index int64 | statement_id int64 | statement string | lineno int64 | end_lineno int64 | comprehension_types list | metadata dict |
|---|---|---|---|---|---|---|
456 | 2 | self.file.write(','.join([str(t) for t in log]) + '\n') | 108 | 108 | [
"ListComp"
] | {
"hexsha": "f7012caea091390e3c93212966f0b19844281957",
"max_stars_repo_name": "Tato14/fastai2",
"max_stars_repo_path": "fastai2/callback/progress.py",
"lang": "Python"
} |
462 | 0 | refs = set([r.strip() for r in refnames.strip("()").split(",")]) | 180 | 180 | [
"ListComp"
] | {
"hexsha": "f701300168d70aab345ae6b11215023d9be8143b",
"max_stars_repo_name": "psyplot/ci-release-test",
"max_stars_repo_path": "release_test/_version.py",
"lang": "Python"
} |
462 | 1 | tags = set([r[len(TAG):] for r in refs if r.startswith(TAG)]) | 184 | 184 | [
"ListComp"
] | {
"hexsha": "f701300168d70aab345ae6b11215023d9be8143b",
"max_stars_repo_name": "psyplot/ci-release-test",
"max_stars_repo_path": "release_test/_version.py",
"lang": "Python"
} |
462 | 2 | tags = set([r for r in refs if re.search(r'\d', r)]) | 193 | 193 | [
"ListComp"
] | {
"hexsha": "f701300168d70aab345ae6b11215023d9be8143b",
"max_stars_repo_name": "psyplot/ci-release-test",
"max_stars_repo_path": "release_test/_version.py",
"lang": "Python"
} |
465 | 0 | if (
exc
and exc.messages
and isinstance(exc.messages, dict)
and all([key is None for key in exc.messages.keys()])
):
exc.messages = list(itertools.chain.from_iterable(exc.messages.values())) | 1,163 | 1,169 | [
"ListComp"
] | {
"hexsha": "f70131b5a4b1638a0ebec960b0e6d3ac3970019e",
"max_stars_repo_name": "annuupadhyayPS/great_expectations",
"max_stars_repo_path": "great_expectations/data_context/types/base.py",
"lang": "Python"
} |
465 | 1 | if data["config_version"] == 0 and any(
[
store_config["class_name"] == "ValidationsStore"
for store_config in data["stores"].values()
]
):
raise ge_exceptions.UnsupportedConfigVersionError(
"You appear to be using a config vers... | 1,194 | 1,202 | [
"ListComp"
] | {
"hexsha": "f70131b5a4b1638a0ebec960b0e6d3ac3970019e",
"max_stars_repo_name": "annuupadhyayPS/great_expectations",
"max_stars_repo_path": "great_expectations/data_context/types/base.py",
"lang": "Python"
} |
465 | 2 | if data["config_version"] < CURRENT_GE_CONFIG_VERSION and (
"checkpoint_store_name" in data
or any(
[
store_config["class_name"] == "CheckpointStore"
for store_config in data["stores"].values()
]
)
):
... | 1,220 | 1,238 | [
"ListComp"
] | {
"hexsha": "f70131b5a4b1638a0ebec960b0e6d3ac3970019e",
"max_stars_repo_name": "annuupadhyayPS/great_expectations",
"max_stars_repo_path": "great_expectations/data_context/types/base.py",
"lang": "Python"
} |
465 | 3 | base_action_list_dict = {action["name"]: action for action in base_action_list} | 2,233 | 2,233 | [
"DictComp"
] | {
"hexsha": "f70131b5a4b1638a0ebec960b0e6d3ac3970019e",
"max_stars_repo_name": "annuupadhyayPS/great_expectations",
"max_stars_repo_path": "great_expectations/data_context/types/base.py",
"lang": "Python"
} |
469 | 0 | fscps = [io.open(scp, "r", encoding="utf-8") for scp in args.scp] | 34 | 34 | [
"ListComp"
] | {
"hexsha": "f701331f418b271808b257dda1cf537ba3ca9082",
"max_stars_repo_name": "texpomru13/espnet",
"max_stars_repo_path": "utils/mix-mono-wav-scp.py",
"lang": "Python"
} |
469 | 1 | if not all(k == keys[0] for k in keys):
raise RuntimeError(
"The ids mismatch. Hint; the input files must be "
"sorted and must have same ids: {}".format(keys)
) | 54 | 58 | [
"GeneratorExp"
] | {
"hexsha": "f701331f418b271808b257dda1cf537ba3ca9082",
"max_stars_repo_name": "texpomru13/espnet",
"max_stars_repo_path": "utils/mix-mono-wav-scp.py",
"lang": "Python"
} |
469 | 2 | args.out.write(
"{} sox -M {} -c {} -t wav - |\n".format(
keys[0], " ".join("{}".format(w) for w in wavs), len(fscps)
)
) | 60 | 64 | [
"GeneratorExp"
] | {
"hexsha": "f701331f418b271808b257dda1cf537ba3ca9082",
"max_stars_repo_name": "texpomru13/espnet",
"max_stars_repo_path": "utils/mix-mono-wav-scp.py",
"lang": "Python"
} |
472 | 0 | word = [e for e in self.db.entries.values()
if a in e.searchaffixes] | 71 | 72 | [
"ListComp"
] | {
"hexsha": "f7013540106d82345f673369326f21c8329a90c1",
"max_stars_repo_name": "lojban/vlasisku",
"max_stars_repo_path": "vlasisku/models.py",
"lang": "Python"
} |
480 | 0 | chars = [random.choice(ascii_letters + digits) for _ in range(15)] | 429 | 429 | [
"ListComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
480 | 1 | settings['FEEDS'] = {
urljoin('file:', pathname2url(str(file_path))): feed
for file_path, feed in FEEDS.items()
} | 438 | 441 | [
"DictComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
480 | 2 | parsed = [json.loads(to_unicode(line)) for line in data['jl'].splitlines()] | 523 | 523 | [
"ListComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
480 | 3 | rows = [{k: v for k, v in row.items() if v} for row in rows] | 524 | 524 | [
"DictComp",
"ListComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
480 | 4 | rows = [{k: v for k, v in row.items() if v} for row in rows] | 536 | 536 | [
"DictComp",
"ListComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
480 | 5 | got_rows = [{e.tag: e.text for e in it} for it in root.findall('item')] | 538 | 538 | [
"DictComp",
"ListComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
480 | 6 | rows = [{k: v for k, v in row.items() if v} for row in rows] | 551 | 551 | [
"DictComp",
"ListComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
480 | 7 | xml_rows = [{e.tag: e.text for e in it} for it in root.findall('item')] | 554 | 554 | [
"DictComp",
"ListComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
480 | 8 | expected = [{k: v for k, v in row.items() if v} for row in rows] | 581 | 581 | [
"DictComp",
"ListComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
480 | 9 | expected = [{k: v for k, v in row.items() if v} for row in rows] | 595 | 595 | [
"DictComp",
"ListComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
480 | 10 | rows_jl = [dict(row) for row in items] | 696 | 696 | [
"ListComp"
] | {
"hexsha": "f7013bc44a2ffbfdf74f6e376e79f89f9dcbc2c0",
"max_stars_repo_name": "KevvKo/scrapy",
"max_stars_repo_path": "tests/test_feedexport.py",
"lang": "Python"
} |
485 | 0 | def recipe(request):
return os.path.join(metadata_dir, request.param) | 80 | 81 | [
"ListComp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
485 | 1 | contents = [p.strip().decode('utf-8') for p in
has_prefix.readlines()] | 703 | 704 | [
"ListComp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
485 | 2 | matches = [entry for entry in contents if entry.endswith('binary-has-prefix') or
entry.endswith('"binary-has-prefix"')] | 706 | 707 | [
"ListComp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
485 | 3 | contents = [p.strip().decode('utf-8') for p in
has_prefix.readlines()] | 719 | 720 | [
"ListComp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
485 | 4 | matches = [entry for entry in contents if entry.endswith('binary-has-prefix') or
entry.endswith('"binary-has-prefix"')] | 722 | 723 | [
"ListComp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
485 | 5 | output = [os.path.join(os.getcwd(), path, 'meta.yaml') for path in files] | 789 | 789 | [
"ListComp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
485 | 6 | assert any('strong_pinned_package 1.0' in req for req in m.meta['requirements']['host']) | 912 | 912 | [
"GeneratorExp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
485 | 7 | assert any(re.match(r'run_exports_subpkg 1.0 h[a-f0-9]{%s}_0' % testing_config.hash_length,
req)
for (m, _, _) in ms for req in m.meta['requirements']['run']) | 934 | 936 | [
"GeneratorExp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
485 | 8 | assert not any_locks, "remaining locks:\n{}".format('\n'.join('->'.join((l, r))
for (l, r) in locks_list)) | 1,017 | 1,018 | [
"GeneratorExp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
485 | 9 | files = [filename for _, _, filenames in os.walk(git_cache_directory)
for filename in filenames] | 1,141 | 1,142 | [
"ListComp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
485 | 10 | assert not any(re.search('python\s+[23]\.', dep) for dep in m.meta['requirements']['run']) | 1,174 | 1,174 | [
"GeneratorExp"
] | {
"hexsha": "f7013ee950543f8a9cca0d5c76ee787cb943881b",
"max_stars_repo_name": "eklitzke/conda-build",
"max_stars_repo_path": "tests/test_api_build.py",
"lang": "Python"
} |
487 | 0 | until_time = [int(s.strip()) for s in
values['Time_{}'.format(i + 1)].split(":") if
s.strip().isdigit()] | 192 | 194 | [
"ListComp"
] | {
"hexsha": "f7013f89ddf7249cb8c21753c974a4e817c0eaa2",
"max_stars_repo_name": "brunomarct/archetypal",
"max_stars_repo_path": "archetypal/schedule.py",
"lang": "Python"
} |
487 | 1 | if any([spe in field.lower() for spe in field_sets]):
f_set, hour, minute, value = self.field_interpreter(field)
if f_set.lower() == 'through':
# main condition. All sub-conditions must obey a
# `Through` condition
# First, in... | 390 | 502 | [
"ListComp"
] | {
"hexsha": "f7013f89ddf7249cb8c21753c974a4e817c0eaa2",
"max_stars_repo_name": "brunomarct/archetypal",
"max_stars_repo_path": "archetypal/schedule.py",
"lang": "Python"
} |
487 | 2 | ep_day = self.idf.add_object(
ep_object='Schedule:Day:Hourly'.upper(),
save=False,
**dict(Name=name,
Schedule_Type_Limits_Name=self.schType,
**{'Hour_{}'.format(i + 1): unique_day[i]
for i in range(24... | 743 | 750 | [
"DictComp"
] | {
"hexsha": "f7013f89ddf7249cb8c21753c974a4e817c0eaa2",
"max_stars_repo_name": "brunomarct/archetypal",
"max_stars_repo_path": "archetypal/schedule.py",
"lang": "Python"
} |
487 | 3 | ep_week = self.idf.add_object(
ep_object='Schedule:Week:Daily'.upper(),
save=False,
**dict(Name=week_id,
**{'{}_ScheduleDay_Name'.format(
weekday): dict_week[week_id][
'day_{}'.format(i)] for
... | 786 | 806 | [
"DictComp"
] | {
"hexsha": "f7013f89ddf7249cb8c21753c974a4e817c0eaa2",
"max_stars_repo_name": "brunomarct/archetypal",
"max_stars_repo_path": "archetypal/schedule.py",
"lang": "Python"
} |
487 | 4 | bincount = [sum(1 for _ in group)
for key, group in itertools.groupby(nws + 1) if key] | 812 | 813 | [
"GeneratorExp",
"ListComp"
] | {
"hexsha": "f7013f89ddf7249cb8c21753c974a4e817c0eaa2",
"max_stars_repo_name": "brunomarct/archetypal",
"max_stars_repo_path": "archetypal/schedule.py",
"lang": "Python"
} |
487 | 5 | week_order = {i: v for i, v in enumerate(np.array(
[key for key, group in itertools.groupby(nws + 1) if key]) - 1)} | 814 | 815 | [
"DictComp",
"ListComp"
] | {
"hexsha": "f7013f89ddf7249cb8c21753c974a4e817c0eaa2",
"max_stars_repo_name": "brunomarct/archetypal",
"max_stars_repo_path": "archetypal/schedule.py",
"lang": "Python"
} |
487 | 6 | date = [day for week in monthcal for day in week if \
day.weekday() == dayofweek and \
day.month == month][nth] | 926 | 928 | [
"ListComp"
] | {
"hexsha": "f7013f89ddf7249cb8c21753c974a4e817c0eaa2",
"max_stars_repo_name": "brunomarct/archetypal",
"max_stars_repo_path": "archetypal/schedule.py",
"lang": "Python"
} |
487 | 7 | dd = [dd for dd in dds if dd.Special_Day_Type.lower() == field
or dd.Special_Day_Type.lower() in special_day_types] | 1,060 | 1,061 | [
"ListComp"
] | {
"hexsha": "f7013f89ddf7249cb8c21753c974a4e817c0eaa2",
"max_stars_repo_name": "brunomarct/archetypal",
"max_stars_repo_path": "archetypal/schedule.py",
"lang": "Python"
} |
487 | 8 | dd = [dd for dd in dds if dd.Day_Type.lower() == field] | 1,090 | 1,090 | [
"ListComp"
] | {
"hexsha": "f7013f89ddf7249cb8c21753c974a4e817c0eaa2",
"max_stars_repo_name": "brunomarct/archetypal",
"max_stars_repo_path": "archetypal/schedule.py",
"lang": "Python"
} |
487 | 9 | date = '/'.join([str(item).zfill(2) for item in data]) | 1,095 | 1,095 | [
"ListComp"
] | {
"hexsha": "f7013f89ddf7249cb8c21753c974a4e817c0eaa2",
"max_stars_repo_name": "brunomarct/archetypal",
"max_stars_repo_path": "archetypal/schedule.py",
"lang": "Python"
} |
491 | 0 | full_cmd = " ".join(f"{k}={v}"
for k, v in env_vars.items()) + " " + cmd_to_run | 898 | 899 | [
"GeneratorExp"
] | {
"hexsha": "f701420d7e91f4bcbdb6b47908438c20bcf682cc",
"max_stars_repo_name": "behnamh217rn21/ray-master",
"max_stars_repo_path": "release/e2e.py",
"lang": "Python"
} |
492 | 0 | results_without_duplicates = [key for (key, ignored) in results.items()] | 25 | 25 | [
"ListComp"
] | {
"hexsha": "f70143280a7d3e0800ab0318774e9f82ec6c1c84",
"max_stars_repo_name": "DReichLab/adna-workflow",
"max_stars_repo_path": "read_groups_from_bam.py",
"lang": "Python"
} |
496 | 0 | return [cls.from_json(j) for j in l] | 205 | 205 | [
"ListComp"
] | {
"hexsha": "f701454a3029889fb15ae188e49b88eafbc88eec",
"max_stars_repo_name": "efritz/localstack",
"max_stars_repo_path": "localstack/utils/common.py",
"lang": "Python"
} |
496 | 1 | return ''.join([obj_to_xml(o) for o in obj]) | 499 | 499 | [
"ListComp"
] | {
"hexsha": "f701454a3029889fb15ae188e49b88eafbc88eec",
"max_stars_repo_name": "efritz/localstack",
"max_stars_repo_path": "localstack/utils/common.py",
"lang": "Python"
} |
496 | 2 | return ''.join(['<{k}>{v}</{k}>'.format(k=k, v=obj_to_xml(v)) for (k, v) in obj.items()]) | 501 | 501 | [
"ListComp"
] | {
"hexsha": "f701454a3029889fb15ae188e49b88eafbc88eec",
"max_stars_repo_name": "efritz/localstack",
"max_stars_repo_path": "localstack/utils/common.py",
"lang": "Python"
} |
496 | 3 | jar_entries = [e for e in zf.infolist() if e.filename.lower().endswith('.jar')] | 840 | 840 | [
"ListComp"
] | {
"hexsha": "f701454a3029889fb15ae188e49b88eafbc88eec",
"max_stars_repo_name": "efritz/localstack",
"max_stars_repo_path": "localstack/utils/common.py",
"lang": "Python"
} |
496 | 4 | matching_prefix = [e for e in jar_entries if
not jar_path_prefix or e.filename.lower().startswith(jar_path_prefix)] | 843 | 844 | [
"ListComp"
] | {
"hexsha": "f701454a3029889fb15ae188e49b88eafbc88eec",
"max_stars_repo_name": "efritz/localstack",
"max_stars_repo_path": "localstack/utils/common.py",
"lang": "Python"
} |
496 | 5 | class_files = [e for e in zf.infolist() if e.filename.endswith('.class')] | 858 | 858 | [
"ListComp"
] | {
"hexsha": "f701454a3029889fb15ae188e49b88eafbc88eec",
"max_stars_repo_name": "efritz/localstack",
"max_stars_repo_path": "localstack/utils/common.py",
"lang": "Python"
} |
496 | 6 | manifest_file = [e for e in zf.infolist() if e.filename.upper() == 'META-INF/MANIFEST.MF'] | 859 | 859 | [
"ListComp"
] | {
"hexsha": "f701454a3029889fb15ae188e49b88eafbc88eec",
"max_stars_repo_name": "efritz/localstack",
"max_stars_repo_path": "localstack/utils/common.py",
"lang": "Python"
} |
496 | 7 | return all([os.path.exists(f) for f in files]) | 884 | 884 | [
"ListComp"
] | {
"hexsha": "f701454a3029889fb15ae188e49b88eafbc88eec",
"max_stars_repo_name": "efritz/localstack",
"max_stars_repo_path": "localstack/utils/common.py",
"lang": "Python"
} |
516 | 0 | requirements = [line.strip() for line in fh] | 29 | 29 | [
"ListComp"
] | {
"hexsha": "f70156a3a2fcf8fcc48c436b8d608cbe337dddd0",
"max_stars_repo_name": "hannes-holey/hans",
"max_stars_repo_path": "setup.py",
"lang": "Python"
} |
517 | 0 | label_to_id = {attribute.find('name').text: idx for idx, attribute in enumerate(label.iter('attribute'))} | 50 | 50 | [
"DictComp"
] | {
"hexsha": "f701581069cfd8be095c0662247dab35763588a4",
"max_stars_repo_name": "APrigarina/open_model_zoo",
"max_stars_repo_path": "tools/accuracy_checker/accuracy_checker/annotation_converters/cvat_multilabel_recognition.py",
"lang": "Python"
} |
517 | 1 | return {'label_map': {value: key for key, value in attribute_values_mapping.items()}} | 83 | 83 | [
"DictComp"
] | {
"hexsha": "f701581069cfd8be095c0662247dab35763588a4",
"max_stars_repo_name": "APrigarina/open_model_zoo",
"max_stars_repo_path": "tools/accuracy_checker/accuracy_checker/annotation_converters/cvat_multilabel_recognition.py",
"lang": "Python"
} |
517 | 2 | label = [label for label in meta.iter('label') if label.find('name').text == self.label] | 86 | 86 | [
"ListComp"
] | {
"hexsha": "f701581069cfd8be095c0662247dab35763588a4",
"max_stars_repo_name": "APrigarina/open_model_zoo",
"max_stars_repo_path": "tools/accuracy_checker/accuracy_checker/annotation_converters/cvat_multilabel_recognition.py",
"lang": "Python"
} |
518 | 0 | return ''.join(
[line.strip() for line in xml_dom.toxml().splitlines()]
) | 316 | 318 | [
"ListComp"
] | {
"hexsha": "f701593506fcf4f739f92e926ff4b2ac42373413",
"max_stars_repo_name": "iilness2/bash-lambda-layer-custom",
"max_stars_repo_path": "bin/awscli/customizations/history/show.py",
"lang": "Python"
} |
519 | 0 | values = [data[k] for k in labels] | 31 | 31 | [
"ListComp"
] | {
"hexsha": "f70159d65a5bfff918de93d5a0e04e7f23f300b0",
"max_stars_repo_name": "HenriqueBuzin/TCC",
"max_stars_repo_path": "Python/venv/lib/python3.7/site-packages/prometheus_client/platform_collector.py",
"lang": "Python"
} |
521 | 0 | groundtruth_boxlists = [
box_list_ops.to_absolute_coordinates(
box_list.BoxList(boxes), true_image_shapes[i, 0],
true_image_shapes[i, 1])
for i, boxes in enumerate(
self.groundtruth_lists(fields.BoxListFields.boxes))
] | 1,551 | 1,557 | [
"ListComp"
] | {
"hexsha": "f7015a05765804fec4cfa4d48e357987ad3578a0",
"max_stars_repo_name": "AXATechLab/models",
"max_stars_repo_path": "research/object_detection/meta_architectures/faster_rcnn_meta_arch_override_RPN.py",
"lang": "Python"
} |
521 | 1 | groundtruth_classes_with_background_list = [
tf.to_float(
tf.pad(one_hot_encoding, [[0, 0], [1, 0]], mode='CONSTANT'))
for one_hot_encoding in self.groundtruth_lists(
fields.BoxListFields.classes)] | 1,558 | 1,562 | [
"ListComp"
] | {
"hexsha": "f7015a05765804fec4cfa4d48e357987ad3578a0",
"max_stars_repo_name": "AXATechLab/models",
"max_stars_repo_path": "research/object_detection/meta_architectures/faster_rcnn_meta_arch_override_RPN.py",
"lang": "Python"
} |
521 | 2 | if any(dim is None for dim in proposals_shape):
proposals_shape = tf.shape(proposals) | 1,663 | 1,664 | [
"GeneratorExp"
] | {
"hexsha": "f7015a05765804fec4cfa4d48e357987ad3578a0",
"max_stars_repo_name": "AXATechLab/models",
"max_stars_repo_path": "research/object_detection/meta_architectures/faster_rcnn_meta_arch_override_RPN.py",
"lang": "Python"
} |
521 | 3 | proposal_boxlists = [
box_list.BoxList(proposal_boxes_single_image)
for proposal_boxes_single_image in tf.unstack(proposal_boxes)] | 2,071 | 2,073 | [
"ListComp"
] | {
"hexsha": "f7015a05765804fec4cfa4d48e357987ad3578a0",
"max_stars_repo_name": "AXATechLab/models",
"max_stars_repo_path": "research/object_detection/meta_architectures/faster_rcnn_meta_arch_override_RPN.py",
"lang": "Python"
} |
521 | 4 | return {var.op.name: var for var in feature_extractor_variables} | 2,337 | 2,337 | [
"DictComp"
] | {
"hexsha": "f7015a05765804fec4cfa4d48e357987ad3578a0",
"max_stars_repo_name": "AXATechLab/models",
"max_stars_repo_path": "research/object_detection/meta_architectures/faster_rcnn_meta_arch_override_RPN.py",
"lang": "Python"
} |
523 | 0 | inputs = [crypto.q - 2 ** 9, crypto.q - 10, 0, 100, 2 ** 200 + 10] + [
common.rand.randrange(0, crypto.q - 2) for _ in range(20)
] | 191 | 193 | [
"ListComp"
] | {
"hexsha": "f7015abd02d2e91af592e552a6b9c0a139f233d9",
"max_stars_repo_name": "ph4r05/monero-agent",
"max_stars_repo_path": "monero_glue_test/test_crypto.py",
"lang": "Python"
} |
523 | 1 | inputs = [crypto.l - 2 ** 9, crypto.l - 10, 0, 100, 2 ** 200 + 10] + [
common.rand.randrange(0, crypto.l - 2) for _ in range(20)
] | 201 | 203 | [
"ListComp"
] | {
"hexsha": "f7015abd02d2e91af592e552a6b9c0a139f233d9",
"max_stars_repo_name": "ph4r05/monero-agent",
"max_stars_repo_path": "monero_glue_test/test_crypto.py",
"lang": "Python"
} |
528 | 0 | image_idx_list = [x.strip() for x in open(split_file).readlines()] | 241 | 241 | [
"ListComp"
] | {
"hexsha": "f7015bc8d1aae686fe1efb7e3d9e149f9f981a3e",
"max_stars_repo_name": "Sakura176/PointRCNN",
"max_stars_repo_path": "tools/train_eval.py",
"lang": "Python"
} |
534 | 0 | a = [reader.int() for _ in range(3 * m)] | 88 | 88 | [
"ListComp"
] | {
"hexsha": "f701614adbe0c289b89493a7ae3140602778980b",
"max_stars_repo_name": "kagemeka/atcoder-submissions",
"max_stars_repo_path": "jp.atcoder/abc012/abc012_4/21865313.py",
"lang": "Python"
} |
538 | 0 | self.assertAllEqual([[0, i] for i in range(6)], out.indices) | 390 | 390 | [
"ListComp"
] | {
"hexsha": "f701647c2b297015f025eb53bd191a1a8c54ec62",
"max_stars_repo_name": "AlexChrisF/udacity",
"max_stars_repo_path": "tensorflow/contrib/layers/python/kernel_tests/sparse_feature_cross_op_test.py",
"lang": "Python"
} |
538 | 1 | self.assertTrue(all(x < 1000 and x >= 0 for x in out.values)) | 391 | 391 | [
"GeneratorExp"
] | {
"hexsha": "f701647c2b297015f025eb53bd191a1a8c54ec62",
"max_stars_repo_name": "AlexChrisF/udacity",
"max_stars_repo_path": "tensorflow/contrib/layers/python/kernel_tests/sparse_feature_cross_op_test.py",
"lang": "Python"
} |
541 | 0 | inlist = np.array([list(map(int, l)) for l in data.split('\n')]) | 49 | 49 | [
"ListComp"
] | {
"hexsha": "f70165831b1a0ae798b12f7c6cfd6eaade682b3b",
"max_stars_repo_name": "vulpicastor/advent-of-code-2021",
"max_stars_repo_path": "src/11.py",
"lang": "Python"
} |
547 | 0 | this_dict = {c.name: c for c in self._linear_feature_columns} | 159 | 159 | [
"DictComp"
] | {
"hexsha": "f7016c5c21cf950aa7d4520f766ef05b3aa9a22c",
"max_stars_repo_name": "calebchoo/modulabs",
"max_stars_repo_path": "tensorflow/contrib/learn/python/learn/estimators/linear.py",
"lang": "Python"
} |
547 | 1 | that_dict = {
c.name: c for c in layers.infer_real_valued_columns(features)
} | 160 | 162 | [
"DictComp"
] | {
"hexsha": "f7016c5c21cf950aa7d4520f766ef05b3aa9a22c",
"max_stars_repo_name": "calebchoo/modulabs",
"max_stars_repo_path": "tensorflow/contrib/learn/python/learn/estimators/linear.py",
"lang": "Python"
} |
547 | 2 | this_dict = {c.name: c for c in self._linear_feature_columns} | 310 | 310 | [
"DictComp"
] | {
"hexsha": "f7016c5c21cf950aa7d4520f766ef05b3aa9a22c",
"max_stars_repo_name": "calebchoo/modulabs",
"max_stars_repo_path": "tensorflow/contrib/learn/python/learn/estimators/linear.py",
"lang": "Python"
} |
547 | 3 | that_dict = {
c.name: c for c in layers.infer_real_valued_columns(features)
} | 311 | 313 | [
"DictComp"
] | {
"hexsha": "f7016c5c21cf950aa7d4520f766ef05b3aa9a22c",
"max_stars_repo_name": "calebchoo/modulabs",
"max_stars_repo_path": "tensorflow/contrib/learn/python/learn/estimators/linear.py",
"lang": "Python"
} |
548 | 0 | if any(not isinstance(i, dict) and not _supported_input_size_type(i) for i in input_sizes):
raise KeyError("An input size must either be a static size or a range of three sizes (min, opt, max) as Dict") | 22 | 23 | [
"GeneratorExp"
] | {
"hexsha": "f7016c7c0c3a67ee7989e59320e22bece5f09791",
"max_stars_repo_name": "peri044/TRTorch",
"max_stars_repo_path": "py/trtorch/_compile_spec.py",
"lang": "Python"
} |
548 | 1 | if all(k in i for k in ["min", "opt", "min"]):
in_range = trtorch._C.InputRange()
in_range.min = i["min"]
in_range.opt = i["opt"]
in_range.max = i["max"]
parsed_input_sizes.append(in_range)
elif "opt" in i:
in_r... | 28 | 44 | [
"GeneratorExp"
] | {
"hexsha": "f7016c7c0c3a67ee7989e59320e22bece5f09791",
"max_stars_repo_name": "peri044/TRTorch",
"max_stars_repo_path": "py/trtorch/_compile_spec.py",
"lang": "Python"
} |
568 | 0 | num_targets = len([x for x in (program, module, code) if x != ()]) | 358 | 358 | [
"ListComp"
] | {
"hexsha": "f701763c784e49214fd9a7e52a90d440b81882b8",
"max_stars_repo_name": "despresj/dotfiles",
"max_stars_repo_path": "vscode/extensions/ms-python.python-2022.4.1/pythonFiles/lib/python/debugpy/adapter/clients.py",
"lang": "Python"
} |
569 | 0 | print(''.join([char + char for char in word])) | 31 | 31 | [
"ListComp"
] | {
"hexsha": "f701767e7eb4bd50bad3cd14a4cce3b563d834a2",
"max_stars_repo_name": "LukeBriggsDev/GCSE-Code-Tasks",
"max_stars_repo_path": "p03.2/double_letters.py",
"lang": "Python"
} |
576 | 0 | DIVISION_RULES = {
k: v.split("/", maxsplit=1)[0] for k, v in mimetypes.types_map.items()
} | 31 | 33 | [
"DictComp"
] | {
"hexsha": "f70179383f15ccce81946c10265dbb68c2fdd06a",
"max_stars_repo_name": "damare01/novelsave",
"max_stars_repo_path": "novelsave/settings.py",
"lang": "Python"
} |
580 | 0 | object_keys = [r['name'] for r in objects] | 261 | 261 | [
"ListComp"
] | {
"hexsha": "f7017af6c3cdf3b84c5e4f104a6d25cb9b08d77a",
"max_stars_repo_name": "Damian-MG/lithops",
"max_stars_repo_path": "lithops/storage/backends/swift/swift.py",
"lang": "Python"
} |
582 | 0 | assert all(look_for in page for look_for in step.look_fors) | 114 | 114 | [
"GeneratorExp"
] | {
"hexsha": "f7017bfdb0cd9b92d160e04e3ef909806fba71cd",
"max_stars_repo_name": "LaudateCorpus1/ansible-navigator",
"max_stars_repo_path": "tests/integration/actions/inventory/base.py",
"lang": "Python"
} |
582 | 1 | assert not any(look_not in page for look_not in step.look_nots) | 117 | 117 | [
"GeneratorExp"
] | {
"hexsha": "f7017bfdb0cd9b92d160e04e3ef909806fba71cd",
"max_stars_repo_name": "LaudateCorpus1/ansible-navigator",
"max_stars_repo_path": "tests/integration/actions/inventory/base.py",
"lang": "Python"
} |
583 | 0 | match = [z for z in balancers if z['name'] == name] | 100 | 100 | [
"ListComp"
] | {
"hexsha": "f7017f4f4ad299560711cdd1fb4c0b007148e3da",
"max_stars_repo_name": "yuriks/salt",
"max_stars_repo_path": "salt/states/libcloud_loadbalancer.py",
"lang": "Python"
} |
583 | 1 | match = [z for z in balancers if z['name'] == name] | 128 | 128 | [
"ListComp"
] | {
"hexsha": "f7017f4f4ad299560711cdd1fb4c0b007148e3da",
"max_stars_repo_name": "yuriks/salt",
"max_stars_repo_path": "salt/states/libcloud_loadbalancer.py",
"lang": "Python"
} |
584 | 0 | return [0 for i in range(size)] | 72 | 72 | [
"ListComp"
] | {
"hexsha": "f7017fa3cd00892a2d9a04db6d620ac61486f985",
"max_stars_repo_name": "ArtFXDev/silex_client",
"max_stars_repo_path": "silex_client/utils/parameter_types.py",
"lang": "Python"
} |
585 | 0 | dp = [[[0] * 2 for _ in range(K + 1)] for _ in range(L + 1)] | 4 | 4 | [
"ListComp"
] | {
"hexsha": "f701801fce4e0791e2126e82c19b415fb5f428d4",
"max_stars_repo_name": "knuu/competitive-programming",
"max_stars_repo_path": "atcoder/abc/abc154_e.py",
"lang": "Python"
} |
601 | 0 | [
bpy.data.objects.remove(obj)
for obj in bpy.data.objects
if obj.type in ("MESH", "LIGHT", "CURVE")
] | 85 | 89 | [
"ListComp"
] | {
"hexsha": "f7018ac86c15a5146e9c8fcde8a6f279fdfb8f77",
"max_stars_repo_name": "Avinash2468/bpycv",
"max_stars_repo_path": "bpycv/scene_setting.py",
"lang": "Python"
} |
602 | 0 | decomm = [tup for tup in site_caps if (tup[2] == period)] | 361 | 361 | [
"ListComp"
] | {
"hexsha": "f7018bb7234e923366e80dfdf0fde1be51c3f094",
"max_stars_repo_name": "zarppy/MUREIL_2014",
"max_stars_repo_path": "generator/txmultigeneratormultisite.py",
"lang": "Python"
} |
602 | 1 | decom_cap = sum([tup[0] for tup in decomm]) | 365 | 365 | [
"ListComp"
] | {
"hexsha": "f7018bb7234e923366e80dfdf0fde1be51c3f094",
"max_stars_repo_name": "zarppy/MUREIL_2014",
"max_stars_repo_path": "generator/txmultigeneratormultisite.py",
"lang": "Python"
} |
602 | 2 | new_list = [tup for tup in site_caps if not (tup[2] == period)] | 379 | 379 | [
"ListComp"
] | {
"hexsha": "f7018bb7234e923366e80dfdf0fde1be51c3f094",
"max_stars_repo_name": "zarppy/MUREIL_2014",
"max_stars_repo_path": "generator/txmultigeneratormultisite.py",
"lang": "Python"
} |
602 | 3 | new_cap_list = [tup[0] for tup in site_data[0] if (tup[1] == period)] | 449 | 449 | [
"ListComp"
] | {
"hexsha": "f7018bb7234e923366e80dfdf0fde1be51c3f094",
"max_stars_repo_name": "zarppy/MUREIL_2014",
"max_stars_repo_path": "generator/txmultigeneratormultisite.py",
"lang": "Python"
} |
602 | 4 | capacity.append(sum([tup[0] for tup in cap_list[site]])) | 478 | 478 | [
"ListComp"
] | {
"hexsha": "f7018bb7234e923366e80dfdf0fde1be51c3f094",
"max_stars_repo_name": "zarppy/MUREIL_2014",
"max_stars_repo_path": "generator/txmultigeneratormultisite.py",
"lang": "Python"
} |
605 | 0 | filenames = [os.path.join(data_dir, 'data_batch_%d.bin' % i)
for i in xrange(1, 6)] | 151 | 152 | [
"ListComp"
] | {
"hexsha": "f7018d7d290f789306ee6408d401f7694b5d77f5",
"max_stars_repo_name": "PepSalehi/algorithms",
"max_stars_repo_path": "ML/tf-cifar-10/cifar10_input.py",
"lang": "Python"
} |
605 | 1 | filenames = [os.path.join(data_dir, 'data_batch_%d.bin' % i)
for i in xrange(1, 6)] | 216 | 217 | [
"ListComp"
] | {
"hexsha": "f7018d7d290f789306ee6408d401f7694b5d77f5",
"max_stars_repo_name": "PepSalehi/algorithms",
"max_stars_repo_path": "ML/tf-cifar-10/cifar10_input.py",
"lang": "Python"
} |
608 | 0 | users = [{'name': name, 'stream': stream} for name, stream in zip(user_names, stream_urls) if stream] | 42 | 42 | [
"ListComp"
] | {
"hexsha": "f7019023ce6c6a82f163a45aaf9b53f99160d360",
"max_stars_repo_name": "schlarpc/oneartplease",
"max_stars_repo_path": "oneartplease.py",
"lang": "Python"
} |
610 | 0 | planid = [_.strip() for _ in planid] | 68 | 68 | [
"ListComp"
] | {
"hexsha": "f701930267eb677de0ff92fb8288386877a8c15a",
"max_stars_repo_name": "hypergravity/bopy",
"max_stars_repo_path": "bopy/spec/lamost.py",
"lang": "Python"
} |
610 | 1 | return np.array(["spec-%05d-%s_sp%02d-%03d%s" %
(mjd[i], planid[i], spid[i], fiberid[i], extname)
for i in range(len(mjd))]) | 78 | 80 | [
"ListComp"
] | {
"hexsha": "f701930267eb677de0ff92fb8288386877a8c15a",
"max_stars_repo_name": "hypergravity/bopy",
"max_stars_repo_path": "bopy/spec/lamost.py",
"lang": "Python"
} |
610 | 2 | return np.array(["%s%s%sspec-%05d-%s_sp%02d-%03d%s" %
(dirpath, planid[i], os.path.sep, mjd[i],
planid[i], spid[i], fiberid[i], extname)
for i in range(len(mjd))]) | 93 | 96 | [
"ListComp"
] | {
"hexsha": "f701930267eb677de0ff92fb8288386877a8c15a",
"max_stars_repo_name": "hypergravity/bopy",
"max_stars_repo_path": "bopy/spec/lamost.py",
"lang": "Python"
} |
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