(yaw * 0.5))
t1 = math.sin(math.radians(yaw * 0.5))
t2 = math.cos(math.radians(roll * 0.5))
t3 = math.sin(math.radians(roll * 0.5))
t4 = math.cos(math.radians(pitch * 0.5))
t5 = math.sin(math.radians(pitch * 0.5))
w = t0 * t2 * t4 ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _rotate_quaternion(self, q):\n self._normalise()\n return self * q * self.conjugate",
"def angle_to_quaternion(angle):\n\treturn Quaternion(*tf.transformations.quaternion_from_euler(0, 0, angle))",
"def angle_to_quaternion(angle):\n return Quaternion(*tf.transformations.quaternion_from_eul... | [
"0.7151884",
"0.70794785",
"0.69795513",
"0.6890196",
"0.6885355",
"0.68387544",
"0.6825451",
"0.6785443",
"0.6781011",
"0.6753861",
"0.6744243",
"0.67363155",
"0.67292994",
"0.6655036",
"0.66510034",
"0.66371715",
"0.66367793",
"0.66176534",
"0.66134346",
"0.6551278",
"0.655... | 0.6149848 | 51 |
Add Comment to post. | def add_comment(cls, uid, person, email, body):
try:
qs = cls.query.add_comment(uid=uid, person=person, email=email, body=body)
record = cls.engine.query(qs, fetch_opts='single')
except (DBAPIError, SnaqlException) as error:
raise Exception(error.args[0])
r... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_comment(cls, post_id, user_id, content):\n c = cls(parent=comment_key(),\n post_id=post_id,\n user_id=user_id,\n content=content)\n c.put()",
"def post(self, post_id):\n comment_content = self.request.get(\"comment_content\")\n Post.add_co... | [
"0.82225007",
"0.7583707",
"0.75809085",
"0.7247829",
"0.7170257",
"0.70538193",
"0.69097257",
"0.6878592",
"0.68745327",
"0.67804384",
"0.6741349",
"0.67374927",
"0.67098224",
"0.66295004",
"0.6624333",
"0.65848434",
"0.65231735",
"0.65173745",
"0.65173745",
"0.6499979",
"0.... | 0.0 | -1 |
Generate a random character string of length n | def gen_random_char_string(n, base_s=""):
if n == 0:
return base_s
c = random.choice(string.ascii_letters)
return gen_random_char_string(n-1, base_s + c) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gen_rand_str(n):\n return \"\".join(random.choice(string.ascii_letters) for _ in range(n))",
"def gen_random_chars(n: int = 10) -> Text:\n if n < 1:\n raise Exception('Number of random chars to generate has to be > 0')\n\n return ''.join(choice(ascii_lowercase + '-_')\n ... | [
"0.86658543",
"0.85566527",
"0.8546031",
"0.84206235",
"0.8215926",
"0.80584174",
"0.8052071",
"0.795686",
"0.79503375",
"0.79443985",
"0.79272246",
"0.7922356",
"0.79156876",
"0.78830683",
"0.7817866",
"0.78086793",
"0.7803741",
"0.7789038",
"0.7785089",
"0.77838916",
"0.778... | 0.8413165 | 4 |
Returns the coordinates of the origin bounding box that are intersected by the intersect bounding box. >>> bounding_box = 10, 100, 30, 110 >>> other_bbox = 20, 100, 40, 105 >>> bounding_box_intersection(bounding_box, other_bbox) (10, 0, 20, 5) >>> bounding_box_intersection(other_bbox, bounding_box) (0, 0, 10, 5) >>> co... | def bounding_box_intersection(origin: Tuple[int, int, int, int], intersect: Tuple[int, int, int, int]) \
-> Optional[Tuple[int, int, int, int]]:
o_t, o_l, o_b, o_r = origin
t, l, b, r = intersect
out_top = max(t, o_t)
out_left = max(l, o_l)
out_bottom = min(b, o_b)
out_right = min(r, o_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def intersection(box0, box1):\n if isinstance(box0, bounding_box_pb2.BoundingBox):\n box0 = BoundingBox(box0.start, box0.size)\n if isinstance(box1, bounding_box_pb2.BoundingBox):\n box1 = BoundingBox(box1.start, box1.size)\n if not isinstance(box0, BoundingBox):\n raise ValueError('box0 must be a Boun... | [
"0.73368526",
"0.68448746",
"0.6794572",
"0.6752013",
"0.6524481",
"0.6365032",
"0.6349253",
"0.6339419",
"0.63276106",
"0.6230844",
"0.6219065",
"0.6181393",
"0.6178924",
"0.6171056",
"0.6161214",
"0.615606",
"0.61267775",
"0.61151683",
"0.60859907",
"0.607529",
"0.60643137"... | 0.7157741 | 1 |
Computes the recall, precision and fscore for the prediction Node given the truth Node. | def pixel_metrics(truth: Node, prediction: Node) -> Tuple[float, float, float]:
recall, precision, fscore = 0, 0, 0
intersection_truth = bounding_box_intersection(truth.bounding_box,
prediction.bounding_box)
if intersection_truth is None:
logging.d... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def compute_recall_precision_fscore(truth: List[Node], prediction: List[Node]) \\\n -> Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray]:\n recall = numpy.zeros((len(truth), len(prediction)))\n precision = numpy.zeros((len(truth), len(prediction)))\n fscore = numpy.zeros((len(truth), len(predictio... | [
"0.7300171",
"0.7163483",
"0.71341056",
"0.69883686",
"0.6961389",
"0.6687912",
"0.66681075",
"0.6655577",
"0.6635931",
"0.6634769",
"0.6633833",
"0.6585825",
"0.6574979",
"0.6558169",
"0.6523462",
"0.65003914",
"0.6488661",
"0.64875406",
"0.64809954",
"0.6479049",
"0.647664"... | 0.0 | -1 |
draws an ellipse around the center of the points | def draw_perimeter(centroid, image, color, scale_factor):
center_x = scale(centroid.coords.item(0), scale_factor)
center_y = scale(centroid.coords.item(1), scale_factor)
max_x = 0
max_y = 0
for point in centroid.points:
scaled_x = scale(point.item(0), scale_factor)
scaled_y = scale... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def drawEllipse(img, center, axes, angle, startAngle=0, endAngle=360, color = (0,0,255), fill = -1):\n\tcv2.ellipse(img, center, axes, angle, startAngle, endAngle, color, fill)",
"def ellipse(self):\n f = self.img\n x = self.x\n y = self.y\n x2 = self.x2\n y2 = self.y2\n xy = ... | [
"0.7842527",
"0.7806552",
"0.7571398",
"0.73608714",
"0.7261851",
"0.7241438",
"0.72338784",
"0.7170632",
"0.7167897",
"0.71314347",
"0.70732373",
"0.7072711",
"0.70466924",
"0.7026025",
"0.70214534",
"0.7007903",
"0.699258",
"0.69773793",
"0.6938472",
"0.6928123",
"0.6868979... | 0.0 | -1 |
Display an image. Wrap `matplotlib.pyplot.imshow` to display a possibly intensity manipulated version of the image `X`. | def imshow(X, ax=None, intensity_func=None, intensity_args=(),
show_axis='frame', **kwargs):
@_decorate_validation
def validate_input():
_numeric('X', ('boolean', 'integer', 'floating'), shape=(-1, -1))
_generic('ax', mpl.axes.Axes, ignore_none=True)
_generic('intensity_func'... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def display_image(X):\n\n\tim = X.reshape(28, 28)\n\ttemp = plt.imshow(im)\n\tplt.show()",
"def plot_img(X: np.ndarray, **kwargs):\n kwargs.setdefault('origin', 'lower') # Sane default\n plt.imshow(X, **kwargs)",
"def show_image(image):\r\n plt.imshow(image, cmap='gray')\r\n plt.show()",
"def di... | [
"0.8321958",
"0.7961306",
"0.75955147",
"0.753911",
"0.7533973",
"0.7476919",
"0.745646",
"0.740446",
"0.73409796",
"0.7315752",
"0.7315752",
"0.7315752",
"0.7277346",
"0.72211635",
"0.71984375",
"0.71843135",
"0.71229005",
"0.71088415",
"0.70842797",
"0.7079816",
"0.70698",
... | 0.7462702 | 6 |
Set the term in the form. | def get_form_kwargs(self, **kwargs):
kwargs = super(CandidateEditView, self).get_form_kwargs(**kwargs)
kwargs['candidate_term'] = self.candidate.term
return kwargs | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_term_text(self, term, fulltext):\n term_entry = self.sql_session.query(Term).get(term)\n if term_entry:\n term_entry.fulltext = fulltext",
"def preg_term(self, preg_term):\n\n self.logger.debug(\"In 'preg_term' setter.\")\n\n self._preg_term = preg_term",
"def ter... | [
"0.71175146",
"0.68550855",
"0.63705415",
"0.6144158",
"0.5816871",
"0.5789726",
"0.57820034",
"0.5767371",
"0.5661654",
"0.56422377",
"0.56371766",
"0.56113946",
"0.56011474",
"0.5574104",
"0.55038446",
"0.55038285",
"0.547851",
"0.5468794",
"0.5446931",
"0.54445195",
"0.544... | 0.0 | -1 |
Set the term of the requirement to the current term. | def form_valid(self, form):
form.instance.term = Term.objects.get_current_term()
messages.success(self.request, '{req_type} requirement created!'.format(
req_type=self.display_req_type))
return super(
ManualCandidateRequirementCreateView, self).form_valid(form) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_term_text(self, term, fulltext):\n term_entry = self.sql_session.query(Term).get(term)\n if term_entry:\n term_entry.fulltext = fulltext",
"def preg_term(self, preg_term):\n\n self.logger.debug(\"In 'preg_term' setter.\")\n\n self._preg_term = preg_term",
"def ter... | [
"0.64847124",
"0.6334201",
"0.5986424",
"0.5544135",
"0.5509674",
"0.54983705",
"0.5456465",
"0.5348691",
"0.5333413",
"0.52703387",
"0.52224094",
"0.52158356",
"0.52030915",
"0.5188148",
"0.5169398",
"0.51674813",
"0.515454",
"0.51141346",
"0.51084954",
"0.5074955",
"0.50479... | 0.5203271 | 12 |
Sets the id of this Game. | def id(self, id):
self._id = id | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_id(self, id):\n self.__id = id",
"def set_id(self, id_):\n\n self.id_ = id_",
"def SetId(self, id):\n self.id = int(id)",
"def set_id(self, player_id):\n pass",
"def set_id(self, id):\n self.data['id'] = id",
"def set_id(self, id):\n self.id = id\n ... | [
"0.79247755",
"0.78860915",
"0.78824073",
"0.7723867",
"0.7681004",
"0.759572",
"0.75824404",
"0.7418058",
"0.7418058",
"0.7418058",
"0.7418058",
"0.7418058",
"0.7418058",
"0.7418058",
"0.7418058",
"0.7418058",
"0.7418058",
"0.7406203",
"0.73548305",
"0.73548305",
"0.73548305... | 0.0 | -1 |
Sets the player_b_name of this Game. | def player_b_name(self, player_b_name):
self._player_b_name = player_b_name | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def player_a_name(self, player_a_name):\n\n self._player_a_name = player_a_name",
"def player_b_games(self, player_b_games):\n\n self._player_b_games = player_b_games",
"def player_b_id(self, player_b_id):\n\n self._player_b_id = player_b_id",
"def bcp_player_variable(self, name, value, ... | [
"0.7046953",
"0.68283844",
"0.6823286",
"0.60431397",
"0.602946",
"0.5915856",
"0.5797274",
"0.57551175",
"0.564356",
"0.5617421",
"0.5611178",
"0.5594154",
"0.5562194",
"0.55580914",
"0.55133885",
"0.54521626",
"0.543514",
"0.5420806",
"0.5417903",
"0.5417903",
"0.5415289",
... | 0.9181073 | 0 |
Sets the player_a_id of this Game. | def player_a_id(self, player_a_id):
self._player_a_id = player_a_id | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_player_id(self, player_id):\n self.player_id = player_id",
"def player_a_games(self, player_a_games):\n\n self._player_a_games = player_a_games",
"def set_id(self, player_id):\n pass",
"def player_id(self, player_id):\n\n self._player_id = player_id",
"def player_id(self... | [
"0.69736564",
"0.69562083",
"0.6944866",
"0.685115",
"0.685115",
"0.67752093",
"0.6499893",
"0.6387207",
"0.61095905",
"0.5931413",
"0.5756862",
"0.5719053",
"0.5642285",
"0.5627128",
"0.5627128",
"0.5627128",
"0.55055493",
"0.5500313",
"0.5443958",
"0.544141",
"0.5326835",
... | 0.8947233 | 0 |
Sets the player_b_id of this Game. | def player_b_id(self, player_b_id):
self._player_b_id = player_b_id | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def player_b_games(self, player_b_games):\n\n self._player_b_games = player_b_games",
"def player_b_name(self, player_b_name):\n\n self._player_b_name = player_b_name",
"def player_a_id(self, player_a_id):\n\n self._player_a_id = player_a_id",
"def set_player_id(self, player_id):\n ... | [
"0.701637",
"0.68415976",
"0.6529189",
"0.6521133",
"0.6509748",
"0.63791966",
"0.63791966",
"0.63403463",
"0.61362946",
"0.609142",
"0.57009405",
"0.56523895",
"0.5555329",
"0.55444074",
"0.54241943",
"0.54158646",
"0.54158646",
"0.54158646",
"0.5270569",
"0.5130478",
"0.512... | 0.8964314 | 0 |
Returns true if both objects are equal | def __eq__(self, other):
if not isinstance(other, Game):
return False
return self.__dict__ == other.__dict__ | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __eq__(self, other):\n return are_equal(self, other)",
"def __eq__(self, other):\n return are_equal(self, other)",
"def __eq__(self,other):\n try: return self.object==other.object and isinstance(self,type(other))\n except: return False",
"def __eq__(self, other):\n if i... | [
"0.8089139",
"0.8089139",
"0.8054507",
"0.79827213",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
"0.79669285",
... | 0.0 | -1 |
Returns true if both objects are not equal | def __ne__(self, other):
return not self == other | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __ne__(self, other: object) -> bool:\n if self.__eq__(other):\n return False\n return True",
"def __ne__(self, other: object) -> bool:\n return not self.__eq__(other)",
"def __ne__(self, other) -> bool:\n return not self.__eq__(other)",
"def __eq__(self, other):\n ... | [
"0.845611",
"0.8391477",
"0.8144138",
"0.81410587",
"0.8132492",
"0.8093973",
"0.80920255",
"0.80920255",
"0.80920255",
"0.8085325",
"0.8085325",
"0.8076365",
"0.8076365",
"0.8065748"
] | 0.0 | -1 |
The conv block is the block that has conv layer at shortcut. Arguments | def conv_block(filters, stage, block, strides=(2, 2)):
def layer(input_tensor):
# extracting params and names for layers
conv_params = get_conv_params()
bn_params = get_bn_params()
conv_name, bn_name, relu_name, sc_name = handle_block_names(stage, block)
x = BatchNormaliza... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def conv_block(self, output_channel, filter_, activate):\n return self.add_layer(conv_block, output_channel, filter_, activate)",
"def conv_block(input_tensor, kernel_size, filters, stage, block_id, strides=(2, 2), data_format='channels_last', train_bn=True):\n\n filter1, filter2, filter3 = filters\n ... | [
"0.754371",
"0.7060612",
"0.7043081",
"0.69984245",
"0.6913935",
"0.68654615",
"0.6839871",
"0.6827021",
"0.6823767",
"0.67977256",
"0.6794483",
"0.6773842",
"0.6742968",
"0.67385846",
"0.6723267",
"0.67199",
"0.6713653",
"0.67034614",
"0.66949296",
"0.6679553",
"0.6656035",
... | 0.6701542 | 18 |
The identity block is the block that has no conv layer at shortcut. Arguments | def identity_block(filters, stage, block):
def layer(input_tensor):
conv_params = get_conv_params()
bn_params = get_bn_params()
conv_name, bn_name, relu_name, sc_name = handle_block_names(stage, block)
x = BatchNormalization(name=bn_name + '0', **bn_params)(input_tensor)
x ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def identity_block(self, input_tensor, filters, activation, stage, block, start_with_batch_norm = True):\n\n # Set the naming convention\n conv_name_base = 'res' + str(stage) + block + '_branch'\n batch_norm_name_base = 'batch_norm' + str(stage) + block + '_branch'\n\n x_shortcut = inpu... | [
"0.71272004",
"0.7022438",
"0.6910338",
"0.68836653",
"0.68505627",
"0.68221945",
"0.6821999",
"0.680346",
"0.6799615",
"0.67849326",
"0.67714536",
"0.67158884",
"0.67146987",
"0.67137283",
"0.6664201",
"0.6624224",
"0.662218",
"0.662218",
"0.66078824",
"0.65984523",
"0.65485... | 0.6847176 | 5 |
The identity block is the block that has no conv layer at shortcut. Arguments | def basic_identity_block(filters, stage, block):
def layer(input_tensor):
conv_params = get_conv_params()
bn_params = get_bn_params()
conv_name, bn_name, relu_name, sc_name = handle_block_names(stage, block)
x = BatchNormalization(name=bn_name + '1', **bn_params)(input_tensor)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def identity_block(self, input_tensor, filters, activation, stage, block, start_with_batch_norm = True):\n\n # Set the naming convention\n conv_name_base = 'res' + str(stage) + block + '_branch'\n batch_norm_name_base = 'batch_norm' + str(stage) + block + '_branch'\n\n x_shortcut = inpu... | [
"0.7127304",
"0.70226824",
"0.69105184",
"0.68836373",
"0.6850498",
"0.68464863",
"0.6822095",
"0.6821457",
"0.6803604",
"0.67993164",
"0.6784702",
"0.6715633",
"0.6714348",
"0.6713607",
"0.6663853",
"0.66239524",
"0.6621875",
"0.6621875",
"0.6607414",
"0.6598225",
"0.6548092... | 0.6770701 | 11 |
The identity block is the block that has no conv layer at shortcut. Arguments | def basic_conv_block(filters, stage, block, strides=(2, 2)):
def layer(input_tensor):
conv_params = get_conv_params()
bn_params = get_bn_params()
conv_name, bn_name, relu_name, sc_name = handle_block_names(stage, block)
x = BatchNormalization(name=bn_name + '1', **bn_params)(input_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def identity_block(self, input_tensor, filters, activation, stage, block, start_with_batch_norm = True):\n\n # Set the naming convention\n conv_name_base = 'res' + str(stage) + block + '_branch'\n batch_norm_name_base = 'batch_norm' + str(stage) + block + '_branch'\n\n x_shortcut = inpu... | [
"0.71272004",
"0.7022438",
"0.6910338",
"0.68836653",
"0.68505627",
"0.6847176",
"0.68221945",
"0.6821999",
"0.680346",
"0.6799615",
"0.67849326",
"0.67714536",
"0.67158884",
"0.67146987",
"0.67137283",
"0.6664201",
"0.6624224",
"0.662218",
"0.662218",
"0.66078824",
"0.659845... | 0.0 | -1 |
The identity block is the block that has no conv layer at shortcut. Arguments | def basic_conv_block2(filters, stage, block, strides=(2, 2)):
def layer(input_tensor):
conv_params = get_conv_params()
bn_params = get_bn_params()
conv_name, bn_name, relu_name, sc_name = handle_block_names(stage, block)
# x = BatchNormalization(name=bn_name + '1', **bn_params)(inp... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def identity_block(self, input_tensor, filters, activation, stage, block, start_with_batch_norm = True):\n\n # Set the naming convention\n conv_name_base = 'res' + str(stage) + block + '_branch'\n batch_norm_name_base = 'batch_norm' + str(stage) + block + '_branch'\n\n x_shortcut = inpu... | [
"0.71272004",
"0.7022438",
"0.6910338",
"0.68836653",
"0.68505627",
"0.6847176",
"0.68221945",
"0.6821999",
"0.680346",
"0.6799615",
"0.67849326",
"0.67714536",
"0.67158884",
"0.67146987",
"0.67137283",
"0.6664201",
"0.6624224",
"0.662218",
"0.662218",
"0.66078824",
"0.659845... | 0.0 | -1 |
The identity block is the block that has no conv layer at shortcut. Arguments | def identity_scse_block(filters, stage, block, re=8):
def layer(input_tensor):
conv_params = get_conv_params()
bn_params = get_bn_params()
conv_name, bn_name, relu_name, sc_name = handle_block_names(stage, block)
x = BatchNormalization(name=bn_name + '0', **bn_params)(input_tensor)... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def identity_block(self, input_tensor, filters, activation, stage, block, start_with_batch_norm = True):\n\n # Set the naming convention\n conv_name_base = 'res' + str(stage) + block + '_branch'\n batch_norm_name_base = 'batch_norm' + str(stage) + block + '_branch'\n\n x_shortcut = inpu... | [
"0.71272004",
"0.7022438",
"0.6910338",
"0.68836653",
"0.68505627",
"0.6847176",
"0.68221945",
"0.6821999",
"0.680346",
"0.6799615",
"0.67849326",
"0.67714536",
"0.67158884",
"0.67146987",
"0.67137283",
"0.6664201",
"0.6624224",
"0.662218",
"0.662218",
"0.66078824",
"0.659845... | 0.59655523 | 40 |
The identity block is the block that has no conv layer at shortcut. Arguments | def conv_scse_block(filters, stage, block, re=8):
def layer(input_tensor):
conv_params = get_conv_params()
bn_params = get_bn_params()
conv_name, bn_name, relu_name, sc_name = handle_block_names(stage, block)
x = BatchNormalization(name=bn_name + '0', **bn_params)(input_tensor)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def identity_block(self, input_tensor, filters, activation, stage, block, start_with_batch_norm = True):\n\n # Set the naming convention\n conv_name_base = 'res' + str(stage) + block + '_branch'\n batch_norm_name_base = 'batch_norm' + str(stage) + block + '_branch'\n\n x_shortcut = inpu... | [
"0.7127304",
"0.70226824",
"0.69105184",
"0.68836373",
"0.6850498",
"0.68464863",
"0.6822095",
"0.6821457",
"0.6803604",
"0.67993164",
"0.6784702",
"0.6770701",
"0.6715633",
"0.6714348",
"0.6713607",
"0.6663853",
"0.66239524",
"0.6621875",
"0.6621875",
"0.6607414",
"0.6598225... | 0.0 | -1 |
The identity block is the block that has no conv layer at shortcut. Arguments | def basic_identity_scse_block(filters, stage, block, re=8):
def layer(input_tensor):
conv_params = get_conv_params()
bn_params = get_bn_params()
conv_name, bn_name, relu_name, sc_name = handle_block_names(stage, block)
x = BatchNormalization(name=bn_name + '1', **bn_params)(input_t... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def identity_block(self, input_tensor, filters, activation, stage, block, start_with_batch_norm = True):\n\n # Set the naming convention\n conv_name_base = 'res' + str(stage) + block + '_branch'\n batch_norm_name_base = 'batch_norm' + str(stage) + block + '_branch'\n\n x_shortcut = inpu... | [
"0.71272004",
"0.7022438",
"0.6910338",
"0.68836653",
"0.68505627",
"0.6847176",
"0.68221945",
"0.6821999",
"0.680346",
"0.6799615",
"0.67849326",
"0.67714536",
"0.67158884",
"0.67146987",
"0.67137283",
"0.6664201",
"0.6624224",
"0.662218",
"0.662218",
"0.66078824",
"0.659845... | 0.60076267 | 37 |
The identity block is the block that has no conv layer at shortcut. Arguments | def basic_conv_scse_block(filters, stage, block, strides=(2, 2), re=8):
def layer(input_tensor):
conv_params = get_conv_params()
bn_params = get_bn_params()
conv_name, bn_name, relu_name, sc_name = handle_block_names(stage, block)
x = BatchNormalization(name=bn_name + '1', **bn_par... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def identity_block(self, input_tensor, filters, activation, stage, block, start_with_batch_norm = True):\n\n # Set the naming convention\n conv_name_base = 'res' + str(stage) + block + '_branch'\n batch_norm_name_base = 'batch_norm' + str(stage) + block + '_branch'\n\n x_shortcut = inpu... | [
"0.71272004",
"0.7022438",
"0.6910338",
"0.68836653",
"0.68505627",
"0.6847176",
"0.68221945",
"0.6821999",
"0.680346",
"0.6799615",
"0.67849326",
"0.67714536",
"0.67158884",
"0.67146987",
"0.67137283",
"0.6664201",
"0.6624224",
"0.662218",
"0.662218",
"0.66078824",
"0.659845... | 0.0 | -1 |
Returns the default collector settings | def get_default_config(self):
config = super(UserScriptsCollector, self).get_default_config()
config.update( {
'path': '.',
'scripts_path': '/etc/diamond/user_scripts/',
'method': 'Threaded',
} )
return config | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_default_config(self):\r\n config = super(CMDCollector, self).get_default_config()\r\n config.update({\r\n 'enabled': 'True',\r\n 'fs': ',',\r\n 'timeout': 300,\r\n })\r\n return config",
"def getDefaultSettings():\n return {}",
"def ge... | [
"0.7051504",
"0.70081085",
"0.6949213",
"0.67133325",
"0.65743",
"0.6530999",
"0.6521596",
"0.65153503",
"0.64666075",
"0.64476866",
"0.6413572",
"0.6397821",
"0.6380573",
"0.6368372",
"0.6357416",
"0.6351892",
"0.6331843",
"0.63120425",
"0.62354094",
"0.6231949",
"0.62074935... | 0.587527 | 49 |
Voice Play the next song in the queue. Accepts no arguments. | def on_skip(self, event):
self.pre_check(event)
if (event.author.id not in self.cool_down["general"] or
time() - self.cool_down["general"][event.author.id] >= 2):
self.get_player(event.guild.id).skip()
self.cool_down["general"][event.author.id] = time()
el... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def play(self, ctx, *, song: str):\n state = self.get_voice_state(ctx.message.server)\n opts = {\n 'default_search': 'ytsearch',\n 'quiet': True,\n }\n\n if state.voice is None:\n success = await ctx.invoke(self.summon)\n if not success:... | [
"0.71854866",
"0.7116944",
"0.69287676",
"0.6867975",
"0.677823",
"0.6712081",
"0.66847193",
"0.6683627",
"0.66687655",
"0.6661358",
"0.66608906",
"0.66580075",
"0.66245365",
"0.66217434",
"0.6613146",
"0.6613146",
"0.6595063",
"0.65922534",
"0.6574445",
"0.6485049",
"0.64724... | 0.0 | -1 |
Voice Get information about next queued song. Accepts no arguments. | def on_next_command(self, event):
self.pre_check(event)
if not self.get_player(event.guild.id).queue:
return event.channel.send_message("There aren't any songs queued.")
ytdata = self.get_ytdl_values(
self.get_player(event.guild.id).queue[0].metadata,
)
ev... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_next_song():\n try:\n next_song = queue.getSong()\n queue_change()\n currently_playing_change(next_song)\n return json.dumps(next_song.to_dict())\n except IndexError as e:\n return json.dumps({'error': 'No songs in the queue'})",
"def get_next_song(self):\r\n ... | [
"0.7528458",
"0.6910447",
"0.68040365",
"0.63107395",
"0.63067645",
"0.627678",
"0.6212034",
"0.6185695",
"0.6137425",
"0.61039096",
"0.6087242",
"0.60314745",
"0.6030844",
"0.60241926",
"0.600748",
"0.5967641",
"0.59300333",
"0.58726114",
"0.5847199",
"0.58364683",
"0.581738... | 0.65402305 | 3 |
Returns total amount received on your account | def get_transaction_totals(self, params=None):
return self.get(f"{self.gateway_path}/totals", params) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def balance(self):\n total_money = 0\n for item in self.ledger:\n total_money += item['amount']\n return total_money",
"def get_total_paid(self):\n return sum(self.paid)",
"def total_spent(self):\n total_sum = Order.objects.filter(\n email=self.email).ag... | [
"0.7104757",
"0.7069385",
"0.6880987",
"0.68749225",
"0.68589234",
"0.6857937",
"0.6842639",
"0.68081063",
"0.67907584",
"0.67608845",
"0.6741547",
"0.6711796",
"0.6690905",
"0.6689272",
"0.6676667",
"0.661183",
"0.6594401",
"0.6575686",
"0.65718985",
"0.6565763",
"0.6565763"... | 0.0 | -1 |
return the index corresponding at the first occurence of value in list | def index(liste, value):
for ii in range(len(liste)):
if liste[ii] == value:
return ii
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def index(self, value):\n self.__validate_value(value)\n for index, v in enumerate(self.__list):\n if v == value:\n return index",
"def closest_value_index(val, lst):\n index = 0\n for item in lst:\n if item > val:\n return index\n index += 1... | [
"0.7666883",
"0.75553674",
"0.75322366",
"0.73974407",
"0.7306116",
"0.72406524",
"0.71949124",
"0.71868026",
"0.7173489",
"0.71538794",
"0.71089154",
"0.7069118",
"0.7064808",
"0.70324296",
"0.7016907",
"0.70150346",
"0.69772476",
"0.69540596",
"0.69502425",
"0.69284594",
"0... | 0.81286085 | 0 |
method to set the name of the output_database | def set_output_database (self, file_name):
try:
self.object_database=file_name
self.filepath_output_database = os.path.join(self.filepath, self.output_database)
print("set output_database filename to", file_name)
except:
print("setting object database fail... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def database_name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"database_name\")",
"def getDatabaseName(self):\n raise NotImplementedError",
"def get_db_name(self):\n\t\treturn conf.db_name",
"def get_name(self) -> str:\n return self.dbname",
"def db_name(self, db_name):\n\n... | [
"0.71581715",
"0.7139252",
"0.70207834",
"0.6973042",
"0.6896915",
"0.6870785",
"0.6853191",
"0.6820632",
"0.668634",
"0.6684695",
"0.6680187",
"0.66756105",
"0.66751665",
"0.66531605",
"0.6643873",
"0.66307545",
"0.6598226",
"0.65926546",
"0.6548423",
"0.65220237",
"0.640572... | 0.8193771 | 0 |
Creates a GetGroupMessage from a protobuf As a requirement of all objects which inherit from Serializable, this method transforms a protobuf object into an instance of this class. | def _proto2object(
proto: GetGroupMessage_PB,
) -> "GetGroupMessage":
return GetGroupMessage(
msg_id=_deserialize(blob=proto.msg_id),
address=_deserialize(blob=proto.address),
content=json.loads(proto.content),
reply_to=_deserialize(blob=proto.reply_t... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _proto2object(\n proto: CreateGroupMessage_PB,\n ) -> \"CreateGroupMessage\":\n\n return CreateGroupMessage(\n msg_id=_deserialize(blob=proto.msg_id),\n address=_deserialize(blob=proto.address),\n content=json.loads(proto.content),\n reply_to=_deseri... | [
"0.8065173",
"0.8059963",
"0.80385315",
"0.7838053",
"0.78343934",
"0.7728165",
"0.772733",
"0.76612204",
"0.75730646",
"0.75216293",
"0.7501986",
"0.7421604",
"0.7359245",
"0.7337106",
"0.72288305",
"0.71763164",
"0.70391303",
"0.70110816",
"0.68666184",
"0.68378156",
"0.645... | 0.8384033 | 0 |
Sets the prev link for the node. | def getPrev(self):
return self.prev | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setPrev(self, prev):\n\t\t\tself.prev = prev",
"def prev(self, prev):\n\n self._prev = prev",
"def set_prev(self, p) -> None:\n self.prev = p",
"def setPrev(self, prev_half_edge):\n self.prev = prev_half_edge",
"def prev_page_url(self, prev_page_url):\n\n self._prev_page_url... | [
"0.7875985",
"0.7465448",
"0.7228299",
"0.7093982",
"0.7074755",
"0.6893062",
"0.68524987",
"0.67959595",
"0.668916",
"0.6375687",
"0.6178108",
"0.61040765",
"0.60961574",
"0.6089415",
"0.6055914",
"0.5996824",
"0.5947542",
"0.59411544",
"0.5934224",
"0.59309167",
"0.5916836"... | 0.5934818 | 18 |
Sets the prev link for the node. | def setPrev(self, prev):
self.prev = prev | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def prev(self, prev):\n\n self._prev = prev",
"def set_prev(self, p) -> None:\n self.prev = p",
"def setPrev(self, prev_half_edge):\n self.prev = prev_half_edge",
"def prev_page_url(self, prev_page_url):\n\n self._prev_page_url = prev_page_url",
"def goToPrevHistory(self: Self, ... | [
"0.7465448",
"0.7228299",
"0.7093982",
"0.7074755",
"0.6893062",
"0.68524987",
"0.67959595",
"0.668916",
"0.6375687",
"0.6178108",
"0.61040765",
"0.60961574",
"0.6089415",
"0.6055914",
"0.5996824",
"0.5947542",
"0.59411544",
"0.5934818",
"0.5934224",
"0.59309167",
"0.5916836"... | 0.7875985 | 0 |
Replace the graph of the given GraphModule with one that contains the same nodes as the original, but in topologically sorted order. This is used by the merge_matmul transformation below, which disturbs the topologically sorted order of its input GraphModule, so that this order is restored before further transformation... | def legalize_graph(gm: pippy.fx.GraphModule) -> pippy.fx.GraphModule:
indeg = {node: 0 for node in gm.graph.nodes}
new_graph = pippy.fx.Graph()
# Track how many unfulfilled dependencies each node has
for node in gm.graph.nodes:
for user in node.users:
indeg[user] += 1
queue: coll... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _reset_topological_order(self):\n self._topological_order = self._input_nodes[:]\n self.sorted = False",
"def transform(g):\n min_nidx = min(g.nodes)\n max_nidx = max(g.nodes)\n\n if min_nidx == 0 and max_nidx == g.number_of_nodes() - 1: # Everything already labeled as wanted\n ... | [
"0.6281253",
"0.6020051",
"0.5968213",
"0.5939152",
"0.5891148",
"0.587402",
"0.57739174",
"0.57242393",
"0.5655821",
"0.56404704",
"0.56368893",
"0.56269574",
"0.56102455",
"0.5603213",
"0.55983084",
"0.5588909",
"0.5579634",
"0.5571751",
"0.55631703",
"0.5544777",
"0.554143... | 0.62657577 | 1 |
Determine which FA environment (Dev/Uat/Prod) the script is running in. Returns the specified path contained in the FExtensionValue which differs for each environment. Also retrieves the list of trade filters separated by ';' in the FExtensionValue config file. | def retrieve_environment(env_config, filter_config):
global path, filter_list_from_config
arena_data_server = acm.FDhDatabase["ADM"].ADSNameAndPort().upper()
configuration = acm.GetDefaultValueFromName(
acm.GetDefaultContext(), acm.FObject, env_config)
filter_list_from_config = acm.GetDefaultV... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_current_environment():\n # Search for the environment variable set by the hutch python setup\n env = os.getenv('CONDA_ENVNAME')\n # Otherwise look for built-in Conda environment variables\n if not env:\n env = os.getenv('CONDA_DEFAULT_ENV')\n # Check the top level PYTHONPATH to see if... | [
"0.5488771",
"0.52747124",
"0.52578723",
"0.5231717",
"0.51516294",
"0.50663215",
"0.506381",
"0.5058923",
"0.505804",
"0.49744675",
"0.49618024",
"0.4936943",
"0.48768833",
"0.48471853",
"0.48470667",
"0.4840807",
"0.48290032",
"0.47938055",
"0.4790978",
"0.47902945",
"0.478... | 0.6358428 | 0 |
initialize the dictionary structure. | def initialize_globals():
for filter_name in filter_list_from_config:
try:
trade_filter = acm.FTradeSelection[filter_name]
live_trade_filters.append(trade_filter)
add_trades(trade_filter)
except Exception:
exc_type, _exc_obj, exc_tb = sys.exc_info()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self):\n self.dict = {}",
"def __init__(self):\n self.dict = {}",
"def __init__(self, dict):\n self.dict = dict",
"def __init__(self, dict):\n self.dict = dict",
"def __init__(self):\n self.dictionary = None",
"def __init__(self):\r\n self.dic={}",
... | [
"0.76089376",
"0.76089376",
"0.7508111",
"0.7508111",
"0.745744",
"0.7422544",
"0.7417321",
"0.7417321",
"0.7382122",
"0.7361919",
"0.7361919",
"0.7361919",
"0.7361919",
"0.73564655",
"0.7314578",
"0.73127544",
"0.72841823",
"0.7283625",
"0.7282861",
"0.7256283",
"0.72472054"... | 0.0 | -1 |
This renders the home page. | def home(request):
context_dict = {}
employee = models.Teacher.objects.filter(
user=request.user
).first()
# context_dict = {
# context_helper.get_emp_info(employee)
# }
# print (context_dict)
context_dict.update(context_helper.get_emp_info(employee))
return render(request, "home.html", context_dict) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def home():\n\n return render_template('home_page.html')",
"def home():\n\n return render_template(\"home.html\")",
"def render_home():\r\n\treturn render_template(\"index.html\")",
"def home():\n return render_template('home.html')",
"def home():\n return render_template('home.html')",
"def ... | [
"0.8908748",
"0.8750969",
"0.87306887",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.86931294",
"0.8677446",
... | 0.0 | -1 |
This function prints and plots the confusion matrix. Normalization can be applied by setting `normalize=True`. | def plot_confusion_matrix(y_true, y_pred, classes=None,
normalize=False,
title=None,
cmap=plt.cm.Blues):
if not title:
if normalize:
title = 'Normalized confusion matrix'
else:
title = 'Confusion ma... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def plot_confusion_matrix(cm, classes=[0,1], normalize=False, title='Confusion matrix', print_matrix=False):\n\n if normalize:\n cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n print(\"Normalized confusion matrix\")\n else:\n print('Confusion matrix, without normalization')\n\n... | [
"0.8194862",
"0.80949175",
"0.8029915",
"0.8019153",
"0.79941195",
"0.7991258",
"0.7980955",
"0.7976606",
"0.79610753",
"0.79590565",
"0.79378676",
"0.7934962",
"0.7934504",
"0.79313844",
"0.7926313",
"0.7924577",
"0.79241234",
"0.7923211",
"0.7923023",
"0.7921931",
"0.791787... | 0.0 | -1 |
Return the name of the Hikvision sensor. | def name(self):
return self._name | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_sensor_name(self):\n return self.data[1]",
"def name(self):\n return self._sensor.name",
"def name(self):\n return self.device.device_data[self.device_id]['name'] + \\\n f' {self._sensor_type}'",
"def name(self):\n return f\"{self._name} {SENSOR_TYPES[self.senso... | [
"0.8268713",
"0.8237671",
"0.78250563",
"0.76772547",
"0.75464255",
"0.7545106",
"0.74908656",
"0.7388705",
"0.7388686",
"0.73761815",
"0.72924775",
"0.71507454",
"0.704222",
"0.7000588",
"0.6804253",
"0.67127144",
"0.67098206",
"0.6688464",
"0.6660511",
"0.6660511",
"0.66605... | 0.0 | -1 |
Return true if sensor is on. | def is_on(self):
return self._sensor_state() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_on(self):\n return getattr(self.coordinator.data[0], self._sensor) is True",
"def is_on(self):\n data = self.sensor_data\n if data and data[\"model\"] == \"SML\" and data[\"changed\"]:\n return data[\"state\"] == STATE_ON\n return False",
"def is_on(self) -> bool:\... | [
"0.8668819",
"0.83718693",
"0.8321358",
"0.82086754",
"0.82086754",
"0.82086754",
"0.8072303",
"0.79461884",
"0.78692335",
"0.78692335",
"0.78290933",
"0.77697575",
"0.7760602",
"0.76900584",
"0.7629474",
"0.7626312",
"0.7625873",
"0.757377",
"0.7554073",
"0.75531846",
"0.752... | 0.88761306 | 0 |
Return the class of this sensor, from DEVICE_CLASSES. | def device_class(self):
try:
return DEVICE_CLASS_MAP[self._sensor]
except KeyError:
# Sensor must be unknown to us, add as generic
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def device_class(self):\n return self.sensor_type[\"class\"]",
"def device_class(self):\n return DEVICE_CLASSES.get(self.sensor_data[\"model\"])",
"def device_class(self):\n return SENSOR_TYPES[self.sensor][3].get(\"device_class\")",
"def device_class(self):\n if self.sensor_class... | [
"0.9062012",
"0.8947314",
"0.8809003",
"0.87462795",
"0.87445956",
"0.87445956",
"0.873263",
"0.87101674",
"0.85638815",
"0.85638815",
"0.85526353",
"0.84336495",
"0.84305036",
"0.83888704",
"0.8281369",
"0.82692766",
"0.8168396",
"0.8107814",
"0.80006665",
"0.7911548",
"0.78... | 0.83166206 | 14 |
Return the state attributes. | def extra_state_attributes(self):
attr = {ATTR_LAST_TRIP_TIME: self._sensor_last_update()}
if self._delay != 0:
attr[ATTR_DELAY] = self._delay
return attr | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def state_attributes(self):\n return self._attributes",
"def state_attributes(self):\n return self._attributes",
"def device_state_attributes(self):\r\n return self.attributes",
"def device_state_attributes(self):\n return self._state_attrs",
"def device_state_attributes(self):\... | [
"0.8953056",
"0.8953056",
"0.8524094",
"0.83673775",
"0.83673775",
"0.83637255",
"0.8335954",
"0.83349335",
"0.8310754",
"0.8291855",
"0.828953",
"0.828953",
"0.82875603",
"0.82875603",
"0.82875603",
"0.82875603",
"0.82875603",
"0.82875603",
"0.82875603",
"0.82875603",
"0.828... | 0.0 | -1 |
Creating flask app and setting all modeuls and config. | def create_app():
config = config_by_name[os.getenv('APP_SETTINGS', 'dev')]
flask_app = Flask(__name__, static_folder=None, instance_relative_config=True)
flask_app.config.from_object(config)
with flask_app.app_context():
app_manager = Manager(flask_app)
from app.models import db, ma
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_app(self):\r\n self.app = Flask(__name__, instance_relative_config=True)\r\n\r\n # Init the secret key of the app -it is a must for flask to run\r\n self.app.config.from_mapping(\r\n SECRET_KEY='!ZNeverSayNever116Z!',\r\n MONGODB_SETTINGS= {'host': 'mongodb://l... | [
"0.862719",
"0.8351689",
"0.8347321",
"0.8346519",
"0.83345604",
"0.8300351",
"0.8289072",
"0.82784265",
"0.8225128",
"0.8211296",
"0.8185404",
"0.8164446",
"0.8142924",
"0.8129862",
"0.80871683",
"0.8087077",
"0.8070512",
"0.8064273",
"0.80463356",
"0.8019652",
"0.80069155",... | 0.81871897 | 10 |
Traverse through the entire BTree to calculate the number of nodes it has. | def numNodes(T):
n = 1
if T.isLeaf:
return n
for i in range(len(T.child)):
n += numNodes(T.child[i])
return n | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def count_nodes(self):\n if self.children is None:\n return 0\n\n total_count = 0\n for child in self.children:\n if child is None:\n return 0\n child_count = child.count_nodes()\n total_count = total_count + child_count\n\n ret... | [
"0.8126878",
"0.78849125",
"0.7833212",
"0.78316116",
"0.7772799",
"0.77459306",
"0.77308065",
"0.7716238",
"0.7689622",
"0.7682001",
"0.767653",
"0.76338",
"0.74925274",
"0.7490429",
"0.7453843",
"0.73934203",
"0.7377626",
"0.7375549",
"0.73751295",
"0.73481226",
"0.7330711"... | 0.8063285 | 1 |
Test case for create_response_descriptor_subscriptions_subscription_subscription_resource | def test_create_response_descriptor_subscriptions_subscription_subscription_resource(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_modify_response_descriptor_subscriptions_subscription_subscription_resource(self):\n pass",
"def test_create_response_descriptor_subscriptions_subscription_subscription_resource_spaces(self):\n pass",
"def test_load_response_descriptor_subscriptions_subscription_subscription_resource(sel... | [
"0.87412554",
"0.8588088",
"0.83379585",
"0.82308966",
"0.7775794",
"0.7608592",
"0.7605677",
"0.75500727",
"0.7347543",
"0.7300998",
"0.7060672",
"0.70161843",
"0.69488347",
"0.69302607",
"0.6744745",
"0.6676874",
"0.66014934",
"0.65724623",
"0.64912724",
"0.6457783",
"0.640... | 0.94596004 | 0 |
Test case for create_response_descriptor_subscriptions_subscription_subscription_resource_spaces | def test_create_response_descriptor_subscriptions_subscription_subscription_resource_spaces(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_modify_response_descriptor_subscriptions_subscription_subscription_resource_spaces(self):\n pass",
"def test_index_response_descriptor_subscriptions_subscription_subscription_resource_spaces(self):\n pass",
"def test_load_response_descriptor_subscriptions_subscription_subscription_resour... | [
"0.87898076",
"0.84957993",
"0.84469354",
"0.8135916",
"0.8024415",
"0.75330555",
"0.74872947",
"0.72072065",
"0.7170737",
"0.7123899",
"0.7024082",
"0.6879563",
"0.68744624",
"0.66875726",
"0.6547886",
"0.6496468",
"0.6405576",
"0.62375563",
"0.62205213",
"0.62015754",
"0.61... | 0.94430006 | 0 |
Test case for list_all_response_descriptor_subscriptions_subscription_subscription_resource | def test_list_all_response_descriptor_subscriptions_subscription_subscription_resource(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_list_all_response_descriptor_subscriptions_subscription_subscription_resource_spaces(self):\n pass",
"def test_load_response_descriptor_subscriptions_subscription_subscription_resource(self):\n pass",
"def test_create_response_descriptor_subscriptions_subscription_subscription_resource(s... | [
"0.8672392",
"0.80634016",
"0.7963346",
"0.79525554",
"0.7950173",
"0.762874",
"0.75751597",
"0.75354266",
"0.75185573",
"0.7085981",
"0.7015135",
"0.6927433",
"0.6609123",
"0.6608625",
"0.65717506",
"0.64721626",
"0.6449704",
"0.6410992",
"0.6408065",
"0.63710225",
"0.632791... | 0.94718015 | 0 |
Test case for modify_response_descriptor_subscriptions_subscription_subscription_resource | def test_modify_response_descriptor_subscriptions_subscription_subscription_resource(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_create_response_descriptor_subscriptions_subscription_subscription_resource(self):\n pass",
"def test_modify_response_descriptor_subscriptions_subscription_subscription_resource_spaces(self):\n pass",
"def test_load_response_descriptor_subscriptions_subscription_subscription_resource(sel... | [
"0.8563571",
"0.84658855",
"0.8058546",
"0.80224764",
"0.7713785",
"0.75516945",
"0.7453322",
"0.7192042",
"0.71334755",
"0.71012443",
"0.70175844",
"0.7000383",
"0.6748506",
"0.6710934",
"0.6697179",
"0.66575694",
"0.66456854",
"0.6641054",
"0.6612385",
"0.6570631",
"0.65649... | 0.9448674 | 0 |
Add a member to a group, by an existing group member. | def add_new_member(self, event):
body = event['body']
body = json.loads(body)
required_fields = ['group_id', 'new_user_id']
for f in required_fields:
if f not in body:
return get_bad_request('POST body missing field {}'.format(f))
group_id = body['gr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_member_to_group(self, group_id, member_id):\n route_values = {}\n if group_id is not None:\n route_values['groupId'] = self._serialize.url('group_id', group_id, 'str')\n if member_id is not None:\n route_values['memberId'] = self._serialize.url('member_id', member... | [
"0.80759203",
"0.7781975",
"0.770071",
"0.7675795",
"0.759767",
"0.7432633",
"0.7386738",
"0.73069775",
"0.7115192",
"0.7030641",
"0.6992207",
"0.6979588",
"0.69104636",
"0.68972623",
"0.6890155",
"0.6796194",
"0.66509473",
"0.6607152",
"0.66037047",
"0.6538465",
"0.6519908",... | 0.6159286 | 37 |
Converting pixels from BGR (Red, Green, Blue) to YCrCb (luma, bluedifference, reddifference) | def bgr_to_ycrcb(matrix3d: np.ndarray) -> np.ndarray:
return np.apply_along_axis(bgr_pixel_to_ycrcb, 2, matrix3d) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def yuv_to_rgb(img_yuv):\n\n y = img_yuv[..., 0]\n u = img_yuv[..., 1]\n v = img_yuv[..., 2]\n\n r = y + 1.14 * v\n g = y - 0.396 * u - 0.581 * v\n b = y + 2.029 * u\n\n img_rgb = np.stack((r, g, b), axis=2)\n img_rgb = np.clip(img_rgb, 0, 1)\n return img_rgb",
"def yuv2rgb(im):\n #... | [
"0.73401994",
"0.72443944",
"0.7191258",
"0.6968075",
"0.69310284",
"0.68717015",
"0.6746351",
"0.6573021",
"0.6481176",
"0.64723957",
"0.6445774",
"0.6442767",
"0.6418211",
"0.6372011",
"0.6353601",
"0.6352888",
"0.6323306",
"0.62929225",
"0.6268779",
"0.6262479",
"0.6217953... | 0.0 | -1 |
Return if the plugin is available for loading. If a plugin is missing dependencies or for some other reason should not be available to the current system it should override this property and return False to exclude itself from the plugin list. | def available(self):
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_loaded(self, plugin):\n return self._get_name(plugin) in self.loaded_plugins",
"def has_plugin(self, name: str) -> bool:\n return name in self._plugins",
"def has_plugin(self, plugin_name):\n return plugin_name in self.plugins.values_list('name', flat=True)",
"def plugin_enabled_b... | [
"0.7220657",
"0.7182119",
"0.7025559",
"0.6910154",
"0.689142",
"0.6865923",
"0.6846862",
"0.68416315",
"0.6709156",
"0.6687168",
"0.65706414",
"0.65523076",
"0.6530908",
"0.65000683",
"0.64809287",
"0.64012355",
"0.63563097",
"0.63315696",
"0.6328762",
"0.63147926",
"0.62802... | 0.6098247 | 38 |
Uses a given batch dictionary and domain kwargs to obtain a SqlAlchemy column object. | def get_compute_domain(
self,
domain_kwargs: Dict,
domain_type: Union[str, MetricDomainTypes],
accessor_keys: Optional[Iterable[str]] = None,
) -> Tuple[Select, dict, dict]:
# Extracting value from enum if it is given for future computation
domain_type = MetricDomainT... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def column(self, domain=None):\n if domain is None:\n return self.col.copy()\n else:\n return self.col.convert_to(domain)",
"def sqlobj_from_dict(obj, values):\n for c in obj.__table__.columns:\n if c.name in values:\n setattr(obj, c.name, values[c.name])\... | [
"0.5431496",
"0.5401011",
"0.5268713",
"0.5224346",
"0.5138979",
"0.5074222",
"0.5069668",
"0.4973821",
"0.49038166",
"0.48214892",
"0.48129463",
"0.48129117",
"0.4805565",
"0.47794953",
"0.47447672",
"0.47046596",
"0.46708152",
"0.46705273",
"0.46506712",
"0.46404663",
"0.46... | 0.5133917 | 5 |
"0x58, 0x59, 0x01, 0x00, 0x00" => [0x58, 0x59, 0x01, 0x00, 0x00] | def hex_str_to_bytes_arr(bytes_str: str) -> List[int]:
return eval(f"[{bytes_str}]") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def hex_list(self):\r\n return [''.join(['{:02X}'.format(b) for b in data]) for data in self.buffers()]",
"def buf_to_list(buf):\r\n buf_stripped = buf.raw.decode().rstrip('\\x00')\r\n# for ch in buf_stripped:\r\n# if (ch == '0') or (ch == '\\t') or (ch == '\\n'):\r\n# name = name.... | [
"0.65582275",
"0.63307226",
"0.6290027",
"0.6262765",
"0.61640704",
"0.6160979",
"0.6156085",
"0.61130404",
"0.610784",
"0.60554963",
"0.6033458",
"0.5946255",
"0.5939836",
"0.58945185",
"0.5894092",
"0.5832303",
"0.5822892",
"0.58158875",
"0.58045244",
"0.580421",
"0.5776219... | 0.6725189 | 0 |
Test being able to unload an entry. | async def test_unload_entry(opp, mock_account):
entry = await setup_integration(opp, mock_account, VACUUM_DOMAIN)
vacuum = opp.states.get(VACUUM_ENTITY_ID)
assert vacuum
assert vacuum.state == STATE_DOCKED
await opp.services.async_call(
VACUUM_DOMAIN,
SERVICE_START,
{ATTR_E... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def test_unload_entry(opp, nzbget_api):\n entry = await init_integration(opp)\n\n assert len(opp.config_entries.async_entries(DOMAIN)) == 1\n assert entry.state is ConfigEntryState.LOADED\n\n assert await opp.config_entries.async_unload(entry.entry_id)\n await opp.async_block_till_done()\n\n ... | [
"0.77138734",
"0.76933795",
"0.74769473",
"0.7384423",
"0.7349679",
"0.73169553",
"0.7288968",
"0.72645843",
"0.72513765",
"0.7182948",
"0.713809",
"0.6820462",
"0.6797362",
"0.6791803",
"0.6683401",
"0.6641027",
"0.66159004",
"0.6594395",
"0.6540514",
"0.64573026",
"0.645170... | 0.720308 | 9 |
dictionary of all default parameters (key=param name). Note that defaults are generally only stored for parameters where the default is different from the configured value | def get_default_parameters(self, default_type):
return self._default_parameters.get(default_type, {}) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def parameters_default(cls):\n return cls._Parameters.__new__.__defaults__",
"def get_parameters(self):\n params = {}\n for p in self.DEFAULT_VALUES.keys():\n params[p] = getattr(self, p)\n return params",
"def defaults() -> dict:\n pass",
"def get_defaults(self)... | [
"0.79437476",
"0.7881707",
"0.77220637",
"0.76504976",
"0.76182073",
"0.756907",
"0.7555116",
"0.7548557",
"0.7531213",
"0.7496584",
"0.7451419",
"0.7296076",
"0.72916055",
"0.72622734",
"0.72622734",
"0.72486615",
"0.7164347",
"0.71471405",
"0.7126808",
"0.7124386",
"0.71238... | 0.76477087 | 4 |
get a specific dataset. | def get_dataset(self, name, multi_instance=0):
return [elem for elem in self._data_list
if elem.name == name and elem.multi_id == multi_instance][0] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_dataset(self):\n return datasets.get_dataset(self.dataset_id)",
"def get_dataset(self, dataset_id):\n return self.session.query(self.Dataset).get(dataset_id)",
"def get(id: str) -> DataSet:\n pass",
"def get(self, name):\n assert name, \"Must input a valid dataset name.\"\... | [
"0.7955141",
"0.7826601",
"0.7670849",
"0.760219",
"0.7440116",
"0.7433901",
"0.73345757",
"0.7322343",
"0.72858053",
"0.7252087",
"0.7180746",
"0.7176037",
"0.71597934",
"0.71402335",
"0.71210235",
"0.7117107",
"0.711563",
"0.7065056",
"0.7016815",
"0.7013039",
"0.7009789",
... | 0.6579869 | 35 |
Assert that a valid CO type amendment statement returns a 200 status. | def test_amendment_court_order_success(session, client, jwt):
# setup
current_app.config.update(PAYMENT_SVC_URL=MOCK_PAY_URL)
rv1 = create_financing_test(session, client, jwt)
assert rv1.status_code == HTTPStatus.CREATED
assert rv1.json['baseRegistrationNumber']
base_reg_num = rv1.json['baseRegi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_status_code_200(self):\n\t\tformatted_status = status_code(self)\n\t\tself.assertEqual(formatted_status, '200')",
"def test_status_code(self):\n formatted_status_code = get_status_code('python')\n self.assertEqual(formatted_status_code, 200) #compares the test result with the result expect... | [
"0.6761491",
"0.6702015",
"0.6561934",
"0.65322626",
"0.64473075",
"0.631492",
"0.6283017",
"0.6236529",
"0.6227647",
"0.6190859",
"0.61854064",
"0.6174831",
"0.61590624",
"0.61475474",
"0.61203253",
"0.6095389",
"0.6056882",
"0.60532194",
"0.60359067",
"0.5995723",
"0.599545... | 0.5729343 | 48 |
Assert that a valid AM type amendment statement returns a 200 status. | def test_amendment_success(session, client, jwt):
# setup
current_app.config.update(PAYMENT_SVC_URL=MOCK_PAY_URL)
rv1 = create_financing_test(session, client, jwt)
assert rv1.status_code == HTTPStatus.CREATED
assert rv1.json['baseRegistrationNumber']
base_reg_num = rv1.json['baseRegistrationNumb... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_status_code_200(self):\n\t\tformatted_status = status_code(self)\n\t\tself.assertEqual(formatted_status, '200')",
"def test_status_code(self):\n formatted_status_code = get_status_code('python')\n self.assertEqual(formatted_status_code, 200) #compares the test result with the result expect... | [
"0.6372946",
"0.63325983",
"0.63275206",
"0.62338895",
"0.62029874",
"0.61930406",
"0.6110963",
"0.60898936",
"0.6039467",
"0.59729207",
"0.5962532",
"0.59578514",
"0.5945757",
"0.59246397",
"0.5898609",
"0.5855304",
"0.5838366",
"0.58124256",
"0.58041656",
"0.57992774",
"0.5... | 0.5846508 | 16 |
Test showing the page of all offers. | def test_offers_show_every(self):
result = self.client.get('/offers_show_every')
self.assertEqual(result.status, '200 OK')
self.assertIn(b'Offers', result.data) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_offers(self):\n pass",
"def test_show_offer(self, mock_find):\n mock_find.return_value = sample_offer\n\n result = self.client.get(f'/offers/{sample_offer_id}')\n self.assertEqual(result.status, '200 OK')\n self.assertIn(b'Description', result.data)",
"def test_b... | [
"0.72028357",
"0.63975585",
"0.6307497",
"0.6142342",
"0.6118828",
"0.6108139",
"0.6106805",
"0.61000824",
"0.60947084",
"0.6088211",
"0.6061273",
"0.6035597",
"0.6009674",
"0.5989309",
"0.59431523",
"0.59197736",
"0.5881938",
"0.5876856",
"0.5876462",
"0.58678347",
"0.582831... | 0.78508234 | 0 |
This method converts the dictionary to the list | def convertToList(dict):
listOfList= [[k, v] for k, v in dict.items()]
for i in listOfList:
if i[1][2]=='x':
listOfList.remove(i)
return listOfList | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __dic2list(self,dic):\n return [(x,dic[x]) for x in dic]",
"def __dic2list(self,dic):\n\treturn map(lambda x:[x,dic[x]],dic)",
"def __dict_to_list(dict):\n\n max_val = 1\n for k,v in dict.items():\n if type(v) is list:\n if len(v) > 1 and (max_val > 1 and len(... | [
"0.80659676",
"0.8013816",
"0.75778276",
"0.75696623",
"0.7395945",
"0.72877353",
"0.727885",
"0.7155753",
"0.70990515",
"0.6958522",
"0.68984103",
"0.6868956",
"0.68315274",
"0.68111265",
"0.6782167",
"0.6775089",
"0.67651856",
"0.6748294",
"0.67303777",
"0.6666534",
"0.6666... | 0.6355936 | 36 |
A person template page without attached person should show an error banner explaining to the user that he/she is misusing the template. | def test_template_person_detail_without_person(self):
page = PageFactory(
template="courses/cms/person_detail.html",
title__language="en",
should_publish=True,
)
with self.assertTemplateUsed(
"courses/cms/fragment_error_detail_template_banner.html... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def errorview(request):\n \n #return a page indicating an error has occured\n return render(request, 'SmellGuessTemplate/error.html')",
"def page_not_found(error):\r\n return render_template('error_template.html' , title = \"404 bud\", \r\n \t\t\t\t\t\t\t\t\t\t\t\tmessage = \"Time to make the chim... | [
"0.6937663",
"0.6863008",
"0.68516415",
"0.6752877",
"0.6686156",
"0.66346717",
"0.6599722",
"0.65577775",
"0.6542976",
"0.650337",
"0.6459382",
"0.6441446",
"0.64403677",
"0.64176124",
"0.63976896",
"0.63921285",
"0.63720983",
"0.63401914",
"0.63311446",
"0.626568",
"0.62625... | 0.7322566 | 0 |
barcode_filename should accept sequences 0107 Sequences 0107 are all represented by singledigit integers, and should be properly zeropadded in the filename. The range allowed here is deliberately shorter than elsewhere in the program because barcode_filename is designed to work only with a corresponding date, and ISO w... | def test_price_code_0(self):
start_date = datetime(2016, 11, 13)
# Note this is a Sunday, and must have timedelta added
for x in range(1, 7):
with self.subTest(x=x):
date = start_date + timedelta(x)
result = star_barcode.barcode_filename(date, x)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_year_boundary(self):\n date = datetime(2017, 1, 1)\n seq = 27\n name = star_barcode.barcode_filename(date, seq)\n self.assertEqual(\n name,\n 'Barcode_2016-W52-7_27.pdf'\n )",
"def test_wrong_sequence(self):\n date = datetime(2016, 11, ... | [
"0.6251834",
"0.6211295",
"0.6178404",
"0.61356765",
"0.6012833",
"0.5837435",
"0.5756376",
"0.5724416",
"0.56670076",
"0.56564724",
"0.5565162",
"0.55428994",
"0.5510424",
"0.5450344",
"0.52778983",
"0.5277632",
"0.51578164",
"0.51521355",
"0.5145388",
"0.5137915",
"0.511371... | 0.54502195 | 14 |
Test the __init__ method when parameter 'ip' is None. Since the field is optional, it should pass. | def test_init_no_ip(self):
# mocks of files
rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)
ap = APInfo(port_id=1, ip=None, mac="bb:bb:bb:bb:bb:bb", radio_mac="bb:bb:bb:bb:bb:00", udp_port=12345, wlc_ip='1.1.1.1',
gateway_ip='1.1.1.2', ap_mode=APMode.LOCAL, rsa_ca_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_init_no_ip(self):\n client = ClientInfo(\"cc:cc:cc:cc:cc:cc\", ip=None, ap_info=self.ap)\n self.assertEqual(client.ip, None)\n self.assertEqual(client.ip_bytes, None)",
"def __init__(__self__, *,\n ip: Optional[pulumi.Input['IPAccessControlArgs']] = None):\n i... | [
"0.7619989",
"0.7324193",
"0.7324193",
"0.7323932",
"0.70612985",
"0.6996996",
"0.6709637",
"0.6705524",
"0.6618657",
"0.65942365",
"0.6415844",
"0.6387556",
"0.6366282",
"0.6358961",
"0.6319033",
"0.6228522",
"0.6208983",
"0.6139439",
"0.6108403",
"0.6083423",
"0.6066069",
... | 0.7339444 | 1 |
Test the __init__ method when mandatory parameter 'mac' is None. | def test_init_no_mac(self):
with self.assertRaises(ValueError):
client = ClientInfo(None, ip="3.3.3.3", ap_info=self.ap) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_init_no_mac(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n with self.assertRaises(ValueError):\n ap = APInfo(port_id=1, ip=\"2.2.2.2\", mac=None, radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n ... | [
"0.7700126",
"0.718434",
"0.7076505",
"0.69038445",
"0.68528235",
"0.64499795",
"0.6309808",
"0.6301054",
"0.6203087",
"0.616466",
"0.6155142",
"0.61442065",
"0.61114347",
"0.609657",
"0.607744",
"0.6011186",
"0.6001735",
"0.59643024",
"0.5931269",
"0.5910585",
"0.5905488",
... | 0.79045194 | 0 |
Test the __init__ method when parameter 'ip' is None. Since the field is optional, it should pass. | def test_init_no_ip(self):
client = ClientInfo("cc:cc:cc:cc:cc:cc", ip=None, ap_info=self.ap)
self.assertEqual(client.ip, None)
self.assertEqual(client.ip_bytes, None) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_init_no_ip(self):\n # mocks of files\n rsa_ca_priv_file, rsa_priv_file, rsa_cert_file = range(3)\n\n ap = APInfo(port_id=1, ip=None, mac=\"bb:bb:bb:bb:bb:bb\", radio_mac=\"bb:bb:bb:bb:bb:00\", udp_port=12345, wlc_ip='1.1.1.1',\n gateway_ip='1.1.1.2', ap_mode=APMode.... | [
"0.7339444",
"0.7324193",
"0.7324193",
"0.7323932",
"0.70612985",
"0.6996996",
"0.6709637",
"0.6705524",
"0.6618657",
"0.65942365",
"0.6415844",
"0.6387556",
"0.6366282",
"0.6358961",
"0.6319033",
"0.6228522",
"0.6208983",
"0.6139439",
"0.6108403",
"0.6083423",
"0.6066069",
... | 0.7619989 | 0 |
User not logged in returns 200 | def test_not_logged_in(self):
response = self.c.get(reverse(map_page), {'lat': 34.0, 'lng': 45.3})
self.assertEqual(response.status_code, 200) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def user_logged_in():\n if not session.get('user_id'):\n return \"nope\", 401\n else:\n return \"yep\", 200",
"def test_returns_401_if_user_not_logged_in(self):\n # Act\n response = self.client.get(self.url)\n self.assertEqual(response.status_code, 401)",
"def test_retu... | [
"0.803735",
"0.7406583",
"0.7406583",
"0.7406583",
"0.7374086",
"0.7358094",
"0.73388165",
"0.72660834",
"0.72058254",
"0.7197486",
"0.7057259",
"0.69839096",
"0.6981634",
"0.6981634",
"0.6972179",
"0.6965677",
"0.6945636",
"0.69440126",
"0.68950224",
"0.68555284",
"0.6853421... | 0.6876522 | 19 |
The expression pt1 == pt2 returns True when pt1 is close to pt2 | def test_almost_equal(self):
x = Point(
lat=23.4,
lng=23.1,
author=self.u
)
self.assertTrue(self.a == x)
self.assertFalse(self.a != x) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _same(p1,p2,prec=0.0001):\n #return num.all(num.equal(p1,p2))\n t1 = num.fabs(p1[0]-p2[0]) < prec\n t2 = num.fabs(p1[1]-p2[1]) < prec\n if t1 and t2:\n #print \"same\", p1,p2\n return True",
"def test_eq_2():\n a = FixedPoint(1, 'Q2.8')\n b = FixedPoin... | [
"0.78786254",
"0.73442125",
"0.73271257",
"0.73021305",
"0.72471225",
"0.72312576",
"0.7224132",
"0.72203106",
"0.7208399",
"0.7186101",
"0.7171681",
"0.71665627",
"0.71387106",
"0.71274626",
"0.71209747",
"0.7108511",
"0.7045949",
"0.7042352",
"0.7017369",
"0.7011124",
"0.69... | 0.6642547 | 39 |
The expression pt1 == pt2 returns False when pt1 is not close to pt2 | def test_not_equal(self):
x = Point(
lat=24.4,
lng=23.1,
author=self.u
)
self.assertFalse(self.a == x)
self.assertTrue(self.a != x) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _same(p1,p2,prec=0.0001):\n #return num.all(num.equal(p1,p2))\n t1 = num.fabs(p1[0]-p2[0]) < prec\n t2 = num.fabs(p1[1]-p2[1]) < prec\n if t1 and t2:\n #print \"same\", p1,p2\n return True",
"def almost_equals(self, other):\n import math\n ox, ... | [
"0.7833791",
"0.7375096",
"0.73340034",
"0.7259631",
"0.7250514",
"0.72273964",
"0.7221379",
"0.7205826",
"0.7195672",
"0.7176461",
"0.716174",
"0.7157015",
"0.7149755",
"0.7145545",
"0.7136548",
"0.7128811",
"0.7119354",
"0.71039134",
"0.7080448",
"0.7078054",
"0.706964",
... | 0.0 | -1 |
Cast schema names which containing special characters to valid names. Here special characters means any characters in | def cast_name(key):
special_symbols = set('{}{}'.format(punctuation, ' '))
special_symbols.remove('_')
new_key = ['_' if x in special_symbols else x for x in key]
casted_key = ''.join(new_key)
return casted_key | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def encodeSchemaName(self, schema):\r\n return '\"{}\"'.format(schema)",
"def _scrub(self, string):\n if not string.isalnum():\n raise ValueError(\"Table name cannot include non-alphanumerics.\")\n return string",
"def normalize_name(word):\n return word.strip(\"0123456789!@#... | [
"0.61856335",
"0.6037464",
"0.6004261",
"0.58687896",
"0.58262765",
"0.5808754",
"0.5807647",
"0.57684666",
"0.5738535",
"0.5723603",
"0.57223094",
"0.57125217",
"0.56966615",
"0.56726086",
"0.5666764",
"0.5645181",
"0.56419724",
"0.5639399",
"0.5602806",
"0.55878466",
"0.558... | 0.53094554 | 57 |
Get learning rate scheduler. | def get_lr_scheduler(self):
try:
scheduler_name = self.configs.OPTIM.LR_SCHEDULER.SCHEDULER_NAME
except AttributeError:
scheduler_name = None
if scheduler_name is None:
lr_scheduler = None
elif scheduler_name == 'plateau':
factor = self.c... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_scheduler(optimizer, opt):\n \n epochs_no_decay = opt.epochs - opt.lr_linear\n lr_policy = opt.lr_policy\n \n if lr_policy == 'linear':\n def lr_lambda(epoch):\n return 1. - max(0, epoch - epochs_no_decay) / float(opt.lr_linear + 1)\n scheduler = lr_scheduler.LambdaL... | [
"0.7635437",
"0.75883573",
"0.75060844",
"0.7453083",
"0.73677176",
"0.7187605",
"0.7152048",
"0.71470124",
"0.7139361",
"0.70922357",
"0.7084877",
"0.7058236",
"0.70532143",
"0.70265824",
"0.70135325",
"0.70125854",
"0.69860375",
"0.6956636",
"0.6950861",
"0.6934655",
"0.692... | 0.7616563 | 1 |
Return list of unique values while preserving order. Values must be hashable. | def uniq(seq: Iterable):
seen, result = {}, []
for item in seq:
if item in seen:
continue
seen[item] = None
result.append(item)
return result | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_unique_value_list(value):\n my_set = set(value)\n new_list = list(my_set)\n new_list.sort()\n return new_list",
"def unique(x):\n\n return list(set(x))",
"def find_remove_duplicates(list_of_values):\r\n output = []\r\n seen = set()\r\n for value in list_of_values:\r\n ... | [
"0.77642304",
"0.73466635",
"0.72686464",
"0.70993155",
"0.7049732",
"0.7036178",
"0.6986363",
"0.69395584",
"0.69315803",
"0.6901696",
"0.6871331",
"0.6860619",
"0.68340397",
"0.68287754",
"0.68124825",
"0.67243654",
"0.6652985",
"0.66490304",
"0.66442025",
"0.6638174",
"0.6... | 0.6244349 | 50 |
Initialize table from listlike container. | def _init_list(self, data: List[Any]):
# Assume data is homogenous in regard to row type
obj = data[0]
column_names = self._column_name_getter(obj)
column_values = self._column_value_getter(obj)
# Map of source to destination column
column_map = {}
# Do not upda... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _init_table(self, table: \"Table\"):\n if not self.columns:\n self.columns = table.columns\n self._data = table.data",
"def __init__(self):\n self.table = {}\n self.ls = []",
"def init_blank(self, T):\n self.headings = []\n self.table = {}\n self.... | [
"0.6741247",
"0.65784097",
"0.6445998",
"0.6421057",
"0.6410227",
"0.62771124",
"0.62656546",
"0.6222653",
"0.62108904",
"0.6183416",
"0.6157158",
"0.61253923",
"0.6124469",
"0.6088853",
"0.60814494",
"0.598742",
"0.59580296",
"0.5902306",
"0.5902306",
"0.5886963",
"0.5882113... | 0.6464922 | 2 |
Initialize table from dictlike container. | def _init_dict(self, data: Dict[Column, Row]):
if not self._columns:
self._columns = list(data.keys())
# Filter values by defined columns
columns = (
to_list(values)
for column, values in data.items()
if column in self._columns
)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _init_table(self, table: \"Table\"):\n if not self.columns:\n self.columns = table.columns\n self._data = table.data",
"def test_create_from_dicts(self):\n cols = list(zip(*self.dtypes))[0]\n dicts = [dict([(cols[i], d[i]) for i in xrange(len(d))])\n for... | [
"0.7078723",
"0.69768757",
"0.6741791",
"0.6514259",
"0.6489797",
"0.6371205",
"0.63667476",
"0.6355663",
"0.63450754",
"0.6337645",
"0.63217604",
"0.63029504",
"0.6181961",
"0.61749095",
"0.61712486",
"0.61712486",
"0.61712486",
"0.61712486",
"0.61712486",
"0.61712486",
"0.6... | 0.6601733 | 3 |
Validate that given column names can be used. | def _validate_columns(self, names):
if not is_list_like(names):
raise ValueError("Columns should be list-like")
if len(set(names)) != len(names):
raise ValueError("Duplicate column names")
if self._data and len(names) != len(self._data[0]):
raise ValueError(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _check_columns(df: pd.DataFrame, names: typing.Sequence[str]) -> None:\n for expected in names:\n if expected not in df.columns:\n raise ValueError(f\"'{expected}' column not found in input\")\n return",
"def _validate_columns(data, ip_column, lat_column, long_column, other_columns):\... | [
"0.8195807",
"0.7515005",
"0.74477583",
"0.73584527",
"0.72443414",
"0.72358197",
"0.7166061",
"0.7122262",
"0.7121349",
"0.711966",
"0.7089864",
"0.708901",
"0.69831634",
"0.6980481",
"0.6958175",
"0.6949049",
"0.692618",
"0.6905489",
"0.6900764",
"0.6798847",
"0.6783542",
... | 0.8290189 | 0 |
Find location for column value. | def column_location(self, value):
# Try to use as-is
try:
return self._columns.index(value)
except ValueError:
pass
# Try as integer index
try:
value = int(value)
if value in self._columns:
location = self._column... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _col_match(sheet, row, value):\r\n for cell in sheet[row]:\r\n if cell.value == value:\r\n return cell.column",
"def _value_column(self, field):\n for field_dict in self.schema['idx_fields']:\n if field_dict['field_name'] == field:\n return field_dict['co... | [
"0.6948674",
"0.6942318",
"0.68900645",
"0.6643696",
"0.6632486",
"0.6617296",
"0.66054964",
"0.6541255",
"0.65210915",
"0.65178216",
"0.64717984",
"0.64717984",
"0.64595383",
"0.63534844",
"0.63455355",
"0.6333555",
"0.6323215",
"0.63208455",
"0.63208455",
"0.63208455",
"0.6... | 0.81713206 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.