Optional[pulumi.Input[Sequence[pulumi.Input['StepArgs']]]]:\n return pulumi.get(self, \"steps\")","def logic_program_form(self):\n #TODO\n # determine step variable\n a_set = set()\n step = self.determineStepVariable()\n s = ''\n # assemble head\n s = s + self.assembleHead(a_set, step)\n # body\n s = s + self.assembleBody(a_set, step)\n return s","def fab_steps(module):\n return tuple(getattr(module, func) for func in get_sorted_strnum(dir(module)))","def _build_experiment_mic_embedded_list():\n imaging_path_embeds = DependencyEmbedder.embed_for_type(\n base_path='imaging_paths.path',\n t='imaging_path',\n additional_embeds=['imaging_rounds', 'experiment_type.title'])\n return (Experiment.embedded_list + imaging_path_embeds + [\n # Files linkTo\n 'files.accession', # detect display_title diff\n\n # MicroscopeSettings linkTo\n 'files.microscope_settings.ch00_light_source_center_wl',\n 'files.microscope_settings.ch01_light_source_center_wl',\n 'files.microscope_settings.ch02_light_source_center_wl',\n 'files.microscope_settings.ch03_light_source_center_wl',\n 'files.microscope_settings.ch04_light_source_center_wl',\n 'files.microscope_settings.ch00_lasers_diodes',\n 'files.microscope_settings.ch01_lasers_diodes',\n 'files.microscope_settings.ch02_lasers_diodes',\n 'files.microscope_settings.ch03_lasers_diodes',\n 'files.microscope_settings.ch04_lasers_diodes',\n\n # MicroscopeConfiguration linkTo\n 'microscope_configuration_master.title',\n 'microscope_configuration_master.microscope.Name',\n 'files.microscope_configuration.title',\n 'files.microscope_configuration.microscope.Name',\n\n # Image linkTo\n 'sample_image.title',\n 'sample_image.caption',\n 'sample_image.microscopy_file.accession',\n 'sample_image.microscopy_file.omerolink',\n 'sample_image.attachment.href',\n 'sample_image.attachment.type',\n 'sample_image.attachment.md5sum',\n 'sample_image.attachment.download',\n 'sample_image.attachment.width',\n 'sample_image.attachment.height',\n ]\n )","def test_quick_build1(self):\n pass","def get_installations():\n github_app = get_default_app()\n pprint(github_app.get_installations())","def workbench_scenarios(): \n return [\n (\"TermsXBlock\",\n \"\"\"<terms/>\n \"\"\"),\n (\"Multiple TermsXBlock\",\n \"\"\"<vertical_demo>\n <terms/>\n <terms/>\n <terms/>\n </vertical_demo>\n \"\"\"),\n ]","def getMakes():\n\n #Get category page as Soup\n soup, _ = getPage(\"/s-motorcycles/c18626\")\n\n #Check if page available\n if soup is None:\n #Not available\n print(\"Can't get motorcycle category page\")\n quit()\n\n\n #Find all makes from main category page\n #Find span with text \"Make\"\n span = soup.find(class_=\"srp-filter-group__filter-name\", text=\"Make\")\n #Move up two parents\n a = span.parent.parent\n #Find all filter names\n b = a.find_all(class_=\"srp-list-filter__item-link link link--no-underline\")\n makes = [i['href'] for i in b]\n return makes","def info_build_test(self):\n\n self._export(\"H0\", \"0.1\")\n\n self._export(\"H1a\", \"0.1\", deps=[(\"H0/0.1@lu/st\", \"private\")])\n self._export(\"H1b\", \"0.1\", deps=[\"H0/0.1@lu/st\"])\n self._export(\"H1c\", \"0.1\", deps=[(\"H0/0.1@lu/st\", \"private\")])\n\n self._export(\"H2a\", \"0.1\", deps=[\"H1a/0.1@lu/st\"])\n self._export(\"H2c\", \"0.1\", deps=[\"H1c/0.1@lu/st\"])\n\n self._export(\"H3\", \"0.1\", deps=[\"H2a/0.1@lu/st\",\n \"H2c/0.1@lu/st\"])\n\n # If we install H3 we need to build all except H1b\n self.clients[\"H3\"].run(\"info --build missing\")\n self.assert_last_line(self.clients[\"H3\"],\n \"H0/0.1@lu/st, H1a/0.1@lu/st, H1c/0.1@lu/st, H2a/0.1@lu/st, H2c/0.1@lu/st\")\n\n # If we install H0 we need to build nothing (current project)\n self.clients[\"H0\"].run(\"info --build missing\")\n self.assert_last_line(self.clients[\"H0\"], \"\")\n\n # If we install H0 we need to build H0\n self.clients[\"H1a\"].run(\"info --build missing\")\n self.assert_last_line(self.clients[\"H1a\"], \"H0/0.1@lu/st\")\n\n # If we build and upload H1a and H1c, no more H0 (private) is required\n self.clients[\"H3\"].run(\"install H1a/0.1@lu/st --build \")\n self.clients[\"H3\"].run(\"install H1c/0.1@lu/st --build \")\n self.clients[\"H3\"].run(\"upload H1a/0.1@lu/st --all\")\n self.clients[\"H3\"].run(\"upload H1c/0.1@lu/st --all\")\n\n self.clients[\"H3\"].run(\"remove '*' -f\")\n self.clients[\"H3\"].run(\"info --build missing\")\n self.assert_last_line(self.clients[\"H3\"],\n \"H2a/0.1@lu/st, H2c/0.1@lu/st\")\n\n # But if we force to build all, all nodes have to be built\n self.clients[\"H3\"].run(\"remove '*' -f\")\n self.clients[\"H3\"].run(\"info --build\")\n self.assert_last_line(self.clients[\"H3\"],\n \"H0/0.1@lu/st, H1a/0.1@lu/st, H1c/0.1@lu/st, H2a/0.1@lu/st, H2c/0.1@lu/st\")\n\n # Now upgrade the recipe H1a and upload it (but not the package)\n # so the package become outdated\n conanfile_path = os.path.join(self.clients[\"H1a\"].current_folder, CONANFILE)\n conanfile = load(conanfile_path)\n conanfile += \"\\n# MODIFIED\"\n save(conanfile_path, conanfile)\n self.clients[\"H1a\"].run(\"export lu/st\")\n self.clients[\"H1a\"].run(\"upload H1a/0.1@lu/st\") # NOW IS OUTDATED!\n\n # Without build outdated the built packages are the same\n self.clients[\"H3\"].run(\"remove '*' -f\")\n self.clients[\"H3\"].run(\"info --build missing\")\n self.assert_last_line(self.clients[\"H3\"],\n \"H2a/0.1@lu/st, H2c/0.1@lu/st\")\n\n # But with build outdated we have to build the private H0 (but only once) and H1a\n self.clients[\"H3\"].run(\"remove '*' -f\")\n self.clients[\"H3\"].run(\"info --build outdated\")\n self.assert_last_line(self.clients[\"H3\"],\n \"H0/0.1@lu/st, H1a/0.1@lu/st, H2a/0.1@lu/st, H2c/0.1@lu/st\")","def prep_steps(self, *, yearmon: str) -> List[Step]:\n steps = []\n\n year, month = dates.parse_yearmon(yearmon)\n\n monthly_vars = ['2m_temperature', 'total_precipitation']\n hourly_vars = ['total_precipitation']\n\n steps += era5.download(output_filename=era5.filename(self.source, 'month', yearmon),\n duration='month',\n yearmon=yearmon,\n variables=monthly_vars)\n\n if year >= 1979:\n steps += era5.download(output_filename=era5.filename(self.source, 'hour', yearmon),\n duration='hour',\n yearmon=yearmon,\n variables=hourly_vars)\n steps += era5.calc_wetdays(input_filename=era5.filename(self.source, 'hour', yearmon),\n output_filename=self.p_wetdays(yearmon=yearmon).file,\n threshold_mm=0.1)\n\n return steps","def generate_launch_description():\n composed = ComposableNodeContainer(\n name='ComponentManager',\n namespace='',\n package='rclcpp_components',\n executable='component_container',\n composable_node_descriptions=[\n ComposableNode(\n package='composition',\n plugin='composition::Talker',\n name='comp_talker'),\n ComposableNode(\n package='composition',\n plugin='composition::Listener',\n name='comp_listener')\n ],\n output='both',\n )\n\n jsp = Node(\n package='joint_state_publisher',\n executable='joint_state_publisher',\n output='both',\n )\n\n lc_talker = LifecycleNode(\n name='lc_talker',\n namespace='',\n package='lifecycle',\n executable='lifecycle_talker',\n output='both',\n )\n\n listener = Node(\n package='demo_nodes_cpp',\n executable='listener',\n output='both',\n )\n\n talker = Node(\n package='demo_nodes_cpp',\n executable='listener',\n output='both',\n )\n\n turtle = Node(\n package='turtlesim',\n executable='turtlesim_node',\n output='both',\n )\n\n return launch.LaunchDescription([\n composed,\n jsp,\n lc_talker,\n listener,\n talker,\n turtle,\n ])","def test_quick_build(self):\n pass","def test_build_pipeline_nine(self):\n args = \"Test_APP TASK\".split(\" \")\n task_list = build_pipeline(args, False)\n self.assertEqual(1, len(task_list))","def test_get_scenarios(self):\n pass","def test_makeliststep_call_from_within_pipeline():\n config_file = t_path(\n Path('steps') / 'makelist_pipeline.cfg'\n )\n results = MakeListPipeline.call(config_file=config_file)\n assert results == [43.0, 'My hovercraft is full of eels.', False]","def workbench_scenarios():\n return [\n (\"simstudentXBlock\",\n \"\"\"<vertical_demo>\n <simstudent/>\n </vertical_demo>\n \"\"\"),\n ]","def process_steps(steplist, build, buildslave, build_status, basedir):\n for step in steplist:\n step.setBuild(build)\n step.setBuildSlave(buildslave)\n step.setStepStatus(build_status.addStepWithName(step.name))\n step.setDefaultWorkdir(os.path.join(basedir, 'build'))\n step.workdir = os.path.join(basedir, 'build')","def test_build_pipeline_seven(self):\n args = \"Test_APP SIX A B C\".split(\" \")\n task_list = build_pipeline(args, False)\n self.assertEqual(1, len(task_list))","def stepStarted(build, step):","def get_buildall_target(self):\n raise NotImplementedError","def get_sim_exe_out_arg(self):\n dirname = os.path.dirname(self.sim_exe)\n if dirname and not os.path.exists(dirname):\n os.makedirs(dirname)\n return ['-o', self.sim_exe]","def build_msms():\r\n\r\n # Prepare include file with dynamic data\r\n f = open(os.path.join(GME_ROOT, \"Install\", \"GME_dyn.wxi\"), 'w')\r\n print >> f, \"<!-- DO NOT EDIT THIS FILE. WILL BE REGENERATED BY THE BUILD SCRIPTS -->\"\r\n print >> f, \"<Include>\"\r\n print >> f, \" <?define GUIDSTRMETAGME='%s' ?>\" % (tools.query_GUID(mta_for_xmp(METAGME_XMP)))\r\n print >> f, \" <?define GUIDSTRHFSM='%s' ?>\" % (tools.query_GUID(mta_for_xmp(HFSM_XMP)))\r\n print >> f, \" <?define GUIDSTRSF='%s' ?>\" % (tools.query_GUID(mta_for_xmp(SF_XMP)))\r\n print >> f, \" <?define GUIDSTRUML='%s' ?>\" % (tools.query_GUID(mta_for_xmp(UML_XMP)))\r\n print >> f, \"</Include>\"\r\n f.close()\r\n\r\n import glob\r\n sources = [f for f in glob.glob(os.path.join(GME_ROOT, \"Install\", \"*.wxs\")) if os.path.basename(f) not in ('GME.wxs', 'GME_bundle.wxs')]\r\n if prefs['arch'] == 'x64':\r\n sources.remove(os.path.join(GME_ROOT, \"Install\", \"GME_paradigms.wxs\"))\r\n for file_ in sources:\r\n extras = []\r\n if os.path.basename(file_) == 'GME_paradigms.wxs':\r\n extras = glob.glob(os.path.join(GME_ROOT, \"Install\", \"PIA*/*.wxi\"))\r\n tools.build_WiX([file_] + extras)","def _build_experiment_seq_embedded_list():\n antibody_embeds = DependencyEmbedder.embed_defaults_for_type(\n base_path='antibody',\n t='antibody')\n return (\n Experiment.embedded_list + antibody_embeds\n )","def _build_main_menu(self):\n if self._args.execution_environment:\n columns = [\"__name\", \"__version\", \"__shadowed\", \"__type\", \"path\"]\n else:\n columns = [\"__name\", \"__version\", \"__shadowed\", \"path\"]\n\n return Step(\n name=\"all_collections\",\n columns=columns,\n select_func=self._build_plugin_menu,\n tipe=\"menu\",\n value=self._collections,\n )","def workbench_scenarios():\n return [\n (\"UcCodemirrorXBlock\",\n \"\"\"<vertical_demo>\n <uc_codemirror/>\n <uc_codemirror/>\n <uc_codemirror/>\n </vertical_demo>\n \"\"\"),\n ]","def get_args(phase):\r\n parser = argparse.ArgumentParser(description='Configuration')\r\n\r\n # Hardware specifications\r\n parser.add_argument('--seed', type=int, default=1, help='random seed')\r\n parser.add_argument(\"--device_id\", type=int, default=0, help=\"device id, default is 0.\")\r\n parser.add_argument('--device_num', type=int, default=1, help='device num, default is 1.')\r\n parser.add_argument('--platform', type=str, default=\"Ascend\", \\\r\n help='run platform, only support Ascend')\r\n parser.add_argument('--save_graphs', type=ast.literal_eval, default=False, \\\r\n help='whether save graphs, default is False.')\r\n parser.add_argument('--dataset', type=str, default=\"large\", choices=(\"large\", \"small\", \"demo\"), \\\r\n help='MIND dataset, support large, small and demo.')\r\n parser.add_argument('--dataset_path', type=str, default=None, help='MIND dataset path.')\r\n\r\n # Model specifications\r\n parser.add_argument('--n_browsed_news', type=int, default=50, help='number of browsed news per user')\r\n parser.add_argument('--n_words_title', type=int, default=16, help='number of words per title')\r\n parser.add_argument('--n_words_abstract', type=int, default=48, help='number of words per abstract')\r\n parser.add_argument('--word_embedding_dim', type=int, default=304, help='dimension of word embedding vector')\r\n parser.add_argument('--category_embedding_dim', type=int, default=112, \\\r\n help='dimension of category embedding vector')\r\n parser.add_argument('--query_vector_dim', type=int, default=208, help='dimension of the query vector in attention')\r\n parser.add_argument('--n_filters', type=int, default=400, help='number of filters in CNN')\r\n parser.add_argument('--window_size', type=int, default=3, help='size of filter in CNN')\r\n parser.add_argument(\"--checkpoint_path\", type=str, default=None, \\\r\n help=\"Pre trained checkpoint path, default is None.\")\r\n parser.add_argument('--batch_size', type=int, default=64, help='size of each batch')\r\n # Training specifications\r\n if phase == \"train\":\r\n parser.add_argument('--epochs', type=int, default=None, help='number of epochs for training')\r\n parser.add_argument('--lr', type=float, default=None, help='learning rate')\r\n parser.add_argument('--beta1', type=float, default=0.9, help='ADAM beta1')\r\n parser.add_argument('--beta2', type=float, default=0.999, help='ADAM beta2')\r\n parser.add_argument('--epsilon', type=float, default=1e-8, help='ADAM epsilon for numerical stability')\r\n parser.add_argument('--neg_sample', type=int, default=4, help='number of negative samples in negative sampling')\r\n parser.add_argument(\"--mixed\", type=ast.literal_eval, default=True, \\\r\n help=\"whether use mixed precision, default is True.\")\r\n parser.add_argument(\"--sink_mode\", type=ast.literal_eval, default=True, \\\r\n help=\"whether use dataset sink, default is True.\")\r\n parser.add_argument('--print_times', type=int, default=None, help='number of print times, default is None')\r\n parser.add_argument(\"--weight_decay\", type=ast.literal_eval, default=True, \\\r\n help=\"whether use weight decay, default is True.\")\r\n parser.add_argument('--save_checkpoint', type=ast.literal_eval, default=True, \\\r\n help='whether save checkpoint, default is True.')\r\n parser.add_argument(\"--save_checkpoint_path\", type=str, default=\"./checkpoint\", \\\r\n help=\"Save checkpoint path, default is checkpoint.\")\r\n parser.add_argument('--dropout_ratio', type=float, default=0.2, help='ratio of dropout')\r\n if phase == \"eval\":\r\n parser.add_argument('--neg_sample', type=int, default=-1, \\\r\n help='number of negative samples in negative sampling')\r\n if phase == \"export\":\r\n parser.add_argument('--file_format', type=str, choices=[\"AIR\", \"ONNX\", \"MINDIR\"], default='AIR', \\\r\n help='file format')\r\n parser.add_argument('--neg_sample', type=int, default=-1, \\\r\n help='number of negative samples in negative sampling')\r\n args = parser.parse_args()\r\n if args.device_num > 1:\r\n context.set_context(mode=context.GRAPH_MODE, device_target=args.platform, save_graphs=args.save_graphs)\r\n context.reset_auto_parallel_context()\r\n context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL, gradients_mean=True,\r\n device_num=args.device_num)\r\n init()\r\n args.rank = get_rank()\r\n args.save_checkpoint_path = os.path.join(args.save_checkpoint_path, \"ckpt_\" + str(args.rank))\r\n else:\r\n context.set_context(mode=context.GRAPH_MODE, device_target=args.platform, device_id=args.device_id,\r\n save_graphs=args.save_graphs, save_graphs_path=\"naml_ir\")\r\n args.rank = 0\r\n args.device_num = 1\r\n args.phase = phase\r\n cfg = get_dataset_config(args.dataset)\r\n args.n_categories = cfg.n_categories\r\n args.n_sub_categories = cfg.n_sub_categories\r\n args.n_words = cfg.n_words\r\n if phase == \"train\":\r\n args.epochs = cfg.epochs if args.epochs is None else args.epochs * math.ceil(args.device_num ** 0.5)\r\n args.lr = cfg.lr if args.lr is None else args.lr\r\n args.print_times = cfg.print_times if args.print_times is None else args.print_times\r\n args.embedding_file = cfg.embedding_file.format(args.dataset_path)\r\n args.word_dict_path = cfg.word_dict_path.format(args.dataset_path)\r\n args.category_dict_path = cfg.category_dict_path.format(args.dataset_path)\r\n args.subcategory_dict_path = cfg.subcategory_dict_path.format(args.dataset_path)\r\n args.uid2index_path = cfg.uid2index_path.format(args.dataset_path)\r\n args.train_dataset_path = cfg.train_dataset_path.format(args.dataset_path)\r\n args.eval_dataset_path = cfg.eval_dataset_path.format(args.dataset_path)\r\n args_dict = vars(args)\r\n for key in args_dict.keys():\r\n print('--> {}:{}'.format(key, args_dict[key]), flush=True)\r\n return args","def ExpectedEnginesToBuild(self, run_params):\n return [\"TRTEngineOp_000\"]","def build(parameters):\n\n\n print(\"In Build module\")","def required_tool_results():\n return [MethylResultModule]","def list_programs():\n return list(INFO)"],"string":"[\n \"def prepare_mobilespec_steps(self):\\n platform = self.platform\\n # required by coho tools to correctly resolve repo location\\n if platform == \\\"blackberry10\\\":\\n platform = \\\"blackberry\\\"\\n return [\\n NPMInstall(workdir='build/cordova-mobile-spec/createmobilespec', haltOnFailure=True, description='Install createmobilespec'),\\n ShellCommand(command=[\\\"cordova-coho/coho\\\", \\\"npm-link\\\"], workdir='build', haltOnFailure=True, description='COHO npm-link'),\\n # add --skiplink for createmobilespec since\\n # it requires cordova-plugman repo to be cloned\\n # Re-directing node output to a file is a workaround for a node.js bug\\n # on windows where a piped stream does not get flushed when process.exit is called.\\n # https://github.com/joyent/node/issues/3584\\n ShellCommand(command=\\\"node cordova-mobile-spec/createmobilespec/createmobilespec.js --\\\" + platform + \\\" mobilespec --debug --skiplink >createmobilespecOut.txt 2>&1\\\",\\n workdir='build', haltOnFailure=True, description='Run createmobilespec', logfiles = {\\\"log\\\" : \\\"createmobilespecOut.txt\\\"}),\\n ShellCommand(command=[\\\"node\\\", \\\"medic/updateconfig.js\\\", \\\"--\\\" + self.platform], workdir='build', haltOnFailure=True, description='Update config')\\n ]\",\n \"def deploy_steps(self):\\n return [ShellCommand(command=[\\\"node\\\", \\\"medic/build_\\\" + self.platform + \\\".js\\\"], workdir='build', timeout=CONFIG.build_timeout, description='Run tests', name='Run tests')]\",\n \"def init_workspace_steps(self):\\n return [\\n InstallShellJS(),\\n RMCommand(path=\\\"~/.cordova/\\\" + self.platform, workdir='build', haltOnFailure=False, description='Remove cache'),\\n RMCommand(path=\\\"*\\\", workdir='build', haltOnFailure=False, description='Clean workdir'),\\n ShellCommand(command=[\\\"git\\\", \\\"clone\\\", \\\"--depth\\\", \\\"1\\\", \\\"-b\\\", CONFIG.branches['TESTMASTER'], CONFIG.repos['TESTMASTER'], \\\"medic\\\"], workdir='build', haltOnFailure=True, description='Get Medic'),\\n # --production switch is used to speed up installation + fruitstrap dev dependency is not supported on Windows\\n NPMInstall([\\\"--production\\\"], workdir='build/medic', haltOnFailure=True, description='Install Medic'),\\n FileDownload(mastersrc=FP+\\\"cordova-config.json\\\", slavedest=\\\"medic/config.json\\\", haltOnFailure=True),\\n FileDownload(mastersrc=FP+\\\"cordova-repos.json\\\", slavedest=\\\"medic/repos.json\\\", haltOnFailure=True),\\n ShellCommand(command=[\\\"git\\\", \\\"clone\\\", \\\"--depth\\\", \\\"1\\\", CONFIG.repos['COHO']], workdir='build', haltOnFailure=True, description='Get COHO'),\\n NPMInstall([\\\"--production\\\"], workdir='build/cordova-coho', haltOnFailure=True, description='Install COHO'),\\n ]\",\n \"def get_all_steps(self):\\n steps = []\\n steps.extend(self.init_workspace_steps())\\n steps.extend(self.repos_clone_steps())\\n steps.extend(self.cli_steps())\\n steps.extend(self.prepare_mobilespec_steps())\\n steps.extend(self.deploy_steps())\\n return steps\",\n \"def getSteps():\",\n \"def plugman_steps(self):\\n return [\\n ShellCommand(command=[\\\"rm\\\", \\\"-rf\\\", \\\"cordova-*\\\"], workdir='build', haltOnFailure=False, description='Cordova Clean'),\\n ShellCommand(command=[\\\"git\\\", \\\"clone\\\", CONFIG.repos['PLUGMAN'], \\\"cordova-plugman\\\"], workdir='build', haltOnFailure=True, description='Get Plugman'),\\n NPMInstall(workdir='build/cordova-plugman', haltOnFailure=True, description='Install Plugman'),\\n ShellCommand(command=[\\\"npm\\\", \\\"test\\\"], workdir='build/cordova-plugman', haltOnFailure=True, description='Test Plugman'),\\n ]\",\n \"def steps(self):\\n\\n if not os.path.exists(self.build_path):\\n raise exceptions.ProjectNotBuildError()\\n\\n steps = []\\n for filename in os.listdir(self.build_path):\\n match = re.match(r'(\\\\d{4})_(.*)\\\\.json', filename)\\n if not match:\\n continue\\n\\n with open(os.path.join(self.build_path, filename), 'r') as f:\\n template = json.loads(f.read())\\n\\n template_type = 'custom' if '_type' in template else 'cloudformation'\\n steps.append((int(match.groups()[0]), match.groups()[1], filename, template_type))\\n steps = sorted(steps, key=lambda x: x[0])\\n\\n return steps\",\n \"def cli_steps(self):\\n return [\\n ShellCommand(command=[\\\"git\\\", \\\"clone\\\", \\\"-b\\\", CONFIG.branches['CLI'], CONFIG.repos['CLI'], \\\"cordova-cli\\\"], workdir='build', haltOnFailure=True, description='Clone CLI'),\\n ShellCommand(command=[\\\"git\\\", \\\"clone\\\", \\\"--depth\\\", \\\"1\\\", \\\"-b\\\", CONFIG.branches['CORDOVA-LIB'], CONFIG.repos['CORDOVA-LIB'], \\\"cordova-lib\\\"], workdir='build', haltOnFailure=True, description='Clone cordova-lib'),\\n NPMInstall([\\\"--production\\\"], workdir='build/cordova-lib/cordova-lib', haltOnFailure=True, description='Install cordova-lib'),\\n ShellCommand(command=[\\\"rm\\\", \\\"-f\\\", \\\"npm-shrinkwrap.json\\\"], workdir='build/cordova-cli', haltOnFailure=False, description='Remove CLI SW'),\\n NPMInstall(workdir='build/cordova-cli', haltOnFailure=True, description='Install CLI'),\\n ShellCommand(command=[\\\"npm\\\", \\\"test\\\"], workdir='build/cordova-cli', haltOnFailure=True, description='Test CLI'),\\n NPMInstall(workdir='build/cordova-js', haltOnFailure=True, description='Install JS'),\\n ]\",\n \"def _get_install_steps(self):\\n\\n content = self._get_yaml_content()\\n\\n return self._fix_install_steps(content['install'])\",\n \"def getBuilds():\",\n \"def build_step(self):\\n\\n pass\",\n \"def getBuild():\",\n \"def build_step(self):\\n pass\",\n \"def build_step(self):\\n pass\",\n \"def get_commands(steplist):\\n commands = []\\n for step in steplist:\\n if hasattr(step, 'command'):\\n cmdhash = {}\\n renderables = []\\n accumulateClassList(step.__class__, 'renderables', renderables)\\n\\n for renderable in renderables:\\n setattr(step, renderable, step.build.render(getattr(step,\\n renderable)))\\n\\n cmdhash['name'] = step.name\\n cmdhash['command'] = step.command\\n cmdhash['workdir'] = step.workdir\\n if hasattr(step, 'env'):\\n cmdhash['env'] = step.env\\n else:\\n cmdhash['env'] = {}\\n if hasattr(step, 'timeout'):\\n print \\\"yay!~\\\"\\n cmdhash['timeout'] = step.timeout\\n\\n cmdhash['description'] = step.description\\n cmdhash['descriptionDone'] = step.descriptionDone\\n commands.append(cmdhash)\\n return commands\",\n \"def getSteps( self ):\\n\\n return self.adb.get( 'steps' )\",\n \"def availableSteps( self ):\\n assert isinstance( self._level, int )\\n assert isinstance( self._steps, list )\\n assert isinstance( self._outter, Env ) or ( self._outter is None )\\n\\n lst = [ ]\\n self._availableSteps( lst )\\n return lst\",\n \"def repos_clone_steps(self):\\n platform = self.platform\\n # required by coho tools to correctly resolve repo location\\n if platform == \\\"blackberry10\\\":\\n platform = \\\"blackberry\\\"\\n return [\\n ShellCommand(command=[\\\"node\\\", \\\"medic/checkout.js\\\", \\\"--path=medic/repos.json\\\", \\\"--cat=CORDOVA-MSPEC\\\", \\\"--releasebranch=\\\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone Mobilespec'),\\n ShellCommand(command=[\\\"node\\\", \\\"medic/checkout.js\\\", \\\"--path=medic/repos.json\\\", \\\"--cat=CORDOVA-PLUGIN\\\", \\\"--releasebranch=\\\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone Plugins'),\\n ShellCommand(command=[\\\"node\\\", \\\"medic/checkout.js\\\", \\\"--path=medic/repos.json\\\", \\\"--cat=CORDOVA-\\\" + platform, \\\"--releasebranch=\\\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone Platform'),\\n ShellCommand(command=[\\\"node\\\", \\\"medic/checkout.js\\\", \\\"--path=medic/repos.json\\\", \\\"--cat=CORDOVA-JS\\\", \\\"--releasebranch=\\\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone JS'),\\n ]\",\n \"def get_pipeline_steps(config):\\n steps = []\\n partial_execution = config.getboolean('General','partial_execution')\\n if partial_execution:\\n start_step = config.getint('General','start_step')\\n end_step = config.getint('General','end_step')\\n else:\\n start_step = 1\\n end_step = 6\\n # Run batching and relation extraction steps?\\n batching = True if start_step == 1 else False\\n rel_extraction = True if end_step == 6 else False\\n #nel = True if start_step<=4 and end_step>4 else False\\n # Parallel pipeline steps, removed parsing.UnstParser(configmap) from list, \\n parallel_step_list = [pre.Preprocessor(configmap), ner.Ner(configmap),nel.Nel(configmap)]\\n parallel_steps = parallel_step_list[max(0,start_step-2):end_step-1]\\n return parallel_steps, batching, rel_extraction\",\n \"def build_all(self):\\n self.android_build()\\n self.generate_patch_build('')\\n self.generate_specs_build()\\n self.generate_interfaces()\",\n \"def _build_experiment_embedded_list():\\n pass\",\n \"def scenario(self):\\n scenario = []\\n for action in self.application_tree['scenario']:\\n scenario.append(action)\\n return scenario\",\n \"def _get_steps(self):\\n return self.steps\",\n \"def do_steps(self):\\n steps = self.get_step_conf()\\n all_step_config = dict()\\n for k, v in steps.items():\\n tmp_list = list()\\n all_step_config[k] = tmp_list\\n start = v[\\\"Start Value\\\"]\\n end = v[\\\"End Value\\\"]\\n # special handling of edge length\\n if(k == \\\"Edge Length\\\"):\\n start = self.convert_to_tuple(start)\\n end = self.convert_to_tuple(end)\\n tmp_list.append(str(start))\\n while(start != end):\\n start = self.add_edge_length(\\n start, self.convert_to_tuple(v[\\\"Step\\\"]))\\n tmp_list.append(str(start))\\n print start\\n else:\\n tmp_list.append(float(start))\\n while float(start) < float(end):\\n start = float(start) + float(v[\\\"Step\\\"])\\n tmp_list.append(start)\\n return all_step_config\",\n \"def get_clean_steps(self, node, ports):\\n return [{'step': 'create_configuration',\\n 'interface': 'raid',\\n 'priority': 0},\\n {'step': 'delete_configuration',\\n 'interface': 'raid',\\n 'priority': 0},\\n {'step': 'erase_devices',\\n 'interface': 'deploy',\\n 'priority': 0},\\n {'step': 'update_firmware',\\n 'interface': 'management',\\n 'priority': 0}]\",\n \"def generate_launch_description():\\n return launch.LaunchDescription(\\n mock.launch.generate_launch_nodes() +\\n [\\n launch_ros.actions.Node(\\n package='py_trees_ros_tutorials',\\n executable=\\\"tree-battery-check\\\",\\n output='screen',\\n emulate_tty=True,\\n )\\n ]\\n )\",\n \"def list(args):\\n experiments = sorted(os.listdir('./litmus'))\\n print_color(\\\"Available Litmus Chaos Experiments:\\\\n\\\\n\\\")\\n if (f\\\"{args.platform}\\\" == \\\"GKE\\\"):\\n i = 1\\n for experiment_file in experiments:\\n print_color(f\\\"\\\\t{i}. {experiment_file.replace('.yaml', '')}\\\")\\n i += 1\\n\\n if (f\\\"{args.platform}\\\" == \\\"kind\\\"):\\n kind_supported = [\\\"pod-delete\\\",\\\"container-kill\\\",\\\"node-cpu-hog\\\",\\\"node-memory-hog\\\"]\\n i = 0\\n for i in range(0, len(kind_supported)):\\n print_color(f\\\"\\\\t{i+1}. {kind_supported[i]}\\\")\\n i += 1\\n\\n if (f\\\"{args.platform}\\\" == \\\"EKS\\\"):\\n i = 1\\n for experiment_file in experiments:\\n print_color(f\\\"\\\\t{i}. {experiment_file.replace('.yaml', '')}\\\")\\n i += 1\",\n \"def steps(name, bootsteps):\\n with BUILDING_DEPENDENCY_GRAPH(name=name) as action:\\n last_bootsteps = [bootstep for bootstep in bootsteps if bootstep.last]\\n if len(last_bootsteps) > 1:\\n raise ValueError(\\n f\\\"Only one boot step can be last. Found {len(last_bootsteps)}.\\\"\\n )\\n\\n dependencies = {\\n bootstep: bootstep.requires\\n for bootstep in bootsteps\\n if bootstep.include_if()\\n }\\n for bootstep in bootsteps:\\n for dependet_bootstep in bootstep.required_by:\\n if dependet_bootstep.include_if():\\n dependencies[dependet_bootstep].add(bootstep)\\n graph = DiGraph(dependencies)\\n\\n if last_bootsteps:\\n last = last_bootsteps[0]\\n for bootstep in graph:\\n if bootstep != last:\\n graph.add_edge(last, bootstep)\\n\\n if not is_directed_acyclic_graph(graph):\\n raise ValueError(\\\"Circular dependencies found.\\\")\\n\\n action.addSuccessFields(name=name, graph=graph)\\n\\n return graph\",\n \"def get_steps(self):\\n return self.steps\",\n \"def _parse_steps(recipe):\\n steps = []\\n\\n filtered_dict = {k: v for k, v in recipe.items() if \\\"step\\\" in k}\\n\\n for key, value in filtered_dict.items():\\n if value:\\n steps.append(value)\\n\\n return steps\",\n \"def instruction_steps(self) -> Sequence['outputs.CodelessUiConnectorConfigPropertiesResponseInstructionSteps']:\\n return pulumi.get(self, \\\"instruction_steps\\\")\",\n \"def workbench_scenarios():\\n return [\\n (\\\"Vr360XBlock\\\",\\n \\\"\\\"\\\"<vr360/>\\n \\\"\\\"\\\"),\\n (\\\"Multiple Vr360XBlock\\\",\\n \\\"\\\"\\\"<vertical_demo>\\n <vr360/>\\n <vr360/>\\n <vr360/>\\n </vertical_demo>\\n \\\"\\\"\\\"),\\n ]\",\n \"def Builds():\\n return builds\",\n \"def generate_specs_build(self):\\n from django_swagger_utils.drf_server.generators.swagger_generator import SwaggerGenerator\\n\\n swagger_gen = SwaggerGenerator(self.parser, self.paths, self.app_name)\\n # generating request_response files\\n swagger_gen.generate_request_response()\\n # testing properties\\n swagger_gen.generate_definitions()\\n # generating global parameters\\n swagger_gen.generate_parameters()\\n # generating global response\\n swagger_gen.generate_responses()\\n # generating urls\\n swagger_gen.generate_urls()\",\n \"def get_specs():\\n from fsm.fsmspec import FSMSpecification\\n spec = FSMSpecification(\\n name='help',\\n hideTabs=True,\\n title='Take the courselet core lessons',\\n pluginNodes=[START, START_MESSAGE, HELP_RESOLVE, END],\\n )\\n return (spec,)\",\n \"def workbench_scenarios():\\n return [\\n (\\\"Oppia Embedding\\\",\\n \\\"\\\"\\\"<vertical_demo>\\n <oppia oppiaid=\\\"0\\\" src=\\\"https://www.oppia.org\\\" width=\\\"700\\\" />\\n </vertical_demo>\\n \\\"\\\"\\\"),\\n ]\",\n \"def cmake_args(self):\\n args = [\\n self.define(\\\"CMAKE_C_COMPILER\\\", self.spec[\\\"mpi\\\"].mpicc),\\n self.define(\\\"BUILD_SHARED_LIBS\\\", True),\\n self.define(\\\"BUILD_TESTING\\\", self.run_tests),\\n ]\\n return args\",\n \"def steps(self) -> pulumi.Output[Sequence['outputs.StepResponse']]:\\n return pulumi.get(self, \\\"steps\\\")\",\n \"def list(ctx):\\n handler = ValidateCommandHandler(ctx.obj['qa_dir'])\\n if handler.validate():\\n handler = ListCommandHandler(ctx.obj['qa_dir'])\\n handler.show_test_case_tree()\\n else:\\n exit(1)\",\n \"def get_steps(self):\\n return self.steps\",\n \"def get_all_makes(self):\\n return self.get('vehicles/GetAllMakes')\",\n \"def getWorkflowSteps(self):\\n\\n return self.dbase.getProcessSteps(self.scene)\",\n \"def test_structure_to_steps(self):\\n test_structure = self.test_structure\\n classes = []\\n counter = 1\\n for c in test_structure:\\n current = []\\n for i in range(c):\\n current.append(counter)\\n counter += 1\\n classes.append(current)\\n return classes\",\n \"def workbench_scenarios():\\n return [\\n (\\\"Markdown\\\",\\n \\\"\\\"\\\"<markdowna />\\n \\\"\\\"\\\")\\n ]\",\n \"def _discover_workflow_specs(self, dir: Optional[str] = None) -> List[str]:\\n if dir is None:\\n dir = self._output_dir\\n\\n specs = []\\n for filename in WORKFLOW_SPEC_FILENAMES:\\n path = os.path.join(dir, filename)\\n if os.path.isfile(path):\\n specs.append(path)\\n return specs\",\n \"def get_next_steps(self, steps):\\n step_list = []\\n\\n steps_remaining = set(steps.keys())\\n counter = 0\\n max_counter = 10000\\n next_steps = set()\\n\\n for step in steps_remaining:\\n dependencies = steps[step]\\n if len(dependencies) == 0:\\n next_steps.add(step)\\n\\n # this is the list of things that can be take for work now\\n return sorted(next_steps)\",\n \"def steps(self):\\n return [\\n MRStep(mapper=self.mapper_data_cleaning,\\n reducer=self.reducer_data_cleaning\\n ),\\n MRStep(\\n mapper_init=self.mapper_get_items_init,\\n mapper=self.mapper_get_items,\\n combiner=self.combiner_count_items,\\n reducer=self.reducer_total_items\\n )\\n ]\",\n \"def getBuildRequests():\",\n \"def get_artifacts(self):\\n\\n self.clml_modules = list(\\n filter(lambda mod: mod.type_key == \\\"clml\\\", self.libm.get_lib().imported_modules)\\n )\\n self.clml_builds[\\\"file_header\\\"] = [self.MakeFileHeader.substitute()]\\n\\n for cmod in self.clml_modules:\\n (sub_module_name, clml_code) = CLMLGetSubModuleSrc(cmod).get_src()\\n self.clml_builds[sub_module_name] = clml_code\\n\\n main_code = []\\n main_code.append(\\n \\\"\\\"\\\"\\n std::vector<CLMLRunner> BuildModules(ToolArgs& args,\\n cl_platform_id arg_platform,\\n cl_context arg_context,\\n cl_device_id arg_device_id,\\n cl_command_queue arg_queue) {\\n std::vector<CLMLRunner> runners;\\\"\\\"\\\"\\n )\\n for key, val in self.clml_builds.items():\\n if key != \\\"file_header\\\":\\n main_code.append(\\n \\\"runners.push_back(\\\"\\n + key\\n + '(\\\"'\\n + key\\n + '\\\", args, arg_platform, arg_context, arg_device_id, arg_queue));'\\n )\\n main_code.append(\\\"return runners;}\\\")\\n self.clml_builds[\\\"MainBuild\\\"] = main_code\\n\\n for key, val in self.clml_builds.items():\\n self.gen_src.extend(val)\\n\\n return (self.get_clml_params(), self.gen_src)\",\n \"def list_builders(self) -> List[str]:\\n return sorted(_iter_builder_names(self._ns2data_dir))\",\n \"def getPendingBuilds():\",\n \"def getPendingBuilds():\",\n \"def _insertAllSteps(self):\\n \\n # Get pointer to input micrographs \\n self.particlePickingRun = self.xmippParticlePicking.get()\\n \\n copyId = self._insertFunctionStep('copyInputFilesStep')\\n # Get micrographs to pick\\n #self.inputMicrographs.set(self.getInputMicrographs())\\n \\n deps = []\\n for mic in self.getInputMicrographs():\\n stepId = self._insertFunctionStep('autopickMicrographStep', mic.getFileName(), prerequisites=[copyId])\\n deps.append(stepId)\\n \\n self._insertFunctionStep('_createOutput',self._getExtraPath(), prerequisites=deps)\",\n \"def generate_steplist(my_factory):\\n steps = []\\n stepnames = {}\\n\\n for factory, cmdargs in my_factory.steps:\\n cmdargs = cmdargs.copy()\\n try:\\n step = factory(**cmdargs)\\n except:\\n print >>sys.stderr, ('error while creating step, factory=%s, args=%s'\\n % (factory, cmdargs))\\n raise\\n name = step.name\\n if name in stepnames:\\n count = stepnames[name]\\n count += 1\\n stepnames[name] = count\\n name = step.name + ('_%d' % count)\\n else:\\n stepnames[name] = 0\\n step.name = name\\n\\n #TODO: is this a bug in FileUpload?\\n if not hasattr(step, 'description') or not step.description:\\n step.description = [step.name]\\n if not hasattr(step, 'descriptionDone') or not step.descriptionDone:\\n step.descriptionDone = [step.name]\\n\\n step.locks = []\\n steps.append(step)\\n\\n return steps\",\n \"def steps():\\n global recorder\\n if recorder is None:\\n print \\\"nothing has been recorded\\\"\\n return None\\n result = []\\n for r in recorder:\\n result += [ r ]\\n return result\",\n \"def build_step(self):\\n run_cmd('./compile.sh', log_all=True, simple=True, log_ok=True)\",\n \"def get_workflow_steps(self):\\n return self._data_dict[self.KEY_WF_STEPS]\",\n \"def test_get_scenarios_expanded(self):\\n pass\",\n \"def steps(self):\\n for step in self._get_paged(\\\"steps\\\", trailing=True):\\n yield self.__get_object(step)\\n\\n return\",\n \"def _generate_steps(\\n episode: Sequence[Any],\\n step_metadata_skip_list: AbstractSet[str]) -> Dict[str, Any]:\\n step_metadata = _empty_nested_list(\\n get_step_metadata(episode[0], step_metadata_skip_list))\\n\\n steps = {\\n 'observation':\\n _empty_nested_list(episode[0].timestep.observation),\\n 'action':\\n _empty_nested_list(episode[0].action),\\n 'reward': [],\\n 'discount': [],\\n 'is_terminal': [],\\n 'is_first': [],\\n 'is_last': [],\\n }\\n steps.update(step_metadata)\\n\\n prev_step = None\\n for step in episode:\\n if prev_step is not None:\\n steps['is_first'].append(prev_step.timestep.first())\\n steps['is_terminal'].append(False)\\n steps['is_last'].append(prev_step.timestep.last())\\n steps['observation'] = _append_nested(\\n steps['observation'], prev_step.timestep.observation)\\n steps['reward'].append(step.timestep.reward)\\n steps['discount'].append(step.timestep.discount)\\n steps['action'] = _append_nested(steps['action'], step.action)\\n step_metadata = get_step_metadata(prev_step, step_metadata_skip_list)\\n for k, v in step_metadata.items():\\n steps[k] = _append_nested(steps[k], v)\\n prev_step = step\\n if prev_step is not None:\\n # We append the observation of the final step (action and reward were\\n # included in the previous step.\\n # The terminal flag is inferred like in termination(), truncation()\\n # from dm_env/_environment.py\\n is_terminal = (\\n prev_step.timestep.last() and prev_step.timestep.discount == 0.0)\\n steps['is_first'].append(prev_step.timestep.first())\\n steps['is_terminal'].append(is_terminal)\\n steps['is_last'].append(True)\\n steps['observation'] = _append_nested(\\n steps['observation'], prev_step.timestep.observation)\\n # Discount, action and reward are meaningless in the terminal step\\n steps['reward'].append(np.zeros_like(prev_step.timestep.reward))\\n steps['discount'].append(\\n np.zeros_like(prev_step.timestep.discount))\\n steps['action'] = _append_nested(\\n steps['action'],\\n tf.nest.map_structure(np.zeros_like, prev_step.action))\\n step_metadata = get_step_metadata(prev_step, step_metadata_skip_list)\\n for k, v in step_metadata.items():\\n steps[k] = _append_nested(steps[k], v)\\n return steps\",\n \"def test_build(self):\\n self.app.build()\",\n \"def getBuildSets():\",\n \"def get_steps(self) -> list:\\n ret_val = []\\n for step_id in self:\\n step_body = Steps.cache_step(step_id)\\n if step_body is not None:\\n ret_val.append(step_body)\\n\\n return ret_val\",\n \"def test__parse_steps():\\n verification_screen_step_0 = VerificationScreenStep(\\n required = True,\\n title = 'Yukari',\\n step_type = VerificationScreenStepType.text_input,\\n values = ['kisaki'],\\n )\\n \\n verification_screen_step_1 = VerificationScreenStep(\\n required = False,\\n title = 'Yurica',\\n step_type = VerificationScreenStepType.rules,\\n values = None,\\n )\\n \\n for input_data, expected_output in (\\n ({}, None),\\n ({'form_fields': None}, None),\\n ({'form_fields': []}, None),\\n (\\n {'form_fields': [verification_screen_step_0.to_data(defaults = True)]},\\n (verification_screen_step_0, ),\\n ),\\n (\\n {\\n 'form_fields': [\\n verification_screen_step_0.to_data(defaults = True),\\n verification_screen_step_1.to_data(defaults = True),\\n ],\\n },\\n (verification_screen_step_0, verification_screen_step_1),\\n ),\\n ):\\n output = parse_steps(input_data)\\n vampytest.assert_eq(output, expected_output)\",\n \"def build_all(c, name, path, force=False):\\n print(40*\\\"-\\\")\\n print(\\\" starting the build and check...\\\")\\n print(40*\\\"-\\\")\\n # genate the app\\n if force:\\n r=c.run(\\\"python generate_app.py -n {} -p {} -f\\\".format(name, path))\\n else:\\n r=c.run(\\\"python generate_app.py -n {} -p {}\\\".format(name, path))\\n \\n print(\\\" .. generated the PythonOnWheels app.\\\")\\n # switch the current dir for invoke. every c.run starts from that dir.\\n app_path=os.path.abspath(os.path.join(path, name))\\n # create a venv\\n if os.name == \\\"nt\\\":\\n with c.cd(app_path):\\n print(\\\" .. creating a virtualenv\\\")\\n c.run(\\\"python -m venv ./venv\\\")\\n print(\\\" .. Installing the PoW requirements\\\")\\n c.run(\\\"cd ./venv/Scripts && pip.exe install -r {}\\\".format(\\n os.path.normpath(os.path.join(\\\"..\\\\..\\\", \\\"requirements.txt\\\"))))\\n elif os.name == \\\"posix\\\":\\n with c.cd(app_path):\\n print(\\\" .. creating a virtualenv\\\")\\n c.run(\\\"python -m venv ./venv\\\")\\n with c.cd(os.path.join(app_path, \\\"venv/bin\\\")):\\n print(\\\" .. Installing the PoW requirements\\\")\\n print(\\\"cwd: \\\" + c.cwd)\\n #pipath= os.path.abspath(os.path.join(app_path, \\\"./venv/bin/pip\\\"))\\n #print(\\\"venv pip path: {}\\\".format( pipath ))\\n reqpath = os.path.normpath(os.path.join( app_path, \\\"requirements.txt\\\"))\\n print(\\\"requirements.txt: {}\\\".format(reqpath))\\n c.run(\\\"./pip install -r {}\\\".format( reqpath ))\\n c.run(\\\"./pip freeze\\\")\\n else:\\n print(\\\"only posix and windows compatible OS are supported, sorry!\\\")\\n sys.exit()\\n test(c,path,name)\\n runserver(c,path,name)\",\n \"def raw_steps(self):\\n return self.obj_payload[\\\"steps\\\"]\",\n \"def getBuild(number):\",\n \"def getBuild(number):\",\n \"def actionBuild():\\n\\n #Init builder logger\\n Builder.init()\\n\\n for target in Settings.targets:\\n targetsToBuild, combineLibs, copyToOutput = Builder.getTargetGnPath(target)\\n for platform in Settings.targetPlatforms:\\n for cpu in Settings.targetCPUs:\\n if System.checkIfCPUIsSupportedForPlatform(cpu,platform):\\n for configuration in Settings.targetConfigurations:\\n if not Summary.checkIfActionFailed(ACTION_PREPARE, target, platform, cpu, configuration):\\n Logger.printStartActionMessage('Build ' + target + ' ' + platform + ' ' + cpu + ' ' + configuration,ColoredFormatter.YELLOW)\\n result = Builder.run(target, targetsToBuild, platform, cpu, configuration, combineLibs, copyToOutput)\\n Summary.addSummary(ACTION_BUILD, target, platform, cpu, configuration, result, Builder.executionTime)\\n if result != NO_ERROR:\\n Logger.printEndActionMessage('Failed building ' + target + ' ' + platform + ' ' + cpu + ' ' + configuration,ColoredFormatter.RED)\\n #Terminate script execution if stopExecutionOnError is set to True in userdef\\n shouldEndOnError(result)\\n else:\\n Logger.printEndActionMessage('Build ' + target + ' ' + platform + ' ' + cpu + ' ' + configuration)\\n else:\\n Logger.printColorMessage('Build cannot run because preparation has failed for ' + target + ' ' + platform + ' ' + cpu + ' ' + configuration,ColoredFormatter.YELLOW)\\n Logger.printEndActionMessage('Build not run for ' + target + ' ' + platform + ' ' + cpu + ' ' + configuration,ColoredFormatter.YELLOW)\",\n \"def _build_experiment_chiapet_embedded_list():\\n antibody_embeds = DependencyEmbedder.embed_defaults_for_type(\\n base_path='antibody',\\n t='antibody')\\n return (\\n Experiment.embedded_list + antibody_embeds\\n )\",\n \"def steps(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['StepArgs']]]]:\\n return pulumi.get(self, \\\"steps\\\")\",\n \"def logic_program_form(self):\\n #TODO\\n # determine step variable\\n a_set = set()\\n step = self.determineStepVariable()\\n s = ''\\n # assemble head\\n s = s + self.assembleHead(a_set, step)\\n # body\\n s = s + self.assembleBody(a_set, step)\\n return s\",\n \"def fab_steps(module):\\n return tuple(getattr(module, func) for func in get_sorted_strnum(dir(module)))\",\n \"def _build_experiment_mic_embedded_list():\\n imaging_path_embeds = DependencyEmbedder.embed_for_type(\\n base_path='imaging_paths.path',\\n t='imaging_path',\\n additional_embeds=['imaging_rounds', 'experiment_type.title'])\\n return (Experiment.embedded_list + imaging_path_embeds + [\\n # Files linkTo\\n 'files.accession', # detect display_title diff\\n\\n # MicroscopeSettings linkTo\\n 'files.microscope_settings.ch00_light_source_center_wl',\\n 'files.microscope_settings.ch01_light_source_center_wl',\\n 'files.microscope_settings.ch02_light_source_center_wl',\\n 'files.microscope_settings.ch03_light_source_center_wl',\\n 'files.microscope_settings.ch04_light_source_center_wl',\\n 'files.microscope_settings.ch00_lasers_diodes',\\n 'files.microscope_settings.ch01_lasers_diodes',\\n 'files.microscope_settings.ch02_lasers_diodes',\\n 'files.microscope_settings.ch03_lasers_diodes',\\n 'files.microscope_settings.ch04_lasers_diodes',\\n\\n # MicroscopeConfiguration linkTo\\n 'microscope_configuration_master.title',\\n 'microscope_configuration_master.microscope.Name',\\n 'files.microscope_configuration.title',\\n 'files.microscope_configuration.microscope.Name',\\n\\n # Image linkTo\\n 'sample_image.title',\\n 'sample_image.caption',\\n 'sample_image.microscopy_file.accession',\\n 'sample_image.microscopy_file.omerolink',\\n 'sample_image.attachment.href',\\n 'sample_image.attachment.type',\\n 'sample_image.attachment.md5sum',\\n 'sample_image.attachment.download',\\n 'sample_image.attachment.width',\\n 'sample_image.attachment.height',\\n ]\\n )\",\n \"def test_quick_build1(self):\\n pass\",\n \"def get_installations():\\n github_app = get_default_app()\\n pprint(github_app.get_installations())\",\n \"def workbench_scenarios(): \\n return [\\n (\\\"TermsXBlock\\\",\\n \\\"\\\"\\\"<terms/>\\n \\\"\\\"\\\"),\\n (\\\"Multiple TermsXBlock\\\",\\n \\\"\\\"\\\"<vertical_demo>\\n <terms/>\\n <terms/>\\n <terms/>\\n </vertical_demo>\\n \\\"\\\"\\\"),\\n ]\",\n \"def getMakes():\\n\\n #Get category page as Soup\\n soup, _ = getPage(\\\"/s-motorcycles/c18626\\\")\\n\\n #Check if page available\\n if soup is None:\\n #Not available\\n print(\\\"Can't get motorcycle category page\\\")\\n quit()\\n\\n\\n #Find all makes from main category page\\n #Find span with text \\\"Make\\\"\\n span = soup.find(class_=\\\"srp-filter-group__filter-name\\\", text=\\\"Make\\\")\\n #Move up two parents\\n a = span.parent.parent\\n #Find all filter names\\n b = a.find_all(class_=\\\"srp-list-filter__item-link link link--no-underline\\\")\\n makes = [i['href'] for i in b]\\n return makes\",\n \"def info_build_test(self):\\n\\n self._export(\\\"H0\\\", \\\"0.1\\\")\\n\\n self._export(\\\"H1a\\\", \\\"0.1\\\", deps=[(\\\"H0/0.1@lu/st\\\", \\\"private\\\")])\\n self._export(\\\"H1b\\\", \\\"0.1\\\", deps=[\\\"H0/0.1@lu/st\\\"])\\n self._export(\\\"H1c\\\", \\\"0.1\\\", deps=[(\\\"H0/0.1@lu/st\\\", \\\"private\\\")])\\n\\n self._export(\\\"H2a\\\", \\\"0.1\\\", deps=[\\\"H1a/0.1@lu/st\\\"])\\n self._export(\\\"H2c\\\", \\\"0.1\\\", deps=[\\\"H1c/0.1@lu/st\\\"])\\n\\n self._export(\\\"H3\\\", \\\"0.1\\\", deps=[\\\"H2a/0.1@lu/st\\\",\\n \\\"H2c/0.1@lu/st\\\"])\\n\\n # If we install H3 we need to build all except H1b\\n self.clients[\\\"H3\\\"].run(\\\"info --build missing\\\")\\n self.assert_last_line(self.clients[\\\"H3\\\"],\\n \\\"H0/0.1@lu/st, H1a/0.1@lu/st, H1c/0.1@lu/st, H2a/0.1@lu/st, H2c/0.1@lu/st\\\")\\n\\n # If we install H0 we need to build nothing (current project)\\n self.clients[\\\"H0\\\"].run(\\\"info --build missing\\\")\\n self.assert_last_line(self.clients[\\\"H0\\\"], \\\"\\\")\\n\\n # If we install H0 we need to build H0\\n self.clients[\\\"H1a\\\"].run(\\\"info --build missing\\\")\\n self.assert_last_line(self.clients[\\\"H1a\\\"], \\\"H0/0.1@lu/st\\\")\\n\\n # If we build and upload H1a and H1c, no more H0 (private) is required\\n self.clients[\\\"H3\\\"].run(\\\"install H1a/0.1@lu/st --build \\\")\\n self.clients[\\\"H3\\\"].run(\\\"install H1c/0.1@lu/st --build \\\")\\n self.clients[\\\"H3\\\"].run(\\\"upload H1a/0.1@lu/st --all\\\")\\n self.clients[\\\"H3\\\"].run(\\\"upload H1c/0.1@lu/st --all\\\")\\n\\n self.clients[\\\"H3\\\"].run(\\\"remove '*' -f\\\")\\n self.clients[\\\"H3\\\"].run(\\\"info --build missing\\\")\\n self.assert_last_line(self.clients[\\\"H3\\\"],\\n \\\"H2a/0.1@lu/st, H2c/0.1@lu/st\\\")\\n\\n # But if we force to build all, all nodes have to be built\\n self.clients[\\\"H3\\\"].run(\\\"remove '*' -f\\\")\\n self.clients[\\\"H3\\\"].run(\\\"info --build\\\")\\n self.assert_last_line(self.clients[\\\"H3\\\"],\\n \\\"H0/0.1@lu/st, H1a/0.1@lu/st, H1c/0.1@lu/st, H2a/0.1@lu/st, H2c/0.1@lu/st\\\")\\n\\n # Now upgrade the recipe H1a and upload it (but not the package)\\n # so the package become outdated\\n conanfile_path = os.path.join(self.clients[\\\"H1a\\\"].current_folder, CONANFILE)\\n conanfile = load(conanfile_path)\\n conanfile += \\\"\\\\n# MODIFIED\\\"\\n save(conanfile_path, conanfile)\\n self.clients[\\\"H1a\\\"].run(\\\"export lu/st\\\")\\n self.clients[\\\"H1a\\\"].run(\\\"upload H1a/0.1@lu/st\\\") # NOW IS OUTDATED!\\n\\n # Without build outdated the built packages are the same\\n self.clients[\\\"H3\\\"].run(\\\"remove '*' -f\\\")\\n self.clients[\\\"H3\\\"].run(\\\"info --build missing\\\")\\n self.assert_last_line(self.clients[\\\"H3\\\"],\\n \\\"H2a/0.1@lu/st, H2c/0.1@lu/st\\\")\\n\\n # But with build outdated we have to build the private H0 (but only once) and H1a\\n self.clients[\\\"H3\\\"].run(\\\"remove '*' -f\\\")\\n self.clients[\\\"H3\\\"].run(\\\"info --build outdated\\\")\\n self.assert_last_line(self.clients[\\\"H3\\\"],\\n \\\"H0/0.1@lu/st, H1a/0.1@lu/st, H2a/0.1@lu/st, H2c/0.1@lu/st\\\")\",\n \"def prep_steps(self, *, yearmon: str) -> List[Step]:\\n steps = []\\n\\n year, month = dates.parse_yearmon(yearmon)\\n\\n monthly_vars = ['2m_temperature', 'total_precipitation']\\n hourly_vars = ['total_precipitation']\\n\\n steps += era5.download(output_filename=era5.filename(self.source, 'month', yearmon),\\n duration='month',\\n yearmon=yearmon,\\n variables=monthly_vars)\\n\\n if year >= 1979:\\n steps += era5.download(output_filename=era5.filename(self.source, 'hour', yearmon),\\n duration='hour',\\n yearmon=yearmon,\\n variables=hourly_vars)\\n steps += era5.calc_wetdays(input_filename=era5.filename(self.source, 'hour', yearmon),\\n output_filename=self.p_wetdays(yearmon=yearmon).file,\\n threshold_mm=0.1)\\n\\n return steps\",\n \"def generate_launch_description():\\n composed = ComposableNodeContainer(\\n name='ComponentManager',\\n namespace='',\\n package='rclcpp_components',\\n executable='component_container',\\n composable_node_descriptions=[\\n ComposableNode(\\n package='composition',\\n plugin='composition::Talker',\\n name='comp_talker'),\\n ComposableNode(\\n package='composition',\\n plugin='composition::Listener',\\n name='comp_listener')\\n ],\\n output='both',\\n )\\n\\n jsp = Node(\\n package='joint_state_publisher',\\n executable='joint_state_publisher',\\n output='both',\\n )\\n\\n lc_talker = LifecycleNode(\\n name='lc_talker',\\n namespace='',\\n package='lifecycle',\\n executable='lifecycle_talker',\\n output='both',\\n )\\n\\n listener = Node(\\n package='demo_nodes_cpp',\\n executable='listener',\\n output='both',\\n )\\n\\n talker = Node(\\n package='demo_nodes_cpp',\\n executable='listener',\\n output='both',\\n )\\n\\n turtle = Node(\\n package='turtlesim',\\n executable='turtlesim_node',\\n output='both',\\n )\\n\\n return launch.LaunchDescription([\\n composed,\\n jsp,\\n lc_talker,\\n listener,\\n talker,\\n turtle,\\n ])\",\n \"def test_quick_build(self):\\n pass\",\n \"def test_build_pipeline_nine(self):\\n args = \\\"Test_APP TASK\\\".split(\\\" \\\")\\n task_list = build_pipeline(args, False)\\n self.assertEqual(1, len(task_list))\",\n \"def test_get_scenarios(self):\\n pass\",\n \"def test_makeliststep_call_from_within_pipeline():\\n config_file = t_path(\\n Path('steps') / 'makelist_pipeline.cfg'\\n )\\n results = MakeListPipeline.call(config_file=config_file)\\n assert results == [43.0, 'My hovercraft is full of eels.', False]\",\n \"def workbench_scenarios():\\n return [\\n (\\\"simstudentXBlock\\\",\\n \\\"\\\"\\\"<vertical_demo>\\n <simstudent/>\\n </vertical_demo>\\n \\\"\\\"\\\"),\\n ]\",\n \"def process_steps(steplist, build, buildslave, build_status, basedir):\\n for step in steplist:\\n step.setBuild(build)\\n step.setBuildSlave(buildslave)\\n step.setStepStatus(build_status.addStepWithName(step.name))\\n step.setDefaultWorkdir(os.path.join(basedir, 'build'))\\n step.workdir = os.path.join(basedir, 'build')\",\n \"def test_build_pipeline_seven(self):\\n args = \\\"Test_APP SIX A B C\\\".split(\\\" \\\")\\n task_list = build_pipeline(args, False)\\n self.assertEqual(1, len(task_list))\",\n \"def stepStarted(build, step):\",\n \"def get_buildall_target(self):\\n raise NotImplementedError\",\n \"def get_sim_exe_out_arg(self):\\n dirname = os.path.dirname(self.sim_exe)\\n if dirname and not os.path.exists(dirname):\\n os.makedirs(dirname)\\n return ['-o', self.sim_exe]\",\n \"def build_msms():\\r\\n\\r\\n # Prepare include file with dynamic data\\r\\n f = open(os.path.join(GME_ROOT, \\\"Install\\\", \\\"GME_dyn.wxi\\\"), 'w')\\r\\n print >> f, \\\"<!-- DO NOT EDIT THIS FILE. WILL BE REGENERATED BY THE BUILD SCRIPTS -->\\\"\\r\\n print >> f, \\\"<Include>\\\"\\r\\n print >> f, \\\" <?define GUIDSTRMETAGME='%s' ?>\\\" % (tools.query_GUID(mta_for_xmp(METAGME_XMP)))\\r\\n print >> f, \\\" <?define GUIDSTRHFSM='%s' ?>\\\" % (tools.query_GUID(mta_for_xmp(HFSM_XMP)))\\r\\n print >> f, \\\" <?define GUIDSTRSF='%s' ?>\\\" % (tools.query_GUID(mta_for_xmp(SF_XMP)))\\r\\n print >> f, \\\" <?define GUIDSTRUML='%s' ?>\\\" % (tools.query_GUID(mta_for_xmp(UML_XMP)))\\r\\n print >> f, \\\"</Include>\\\"\\r\\n f.close()\\r\\n\\r\\n import glob\\r\\n sources = [f for f in glob.glob(os.path.join(GME_ROOT, \\\"Install\\\", \\\"*.wxs\\\")) if os.path.basename(f) not in ('GME.wxs', 'GME_bundle.wxs')]\\r\\n if prefs['arch'] == 'x64':\\r\\n sources.remove(os.path.join(GME_ROOT, \\\"Install\\\", \\\"GME_paradigms.wxs\\\"))\\r\\n for file_ in sources:\\r\\n extras = []\\r\\n if os.path.basename(file_) == 'GME_paradigms.wxs':\\r\\n extras = glob.glob(os.path.join(GME_ROOT, \\\"Install\\\", \\\"PIA*/*.wxi\\\"))\\r\\n tools.build_WiX([file_] + extras)\",\n \"def _build_experiment_seq_embedded_list():\\n antibody_embeds = DependencyEmbedder.embed_defaults_for_type(\\n base_path='antibody',\\n t='antibody')\\n return (\\n Experiment.embedded_list + antibody_embeds\\n )\",\n \"def _build_main_menu(self):\\n if self._args.execution_environment:\\n columns = [\\\"__name\\\", \\\"__version\\\", \\\"__shadowed\\\", \\\"__type\\\", \\\"path\\\"]\\n else:\\n columns = [\\\"__name\\\", \\\"__version\\\", \\\"__shadowed\\\", \\\"path\\\"]\\n\\n return Step(\\n name=\\\"all_collections\\\",\\n columns=columns,\\n select_func=self._build_plugin_menu,\\n tipe=\\\"menu\\\",\\n value=self._collections,\\n )\",\n \"def workbench_scenarios():\\n return [\\n (\\\"UcCodemirrorXBlock\\\",\\n \\\"\\\"\\\"<vertical_demo>\\n <uc_codemirror/>\\n <uc_codemirror/>\\n <uc_codemirror/>\\n </vertical_demo>\\n \\\"\\\"\\\"),\\n ]\",\n \"def get_args(phase):\\r\\n parser = argparse.ArgumentParser(description='Configuration')\\r\\n\\r\\n # Hardware specifications\\r\\n parser.add_argument('--seed', type=int, default=1, help='random seed')\\r\\n parser.add_argument(\\\"--device_id\\\", type=int, default=0, help=\\\"device id, default is 0.\\\")\\r\\n parser.add_argument('--device_num', type=int, default=1, help='device num, default is 1.')\\r\\n parser.add_argument('--platform', type=str, default=\\\"Ascend\\\", \\\\\\r\\n help='run platform, only support Ascend')\\r\\n parser.add_argument('--save_graphs', type=ast.literal_eval, default=False, \\\\\\r\\n help='whether save graphs, default is False.')\\r\\n parser.add_argument('--dataset', type=str, default=\\\"large\\\", choices=(\\\"large\\\", \\\"small\\\", \\\"demo\\\"), \\\\\\r\\n help='MIND dataset, support large, small and demo.')\\r\\n parser.add_argument('--dataset_path', type=str, default=None, help='MIND dataset path.')\\r\\n\\r\\n # Model specifications\\r\\n parser.add_argument('--n_browsed_news', type=int, default=50, help='number of browsed news per user')\\r\\n parser.add_argument('--n_words_title', type=int, default=16, help='number of words per title')\\r\\n parser.add_argument('--n_words_abstract', type=int, default=48, help='number of words per abstract')\\r\\n parser.add_argument('--word_embedding_dim', type=int, default=304, help='dimension of word embedding vector')\\r\\n parser.add_argument('--category_embedding_dim', type=int, default=112, \\\\\\r\\n help='dimension of category embedding vector')\\r\\n parser.add_argument('--query_vector_dim', type=int, default=208, help='dimension of the query vector in attention')\\r\\n parser.add_argument('--n_filters', type=int, default=400, help='number of filters in CNN')\\r\\n parser.add_argument('--window_size', type=int, default=3, help='size of filter in CNN')\\r\\n parser.add_argument(\\\"--checkpoint_path\\\", type=str, default=None, \\\\\\r\\n help=\\\"Pre trained checkpoint path, default is None.\\\")\\r\\n parser.add_argument('--batch_size', type=int, default=64, help='size of each batch')\\r\\n # Training specifications\\r\\n if phase == \\\"train\\\":\\r\\n parser.add_argument('--epochs', type=int, default=None, help='number of epochs for training')\\r\\n parser.add_argument('--lr', type=float, default=None, help='learning rate')\\r\\n parser.add_argument('--beta1', type=float, default=0.9, help='ADAM beta1')\\r\\n parser.add_argument('--beta2', type=float, default=0.999, help='ADAM beta2')\\r\\n parser.add_argument('--epsilon', type=float, default=1e-8, help='ADAM epsilon for numerical stability')\\r\\n parser.add_argument('--neg_sample', type=int, default=4, help='number of negative samples in negative sampling')\\r\\n parser.add_argument(\\\"--mixed\\\", type=ast.literal_eval, default=True, \\\\\\r\\n help=\\\"whether use mixed precision, default is True.\\\")\\r\\n parser.add_argument(\\\"--sink_mode\\\", type=ast.literal_eval, default=True, \\\\\\r\\n help=\\\"whether use dataset sink, default is True.\\\")\\r\\n parser.add_argument('--print_times', type=int, default=None, help='number of print times, default is None')\\r\\n parser.add_argument(\\\"--weight_decay\\\", type=ast.literal_eval, default=True, \\\\\\r\\n help=\\\"whether use weight decay, default is True.\\\")\\r\\n parser.add_argument('--save_checkpoint', type=ast.literal_eval, default=True, \\\\\\r\\n help='whether save checkpoint, default is True.')\\r\\n parser.add_argument(\\\"--save_checkpoint_path\\\", type=str, default=\\\"./checkpoint\\\", \\\\\\r\\n help=\\\"Save checkpoint path, default is checkpoint.\\\")\\r\\n parser.add_argument('--dropout_ratio', type=float, default=0.2, help='ratio of dropout')\\r\\n if phase == \\\"eval\\\":\\r\\n parser.add_argument('--neg_sample', type=int, default=-1, \\\\\\r\\n help='number of negative samples in negative sampling')\\r\\n if phase == \\\"export\\\":\\r\\n parser.add_argument('--file_format', type=str, choices=[\\\"AIR\\\", \\\"ONNX\\\", \\\"MINDIR\\\"], default='AIR', \\\\\\r\\n help='file format')\\r\\n parser.add_argument('--neg_sample', type=int, default=-1, \\\\\\r\\n help='number of negative samples in negative sampling')\\r\\n args = parser.parse_args()\\r\\n if args.device_num > 1:\\r\\n context.set_context(mode=context.GRAPH_MODE, device_target=args.platform, save_graphs=args.save_graphs)\\r\\n context.reset_auto_parallel_context()\\r\\n context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL, gradients_mean=True,\\r\\n device_num=args.device_num)\\r\\n init()\\r\\n args.rank = get_rank()\\r\\n args.save_checkpoint_path = os.path.join(args.save_checkpoint_path, \\\"ckpt_\\\" + str(args.rank))\\r\\n else:\\r\\n context.set_context(mode=context.GRAPH_MODE, device_target=args.platform, device_id=args.device_id,\\r\\n save_graphs=args.save_graphs, save_graphs_path=\\\"naml_ir\\\")\\r\\n args.rank = 0\\r\\n args.device_num = 1\\r\\n args.phase = phase\\r\\n cfg = get_dataset_config(args.dataset)\\r\\n args.n_categories = cfg.n_categories\\r\\n args.n_sub_categories = cfg.n_sub_categories\\r\\n args.n_words = cfg.n_words\\r\\n if phase == \\\"train\\\":\\r\\n args.epochs = cfg.epochs if args.epochs is None else args.epochs * math.ceil(args.device_num ** 0.5)\\r\\n args.lr = cfg.lr if args.lr is None else args.lr\\r\\n args.print_times = cfg.print_times if args.print_times is None else args.print_times\\r\\n args.embedding_file = cfg.embedding_file.format(args.dataset_path)\\r\\n args.word_dict_path = cfg.word_dict_path.format(args.dataset_path)\\r\\n args.category_dict_path = cfg.category_dict_path.format(args.dataset_path)\\r\\n args.subcategory_dict_path = cfg.subcategory_dict_path.format(args.dataset_path)\\r\\n args.uid2index_path = cfg.uid2index_path.format(args.dataset_path)\\r\\n args.train_dataset_path = cfg.train_dataset_path.format(args.dataset_path)\\r\\n args.eval_dataset_path = cfg.eval_dataset_path.format(args.dataset_path)\\r\\n args_dict = vars(args)\\r\\n for key in args_dict.keys():\\r\\n print('--> {}:{}'.format(key, args_dict[key]), flush=True)\\r\\n return args\",\n \"def ExpectedEnginesToBuild(self, run_params):\\n return [\\\"TRTEngineOp_000\\\"]\",\n \"def build(parameters):\\n\\n\\n print(\\\"In Build module\\\")\",\n \"def required_tool_results():\\n return [MethylResultModule]\",\n \"def list_programs():\\n return list(INFO)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.779069","0.67776674","0.64382553","0.624265","0.60818905","0.6052851","0.6028818","0.57117945","0.56699735","0.5631484","0.5578449","0.5562804","0.5509476","0.5509476","0.5501834","0.5475979","0.5436348","0.53203976","0.5319532","0.5312754","0.5293944","0.5197324","0.5161105","0.5103497","0.5096082","0.50769687","0.507214","0.50719094","0.50602704","0.5048313","0.50453556","0.50207776","0.5019613","0.50120604","0.5007563","0.49773866","0.4976406","0.49717116","0.49646947","0.4936787","0.4908193","0.4907262","0.48848343","0.48736265","0.486974","0.4857556","0.4847125","0.48412544","0.4807483","0.48025307","0.47935796","0.47935796","0.4791866","0.4789688","0.47853112","0.47844276","0.4784182","0.47834328","0.47826746","0.476909","0.4763872","0.47590482","0.47587237","0.47537285","0.47515497","0.4750847","0.47435522","0.47435522","0.4743462","0.47427946","0.47347343","0.4718263","0.47180453","0.47149146","0.4714912","0.47072035","0.47061965","0.4705948","0.4703442","0.47012413","0.46954703","0.46928623","0.46897715","0.46859038","0.4676737","0.46627516","0.46596125","0.46578702","0.46526423","0.46494046","0.46387687","0.46196425","0.46186087","0.46046287","0.4603459","0.46001422","0.45955157","0.45946085","0.45909268","0.45891342"],"string":"[\n \"0.779069\",\n \"0.67776674\",\n \"0.64382553\",\n \"0.624265\",\n \"0.60818905\",\n \"0.6052851\",\n \"0.6028818\",\n \"0.57117945\",\n \"0.56699735\",\n \"0.5631484\",\n \"0.5578449\",\n \"0.5562804\",\n \"0.5509476\",\n \"0.5509476\",\n \"0.5501834\",\n \"0.5475979\",\n \"0.5436348\",\n \"0.53203976\",\n \"0.5319532\",\n \"0.5312754\",\n \"0.5293944\",\n \"0.5197324\",\n \"0.5161105\",\n \"0.5103497\",\n \"0.5096082\",\n \"0.50769687\",\n \"0.507214\",\n \"0.50719094\",\n \"0.50602704\",\n \"0.5048313\",\n \"0.50453556\",\n \"0.50207776\",\n \"0.5019613\",\n \"0.50120604\",\n \"0.5007563\",\n \"0.49773866\",\n \"0.4976406\",\n \"0.49717116\",\n \"0.49646947\",\n \"0.4936787\",\n \"0.4908193\",\n \"0.4907262\",\n \"0.48848343\",\n \"0.48736265\",\n \"0.486974\",\n \"0.4857556\",\n \"0.4847125\",\n \"0.48412544\",\n \"0.4807483\",\n \"0.48025307\",\n \"0.47935796\",\n \"0.47935796\",\n \"0.4791866\",\n \"0.4789688\",\n \"0.47853112\",\n \"0.47844276\",\n \"0.4784182\",\n \"0.47834328\",\n \"0.47826746\",\n \"0.476909\",\n \"0.4763872\",\n \"0.47590482\",\n \"0.47587237\",\n \"0.47537285\",\n \"0.47515497\",\n \"0.4750847\",\n \"0.47435522\",\n \"0.47435522\",\n \"0.4743462\",\n \"0.47427946\",\n \"0.47347343\",\n \"0.4718263\",\n \"0.47180453\",\n \"0.47149146\",\n \"0.4714912\",\n \"0.47072035\",\n \"0.47061965\",\n \"0.4705948\",\n \"0.4703442\",\n \"0.47012413\",\n \"0.46954703\",\n \"0.46928623\",\n \"0.46897715\",\n \"0.46859038\",\n \"0.4676737\",\n \"0.46627516\",\n \"0.46596125\",\n \"0.46578702\",\n \"0.46526423\",\n \"0.46494046\",\n \"0.46387687\",\n \"0.46196425\",\n \"0.46186087\",\n \"0.46046287\",\n \"0.4603459\",\n \"0.46001422\",\n \"0.45955157\",\n \"0.45946085\",\n \"0.45909268\",\n \"0.45891342\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6734113"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":75199,"cells":{"query":{"kind":"string","value":"Returns a list of all steps current platform"},"document":{"kind":"string","value":"def get_all_steps(self):\n steps = []\n steps.extend(self.init_workspace_steps())\n steps.extend(self.repos_clone_steps())\n steps.extend(self.cli_steps())\n steps.extend(self.prepare_mobilespec_steps())\n steps.extend(self.deploy_steps())\n return steps"},"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 availableSteps( self ):\n assert isinstance( self._level, int )\n assert isinstance( self._steps, list )\n assert isinstance( self._outter, Env ) or ( self._outter is None )\n\n lst = [ ]\n self._availableSteps( lst )\n return lst","def Platforms():\n return platforms","def list_platforms(self):\n return self.do_rpc('list_platforms')","def available_platforms(verbose=True):\n\n\n import simtk.openmm as mm\n\n platforms_available = []\n\n for ii in range(mm.Platform.getNumPlatforms()):\n platform_name = mm.Platform.getPlatform(ii).getName()\n platform = mm.Platform.getPlatformByName(platform_name)\n platform_speed = platform.getSpeed()\n platforms_available.append(platform_name)\n if verbose:\n print('Platform {} with speed {}'.format(platform_name,platform_speed))\n del(platform_name, platform, platform_speed)\n\n if verbose is False:\n return platforms_available","def getSteps():","def platforms(self):\n return self.rpc.call(MsfRpcMethod.ModulePlatforms)","def get_platforms(self):\n _log.debug(\"Passing platforms back: {}\".format(\n self._registered_platforms.keys()))\n return self._registered_platforms.values()","def _get_steps(self):\n return self.steps","def getSteps( self ):\n\n return self.adb.get( 'steps' )","def init_workspace_steps(self):\n return [\n InstallShellJS(),\n RMCommand(path=\"~/.cordova/\" + self.platform, workdir='build', haltOnFailure=False, description='Remove cache'),\n RMCommand(path=\"*\", workdir='build', haltOnFailure=False, description='Clean workdir'),\n ShellCommand(command=[\"git\", \"clone\", \"--depth\", \"1\", \"-b\", CONFIG.branches['TESTMASTER'], CONFIG.repos['TESTMASTER'], \"medic\"], workdir='build', haltOnFailure=True, description='Get Medic'),\n # --production switch is used to speed up installation + fruitstrap dev dependency is not supported on Windows\n NPMInstall([\"--production\"], workdir='build/medic', haltOnFailure=True, description='Install Medic'),\n FileDownload(mastersrc=FP+\"cordova-config.json\", slavedest=\"medic/config.json\", haltOnFailure=True),\n FileDownload(mastersrc=FP+\"cordova-repos.json\", slavedest=\"medic/repos.json\", haltOnFailure=True),\n ShellCommand(command=[\"git\", \"clone\", \"--depth\", \"1\", CONFIG.repos['COHO']], workdir='build', haltOnFailure=True, description='Get COHO'),\n NPMInstall([\"--production\"], workdir='build/cordova-coho', haltOnFailure=True, description='Install COHO'),\n ]","def platforms(self):\n logger.debug(\"Get platforms\")\n return self._raw_api.platforms.get()","def get_steps(self) -> list:\n ret_val = []\n for step_id in self:\n step_body = Steps.cache_step(step_id)\n if step_body is not None:\n ret_val.append(step_body)\n\n return ret_val","def get_platforms(self):\n if self.platform == 'All':\n return PLATFORMS\n else:\n return self.platform.split(':')","def getProcessingHistoryList(context):\n projectDir = context.projectDir\n steps = []\n history = GenericMetadata._readEntriesForSection(projectDir, GenericMetadata.HISTORY_SECTION)\n try:\n idx = int(history['numsteps']) + 1\n for i in xrange(1, idx):\n key = GenericMetadata.HISTORY_PROTO + str(i)\n steps.append(history[key])\n except KeyError:\n pass\n \n return steps","def get_steps(self):\n return self.steps","def get_steps(self):\n return self.steps","def availablePremises( self ):\n assert isinstance( self._env, Env )\n assert isinstance( self._steps, list )\n\n return self._env.availableSteps( )","def _GetMachineList(self):\n machines = self._experiment.remote\n # All Label.remote is a sublist of experiment.remote.\n for l in self._experiment.labels:\n for r in l.remote:\n assert r in machines\n return machines","def get_commands(steplist):\n commands = []\n for step in steplist:\n if hasattr(step, 'command'):\n cmdhash = {}\n renderables = []\n accumulateClassList(step.__class__, 'renderables', renderables)\n\n for renderable in renderables:\n setattr(step, renderable, step.build.render(getattr(step,\n renderable)))\n\n cmdhash['name'] = step.name\n cmdhash['command'] = step.command\n cmdhash['workdir'] = step.workdir\n if hasattr(step, 'env'):\n cmdhash['env'] = step.env\n else:\n cmdhash['env'] = {}\n if hasattr(step, 'timeout'):\n print \"yay!~\"\n cmdhash['timeout'] = step.timeout\n\n cmdhash['description'] = step.description\n cmdhash['descriptionDone'] = step.descriptionDone\n commands.append(cmdhash)\n return commands","def get_platforms():\n # Get all CL platforms\n platforms = cl.get_platforms()\n for p in platforms:\n # Not a safe way\n p.__class__ = Platform\n p.devices = p.get_devices()\n for d in p.devices:\n d.__class__ = Device\n return platforms","def getWorkflowSteps(self):\n\n return self.dbase.getProcessSteps(self.scene)","def steps(self):\n for step in self._get_paged(\"steps\", trailing=True):\n yield self.__get_object(step)\n\n return","def deploy_steps(self):\n return [ShellCommand(command=[\"node\", \"medic/build_\" + self.platform + \".js\"], workdir='build', timeout=CONFIG.build_timeout, description='Run tests', name='Run tests')]","def platforms(self) -> Any:\n\n return search_api(\"platforms\")","def default_platform_list(self):\n for platform in self.database.platforms:\n if self.database.has(platform=platform, architecture=default.architecture):\n release = self.database.latest_release(\n platform, architecture=default.architecture\n )\n name = _format_platform(platform, release)\n image = f\"{_REPOSITORY}:<version>-{platform}\"\n link = md.link(md.pre(image), md.anchor(name))\n yield md.item(f\"{link} ({name})\")","def steps(self) -> pulumi.Output[Sequence['outputs.StepResponse']]:\n return pulumi.get(self, \"steps\")","def next_steps(self) -> List[FlowNode]:\n return [node for predicate, node in self._current_step.children]","def _get_install_steps(self):\n\n content = self._get_yaml_content()\n\n return self._fix_install_steps(content['install'])","def platform(self) -> Platform:\n _args: list[Arg] = []\n _ctx = self._select(\"platform\", _args)\n return _ctx.execute_sync(Platform)","def steps(self):\n\n if not os.path.exists(self.build_path):\n raise exceptions.ProjectNotBuildError()\n\n steps = []\n for filename in os.listdir(self.build_path):\n match = re.match(r'(\\d{4})_(.*)\\.json', filename)\n if not match:\n continue\n\n with open(os.path.join(self.build_path, filename), 'r') as f:\n template = json.loads(f.read())\n\n template_type = 'custom' if '_type' in template else 'cloudformation'\n steps.append((int(match.groups()[0]), match.groups()[1], filename, template_type))\n steps = sorted(steps, key=lambda x: x[0])\n\n return steps","def fetch_all(self, platform_list=[]):\n for platform in platform_list:\n for game in self.fetch(platform):\n yield game","def get_all_components(self, platform: RuntimeProcessorType) -> List[Component]:\n components: List[Component] = []\n\n catalogs = self._component_cache.get(platform.name, {})\n for catalog_name, catalog_properties in catalogs.items():\n components.extend(list(catalog_properties.get(\"components\", {}).values()))\n\n if not components and platform != RuntimeProcessorType.LOCAL:\n self.log.error(f\"No components could be found in any catalog for platform type '{platform.name}'.\")\n\n return components","def get_workflow_steps(self):\n return self._data_dict[self.KEY_WF_STEPS]","def get_next_steps(self, steps):\n step_list = []\n\n steps_remaining = set(steps.keys())\n counter = 0\n max_counter = 10000\n next_steps = set()\n\n for step in steps_remaining:\n dependencies = steps[step]\n if len(dependencies) == 0:\n next_steps.add(step)\n\n # this is the list of things that can be take for work now\n return sorted(next_steps)","def build_platform_step(self):\n return [ShellCommand(command=[\"../cordova-cli/bin/cordova\", \"build\", self.platform], workdir='build/mobilespec', timeout=CONFIG.build_timeout, description='Build', name='Build')]","def list_windows(cls):\n\n\t\tif cls._interface:\n\t\t\treturn tuple(cls(window) for window in cls._interface.list_windows())\n\t\telse:\n\t\t\traise NotImplementedError('Unsupported platform')","def get_matched_platforms(self, platform):\n raise NotImplemented","def plugman_steps(self):\n return [\n ShellCommand(command=[\"rm\", \"-rf\", \"cordova-*\"], workdir='build', haltOnFailure=False, description='Cordova Clean'),\n ShellCommand(command=[\"git\", \"clone\", CONFIG.repos['PLUGMAN'], \"cordova-plugman\"], workdir='build', haltOnFailure=True, description='Get Plugman'),\n NPMInstall(workdir='build/cordova-plugman', haltOnFailure=True, description='Install Plugman'),\n ShellCommand(command=[\"npm\", \"test\"], workdir='build/cordova-plugman', haltOnFailure=True, description='Test Plugman'),\n ]","def get_platform():\n query = {\n \"type\": \"config\",\n \"action\": \"get\",\n \"xpath\": \"/config/devices/entry[@name='localhost.localdomain']/platform\",\n }\n\n return __proxy__[\"panos.call\"](query)","def available_shells(self):","def steps(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['StepArgs']]]]:\n return pulumi.get(self, \"steps\")","def platform(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"platform\")","def __iter__( self ):\n assert isinstance( self._env, Env )\n assert isinstance( self._steps, list )\n\n return iter( self._steps )","def raw_steps(self):\n return self.obj_payload[\"steps\"]","def get_platforms(one_class):\n platforms = []\n\n platform = one_class.split(' ')[-1]\n if platform == 'win':\n platforms.append('Windows')\n if platform == 'mac':\n platforms.append('Mac os')\n if platform == 'linux':\n platforms.append('Linux')\n if platform == 'vr_supported':\n platforms.append('VR Supported')\n\n return platforms","def list():\n manager = Actions()\n tasks_list = manager.get_tasks_list()\n console_utils.print_tree(manager, tasks_list)","def get_platforms(self: object, parameters: dict = None, **kwargs) -> dict:\n # [GET] https://assets.falcon.crowdstrike.com/support/api/swagger.html#/custom-ioa/get-platformsMixin0\n return process_service_request(\n calling_object=self,\n endpoints=Endpoints,\n operation_id=\"get_platformsMixin0\",\n keywords=kwargs,\n params=parameters\n )","def steps(self):\n for step in self._steps:\n yield step","def get_all_environments():\n return ENVIRONMENTS","def xmlStationGetPlatforms(stationObj, stationElement, whenCreated):\n for platformElement in \\\n stationElement.iter(\"{http://trackernet.lul.co.uk}P\"):\n name = platformElement.get(\"N\")\n number = platformElement.get(\"Num\")\n trackCode = platformElement.get(\"TrackCode\")\n platformObj = stationObj.addPlatform(number, name, trackCode)\n xmlPlatformGetTrains(platformObj, platformElement, whenCreated)","def repos_clone_steps(self):\n platform = self.platform\n # required by coho tools to correctly resolve repo location\n if platform == \"blackberry10\":\n platform = \"blackberry\"\n return [\n ShellCommand(command=[\"node\", \"medic/checkout.js\", \"--path=medic/repos.json\", \"--cat=CORDOVA-MSPEC\", \"--releasebranch=\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone Mobilespec'),\n ShellCommand(command=[\"node\", \"medic/checkout.js\", \"--path=medic/repos.json\", \"--cat=CORDOVA-PLUGIN\", \"--releasebranch=\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone Plugins'),\n ShellCommand(command=[\"node\", \"medic/checkout.js\", \"--path=medic/repos.json\", \"--cat=CORDOVA-\" + platform, \"--releasebranch=\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone Platform'),\n ShellCommand(command=[\"node\", \"medic/checkout.js\", \"--path=medic/repos.json\", \"--cat=CORDOVA-JS\", \"--releasebranch=\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone JS'),\n ]","def get_entities():\n entities = []\n hc_api = hass.data[DOMAIN][config_entry.entry_id]\n for device_dict in hc_api.devices:\n entity_dicts = device_dict.get(CONF_ENTITIES, {}).get(\"switch\", [])\n entity_list = [HomeConnectProgramSwitch(**d) for d in entity_dicts]\n entity_list += [HomeConnectPowerSwitch(device_dict[CONF_DEVICE])]\n entities += entity_list\n return entities","def get_steps_names(self) -> List[str]:\n return [step.Name.lower() for step in self.Sequence if isinstance(step, Step) and step.Name != \"\"]","def list(args):\n experiments = sorted(os.listdir('./litmus'))\n print_color(\"Available Litmus Chaos Experiments:\\n\\n\")\n if (f\"{args.platform}\" == \"GKE\"):\n i = 1\n for experiment_file in experiments:\n print_color(f\"\\t{i}. {experiment_file.replace('.yaml', '')}\")\n i += 1\n\n if (f\"{args.platform}\" == \"kind\"):\n kind_supported = [\"pod-delete\",\"container-kill\",\"node-cpu-hog\",\"node-memory-hog\"]\n i = 0\n for i in range(0, len(kind_supported)):\n print_color(f\"\\t{i+1}. {kind_supported[i]}\")\n i += 1\n\n if (f\"{args.platform}\" == \"EKS\"):\n i = 1\n for experiment_file in experiments:\n print_color(f\"\\t{i}. {experiment_file.replace('.yaml', '')}\")\n i += 1","def platform_table(self):\n\n yield from md.table(\n [[md.pre(architecture) for architecture in self.database.architectures]]\n + [\n [\n self._release_list(architecture, platform)\n for architecture in self.database.architectures\n ]\n for platform in self.database.platforms\n ]\n )","def getPlatform(self):\n\t\treturn None","def ListInstances(self, hvparams=None):\n return [name for name in os.listdir(self._ROOT_DIR)\n if self._IsDirLive(utils.PathJoin(self._ROOT_DIR, name))]","def get_pipeline_steps(config):\n steps = []\n partial_execution = config.getboolean('General','partial_execution')\n if partial_execution:\n start_step = config.getint('General','start_step')\n end_step = config.getint('General','end_step')\n else:\n start_step = 1\n end_step = 6\n # Run batching and relation extraction steps?\n batching = True if start_step == 1 else False\n rel_extraction = True if end_step == 6 else False\n #nel = True if start_step<=4 and end_step>4 else False\n # Parallel pipeline steps, removed parsing.UnstParser(configmap) from list, \n parallel_step_list = [pre.Preprocessor(configmap), ner.Ner(configmap),nel.Nel(configmap)]\n parallel_steps = parallel_step_list[max(0,start_step-2):end_step-1]\n return parallel_steps, batching, rel_extraction","def getCurrentStep():","def do_steps(self):\n steps = self.get_step_conf()\n all_step_config = dict()\n for k, v in steps.items():\n tmp_list = list()\n all_step_config[k] = tmp_list\n start = v[\"Start Value\"]\n end = v[\"End Value\"]\n # special handling of edge length\n if(k == \"Edge Length\"):\n start = self.convert_to_tuple(start)\n end = self.convert_to_tuple(end)\n tmp_list.append(str(start))\n while(start != end):\n start = self.add_edge_length(\n start, self.convert_to_tuple(v[\"Step\"]))\n tmp_list.append(str(start))\n print start\n else:\n tmp_list.append(float(start))\n while float(start) < float(end):\n start = float(start) + float(v[\"Step\"])\n tmp_list.append(start)\n return all_step_config","def all_machines():\n return sorted(MACHINES, key=str)","def load_steps(self):\n # Clear stepsListWidget\n self.stepsListWidget.clear()\n\n steps = self.mgr.obj.steps\n for i, step in enumerate(steps):\n item = QListWidgetItem('Step {:d}: {:s}'.format(i, step.function_name))\n self.stepsListWidget.addItem(item)","def getTrajectories(self):\n\n\t\t\treturn self.__XPEnsembleBefore, self.__XPEnsembleAfter","def default_configuration_list(platform, ide):\n\n # All platforms support this format.\n results = [\"Debug\", \"Internal\", \"Release\"]\n\n # Xbox and Windows support link time code generation\n # as a platform\n if ide.is_visual_studio() and platform.is_windows(\n ) or platform in (PlatformTypes.xbox360,):\n results.append(\"Release_LTCG\")\n\n # Configurations specific to the Xbox 360\n if platform is PlatformTypes.xbox360:\n results.extend([\"Profile\", \"Profile_FastCap\", \"CodeAnalysis\"])\n return results","def platform_iterator(cls, platform):\r\n if cls.is_macosx_platform(platform):\r\n for plat in cls.iter_compatible_osx_platforms(platform):\r\n yield plat\r\n else:\r\n yield platform","async def async_process_hardware_platforms(hass: HomeAssistant) -> None:\n hass.data[DOMAIN][\"hardware_platform\"] = {}\n\n await async_process_integration_platforms(hass, DOMAIN, _register_hardware_platform)","def get_all_menu():","def instruction_steps(self) -> Sequence['outputs.CodelessUiConnectorConfigPropertiesResponseInstructionSteps']:\n return pulumi.get(self, \"instruction_steps\")","def _availableSteps( self, lst, includeSubproofs=True ):\n assert isinstance( lst, list )\n assert isinstance( includeSubproofs, bool )\n\n assert isinstance( self._level, int )\n assert isinstance( self._steps, list )\n assert isinstance( self._outter, Env ) or ( self._outter is None )\n\n if self._outter:\n self._outter._availableSteps( lst, False )\n\n for entry in self._steps:\n if isinstance( entry, tuple ):\n if includeSubproofs:\n lst.append( entry )\n else:\n lst.append( entry )","def extensions(self, global_step):\n return []","def extensions(self, global_step):\n return []","def scenario(self):\n scenario = []\n for action in self.application_tree['scenario']:\n scenario.append(action)\n return scenario","def get_platforms(tag, platform=\"pc\", region=\"eu\"):\n #\n platform_list = []\n try:\n context = ssl._create_unverified_context()\n platforms = json.load(\n const.codec(urlopen(const.URL + platform + \"/\" + region + \"/\" + tag + \"/get-platforms\", context=context)))\n #\n if \"error\" in platforms:\n raise BattleTagNotFound(platforms['error'])\n exit(1)\n #\n for platform in platforms['profile']:\n result = pl.Platforms(platform['platform'],\n platform['region'],\n platform['hasAccount'])\n platform_list.append(result)\n return platform_list\n except urllib.error.URLError as e:\n print(\"An error occurred when fetching stats\\n\" + e)\n exit(1)\n except Exception as e:\n print(\"An error occurred:\\n \" + str(e))\n exit(1)","def machines():\n return [name for name, state in _status()]","def platform():\n return ['linux']","def cli_steps(self):\n return [\n ShellCommand(command=[\"git\", \"clone\", \"-b\", CONFIG.branches['CLI'], CONFIG.repos['CLI'], \"cordova-cli\"], workdir='build', haltOnFailure=True, description='Clone CLI'),\n ShellCommand(command=[\"git\", \"clone\", \"--depth\", \"1\", \"-b\", CONFIG.branches['CORDOVA-LIB'], CONFIG.repos['CORDOVA-LIB'], \"cordova-lib\"], workdir='build', haltOnFailure=True, description='Clone cordova-lib'),\n NPMInstall([\"--production\"], workdir='build/cordova-lib/cordova-lib', haltOnFailure=True, description='Install cordova-lib'),\n ShellCommand(command=[\"rm\", \"-f\", \"npm-shrinkwrap.json\"], workdir='build/cordova-cli', haltOnFailure=False, description='Remove CLI SW'),\n NPMInstall(workdir='build/cordova-cli', haltOnFailure=True, description='Install CLI'),\n ShellCommand(command=[\"npm\", \"test\"], workdir='build/cordova-cli', haltOnFailure=True, description='Test CLI'),\n NPMInstall(workdir='build/cordova-js', haltOnFailure=True, description='Install JS'),\n ]","def _build_main_menu(self):\n if self._args.execution_environment:\n columns = [\"__name\", \"__version\", \"__shadowed\", \"__type\", \"path\"]\n else:\n columns = [\"__name\", \"__version\", \"__shadowed\", \"path\"]\n\n return Step(\n name=\"all_collections\",\n columns=columns,\n select_func=self._build_plugin_menu,\n tipe=\"menu\",\n value=self._collections,\n )","def get_all_setups_nodes():\n ta_roots = get_all_setups_roots()\n ta_nodes = [TechAnim_Setup(x) for x in ta_roots]\n return ta_nodes","def subclass_steps(cls):\n steps = []\n for attrname in dir(cls):\n obj = getattr(cls, attrname)\n if isinstance(obj, type) and issubclass(obj, StepBaseAbs):\n steps.append(obj)\n return steps","def get_clean_steps(self, node, ports):\n return [{'step': 'create_configuration',\n 'interface': 'raid',\n 'priority': 0},\n {'step': 'delete_configuration',\n 'interface': 'raid',\n 'priority': 0},\n {'step': 'erase_devices',\n 'interface': 'deploy',\n 'priority': 0},\n {'step': 'update_firmware',\n 'interface': 'management',\n 'priority': 0}]","def available_shells(self):\n return list(iterkeys(self._shells))","def prepare_mobilespec_steps(self):\n platform = self.platform\n # required by coho tools to correctly resolve repo location\n if platform == \"blackberry10\":\n platform = \"blackberry\"\n return [\n NPMInstall(workdir='build/cordova-mobile-spec/createmobilespec', haltOnFailure=True, description='Install createmobilespec'),\n ShellCommand(command=[\"cordova-coho/coho\", \"npm-link\"], workdir='build', haltOnFailure=True, description='COHO npm-link'),\n # add --skiplink for createmobilespec since\n # it requires cordova-plugman repo to be cloned\n # Re-directing node output to a file is a workaround for a node.js bug\n # on windows where a piped stream does not get flushed when process.exit is called.\n # https://github.com/joyent/node/issues/3584\n ShellCommand(command=\"node cordova-mobile-spec/createmobilespec/createmobilespec.js --\" + platform + \" mobilespec --debug --skiplink >createmobilespecOut.txt 2>&1\",\n workdir='build', haltOnFailure=True, description='Run createmobilespec', logfiles = {\"log\" : \"createmobilespecOut.txt\"}),\n ShellCommand(command=[\"node\", \"medic/updateconfig.js\", \"--\" + self.platform], workdir='build', haltOnFailure=True, description='Update config')\n ]","def step_list(test, checks=None):\n if checks is None:\n checks = []\n test.cmd(\n \"az networkcloud virtualmachine console list \"\n \"--resource-group {resourceGroup} --virtual-machine-name {virtualMachineName}\",\n checks=checks,\n )","def list():\n infos = manager.get_all()\n if not infos:\n print(\"No known TensorBoard instances running.\")\n return\n\n print(\"Known TensorBoard instances:\")\n for info in infos:\n template = \" - port {port}: {data_source} (started {delta} ago; pid {pid})\"\n print(template.format(\n port=info.port,\n data_source=manager.data_source_from_info(info),\n delta=_time_delta_from_info(info),\n pid=info.pid,\n ))","def get_platform_combinations():\n mapped_osname = platform_map(g_osname)\n mapped_osarch = g_osarch\n ret = [mapped_osname]\n while True:\n ret += [mapped_osarch, mapped_osname + \"-\" + mapped_osarch]\n mapped_osarch = platform_map_iterate(mapped_osarch)\n if not mapped_osarch:\n break\n return sorted(ret, reverse=True) + [\"default\"]","def find_unique_platforms(self):\n db_engine = sqlalchemy.create_engine(self.db_info_obj.dbConn)\n session_sqlalc = sqlalchemy.orm.sessionmaker(bind=db_engine)\n ses = session_sqlalc()\n platforms = ses.query(EDDSentinel1ASF.Platform).group_by(EDDSentinel1ASF.Platform)\n ses.close()\n return platforms","def steps_location(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"steps_location\")","def get_buildroot(self, worker_metadatas):\n buildroots = []\n for platform in sorted(worker_metadatas.keys()):\n for instance in worker_metadatas[platform]['buildroots']:\n instance['id'] = '{}-{}'.format(platform, instance['id'])\n buildroots.append(instance)\n\n return buildroots","def extension_hooks(self, global_step):\n return []","def extension_hooks(self, global_step):\n return []","def list_test_instances():\n run('ls -1 %s' % env.site_root)","def all_upstream_steps(self):\n all_steps_ = {}\n all_steps_ = self._get_steps(all_steps_)\n return all_steps_","def info_list(self):\n import numpy.distutils.proc as numpy_proc\n res = self.apply(numpy_proc.machine_info,())\n return res","def ls():\n # TODO: listing all availabe containers form sequence\n return","def list_systems():\n return sorted(systems.keys())","def default_steps(self):\n steps = {}\n for code, color in (\n ('Client', '255,255,255'),\n ('Online', '254,92,255'),\n ('Roto', '253,254,152'),\n ('MM', '254,151,152'),\n ('Anm', '254,173,146'),\n ('FX', '255,218,137'),\n ('Light', '254,205,138'),\n ('Comp', '161,236,154'),\n ('Art', '0,230,254'),\n ('Model', '254,205,138'),\n ('Rig', '253,254,152'),\n ('Surface', '231,251,154'),\n ):\n steps[code] = self.find_or_create('Step', dict(\n code=code,\n short_name=code,\n color=color,\n ))\n return steps","def platform(self):\n return self.random.choice([\n 'Laptop', \n 'Desktop', \n 'Workstation', \n 'Server', \n 'Virtual Machine', \n 'Container', \n 'Micro-Service', \n 'Droplet', \n 'SaaS'\n ])","def fetch_models(self):\n if self.model_pool is None:\n print(\"Please train a model first.\", file=STDE)\n EXIT(1)\n else:\n return [copy.deepcopy(m.steps[-1][-1]) for m in self.model_pool]","def ls():\n cfgmgr = ConfigManager()\n apps = cfgmgr['apps']\n for i in apps:\n print(fc(\"- {g}{appname}{rst}\", appname=i))","def list_switches(self):\n return [x for x,y in self.devices.items() if y.device_type == \"Switch\"]"],"string":"[\n \"def availableSteps( self ):\\n assert isinstance( self._level, int )\\n assert isinstance( self._steps, list )\\n assert isinstance( self._outter, Env ) or ( self._outter is None )\\n\\n lst = [ ]\\n self._availableSteps( lst )\\n return lst\",\n \"def Platforms():\\n return platforms\",\n \"def list_platforms(self):\\n return self.do_rpc('list_platforms')\",\n \"def available_platforms(verbose=True):\\n\\n\\n import simtk.openmm as mm\\n\\n platforms_available = []\\n\\n for ii in range(mm.Platform.getNumPlatforms()):\\n platform_name = mm.Platform.getPlatform(ii).getName()\\n platform = mm.Platform.getPlatformByName(platform_name)\\n platform_speed = platform.getSpeed()\\n platforms_available.append(platform_name)\\n if verbose:\\n print('Platform {} with speed {}'.format(platform_name,platform_speed))\\n del(platform_name, platform, platform_speed)\\n\\n if verbose is False:\\n return platforms_available\",\n \"def getSteps():\",\n \"def platforms(self):\\n return self.rpc.call(MsfRpcMethod.ModulePlatforms)\",\n \"def get_platforms(self):\\n _log.debug(\\\"Passing platforms back: {}\\\".format(\\n self._registered_platforms.keys()))\\n return self._registered_platforms.values()\",\n \"def _get_steps(self):\\n return self.steps\",\n \"def getSteps( self ):\\n\\n return self.adb.get( 'steps' )\",\n \"def init_workspace_steps(self):\\n return [\\n InstallShellJS(),\\n RMCommand(path=\\\"~/.cordova/\\\" + self.platform, workdir='build', haltOnFailure=False, description='Remove cache'),\\n RMCommand(path=\\\"*\\\", workdir='build', haltOnFailure=False, description='Clean workdir'),\\n ShellCommand(command=[\\\"git\\\", \\\"clone\\\", \\\"--depth\\\", \\\"1\\\", \\\"-b\\\", CONFIG.branches['TESTMASTER'], CONFIG.repos['TESTMASTER'], \\\"medic\\\"], workdir='build', haltOnFailure=True, description='Get Medic'),\\n # --production switch is used to speed up installation + fruitstrap dev dependency is not supported on Windows\\n NPMInstall([\\\"--production\\\"], workdir='build/medic', haltOnFailure=True, description='Install Medic'),\\n FileDownload(mastersrc=FP+\\\"cordova-config.json\\\", slavedest=\\\"medic/config.json\\\", haltOnFailure=True),\\n FileDownload(mastersrc=FP+\\\"cordova-repos.json\\\", slavedest=\\\"medic/repos.json\\\", haltOnFailure=True),\\n ShellCommand(command=[\\\"git\\\", \\\"clone\\\", \\\"--depth\\\", \\\"1\\\", CONFIG.repos['COHO']], workdir='build', haltOnFailure=True, description='Get COHO'),\\n NPMInstall([\\\"--production\\\"], workdir='build/cordova-coho', haltOnFailure=True, description='Install COHO'),\\n ]\",\n \"def platforms(self):\\n logger.debug(\\\"Get platforms\\\")\\n return self._raw_api.platforms.get()\",\n \"def get_steps(self) -> list:\\n ret_val = []\\n for step_id in self:\\n step_body = Steps.cache_step(step_id)\\n if step_body is not None:\\n ret_val.append(step_body)\\n\\n return ret_val\",\n \"def get_platforms(self):\\n if self.platform == 'All':\\n return PLATFORMS\\n else:\\n return self.platform.split(':')\",\n \"def getProcessingHistoryList(context):\\n projectDir = context.projectDir\\n steps = []\\n history = GenericMetadata._readEntriesForSection(projectDir, GenericMetadata.HISTORY_SECTION)\\n try:\\n idx = int(history['numsteps']) + 1\\n for i in xrange(1, idx):\\n key = GenericMetadata.HISTORY_PROTO + str(i)\\n steps.append(history[key])\\n except KeyError:\\n pass\\n \\n return steps\",\n \"def get_steps(self):\\n return self.steps\",\n \"def get_steps(self):\\n return self.steps\",\n \"def availablePremises( self ):\\n assert isinstance( self._env, Env )\\n assert isinstance( self._steps, list )\\n\\n return self._env.availableSteps( )\",\n \"def _GetMachineList(self):\\n machines = self._experiment.remote\\n # All Label.remote is a sublist of experiment.remote.\\n for l in self._experiment.labels:\\n for r in l.remote:\\n assert r in machines\\n return machines\",\n \"def get_commands(steplist):\\n commands = []\\n for step in steplist:\\n if hasattr(step, 'command'):\\n cmdhash = {}\\n renderables = []\\n accumulateClassList(step.__class__, 'renderables', renderables)\\n\\n for renderable in renderables:\\n setattr(step, renderable, step.build.render(getattr(step,\\n renderable)))\\n\\n cmdhash['name'] = step.name\\n cmdhash['command'] = step.command\\n cmdhash['workdir'] = step.workdir\\n if hasattr(step, 'env'):\\n cmdhash['env'] = step.env\\n else:\\n cmdhash['env'] = {}\\n if hasattr(step, 'timeout'):\\n print \\\"yay!~\\\"\\n cmdhash['timeout'] = step.timeout\\n\\n cmdhash['description'] = step.description\\n cmdhash['descriptionDone'] = step.descriptionDone\\n commands.append(cmdhash)\\n return commands\",\n \"def get_platforms():\\n # Get all CL platforms\\n platforms = cl.get_platforms()\\n for p in platforms:\\n # Not a safe way\\n p.__class__ = Platform\\n p.devices = p.get_devices()\\n for d in p.devices:\\n d.__class__ = Device\\n return platforms\",\n \"def getWorkflowSteps(self):\\n\\n return self.dbase.getProcessSteps(self.scene)\",\n \"def steps(self):\\n for step in self._get_paged(\\\"steps\\\", trailing=True):\\n yield self.__get_object(step)\\n\\n return\",\n \"def deploy_steps(self):\\n return [ShellCommand(command=[\\\"node\\\", \\\"medic/build_\\\" + self.platform + \\\".js\\\"], workdir='build', timeout=CONFIG.build_timeout, description='Run tests', name='Run tests')]\",\n \"def platforms(self) -> Any:\\n\\n return search_api(\\\"platforms\\\")\",\n \"def default_platform_list(self):\\n for platform in self.database.platforms:\\n if self.database.has(platform=platform, architecture=default.architecture):\\n release = self.database.latest_release(\\n platform, architecture=default.architecture\\n )\\n name = _format_platform(platform, release)\\n image = f\\\"{_REPOSITORY}:<version>-{platform}\\\"\\n link = md.link(md.pre(image), md.anchor(name))\\n yield md.item(f\\\"{link} ({name})\\\")\",\n \"def steps(self) -> pulumi.Output[Sequence['outputs.StepResponse']]:\\n return pulumi.get(self, \\\"steps\\\")\",\n \"def next_steps(self) -> List[FlowNode]:\\n return [node for predicate, node in self._current_step.children]\",\n \"def _get_install_steps(self):\\n\\n content = self._get_yaml_content()\\n\\n return self._fix_install_steps(content['install'])\",\n \"def platform(self) -> Platform:\\n _args: list[Arg] = []\\n _ctx = self._select(\\\"platform\\\", _args)\\n return _ctx.execute_sync(Platform)\",\n \"def steps(self):\\n\\n if not os.path.exists(self.build_path):\\n raise exceptions.ProjectNotBuildError()\\n\\n steps = []\\n for filename in os.listdir(self.build_path):\\n match = re.match(r'(\\\\d{4})_(.*)\\\\.json', filename)\\n if not match:\\n continue\\n\\n with open(os.path.join(self.build_path, filename), 'r') as f:\\n template = json.loads(f.read())\\n\\n template_type = 'custom' if '_type' in template else 'cloudformation'\\n steps.append((int(match.groups()[0]), match.groups()[1], filename, template_type))\\n steps = sorted(steps, key=lambda x: x[0])\\n\\n return steps\",\n \"def fetch_all(self, platform_list=[]):\\n for platform in platform_list:\\n for game in self.fetch(platform):\\n yield game\",\n \"def get_all_components(self, platform: RuntimeProcessorType) -> List[Component]:\\n components: List[Component] = []\\n\\n catalogs = self._component_cache.get(platform.name, {})\\n for catalog_name, catalog_properties in catalogs.items():\\n components.extend(list(catalog_properties.get(\\\"components\\\", {}).values()))\\n\\n if not components and platform != RuntimeProcessorType.LOCAL:\\n self.log.error(f\\\"No components could be found in any catalog for platform type '{platform.name}'.\\\")\\n\\n return components\",\n \"def get_workflow_steps(self):\\n return self._data_dict[self.KEY_WF_STEPS]\",\n \"def get_next_steps(self, steps):\\n step_list = []\\n\\n steps_remaining = set(steps.keys())\\n counter = 0\\n max_counter = 10000\\n next_steps = set()\\n\\n for step in steps_remaining:\\n dependencies = steps[step]\\n if len(dependencies) == 0:\\n next_steps.add(step)\\n\\n # this is the list of things that can be take for work now\\n return sorted(next_steps)\",\n \"def build_platform_step(self):\\n return [ShellCommand(command=[\\\"../cordova-cli/bin/cordova\\\", \\\"build\\\", self.platform], workdir='build/mobilespec', timeout=CONFIG.build_timeout, description='Build', name='Build')]\",\n \"def list_windows(cls):\\n\\n\\t\\tif cls._interface:\\n\\t\\t\\treturn tuple(cls(window) for window in cls._interface.list_windows())\\n\\t\\telse:\\n\\t\\t\\traise NotImplementedError('Unsupported platform')\",\n \"def get_matched_platforms(self, platform):\\n raise NotImplemented\",\n \"def plugman_steps(self):\\n return [\\n ShellCommand(command=[\\\"rm\\\", \\\"-rf\\\", \\\"cordova-*\\\"], workdir='build', haltOnFailure=False, description='Cordova Clean'),\\n ShellCommand(command=[\\\"git\\\", \\\"clone\\\", CONFIG.repos['PLUGMAN'], \\\"cordova-plugman\\\"], workdir='build', haltOnFailure=True, description='Get Plugman'),\\n NPMInstall(workdir='build/cordova-plugman', haltOnFailure=True, description='Install Plugman'),\\n ShellCommand(command=[\\\"npm\\\", \\\"test\\\"], workdir='build/cordova-plugman', haltOnFailure=True, description='Test Plugman'),\\n ]\",\n \"def get_platform():\\n query = {\\n \\\"type\\\": \\\"config\\\",\\n \\\"action\\\": \\\"get\\\",\\n \\\"xpath\\\": \\\"/config/devices/entry[@name='localhost.localdomain']/platform\\\",\\n }\\n\\n return __proxy__[\\\"panos.call\\\"](query)\",\n \"def available_shells(self):\",\n \"def steps(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['StepArgs']]]]:\\n return pulumi.get(self, \\\"steps\\\")\",\n \"def platform(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"platform\\\")\",\n \"def __iter__( self ):\\n assert isinstance( self._env, Env )\\n assert isinstance( self._steps, list )\\n\\n return iter( self._steps )\",\n \"def raw_steps(self):\\n return self.obj_payload[\\\"steps\\\"]\",\n \"def get_platforms(one_class):\\n platforms = []\\n\\n platform = one_class.split(' ')[-1]\\n if platform == 'win':\\n platforms.append('Windows')\\n if platform == 'mac':\\n platforms.append('Mac os')\\n if platform == 'linux':\\n platforms.append('Linux')\\n if platform == 'vr_supported':\\n platforms.append('VR Supported')\\n\\n return platforms\",\n \"def list():\\n manager = Actions()\\n tasks_list = manager.get_tasks_list()\\n console_utils.print_tree(manager, tasks_list)\",\n \"def get_platforms(self: object, parameters: dict = None, **kwargs) -> dict:\\n # [GET] https://assets.falcon.crowdstrike.com/support/api/swagger.html#/custom-ioa/get-platformsMixin0\\n return process_service_request(\\n calling_object=self,\\n endpoints=Endpoints,\\n operation_id=\\\"get_platformsMixin0\\\",\\n keywords=kwargs,\\n params=parameters\\n )\",\n \"def steps(self):\\n for step in self._steps:\\n yield step\",\n \"def get_all_environments():\\n return ENVIRONMENTS\",\n \"def xmlStationGetPlatforms(stationObj, stationElement, whenCreated):\\n for platformElement in \\\\\\n stationElement.iter(\\\"{http://trackernet.lul.co.uk}P\\\"):\\n name = platformElement.get(\\\"N\\\")\\n number = platformElement.get(\\\"Num\\\")\\n trackCode = platformElement.get(\\\"TrackCode\\\")\\n platformObj = stationObj.addPlatform(number, name, trackCode)\\n xmlPlatformGetTrains(platformObj, platformElement, whenCreated)\",\n \"def repos_clone_steps(self):\\n platform = self.platform\\n # required by coho tools to correctly resolve repo location\\n if platform == \\\"blackberry10\\\":\\n platform = \\\"blackberry\\\"\\n return [\\n ShellCommand(command=[\\\"node\\\", \\\"medic/checkout.js\\\", \\\"--path=medic/repos.json\\\", \\\"--cat=CORDOVA-MSPEC\\\", \\\"--releasebranch=\\\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone Mobilespec'),\\n ShellCommand(command=[\\\"node\\\", \\\"medic/checkout.js\\\", \\\"--path=medic/repos.json\\\", \\\"--cat=CORDOVA-PLUGIN\\\", \\\"--releasebranch=\\\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone Plugins'),\\n ShellCommand(command=[\\\"node\\\", \\\"medic/checkout.js\\\", \\\"--path=medic/repos.json\\\", \\\"--cat=CORDOVA-\\\" + platform, \\\"--releasebranch=\\\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone Platform'),\\n ShellCommand(command=[\\\"node\\\", \\\"medic/checkout.js\\\", \\\"--path=medic/repos.json\\\", \\\"--cat=CORDOVA-JS\\\", \\\"--releasebranch=\\\" + CONFIG.branch_release], workdir='build', haltOnFailure=True, description='Clone JS'),\\n ]\",\n \"def get_entities():\\n entities = []\\n hc_api = hass.data[DOMAIN][config_entry.entry_id]\\n for device_dict in hc_api.devices:\\n entity_dicts = device_dict.get(CONF_ENTITIES, {}).get(\\\"switch\\\", [])\\n entity_list = [HomeConnectProgramSwitch(**d) for d in entity_dicts]\\n entity_list += [HomeConnectPowerSwitch(device_dict[CONF_DEVICE])]\\n entities += entity_list\\n return entities\",\n \"def get_steps_names(self) -> List[str]:\\n return [step.Name.lower() for step in self.Sequence if isinstance(step, Step) and step.Name != \\\"\\\"]\",\n \"def list(args):\\n experiments = sorted(os.listdir('./litmus'))\\n print_color(\\\"Available Litmus Chaos Experiments:\\\\n\\\\n\\\")\\n if (f\\\"{args.platform}\\\" == \\\"GKE\\\"):\\n i = 1\\n for experiment_file in experiments:\\n print_color(f\\\"\\\\t{i}. {experiment_file.replace('.yaml', '')}\\\")\\n i += 1\\n\\n if (f\\\"{args.platform}\\\" == \\\"kind\\\"):\\n kind_supported = [\\\"pod-delete\\\",\\\"container-kill\\\",\\\"node-cpu-hog\\\",\\\"node-memory-hog\\\"]\\n i = 0\\n for i in range(0, len(kind_supported)):\\n print_color(f\\\"\\\\t{i+1}. {kind_supported[i]}\\\")\\n i += 1\\n\\n if (f\\\"{args.platform}\\\" == \\\"EKS\\\"):\\n i = 1\\n for experiment_file in experiments:\\n print_color(f\\\"\\\\t{i}. {experiment_file.replace('.yaml', '')}\\\")\\n i += 1\",\n \"def platform_table(self):\\n\\n yield from md.table(\\n [[md.pre(architecture) for architecture in self.database.architectures]]\\n + [\\n [\\n self._release_list(architecture, platform)\\n for architecture in self.database.architectures\\n ]\\n for platform in self.database.platforms\\n ]\\n )\",\n \"def getPlatform(self):\\n\\t\\treturn None\",\n \"def ListInstances(self, hvparams=None):\\n return [name for name in os.listdir(self._ROOT_DIR)\\n if self._IsDirLive(utils.PathJoin(self._ROOT_DIR, name))]\",\n \"def get_pipeline_steps(config):\\n steps = []\\n partial_execution = config.getboolean('General','partial_execution')\\n if partial_execution:\\n start_step = config.getint('General','start_step')\\n end_step = config.getint('General','end_step')\\n else:\\n start_step = 1\\n end_step = 6\\n # Run batching and relation extraction steps?\\n batching = True if start_step == 1 else False\\n rel_extraction = True if end_step == 6 else False\\n #nel = True if start_step<=4 and end_step>4 else False\\n # Parallel pipeline steps, removed parsing.UnstParser(configmap) from list, \\n parallel_step_list = [pre.Preprocessor(configmap), ner.Ner(configmap),nel.Nel(configmap)]\\n parallel_steps = parallel_step_list[max(0,start_step-2):end_step-1]\\n return parallel_steps, batching, rel_extraction\",\n \"def getCurrentStep():\",\n \"def do_steps(self):\\n steps = self.get_step_conf()\\n all_step_config = dict()\\n for k, v in steps.items():\\n tmp_list = list()\\n all_step_config[k] = tmp_list\\n start = v[\\\"Start Value\\\"]\\n end = v[\\\"End Value\\\"]\\n # special handling of edge length\\n if(k == \\\"Edge Length\\\"):\\n start = self.convert_to_tuple(start)\\n end = self.convert_to_tuple(end)\\n tmp_list.append(str(start))\\n while(start != end):\\n start = self.add_edge_length(\\n start, self.convert_to_tuple(v[\\\"Step\\\"]))\\n tmp_list.append(str(start))\\n print start\\n else:\\n tmp_list.append(float(start))\\n while float(start) < float(end):\\n start = float(start) + float(v[\\\"Step\\\"])\\n tmp_list.append(start)\\n return all_step_config\",\n \"def all_machines():\\n return sorted(MACHINES, key=str)\",\n \"def load_steps(self):\\n # Clear stepsListWidget\\n self.stepsListWidget.clear()\\n\\n steps = self.mgr.obj.steps\\n for i, step in enumerate(steps):\\n item = QListWidgetItem('Step {:d}: {:s}'.format(i, step.function_name))\\n self.stepsListWidget.addItem(item)\",\n \"def getTrajectories(self):\\n\\n\\t\\t\\treturn self.__XPEnsembleBefore, self.__XPEnsembleAfter\",\n \"def default_configuration_list(platform, ide):\\n\\n # All platforms support this format.\\n results = [\\\"Debug\\\", \\\"Internal\\\", \\\"Release\\\"]\\n\\n # Xbox and Windows support link time code generation\\n # as a platform\\n if ide.is_visual_studio() and platform.is_windows(\\n ) or platform in (PlatformTypes.xbox360,):\\n results.append(\\\"Release_LTCG\\\")\\n\\n # Configurations specific to the Xbox 360\\n if platform is PlatformTypes.xbox360:\\n results.extend([\\\"Profile\\\", \\\"Profile_FastCap\\\", \\\"CodeAnalysis\\\"])\\n return results\",\n \"def platform_iterator(cls, platform):\\r\\n if cls.is_macosx_platform(platform):\\r\\n for plat in cls.iter_compatible_osx_platforms(platform):\\r\\n yield plat\\r\\n else:\\r\\n yield platform\",\n \"async def async_process_hardware_platforms(hass: HomeAssistant) -> None:\\n hass.data[DOMAIN][\\\"hardware_platform\\\"] = {}\\n\\n await async_process_integration_platforms(hass, DOMAIN, _register_hardware_platform)\",\n \"def get_all_menu():\",\n \"def instruction_steps(self) -> Sequence['outputs.CodelessUiConnectorConfigPropertiesResponseInstructionSteps']:\\n return pulumi.get(self, \\\"instruction_steps\\\")\",\n \"def _availableSteps( self, lst, includeSubproofs=True ):\\n assert isinstance( lst, list )\\n assert isinstance( includeSubproofs, bool )\\n\\n assert isinstance( self._level, int )\\n assert isinstance( self._steps, list )\\n assert isinstance( self._outter, Env ) or ( self._outter is None )\\n\\n if self._outter:\\n self._outter._availableSteps( lst, False )\\n\\n for entry in self._steps:\\n if isinstance( entry, tuple ):\\n if includeSubproofs:\\n lst.append( entry )\\n else:\\n lst.append( entry )\",\n \"def extensions(self, global_step):\\n return []\",\n \"def extensions(self, global_step):\\n return []\",\n \"def scenario(self):\\n scenario = []\\n for action in self.application_tree['scenario']:\\n scenario.append(action)\\n return scenario\",\n \"def get_platforms(tag, platform=\\\"pc\\\", region=\\\"eu\\\"):\\n #\\n platform_list = []\\n try:\\n context = ssl._create_unverified_context()\\n platforms = json.load(\\n const.codec(urlopen(const.URL + platform + \\\"/\\\" + region + \\\"/\\\" + tag + \\\"/get-platforms\\\", context=context)))\\n #\\n if \\\"error\\\" in platforms:\\n raise BattleTagNotFound(platforms['error'])\\n exit(1)\\n #\\n for platform in platforms['profile']:\\n result = pl.Platforms(platform['platform'],\\n platform['region'],\\n platform['hasAccount'])\\n platform_list.append(result)\\n return platform_list\\n except urllib.error.URLError as e:\\n print(\\\"An error occurred when fetching stats\\\\n\\\" + e)\\n exit(1)\\n except Exception as e:\\n print(\\\"An error occurred:\\\\n \\\" + str(e))\\n exit(1)\",\n \"def machines():\\n return [name for name, state in _status()]\",\n \"def platform():\\n return ['linux']\",\n \"def cli_steps(self):\\n return [\\n ShellCommand(command=[\\\"git\\\", \\\"clone\\\", \\\"-b\\\", CONFIG.branches['CLI'], CONFIG.repos['CLI'], \\\"cordova-cli\\\"], workdir='build', haltOnFailure=True, description='Clone CLI'),\\n ShellCommand(command=[\\\"git\\\", \\\"clone\\\", \\\"--depth\\\", \\\"1\\\", \\\"-b\\\", CONFIG.branches['CORDOVA-LIB'], CONFIG.repos['CORDOVA-LIB'], \\\"cordova-lib\\\"], workdir='build', haltOnFailure=True, description='Clone cordova-lib'),\\n NPMInstall([\\\"--production\\\"], workdir='build/cordova-lib/cordova-lib', haltOnFailure=True, description='Install cordova-lib'),\\n ShellCommand(command=[\\\"rm\\\", \\\"-f\\\", \\\"npm-shrinkwrap.json\\\"], workdir='build/cordova-cli', haltOnFailure=False, description='Remove CLI SW'),\\n NPMInstall(workdir='build/cordova-cli', haltOnFailure=True, description='Install CLI'),\\n ShellCommand(command=[\\\"npm\\\", \\\"test\\\"], workdir='build/cordova-cli', haltOnFailure=True, description='Test CLI'),\\n NPMInstall(workdir='build/cordova-js', haltOnFailure=True, description='Install JS'),\\n ]\",\n \"def _build_main_menu(self):\\n if self._args.execution_environment:\\n columns = [\\\"__name\\\", \\\"__version\\\", \\\"__shadowed\\\", \\\"__type\\\", \\\"path\\\"]\\n else:\\n columns = [\\\"__name\\\", \\\"__version\\\", \\\"__shadowed\\\", \\\"path\\\"]\\n\\n return Step(\\n name=\\\"all_collections\\\",\\n columns=columns,\\n select_func=self._build_plugin_menu,\\n tipe=\\\"menu\\\",\\n value=self._collections,\\n )\",\n \"def get_all_setups_nodes():\\n ta_roots = get_all_setups_roots()\\n ta_nodes = [TechAnim_Setup(x) for x in ta_roots]\\n return ta_nodes\",\n \"def subclass_steps(cls):\\n steps = []\\n for attrname in dir(cls):\\n obj = getattr(cls, attrname)\\n if isinstance(obj, type) and issubclass(obj, StepBaseAbs):\\n steps.append(obj)\\n return steps\",\n \"def get_clean_steps(self, node, ports):\\n return [{'step': 'create_configuration',\\n 'interface': 'raid',\\n 'priority': 0},\\n {'step': 'delete_configuration',\\n 'interface': 'raid',\\n 'priority': 0},\\n {'step': 'erase_devices',\\n 'interface': 'deploy',\\n 'priority': 0},\\n {'step': 'update_firmware',\\n 'interface': 'management',\\n 'priority': 0}]\",\n \"def available_shells(self):\\n return list(iterkeys(self._shells))\",\n \"def prepare_mobilespec_steps(self):\\n platform = self.platform\\n # required by coho tools to correctly resolve repo location\\n if platform == \\\"blackberry10\\\":\\n platform = \\\"blackberry\\\"\\n return [\\n NPMInstall(workdir='build/cordova-mobile-spec/createmobilespec', haltOnFailure=True, description='Install createmobilespec'),\\n ShellCommand(command=[\\\"cordova-coho/coho\\\", \\\"npm-link\\\"], workdir='build', haltOnFailure=True, description='COHO npm-link'),\\n # add --skiplink for createmobilespec since\\n # it requires cordova-plugman repo to be cloned\\n # Re-directing node output to a file is a workaround for a node.js bug\\n # on windows where a piped stream does not get flushed when process.exit is called.\\n # https://github.com/joyent/node/issues/3584\\n ShellCommand(command=\\\"node cordova-mobile-spec/createmobilespec/createmobilespec.js --\\\" + platform + \\\" mobilespec --debug --skiplink >createmobilespecOut.txt 2>&1\\\",\\n workdir='build', haltOnFailure=True, description='Run createmobilespec', logfiles = {\\\"log\\\" : \\\"createmobilespecOut.txt\\\"}),\\n ShellCommand(command=[\\\"node\\\", \\\"medic/updateconfig.js\\\", \\\"--\\\" + self.platform], workdir='build', haltOnFailure=True, description='Update config')\\n ]\",\n \"def step_list(test, checks=None):\\n if checks is None:\\n checks = []\\n test.cmd(\\n \\\"az networkcloud virtualmachine console list \\\"\\n \\\"--resource-group {resourceGroup} --virtual-machine-name {virtualMachineName}\\\",\\n checks=checks,\\n )\",\n \"def list():\\n infos = manager.get_all()\\n if not infos:\\n print(\\\"No known TensorBoard instances running.\\\")\\n return\\n\\n print(\\\"Known TensorBoard instances:\\\")\\n for info in infos:\\n template = \\\" - port {port}: {data_source} (started {delta} ago; pid {pid})\\\"\\n print(template.format(\\n port=info.port,\\n data_source=manager.data_source_from_info(info),\\n delta=_time_delta_from_info(info),\\n pid=info.pid,\\n ))\",\n \"def get_platform_combinations():\\n mapped_osname = platform_map(g_osname)\\n mapped_osarch = g_osarch\\n ret = [mapped_osname]\\n while True:\\n ret += [mapped_osarch, mapped_osname + \\\"-\\\" + mapped_osarch]\\n mapped_osarch = platform_map_iterate(mapped_osarch)\\n if not mapped_osarch:\\n break\\n return sorted(ret, reverse=True) + [\\\"default\\\"]\",\n \"def find_unique_platforms(self):\\n db_engine = sqlalchemy.create_engine(self.db_info_obj.dbConn)\\n session_sqlalc = sqlalchemy.orm.sessionmaker(bind=db_engine)\\n ses = session_sqlalc()\\n platforms = ses.query(EDDSentinel1ASF.Platform).group_by(EDDSentinel1ASF.Platform)\\n ses.close()\\n return platforms\",\n \"def steps_location(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"steps_location\\\")\",\n \"def get_buildroot(self, worker_metadatas):\\n buildroots = []\\n for platform in sorted(worker_metadatas.keys()):\\n for instance in worker_metadatas[platform]['buildroots']:\\n instance['id'] = '{}-{}'.format(platform, instance['id'])\\n buildroots.append(instance)\\n\\n return buildroots\",\n \"def extension_hooks(self, global_step):\\n return []\",\n \"def extension_hooks(self, global_step):\\n return []\",\n \"def list_test_instances():\\n run('ls -1 %s' % env.site_root)\",\n \"def all_upstream_steps(self):\\n all_steps_ = {}\\n all_steps_ = self._get_steps(all_steps_)\\n return all_steps_\",\n \"def info_list(self):\\n import numpy.distutils.proc as numpy_proc\\n res = self.apply(numpy_proc.machine_info,())\\n return res\",\n \"def ls():\\n # TODO: listing all availabe containers form sequence\\n return\",\n \"def list_systems():\\n return sorted(systems.keys())\",\n \"def default_steps(self):\\n steps = {}\\n for code, color in (\\n ('Client', '255,255,255'),\\n ('Online', '254,92,255'),\\n ('Roto', '253,254,152'),\\n ('MM', '254,151,152'),\\n ('Anm', '254,173,146'),\\n ('FX', '255,218,137'),\\n ('Light', '254,205,138'),\\n ('Comp', '161,236,154'),\\n ('Art', '0,230,254'),\\n ('Model', '254,205,138'),\\n ('Rig', '253,254,152'),\\n ('Surface', '231,251,154'),\\n ):\\n steps[code] = self.find_or_create('Step', dict(\\n code=code,\\n short_name=code,\\n color=color,\\n ))\\n return steps\",\n \"def platform(self):\\n return self.random.choice([\\n 'Laptop', \\n 'Desktop', \\n 'Workstation', \\n 'Server', \\n 'Virtual Machine', \\n 'Container', \\n 'Micro-Service', \\n 'Droplet', \\n 'SaaS'\\n ])\",\n \"def fetch_models(self):\\n if self.model_pool is None:\\n print(\\\"Please train a model first.\\\", file=STDE)\\n EXIT(1)\\n else:\\n return [copy.deepcopy(m.steps[-1][-1]) for m in self.model_pool]\",\n \"def ls():\\n cfgmgr = ConfigManager()\\n apps = cfgmgr['apps']\\n for i in apps:\\n print(fc(\\\"- {g}{appname}{rst}\\\", appname=i))\",\n \"def list_switches(self):\\n return [x for x,y in self.devices.items() if y.device_type == \\\"Switch\\\"]\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6643733","0.6476299","0.6185028","0.59915143","0.5967349","0.59573674","0.5938493","0.5935553","0.59315646","0.5929291","0.5864497","0.58506036","0.58318293","0.58021766","0.5801714","0.57479554","0.5633305","0.5621189","0.56003636","0.55945224","0.5584528","0.55766237","0.55636436","0.55533814","0.5499317","0.548607","0.54598343","0.54289204","0.54279137","0.5400402","0.5377158","0.5334138","0.53278565","0.52944416","0.5277428","0.5230207","0.52288616","0.52286816","0.5202022","0.51967764","0.5193806","0.5192525","0.5192066","0.5184841","0.51820034","0.51727813","0.5153253","0.51480454","0.5140919","0.5130285","0.51294297","0.5117322","0.5116863","0.5115009","0.5097445","0.5093695","0.5085705","0.5035323","0.5034456","0.50343907","0.50201356","0.4993182","0.49822193","0.4976224","0.496908","0.4966528","0.49560124","0.4949891","0.49335903","0.49299094","0.49299094","0.49243596","0.49074617","0.49061474","0.48840111","0.48837686","0.48790604","0.48692566","0.48688722","0.48671234","0.48635027","0.4860094","0.48584023","0.48533854","0.48481083","0.48469132","0.48421803","0.482817","0.4826807","0.4826807","0.48238322","0.4820832","0.48193362","0.48155555","0.48152387","0.4814424","0.48043567","0.47995615","0.4778314","0.476789"],"string":"[\n \"0.6643733\",\n \"0.6476299\",\n \"0.6185028\",\n \"0.59915143\",\n \"0.5967349\",\n \"0.59573674\",\n \"0.5938493\",\n \"0.5935553\",\n \"0.59315646\",\n \"0.5929291\",\n \"0.5864497\",\n \"0.58506036\",\n \"0.58318293\",\n \"0.58021766\",\n \"0.5801714\",\n \"0.57479554\",\n \"0.5633305\",\n \"0.5621189\",\n \"0.56003636\",\n \"0.55945224\",\n \"0.5584528\",\n \"0.55766237\",\n \"0.55636436\",\n \"0.55533814\",\n \"0.5499317\",\n \"0.548607\",\n \"0.54598343\",\n \"0.54289204\",\n \"0.54279137\",\n \"0.5400402\",\n \"0.5377158\",\n \"0.5334138\",\n \"0.53278565\",\n \"0.52944416\",\n \"0.5277428\",\n \"0.5230207\",\n \"0.52288616\",\n \"0.52286816\",\n \"0.5202022\",\n \"0.51967764\",\n \"0.5193806\",\n \"0.5192525\",\n \"0.5192066\",\n \"0.5184841\",\n \"0.51820034\",\n \"0.51727813\",\n \"0.5153253\",\n \"0.51480454\",\n \"0.5140919\",\n \"0.5130285\",\n \"0.51294297\",\n \"0.5117322\",\n \"0.5116863\",\n \"0.5115009\",\n \"0.5097445\",\n \"0.5093695\",\n \"0.5085705\",\n \"0.5035323\",\n \"0.5034456\",\n \"0.50343907\",\n \"0.50201356\",\n \"0.4993182\",\n \"0.49822193\",\n \"0.4976224\",\n \"0.496908\",\n \"0.4966528\",\n \"0.49560124\",\n \"0.4949891\",\n \"0.49335903\",\n \"0.49299094\",\n \"0.49299094\",\n \"0.49243596\",\n \"0.49074617\",\n \"0.49061474\",\n \"0.48840111\",\n \"0.48837686\",\n \"0.48790604\",\n \"0.48692566\",\n \"0.48688722\",\n \"0.48671234\",\n \"0.48635027\",\n \"0.4860094\",\n \"0.48584023\",\n \"0.48533854\",\n \"0.48481083\",\n \"0.48469132\",\n \"0.48421803\",\n \"0.482817\",\n \"0.4826807\",\n \"0.4826807\",\n \"0.48238322\",\n \"0.4820832\",\n \"0.48193362\",\n \"0.48155555\",\n \"0.48152387\",\n \"0.4814424\",\n \"0.48043567\",\n \"0.47995615\",\n \"0.4778314\",\n 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query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Raise a changed event, unless it's been locked out by update() | def _changed(self, name, value):
have_lock = self._change_lock.acquire(blocking=False)
if have_lock:
self._change_lock.release()
self.changed()
if not name.startswith('_'):
self.PropertiesChanged(self.INTERFACE, {name: value}, []) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def changed_event(self):\n return True",
"def _set_changed(self) -> None:\n self._changed = True",
"def setChanged(self,value=True):\n self.changed = value",
"def setChanged(self,value=True):\n self.changed = value",
"def changed(self):\n\t\tpass",
"def __itemChanged(self, eve... | [
"0.71976435",
"0.67700016",
"0.6700296",
"0.6700296",
"0.66102016",
"0.64516914",
"0.64472085",
"0.6384654",
"0.6346707",
"0.6346707",
"0.63417584",
"0.63403016",
"0.63403016",
"0.63027227",
"0.6270179",
"0.62422806",
"0.62234294",
"0.6210248",
"0.61960757",
"0.6192888",
"0.6... | 0.7286034 | 0 |
Gets a userdefined property. | def GetProp(self, name):
return self._props.get(name) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_property(self,name):\n return self.dp.get_property(name)",
"def get_property(self, property):\n return self.shell([\"getprop\", property])",
"def prop(self):\n return getattr(self, name)",
"def get_property(self, name):\n if (not name in self.properties):\n raise KeyError... | [
"0.7372728",
"0.7352151",
"0.7138261",
"0.7123359",
"0.7121722",
"0.70445794",
"0.699618",
"0.6932403",
"0.68578386",
"0.67842364",
"0.6733945",
"0.67140526",
"0.6676563",
"0.6603335",
"0.6569704",
"0.65058297",
"0.64743257",
"0.6459241",
"0.6434125",
"0.6430919",
"0.642791",... | 0.6837438 | 9 |
Sets a userdefined property. | def SetProp(self, name, value):
self._props[name] = value
self._changed(name, value) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_user_property(self, property, value):\n self._user_properties.update({property: value})",
"def set_property(self, name, value):\n self.properties[name] = value",
"def prop_set(prop, value, extra_args=None, cibfile=None):\n return item_create(\n item=\"property\",\n item_id=\"... | [
"0.8646349",
"0.7482961",
"0.7250825",
"0.7238759",
"0.69536626",
"0.69182163",
"0.6890837",
"0.68648195",
"0.680956",
"0.68038446",
"0.6799929",
"0.66651535",
"0.6622268",
"0.65920764",
"0.6560548",
"0.6558341",
"0.6558341",
"0.6558341",
"0.6558341",
"0.6558341",
"0.6515455"... | 0.6766817 | 11 |
Convert this object to builtin types only. | def json(self):
rv = {
prop: getattr(self, prop)
for prop in self.__properties__
if prop in vars(self)
}
rv.update(self._props)
return rv | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _initialize_builtins():\n # type: () -> None\n cast_map = (\n (a, b)\n for a in (str, int, float, bool)\n for b in (str, int, float, bool)\n )\n for source, target in cast_map:\n add_conversion(1, source, (), target, (), target)\n\n # TODO: Consider support for more g... | [
"0.65351224",
"0.64425725",
"0.63635373",
"0.62754744",
"0.61544544",
"0.6077892",
"0.5975018",
"0.5902368",
"0.58236426",
"0.5772046",
"0.5742609",
"0.5693393",
"0.567364",
"0.56619287",
"0.5643627",
"0.562659",
"0.5623451",
"0.5613437",
"0.5570497",
"0.5533262",
"0.5504444"... | 0.0 | -1 |
Used to substitute the sqlite.Row factory. This is done to avoid the tuple output from sqlite.Row. | def dict_factory(cursor, row):
d = {}
for idx, col in enumerate(cursor.description):
d[col[0]] = row[idx]
return d | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def row_factory(self):\n return self._hndl.row_factory",
"def row(self, row_id):\r\n return Row(self, row_id)",
"def sqlite3_dict_factory(cursor, row):\n dict_row = dict()\n for idx, col in enumerate(cursor.description):\n dict_row[col[0]] = row[idx]\n dict_row[idx] = row[idx]... | [
"0.6726382",
"0.6358366",
"0.63440126",
"0.6269724",
"0.6238853",
"0.6218866",
"0.621269",
"0.6068849",
"0.60422164",
"0.6018834",
"0.60167015",
"0.60030633",
"0.5952345",
"0.59359425",
"0.5914724",
"0.59121126",
"0.5910043",
"0.58957016",
"0.579632",
"0.5783978",
"0.5777899"... | 0.58094245 | 20 |
Connecto to a mongodb database. | def connect_mongo_db():
host = parsed_mongodb_url['host']
port = parsed_mongodb_url['port']
database = parsed_mongodb_url['database']
username = parsed_mongodb_url['username']
password = parsed_mongodb_url['password']
connection = Connection(host, port)
if username and password:
co... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def mongodb_connect():\n # Load environment variables\n dotenv_path = find_dotenv()\n load_dotenv(dotenv_path)\n # Connect to the db\n # DB will be created if it doesn't already exist\n client = pymongo.MongoClient(os.environ.get(\"DATABASE_URL\"), 27017)\n db = client.tweetbase\n return db... | [
"0.8210052",
"0.81336415",
"0.8117833",
"0.80774117",
"0.80349237",
"0.80312437",
"0.78603804",
"0.7805554",
"0.77723104",
"0.77163285",
"0.771416",
"0.7606415",
"0.75520486",
"0.7456694",
"0.7437505",
"0.7350662",
"0.7344814",
"0.73362505",
"0.73249835",
"0.73201",
"0.729642... | 0.81907785 | 1 |
Opens a new database connection if there is none yet for the current application context. | def get_db():
if not hasattr(g, 'mongo_db'):
g.db = get_mongo_db()
return g.db | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def db_open():\n if not hasattr(g, 'sqlite_db'):\n g.sqlite_db = db_connect()\n return g.sqlite_db",
"def open_database(self):\n if self._conn is None:\n self._conn = sqlite3.connect(self._db_path)",
"def open_db(db_name: str = DB_NAME) -> DBConnection:\n return sqlite3.connec... | [
"0.77379817",
"0.75827783",
"0.731633",
"0.716833",
"0.702289",
"0.6965276",
"0.6953964",
"0.6948672",
"0.68981296",
"0.68425506",
"0.6828195",
"0.6819551",
"0.68043447",
"0.67949706",
"0.67684644",
"0.6760031",
"0.675094",
"0.6747081",
"0.67314476",
"0.66986555",
"0.668763",... | 0.0 | -1 |
Opens a new mongodb connection if there isn't one for the current application context. | def get_mongo_db():
if not hasattr(g, 'mongodb'):
g.mongodb = connect_mongo_db()
g.mongodb.register([Testimonial])
g.mongodb.register([Town])
return g.mongodb | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def open_db_connection():\n client = MongoClient() #'104.131.185.191', 27017\n db = client[\"225VOH\"]\n return client, db",
"def connect_mongo():\n global MONGO_CLIENT\n\n with open('config.json') as config_file:\n config_data = json.load(config_file)\n\n MONGO_CLIENT = init_mongodb(con... | [
"0.7272311",
"0.7200479",
"0.71043235",
"0.70114166",
"0.7010941",
"0.7004676",
"0.6985721",
"0.69536436",
"0.6806279",
"0.68060654",
"0.6798944",
"0.6794018",
"0.67688376",
"0.6746943",
"0.6710124",
"0.66940784",
"0.6672508",
"0.66650826",
"0.6637785",
"0.66296685",
"0.66251... | 0.6309958 | 40 |
Loads into session all towns (municipios) in PR | def load_towns():
if not hasattr(g, 'towns'):
#g.towns = run_query('select id, name from municipios')
g.towns = get_towns()
return g.towns | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cargarObras(self):\n self.cargarObjetos(self.tableOs,\n ObraSocialModel.buscarTodos(\"razon_social\", self.sesion).all(),\n (\"razon_social\", \"cuit\", \"direccion\")\n )",
"def cargar_obras(self):\n self.cargarObjetos(self.tableObra,\n ObraSocialModel.b... | [
"0.5073809",
"0.50361466",
"0.4984311",
"0.48095226",
"0.47972944",
"0.47878638",
"0.47013986",
"0.46942475",
"0.46800122",
"0.46402198",
"0.46401247",
"0.4626877",
"0.4625208",
"0.46250755",
"0.4604238",
"0.45999122",
"0.45901167",
"0.45484176",
"0.4535182",
"0.45259017",
"0... | 0.6556211 | 0 |
Closes the database again at the end of the request | def close_db(error):
if hasattr(g, "sqlite_db"):
g.sqlite_db.close() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def after_request():\n db.close()",
"def close(self):\n\t\tself.db.close()",
"def close(self):\n self.db.close()",
"def close(self):\n if getattr(self, \"_db\", None):\n self._db.close()\n self._db = None",
"def close(self):\n self._flush()\n self.databa... | [
"0.8462045",
"0.82006633",
"0.79665846",
"0.78968066",
"0.7885584",
"0.7883566",
"0.78716004",
"0.78716004",
"0.78716004",
"0.7854064",
"0.7829076",
"0.78159904",
"0.78073823",
"0.779122",
"0.77713525",
"0.77128124",
"0.7709551",
"0.7643279",
"0.7643279",
"0.7643279",
"0.7643... | 0.0 | -1 |
Get all videos from specified city and renders them in the videos view. | def get_videos(town):
entries = get_town_videos(town)
print entries
if entries:
return render_template('videos.html', videos=entries, town=town)
else:
flash('No se encontraron videos.')
return render_template('videos.html', town=town) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def index():\n seen = set()\n seen_add = seen.add\n videos = []\n all_videos = mythVideo.searchVideos(insertedafter = '1900-01-01 00:00:00')\n\n for video in all_videos:\n path = video.filename.split('/')[0]\n if path not in seen and not seen_add(path):\n video.url = url_for... | [
"0.6410316",
"0.6264452",
"0.62203085",
"0.6112654",
"0.6078136",
"0.60360736",
"0.60235083",
"0.59724677",
"0.5959065",
"0.5951703",
"0.58861005",
"0.5864474",
"0.58401585",
"0.5825435",
"0.5802346",
"0.5778463",
"0.57751334",
"0.576849",
"0.5715935",
"0.57039154",
"0.568702... | 0.73999655 | 0 |
List available sparse deep learning sentiment analysis models. | def available_sparse_deep_model():
return ['fast-text-char'] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sparse_deep_model(model = 'fast-text-char', validate = True):\n return _softmax_class.sparse_deep_model(\n PATH_SENTIMENTS,\n S3_PATH_SENTIMENTS,\n 'sentiment',\n ['negative', 'positive'],\n 2,\n model = model,\n validate = validate,\n )",
"def list_avai... | [
"0.6248117",
"0.58962804",
"0.5852594",
"0.5757067",
"0.5678869",
"0.5617868",
"0.55847305",
"0.5567628",
"0.5551601",
"0.55444086",
"0.54956007",
"0.5494975",
"0.5451769",
"0.5421671",
"0.5360751",
"0.5297726",
"0.529192",
"0.51928556",
"0.51770246",
"0.516783",
"0.51540864"... | 0.68045807 | 0 |
List available deep learning sentiment analysis models. | def available_deep_model():
return [
'fast-text',
'hierarchical',
'bahdanau',
'luong',
'bidirectional',
'bert',
'entity-network',
] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def list_available_models(cls) -> List[PretrainedModelInfo]:\n list_of_models = []\n\n # en-US, ARPABET-based\n model = PretrainedModelInfo(\n pretrained_model_name=\"tts_en_radtts_aligner\",\n location=\"https://api.ngc.nvidia.com/v2/models/nvidia/nemo/tts_en_radtts_alig... | [
"0.68529797",
"0.6511286",
"0.6198815",
"0.6003524",
"0.58048916",
"0.5759036",
"0.57087564",
"0.5695869",
"0.56604546",
"0.5656096",
"0.5618853",
"0.55990726",
"0.5555275",
"0.5535813",
"0.5522266",
"0.5472041",
"0.54421264",
"0.54421264",
"0.54421264",
"0.54421264",
"0.5425... | 0.659194 | 1 |
Load deep learning sentiment analysis model. | def sparse_deep_model(model = 'fast-text-char', validate = True):
return _softmax_class.sparse_deep_model(
PATH_SENTIMENTS,
S3_PATH_SENTIMENTS,
'sentiment',
['negative', 'positive'],
2,
model = model,
validate = validate,
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_model(self):\n try:\n self.model = Word2Vec.load(self.config[\"model_path\"])\n self.model.init_sims(replace=True)\n except Exception as e:\n print(e)\n print(\"error in model loading!\")",
"def loadSavedModel(folder, spark_session):\n fro... | [
"0.6783818",
"0.66706735",
"0.66299415",
"0.6601698",
"0.6589383",
"0.6528808",
"0.6501299",
"0.6481838",
"0.64551425",
"0.64387673",
"0.64037585",
"0.6346428",
"0.6345054",
"0.63389415",
"0.6333392",
"0.6330937",
"0.6310681",
"0.6279278",
"0.6274967",
"0.62734914",
"0.626966... | 0.58360213 | 90 |
Load deep learning sentiment analysis model. | def deep_model(model = 'luong', validate = True):
return _softmax_class.deep_model(
PATH_SENTIMENTS,
S3_PATH_SENTIMENTS,
'sentiment',
['negative', 'positive'],
model = model,
validate = validate,
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_model(self):\n try:\n self.model = Word2Vec.load(self.config[\"model_path\"])\n self.model.init_sims(replace=True)\n except Exception as e:\n print(e)\n print(\"error in model loading!\")",
"def loadSavedModel(folder, spark_session):\n fro... | [
"0.67835915",
"0.66707486",
"0.6630123",
"0.65895396",
"0.65296984",
"0.65017945",
"0.6480464",
"0.6453746",
"0.6438888",
"0.64033544",
"0.6345082",
"0.634343",
"0.6337633",
"0.633442",
"0.63291806",
"0.6311232",
"0.62784225",
"0.62733686",
"0.6273227",
"0.6270561",
"0.626577... | 0.6603306 | 3 |
Load multinomial sentiment model. | def multinomial(validate = True):
return _softmax_class.multinomial(
PATH_SENTIMENTS,
S3_PATH_SENTIMENTS,
'sentiment',
['negative', 'positive'],
validate = validate,
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def model(self):\n filePath = self.config['data_path']['train_data']\n data = self.loadCSV(filePath)\n cleandata = self.preprocess(data)\n X, y = self.dataSplit(cleandata)\n X = self.CountVect(X, self.config['transform_path']['transform_model_path'])\n X_train, X_test, y_t... | [
"0.68189096",
"0.617218",
"0.60250115",
"0.5983554",
"0.5976382",
"0.5950238",
"0.5835725",
"0.57773966",
"0.5776157",
"0.5773181",
"0.5766718",
"0.57583266",
"0.5724592",
"0.57227194",
"0.5721556",
"0.57197523",
"0.5689089",
"0.5656369",
"0.5639414",
"0.5621266",
"0.561324",... | 0.69505644 | 0 |
Load XGB sentiment model. | def xgb(validate = True):
return _softmax_class.xgb(
PATH_SENTIMENTS,
S3_PATH_SENTIMENTS,
'sentiment',
['negative', 'positive'],
validate = validate,
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def xgb_train(X_train, y_train, write=False):\n model_xgb = xgb.XGBClassifier(max_depth=7,\n min_child_weight=1,\n learning_rate=0.01,\n n_estimators=5000,\n gamma=0.8,\n ... | [
"0.63705534",
"0.600376",
"0.5956303",
"0.59472424",
"0.5885772",
"0.5884835",
"0.5846589",
"0.5845727",
"0.5843475",
"0.5840624",
"0.58338577",
"0.5799269",
"0.5791677",
"0.5769696",
"0.573035",
"0.5723262",
"0.5718337",
"0.5708251",
"0.5689359",
"0.5683162",
"0.5681601",
... | 0.6143412 | 1 |
Train a multinomial model using your own corpus / dataset. | def train_multinomial(corpus, vector = 'tfidf', split_size = 0.2, **kwargs):
if not (
isinstance(corpus, str)
or isinstance(corpus, list)
or isinstance(corpus, tuple)
):
raise ValueError(
'corpus must be a string location or list of strings or tuple of strings'
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def model(self):\n filePath = self.config['data_path']['train_data']\n data = self.loadCSV(filePath)\n cleandata = self.preprocess(data)\n X, y = self.dataSplit(cleandata)\n X = self.CountVect(X, self.config['transform_path']['transform_model_path'])\n X_train, X_test, y_t... | [
"0.70000553",
"0.67839295",
"0.6768168",
"0.6745569",
"0.67182845",
"0.66143817",
"0.64957803",
"0.642929",
"0.63806903",
"0.6358394",
"0.6341894",
"0.63235986",
"0.6289102",
"0.6270932",
"0.6254924",
"0.6250245",
"0.6211102",
"0.6208206",
"0.6197866",
"0.61841744",
"0.617134... | 0.75276536 | 0 |
Set URL or slug. | def set_url_slug(self, slug):
slug = slug[-7:]
if len(slug) == 7 and \
slug[0] == "p" and \
all(x in ascii_letters + digits for x in slug):
self.slug = slug
self.url = "https://rpaste.com/" + slug
self.api_url = "https://rpaste.com/api/... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_slug(self, slug):\n if self.slug is None:\n self.slug = slug",
"def set_slug(self):\n if not self.slug:\n self.slug = slugify(self.name)[:50]",
"def set_url(self, url):\n self.url = url",
"def set_url(self, url):\n if url is not None:\n self.ur... | [
"0.7856565",
"0.7317531",
"0.71623856",
"0.70424086",
"0.70105034",
"0.6976292",
"0.69207335",
"0.6873143",
"0.6664493",
"0.65894234",
"0.6582367",
"0.6552071",
"0.6471977",
"0.6464758",
"0.6464758",
"0.63565755",
"0.63444626",
"0.6283054",
"0.62376636",
"0.62376636",
"0.6237... | 0.74837345 | 1 |
A helper function to calculate the variance/std. Used to keep the decomposition functions cleaner | def variance(self, decomp_type, n=5000, conf=0.99):
if self.submitted_n is not None:
n = self.submitted_n
if self.submitted_conf is not None:
conf = self.submitted_conf
if self.submitted_weight is not None:
submitted_weight = [
self.submitted_w... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def variance(self):\n sum_sqdif = 0 # initialize sum of squared differences\n # Calculate sum of squared differences\n for site in self.sites:\n sqdif = (site.siteZmArea - self.meanZmArea()) ** 2\n sum_sqdif = sqdif + sum_sqdif \n # Standard Deviation\n std... | [
"0.7770966",
"0.77011114",
"0.7629859",
"0.7627399",
"0.76196456",
"0.76110536",
"0.759898",
"0.759898",
"0.7584078",
"0.7584078",
"0.7584078",
"0.7558786",
"0.75491595",
"0.7532591",
"0.74610096",
"0.74437755",
"0.7442035",
"0.7442035",
"0.7432372",
"0.7398957",
"0.73813015"... | 0.0 | -1 |
Calculates the threefold Oaxaca Blinder Decompositions | def three_fold(self, std=False, n=None, conf=None):
self.submitted_n = n
self.submitted_conf = conf
self.submitted_weight = None
std_val = None
self.endow_eff = (
self.exog_f_mean - self.exog_s_mean
) @ self._s_model.params
self.coef_eff = self.exog_s_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def f3a_ab(self,a,b,c):\n ans = ((b*b/a) * (b*c - a)/(a*a + b*b - 2.*a*b*c)) * self.g2(a,b,-c) +\\\n 7. * (b*c/a) * self.f2(a,b,-c)/2.\n\n return ans/18.",
"def f3ba_a(self,a,b,c):\n ans = self.g2(a,b,c)*(7.*(b*b + a*b*c) - (b/a)**2 * (a*a + a*b*c))/\\\n (a*a+b*b+2.... | [
"0.6176517",
"0.6096917",
"0.5984615",
"0.5977737",
"0.5936238",
"0.59067196",
"0.58038735",
"0.575884",
"0.5722932",
"0.56830734",
"0.56759137",
"0.5673592",
"0.56575257",
"0.5650651",
"0.56390727",
"0.5593081",
"0.5566512",
"0.5547644",
"0.55393654",
"0.5535565",
"0.5530780... | 0.0 | -1 |
Calculates the twofold or pooled Oaxaca Blinder Decompositions Methods | def two_fold(
self,
std=False,
two_fold_type="pooled",
submitted_weight=None,
n=None,
conf=None,
):
self.submitted_n = n
self.submitted_conf = conf
std_val = None
self.two_fold_type = two_fold_type
self.submitted_weight = submit... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Bo_Bosol_calc(self):\n self.Bosol = (self.g*self.alpha * self.srflx ) \n #ZEROS FOR T3W APPLICATION\n self.Bo = np.zeros([self.b.shape[0]])",
"def bcL(self, rng=None):\n if rng is None:\n rng = random.PRNGKey(1)\n n = self.n\n x = onp.sin(self.bcmesh * np.pi)\n n_y = (np... | [
"0.6497755",
"0.60998803",
"0.57794124",
"0.5739765",
"0.5676304",
"0.5658211",
"0.5624913",
"0.55605114",
"0.55602336",
"0.55324084",
"0.55169976",
"0.5512204",
"0.55107075",
"0.5499989",
"0.5471748",
"0.54679704",
"0.54672104",
"0.54498965",
"0.5433238",
"0.5411353",
"0.540... | 0.0 | -1 |
Print a summary table with the OaxacaBlinder effects | def summary(self):
if self.model_type == 2:
if self.std is None:
print(
dedent(
f"""\
Oaxaca-Blinder Two-fold Effects
Unexplained Effect: {self.params[0]:.5f}
Explained Effect: {self.params[1]... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def printSummary(self):\n pass",
"def print_summary(self):\n self.model.summary()",
"def print_summary(self):\n\t\t\n\t\tif not self.objects:\n\t\t\tsys.stderr.write(\"No objects.\\n\")\n\t\t\treturn\n\t\t\n\t\t# Summary header data\n\t\theader = (\"ok\", \"error\", \"zdata\", \"xdata\", \"odata\... | [
"0.6694312",
"0.65748495",
"0.65513104",
"0.6474881",
"0.64278984",
"0.6423322",
"0.642323",
"0.6371663",
"0.63329065",
"0.62521726",
"0.621067",
"0.6206692",
"0.6201745",
"0.6167351",
"0.616657",
"0.6162669",
"0.6134523",
"0.61327744",
"0.6120603",
"0.611306",
"0.6099873",
... | 0.682384 | 0 |
This function builds the network architecture and performs the forward pass Two main architectures depending on where to insert the inception or residual layer | def forward_pass_unet(images, phase_train):
K = 4
images = tf.expand_dims(images, -1)
# Network blocks
conv1 = sdn.convolution('Conv1', images, 3, K, 1, phase_train=phase_train)
down = sdn.convolution('Down128', conv1, 2, K*2, 2, phase_train=phase_train)
conv2 = sdn.convolution('Conv2', down,... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def forward_pass(X,architecture):\n \n architecture['layer1'][0] = X\n kernel_shape1 = architecture['layer1'][7]\n stride1 = architecture['layer1'][8]\n if kernel_shape1 is not None and not isinstance(kernel_shape1,int):\n X_input_1_im2col,imX = im2col(X,kernel_shape1,stride1,im_needed = Fals... | [
"0.68315536",
"0.6485952",
"0.6467596",
"0.63724136",
"0.62841123",
"0.6239884",
"0.62038857",
"0.61176187",
"0.61051875",
"0.6099765",
"0.60895264",
"0.6078947",
"0.6060508",
"0.60420495",
"0.60374236",
"0.60353327",
"0.6006014",
"0.5988528",
"0.5984095",
"0.59753525",
"0.59... | 0.5818436 | 37 |
This function performs our backward pass and updates our gradients | def backward_pass(total_loss):
# Get the tensor that keeps track of step in this graph or create one if not there
global_step = tf.train.get_or_create_global_step()
# Print summary of total loss
tf.summary.scalar('Total_Loss', total_loss)
# Decay the learning rate
dk_steps = int((FLAGS.epoch_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def backward(self, gradient):\n #TODO\n pass",
"def backward(self, gradient):\n #TODO\n pass",
"def backward(self, gradient):\n raise NotImplementedError()",
"def backward_gradient(\n self, input: np.ndarray, head_gradients: Dict[str, np.ndarray]\n ) -> np.ndarray... | [
"0.8300835",
"0.8300835",
"0.813848",
"0.78645897",
"0.78537637",
"0.78537637",
"0.7841489",
"0.7801662",
"0.77778167",
"0.7776895",
"0.7717503",
"0.76866966",
"0.768577",
"0.7681438",
"0.7671628",
"0.76125723",
"0.76096076",
"0.7601533",
"0.7591049",
"0.75710464",
"0.7567065... | 0.0 | -1 |
Send OTP to given mobile number. | def send_otp_to_primary_mobile(otp, mobile):
print('Sending otp to mobile: ', otp, mobile) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sendOTP(code):\n # Modify the code here to change from print to any output \n print(\"Your OTP is \" + code + \". Kindly do not share it with anyone\")",
"def send_sms_via_modem(self, mobile, text=\"\"):\n\n mobile = self.sanitise_phone(mobile)\n\n # Add '+' before country code\n m... | [
"0.7327891",
"0.6951887",
"0.6793021",
"0.6524199",
"0.6296417",
"0.6277992",
"0.62462425",
"0.62288713",
"0.6222681",
"0.61966944",
"0.6191283",
"0.61755615",
"0.6162277",
"0.6120458",
"0.6107131",
"0.6077225",
"0.60114545",
"0.6000302",
"0.59869677",
"0.5910572",
"0.5873281... | 0.81184644 | 0 |
initializes database in the proper application context | def create_database_tables():
with APP.app_context():
DB.create_all() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def init_database(self):\n # init_database(self.engine)",
"def init_database(self):\n init_database(self.engine)",
"def init_db(cls, app):\n cls.logger.info(\"Initializing database\")\n cls.app = app\n # This is where we initialize SQLAlchemy from the Flask app\n db.in... | [
"0.8124815",
"0.80716336",
"0.80530757",
"0.80530757",
"0.783656",
"0.7787664",
"0.7693651",
"0.7677367",
"0.76722753",
"0.76453185",
"0.7514829",
"0.74404836",
"0.7437218",
"0.74203247",
"0.73997235",
"0.7374926",
"0.7349836",
"0.7348413",
"0.7294877",
"0.7275894",
"0.725955... | 0.0 | -1 |
error handler for 404 | def page_not_found(_error):
return render_template('404.html'), 404 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def handleStatus_404(self):\n log.err('HTTP Error 404')",
"def not_found():\n return HttpError(404)",
"def error_404(error):\n return '404 Error'",
"def error404(e) -> tuple:\n return render_template('404.html'), 404",
"def not_found_error_handler(error):\r\n return render_template('erro... | [
"0.8457733",
"0.81392837",
"0.8081069",
"0.80523026",
"0.80397505",
"0.8021954",
"0.80149484",
"0.7941188",
"0.7924955",
"0.7918556",
"0.7911572",
"0.7868195",
"0.7861067",
"0.78284514",
"0.78221476",
"0.7819732",
"0.7791562",
"0.777492",
"0.7727866",
"0.77059907",
"0.7682928... | 0.74724215 | 54 |
callback that is used to reload user object from the User uid | def load_user(uid):
return User.query.get(uid) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def user(self, uid):",
"def update_user():",
"def reload_user(self, user):\n return get_user_model().objects.get(pk=user.pk)",
"def update_user():\n #TODO user update \n pass",
"def update(cls, uid, func=lambda x: x):\n users = cls.db().get(cls.udb, default={}, touch=True)\n user... | [
"0.78098977",
"0.71555156",
"0.6917469",
"0.66156393",
"0.6577618",
"0.6472429",
"0.6440136",
"0.64400506",
"0.6378906",
"0.63667274",
"0.630829",
"0.6218003",
"0.6159437",
"0.61501944",
"0.6136581",
"0.612455",
"0.61069703",
"0.6082375",
"0.6038577",
"0.6038577",
"0.6038577"... | 0.6200807 | 12 |
view that displays the post of the board specified by the provided bid | def board(bid):
form = PostForm(request.form)
posts = Post.query.filter_by(
bid=bid, deleted=False).outerjoin(Comment).order_by(
text("comment.date desc"))
brd = Board.query.get(bid)
return render_template('posts.html', posts=posts, b=brd, pform=form) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def view_post(post_id):\n\n posts = models.Post.select().where(models.Post.id == post_id)\n if posts.count() == 0:\n abort(404)\n return render_template('detail.html', posts=posts)",
"def view_post(post_id):\n\n db_post = Post.query.get_or_404(post_id)\n full_name = db_post.user.get_full_na... | [
"0.64238364",
"0.64142495",
"0.6369537",
"0.6365728",
"0.6306215",
"0.63038635",
"0.6273676",
"0.62036043",
"0.6188795",
"0.6163974",
"0.61500585",
"0.6116142",
"0.6069818",
"0.60510933",
"0.60215914",
"0.60149276",
"0.59924364",
"0.59832865",
"0.5954234",
"0.5937921",
"0.592... | 0.8378358 | 0 |
logs in user if proper parameters are entered and creates a session for that user | def login():
if current_user.is_authenticated:
flash('You are already logged in!')
return redirect(url_for('index'))
form = LoginForm(request.form)
if request.method == 'POST' and form.validate():
user = User.query.filter_by(
username=form.username.data.lower()).first()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def login():",
"def login():",
"def do_login():\n\n isTeacher = False\n\n # check if this_user is admin or normal user\n this_user = User.query.filter_by(username=request.form['username']).first()\n \n # is this_user is not student or admin then check teacher table\n if this_user is None:\n ... | [
"0.757024",
"0.757024",
"0.7559482",
"0.74683917",
"0.7328798",
"0.72918135",
"0.7247259",
"0.7220366",
"0.7187893",
"0.71351975",
"0.70968705",
"0.70551777",
"0.7025809",
"0.70155424",
"0.69823694",
"0.69715047",
"0.6962551",
"0.6962551",
"0.69526553",
"0.69518083",
"0.69256... | 0.0 | -1 |
logs out user and redirects to front page | def logout():
logout_user()
flash('Successfully logged out.')
return redirect(request.referrer) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def logout():\n session.pop(\"user\")\n return redirect(url_for(\"home\"))",
"def logout():\n flash(_('You were logged out'))\n session.pop('user_id', None)\n return redirect(url_for('index'))\n #return redirect(url_for('public_timeline'))",
"def logout_user(request):\n if request.user.is_... | [
"0.80933905",
"0.8053985",
"0.80535305",
"0.804667",
"0.8031641",
"0.8031641",
"0.8021012",
"0.79906225",
"0.7966582",
"0.79636705",
"0.795637",
"0.793604",
"0.79314876",
"0.79279006",
"0.7921493",
"0.7912729",
"0.79045266",
"0.78937733",
"0.78929514",
"0.78929514",
"0.789200... | 0.7842872 | 27 |
creates board if form parameters meet requirements | def create_board():
form = BoardForm(request.form)
if current_user.is_admin and request.method == 'POST' and form.validate():
if Board.query.filter(
func.lower(Board.name) == func.lower(form.name.data)
).scalar() is None:
DB.session.add(Board(form.name.data, form.desc.dat... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_board(self):\n for field in self.fields_start_locs:\n loc = self.loc_to_view(field[0], field[1])\n new_field = Field(loc, self.piece_size)\n self.sprite_group.add(new_field)\n self.click_sprites.add(new_field)\n self.fields.append(new_field)"... | [
"0.603793",
"0.5859027",
"0.57967037",
"0.57193846",
"0.5695587",
"0.56434304",
"0.56327605",
"0.5564936",
"0.5536575",
"0.55322415",
"0.5510225",
"0.55069685",
"0.54559624",
"0.54472303",
"0.5427493",
"0.54243577",
"0.5404887",
"0.5402026",
"0.5395092",
"0.53867",
"0.5363956... | 0.6169846 | 0 |
allows the editing of a board with the provided bid | def edit_board(bid):
form = BoardForm(request.form)
brd = Board.query.get(bid)
if current_user.is_admin and request.method == 'POST':
if form.validate():
if brd.name != form.name.data or brd.desc != form.desc.data:
brd.name = form.name.data
brd.desc = form... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def revive_board(bid):\n if current_user.is_admin:\n Board.query.get(bid).deleted = False\n DB.session.commit()\n msg = 'Board {} is now visible again.'\n flash(msg.format(bid))\n else:\n flash(constants.DEFAULT_SUBMISSION_ERR)\n return redirect(request.referrer)",
"de... | [
"0.6417084",
"0.63343984",
"0.6053781",
"0.60441285",
"0.5873083",
"0.5831679",
"0.5816733",
"0.57996845",
"0.57737195",
"0.5772161",
"0.57612866",
"0.5756384",
"0.57373023",
"0.5682081",
"0.56092197",
"0.5580099",
"0.55707616",
"0.55353636",
"0.5534937",
"0.5500094",
"0.5460... | 0.8023971 | 0 |
allows the board to be flagged for deletion by an admin | def delete_board(bid):
if current_user.is_admin:
Board.query.get(bid).deleted = True
DB.session.commit()
flash('Board {} is no longer viewable.'.format(bid))
return redirect(request.referrer) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def can_delete(self):\r\n return True",
"def on_model_delete(self, model):\n if not current_user.is_active or not current_user.is_authenticated:\n abort(403)\n if not user_has_permission(current_user, 'can_delete','admins'):\n abort(403)",
"def test_handle_delete_not_... | [
"0.67879754",
"0.6325901",
"0.62908286",
"0.62738276",
"0.61669207",
"0.6166666",
"0.6165566",
"0.6154188",
"0.6142294",
"0.61347324",
"0.6094835",
"0.6094835",
"0.6094835",
"0.6083285",
"0.6021208",
"0.6018292",
"0.5990092",
"0.5981776",
"0.59772396",
"0.5955287",
"0.5955114... | 0.707618 | 0 |
allows the creation of a post as long as parameters are met and the user is in an active session | def create_post(bid):
form = PostForm(request.form)
if request.method == 'POST':
if form.validate():
DB.session.add(
Post(
bid,
current_user.uid,
form.name.data,
form.desc.data))
DB.se... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_post():\n\n #Get prompt id\n prompt_id = request.form.get('prompt_id')\n\n # Get post text\n post_text = request.form.get('user_post')\n\n # Create post timestamp\n created_at = datetime.now()\n user_facing_date = created_at.strftime(\"%B %d, %Y\")\n\n # Save post and related dat... | [
"0.7211455",
"0.70679027",
"0.6925175",
"0.67390615",
"0.6700689",
"0.6668551",
"0.6650431",
"0.6628169",
"0.65903986",
"0.65749836",
"0.65330535",
"0.6490874",
"0.6482665",
"0.64730823",
"0.6450237",
"0.6409941",
"0.6389672",
"0.63893265",
"0.63873065",
"0.6385716",
"0.63759... | 0.671704 | 4 |
allows the editing of a post as long as the active user is the post creator or admin | def edit_post(bid, pid):
# pylint: disable=unused-argument
pst = Post.query.get(pid)
form = PostForm(request.form)
if request.method == 'POST' and current_user.uid == pst.uid:
if form.validate():
if pst.name != form.name.data or pst.text != form.desc.data:
og_name = p... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def post_permissions(request, post):\n user = request.user\n is_editable = has_ownership = False\n\n if user.is_authenticated():\n\n if user == post.author :\n has_ownership = is_editable = True\n elif user.is_moderator or user.is_staff:\n is_editable = True\n\n post... | [
"0.80510914",
"0.72609615",
"0.7226267",
"0.71686494",
"0.71497864",
"0.71302485",
"0.70795995",
"0.7057716",
"0.7032421",
"0.6998917",
"0.69817406",
"0.69667983",
"0.69324255",
"0.689023",
"0.6886989",
"0.68172026",
"0.67966056",
"0.6777565",
"0.6759076",
"0.67485136",
"0.67... | 0.6869949 | 15 |
allows for the deletion of a post as long as the active user is the post creator or admin | def delete_post(bid, pid):
# pylint: disable=unused-argument
if current_user.is_admin or current_user == Post.query.get(int(pid)).uid:
Post.query.get(pid).deleted = True
DB.session.commit()
return redirect(request.referrer) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def post(self):\n post_id = int(self.request.get('post_id'))\n post = Posts.get_by_id(post_id)\n if post.submitter_id == self.get_active_user().key().id():\n post.delete()\n else:\n self.error(403)\n self.redirect('/')",
"def delete_post(request, post_id):... | [
"0.812043",
"0.7826384",
"0.7608697",
"0.753139",
"0.7525019",
"0.75085485",
"0.7404617",
"0.736625",
"0.73437005",
"0.73198605",
"0.73052835",
"0.72591406",
"0.723565",
"0.7205305",
"0.7202058",
"0.7201454",
"0.71928406",
"0.7180946",
"0.713976",
"0.713678",
"0.71364546",
... | 0.7809568 | 2 |
allows for the creation of a comment by an active user | def create_comment(bid, pid):
# pylint: disable=unused-argument
form = CommentForm(request.form)
if request.method == 'POST':
if form.validate():
DB.session.add(Comment(pid, current_user.uid, form.text.data))
DB.session.commit()
flash('Comment successfully created... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def obj_create(self, bundle, request=None, **kwargs):\n return super(CommentResource, self).obj_create(bundle, request, user=request.user, site=Site.objects.get_current())",
"def form_valid(self, form):\n author = Profile.objects.get(user=self.request.user)\n object = self.get_object()\n ... | [
"0.69678545",
"0.68733394",
"0.68367547",
"0.67674065",
"0.676233",
"0.6698197",
"0.6653947",
"0.6653032",
"0.6644549",
"0.6617098",
"0.6610111",
"0.66029644",
"0.65430397",
"0.6537922",
"0.6513555",
"0.6511368",
"0.6444499",
"0.6426328",
"0.63783514",
"0.63498986",
"0.627524... | 0.68905306 | 1 |
allows the editing of a post as long as the active user is the post creator or admin | def edit_comment(bid, pid, cid):
# pylint: disable=unused-argument
comment = Comment.query.get(cid)
form = CommentForm(request.form)
if request.method == 'POST' and current_user.uid == comment.uid:
if form.validate():
if comment.text != form.text.data:
comment.text = ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def post_permissions(request, post):\n user = request.user\n is_editable = has_ownership = False\n\n if user.is_authenticated():\n\n if user == post.author :\n has_ownership = is_editable = True\n elif user.is_moderator or user.is_staff:\n is_editable = True\n\n post... | [
"0.8052066",
"0.72612363",
"0.72258705",
"0.71685565",
"0.7149761",
"0.71297675",
"0.7078617",
"0.70570725",
"0.7032085",
"0.6998435",
"0.69808286",
"0.69673204",
"0.69330925",
"0.68888074",
"0.6885943",
"0.6869112",
"0.68170947",
"0.6795856",
"0.6777252",
"0.67587143",
"0.67... | 0.0 | -1 |
allows for a comment to be 'deleted' by the comment creator or admin | def delete_comment(bid, pid, cid):
# pylint: disable=unused-argument
comment = Comment.query.filter_by(pid=pid, cid=cid).first()
if current_user.is_admin or current_user.uid == comment.uid:
comment.deleted = True
DB.session.commit()
return redirect(request.referrer) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_comment(request, comment_id):\n raise NotImplementedError",
"async def delete_comment(comment: models.Comment = Depends(resolve_comment_for_comment_owner_or_resub_owner),\n db: Session = Depends(get_db)):\n crud.delete_comment(db, comment.id)",
"def delete(request, comm... | [
"0.80480784",
"0.7736271",
"0.77149045",
"0.7659918",
"0.75418705",
"0.7515988",
"0.7294807",
"0.7271467",
"0.7246589",
"0.7212666",
"0.7187633",
"0.7138442",
"0.70837605",
"0.70724744",
"0.70158875",
"0.7010586",
"0.7005397",
"0.69440895",
"0.6943539",
"0.6927659",
"0.692345... | 0.7410943 | 6 |
allows for a 'deleted' comment to be 'revived' by an admin | def revive_comment(bid, pid, cid):
# pylint: disable=unused-argument
comment = Comment.query.filter_by(pid=pid, cid=cid).first()
if current_user.is_admin:
comment.deleted = False
DB.session.commit()
return redirect(request.referrer) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete(request, comment_id):\n try:\n comment = comments.get_object(pk=comment_id, site__id__exact=SITE_ID)\n except comments.CommentDoesNotExist:\n raise Http404\n if not comments.user_is_moderator(request.user):\n raise Http404\n if request.POST:\n # If the comment has... | [
"0.67821044",
"0.67004305",
"0.6567313",
"0.6491898",
"0.64727014",
"0.64379954",
"0.6308174",
"0.6294083",
"0.62237483",
"0.6213215",
"0.61960703",
"0.6177323",
"0.61392194",
"0.6132944",
"0.61212826",
"0.60846806",
"0.60760844",
"0.606019",
"0.6057162",
"0.60461766",
"0.603... | 0.71453315 | 0 |
admin "erase" board route | def erase_board(bid):
if current_user.is_admin:
DB.session.delete(Board.query.get(bid))
DB.session.commit()
msg = 'Board {} permanently removed from database. '\
'All associated posts and comments have also been removed.'
flash(msg.format(bid))
else:
flash(con... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_board(bid):\n if current_user.is_admin:\n Board.query.get(bid).deleted = True\n DB.session.commit()\n flash('Board {} is no longer viewable.'.format(bid))\n return redirect(request.referrer)",
"def revive_board(bid):\n if current_user.is_admin:\n Board.query.get(bi... | [
"0.6663433",
"0.6346066",
"0.61803126",
"0.6123992",
"0.6109822",
"0.6013274",
"0.5860381",
"0.578081",
"0.5780407",
"0.5756733",
"0.5743018",
"0.5732131",
"0.5723054",
"0.56639546",
"0.56594646",
"0.5619822",
"0.5611579",
"0.5577402",
"0.55449736",
"0.5531958",
"0.5501947",
... | 0.706307 | 0 |
admin revive board route | def revive_board(bid):
if current_user.is_admin:
Board.query.get(bid).deleted = False
DB.session.commit()
msg = 'Board {} is now visible again.'
flash(msg.format(bid))
else:
flash(constants.DEFAULT_SUBMISSION_ERR)
return redirect(request.referrer) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def route(self):\n pass",
"def route(self):\n # TODO: wenn keine url, herausfinden, welche ????\n # TODO: wenn url = hostname (fqdn), dann -> google.ch\n if not (self.META.has_key('REMOTE_ADDR') and \n self.GET.has_key('provider')):\n #self.GET.has_key('url')):\n #return HttpRe... | [
"0.639884",
"0.57397103",
"0.5584636",
"0.54806924",
"0.54461694",
"0.5399685",
"0.53785545",
"0.5375579",
"0.53507906",
"0.53437626",
"0.53437626",
"0.5334951",
"0.5329222",
"0.5291434",
"0.52833575",
"0.52498335",
"0.5245823",
"0.52204305",
"0.52161586",
"0.5197525",
"0.519... | 0.63001364 | 1 |
c7n cloudwatch log group exporter | def cli(): | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def log_group_name(self) -> str:\n ...",
"def log_group_arn(self) -> str:\n ...",
"def __on_group_created(self, logger, *args):",
"def test_create_cloudwatch_log_group(cloudwatch_logs):\n cloudwatch_logs.create_log_group(\n logGroupName='/ecs/mongo/change-stream',\n tags={'env'... | [
"0.6710038",
"0.6464622",
"0.61767995",
"0.61572605",
"0.6029598",
"0.5876371",
"0.58752686",
"0.57443726",
"0.55814475",
"0.5555984",
"0.55552804",
"0.5547609",
"0.5547609",
"0.5528474",
"0.5375495",
"0.5355001",
"0.5324256",
"0.53136575",
"0.531029",
"0.52705467",
"0.527054... | 0.0 | -1 |
subscribe accounts log groups to target account log group destination | def subscribe(config, accounts, region, merge, debug):
config = validate.callback(config)
subscription = config.get('subscription')
if subscription is None:
log.error("config file: logs subscription missing")
sys.exit(1)
def converge_destination_policy(client, config):
destinat... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _subscribe_users(self):\n group = self.env.ref('odoo_magento2_ept.group_connector_manager')\n if not group:\n return\n companies = self.mapped('company_id')\n domain = [('groups_id', '=', group.id)]\n if companies:\n domain.append(('company_id', 'child_o... | [
"0.6371777",
"0.6259225",
"0.5749728",
"0.56459796",
"0.55690557",
"0.55181706",
"0.5429786",
"0.5353789",
"0.51864505",
"0.5160758",
"0.51556367",
"0.51556367",
"0.51556367",
"0.51459944",
"0.5069009",
"0.5033788",
"0.50062",
"0.49968696",
"0.49712193",
"0.49004823",
"0.4897... | 0.7344485 | 0 |
run export across accounts and log groups specified in config. | def run(config, start, end, accounts, region, debug):
config = validate.callback(config)
destination = config.get('destination')
start = start and parse(start) or start
end = end and parse(end) or datetime.now()
executor = debug and MainThreadExecutor or ThreadPoolExecutor
with executor(max_work... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def access(config, region, accounts=()):\n config = validate.callback(config)\n accounts_report = []\n\n def check_access(account):\n accounts_report.append(account)\n session = get_session(account['role'], region)\n identity = session.client('sts').get_caller_identity()\n acco... | [
"0.61790913",
"0.5990142",
"0.57580197",
"0.5699163",
"0.56428206",
"0.5430614",
"0.5360654",
"0.53571796",
"0.5353356",
"0.51873606",
"0.5173957",
"0.51684934",
"0.5089368",
"0.50287056",
"0.50019586",
"0.49614125",
"0.49474218",
"0.49337208",
"0.49278173",
"0.4878865",
"0.4... | 0.48856384 | 19 |
simple decorator that will auto fan out async style in lambda. outside of lambda, this will invoke synchrously. | def lambdafan(func):
if 'AWS_LAMBDA_FUNCTION_NAME' not in os.environ:
return func
@functools.wraps(func)
def scaleout(*args, **kw):
client = boto3.client('lambda')
client.invoke(
FunctionName=os.environ['AWS_LAMBDA_FUNCTION_NAME'],
InvocationType='Event',
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def public_async_generator(func):\n @functools.wraps(func)\n def function(*args, **kwargs):\n \"Wrapped function\"\n return GeneratorFuture(func(*args, **kwargs)).future\n return function",
"def async_generator(func):\n @functools.wraps(func)\n def function(*args, **kwargs):\n ... | [
"0.71401983",
"0.7095293",
"0.692637",
"0.6761418",
"0.66672474",
"0.6651891",
"0.66168404",
"0.6510454",
"0.6495293",
"0.64642245",
"0.6446209",
"0.6440772",
"0.6432568",
"0.64141804",
"0.63846105",
"0.638452",
"0.636017",
"0.63143176",
"0.6230892",
"0.61843586",
"0.61801624... | 0.0 | -1 |
Filter log groups by shell patterns. | def filter_group_names(groups, patterns):
group_names = [g['logGroupName'] for g in groups]
matched = set()
for p in patterns:
matched.update(fnmatch.filter(group_names, p))
return [g for g in groups if g['logGroupName'] in matched] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def list_command_filter(self, testsuite_pattern, testcase_pattern):\n return None # Hobbes-test does not support listing by filter",
"def list(self, pattern='*'):\n if self._group_dict is None:\n self._group_dict = collections.OrderedDict(\n (group.name, group) for group in self._client.... | [
"0.6008613",
"0.5841888",
"0.5739808",
"0.5477056",
"0.5305808",
"0.5287709",
"0.5283606",
"0.5276361",
"0.5276361",
"0.5247437",
"0.5243044",
"0.52194685",
"0.521362",
"0.519743",
"0.5168097",
"0.5156099",
"0.5154336",
"0.51460075",
"0.51007366",
"0.50932705",
"0.50567377",
... | 0.6737141 | 0 |
Filter log groups by their creation date. Also sets group specific value for start to the minimum of creation date or start. | def filter_creation_date(groups, start, end):
results = []
for g in groups:
created = datetime.fromtimestamp(g['creationTime'] / 1000.0)
if created > end:
continue
if created > start:
g['exportStart'] = created
else:
g['exportStart'] = start
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _groupDate(item):\n return item.time.date()",
"def filter_last_write(client, groups, start):\n retry = get_retry(('ThrottlingException',))\n\n def process_group(group_set):\n matched = []\n for g in group_set:\n streams = retry(\n client.describe_log_streams,\... | [
"0.5349732",
"0.53088593",
"0.5135366",
"0.51161885",
"0.50460446",
"0.50092417",
"0.49472526",
"0.4919195",
"0.4872214",
"0.47953695",
"0.47320732",
"0.47296935",
"0.47275117",
"0.4711657",
"0.4679824",
"0.46712154",
"0.46613857",
"0.46525186",
"0.46412024",
"0.4633902",
"0.... | 0.7864727 | 0 |
Filter log groups where the last write was before the start date. | def filter_last_write(client, groups, start):
retry = get_retry(('ThrottlingException',))
def process_group(group_set):
matched = []
for g in group_set:
streams = retry(
client.describe_log_streams,
logGroupName=g['logGroupName'],
orde... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def filter_creation_date(groups, start, end):\n results = []\n for g in groups:\n created = datetime.fromtimestamp(g['creationTime'] / 1000.0)\n if created > end:\n continue\n if created > start:\n g['exportStart'] = created\n else:\n g['exportStar... | [
"0.6635909",
"0.52722096",
"0.52423257",
"0.518209",
"0.51671964",
"0.51543635",
"0.5145697",
"0.5122798",
"0.51035225",
"0.5058704",
"0.50209457",
"0.5015845",
"0.49920514",
"0.4966966",
"0.49647346",
"0.49560562",
"0.49525395",
"0.48545003",
"0.48374102",
"0.4812402",
"0.47... | 0.6843721 | 0 |
Filter days where the bucket already has extant export keys. | def filter_extant_exports(client, bucket, prefix, days, start, end=None):
end = end or datetime.now()
# days = [start + timedelta(i) for i in range((end-start).days)]
try:
tag_set = client.get_object_tagging(Bucket=bucket, Key=prefix).get('TagSet', [])
except ClientError as e:
if e.respo... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def clean_up_old_exports(self):\n threshold = datetime.datetime.utcnow() - datetime.timedelta(days=30)\n self.session.query(Export).filter(Export.started_at < threshold).delete()",
"def export_old_audits(min_to_export=1000, export_count=500):\n try:\n # print min_to_export, export_count\n... | [
"0.52053744",
"0.5099278",
"0.50236905",
"0.5003069",
"0.4969293",
"0.49566582",
"0.49530184",
"0.49155438",
"0.4885868",
"0.48518157",
"0.48443332",
"0.48185405",
"0.48138407",
"0.4807479",
"0.47937182",
"0.47893035",
"0.47234836",
"0.47130275",
"0.47066486",
"0.46859834",
"... | 0.7333458 | 0 |
Check iam permissions for log export access in each account | def access(config, region, accounts=()):
config = validate.callback(config)
accounts_report = []
def check_access(account):
accounts_report.append(account)
session = get_session(account['role'], region)
identity = session.client('sts').get_caller_identity()
account['account_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _is_accessible_to_all(self, pvm: PermissionView) -> bool:\n\n return pvm.permission.name in self.ACCESSIBLE_PERMS",
"def has_export_permission(self, request):\n opts = self.opts\n codename = get_permission_codename('export', opts)\n return request.user.has_perm(\"%s.%s\" % (opts.a... | [
"0.5922439",
"0.5674963",
"0.5661662",
"0.560372",
"0.5548407",
"0.5503811",
"0.5503811",
"0.5503811",
"0.5503811",
"0.5503811",
"0.54923755",
"0.54669565",
"0.5439774",
"0.5423338",
"0.5386345",
"0.53821",
"0.53797674",
"0.5375663",
"0.5375663",
"0.5371909",
"0.53555375",
... | 0.60143447 | 0 |
size of exported records for a given day. | def size(config, accounts=(), day=None, group=None, human=True, region=None):
config = validate.callback(config)
destination = config.get('destination')
client = boto3.Session().client('s3')
day = parse(day)
def export_size(client, account):
paginator = client.get_paginator('list_objects_v2... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_record_count(self):\n return os.path.getsize(self.path) / self._get_record_size()",
"def get_dayu_size(self):\n return self._dayu_size",
"def get_dayu_size(self):\n return self._dayu_size",
"def size(self):\n\t\treturn (self.dates[1] - self.dates[0]).days",
"def file_size(hdf... | [
"0.6221909",
"0.6163865",
"0.6163865",
"0.6151718",
"0.5874076",
"0.5849746",
"0.5767309",
"0.5767309",
"0.5767309",
"0.5713602",
"0.5705803",
"0.5697264",
"0.56610096",
"0.5648509",
"0.5621126",
"0.5561575",
"0.5548188",
"0.5530563",
"0.55203176",
"0.55025476",
"0.55005616",... | 0.5952901 | 4 |
sync last recorded export to actual Use dryrun to check status. | def sync(config, group, accounts=(), dryrun=False, region=None):
config = validate.callback(config)
destination = config.get('destination')
client = boto3.Session().client('s3')
for account in config.get('accounts', ()):
if accounts and account['name'] not in accounts:
continue
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _post_sync(self):",
"def _pre_sync(self):",
"def sync() -> None:",
"def _sync_log_event(self):\n # sync only after first run and if not currently running\n if self.auto_sync and not self._running and self._has_run:\n self.sync_exp(upload_resources=False)",
"def sync_update(self... | [
"0.63388246",
"0.6224563",
"0.61723065",
"0.60717195",
"0.60589373",
"0.59674937",
"0.5963909",
"0.59499013",
"0.59499013",
"0.5817301",
"0.5811279",
"0.57902735",
"0.56796926",
"0.5558574",
"0.55518734",
"0.55510104",
"0.5530432",
"0.55055076",
"0.5468405",
"0.5459672",
"0.5... | 0.5130186 | 47 |
report current export state status | def status(config, group, accounts=(), region=None):
config = validate.callback(config)
destination = config.get('destination')
client = boto3.Session().client('s3')
for account in config.get('accounts', ()):
if accounts and account['name'] not in accounts:
continue
session... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def status(self):",
"def _print_status(self):",
"def status(self):\n pass",
"def status(self):\n pass",
"def export_status(self, file_id):\n response = self._client.get('workbenches/export/%(file_id)s/status',\n path_params={'file_id': file_id})\n ... | [
"0.68302184",
"0.67881507",
"0.6752981",
"0.6752981",
"0.67016155",
"0.65821147",
"0.6570133",
"0.6531288",
"0.6507663",
"0.6278986",
"0.62787443",
"0.62783325",
"0.6257841",
"0.6221025",
"0.61823666",
"0.61173105",
"0.61118686",
"0.60641307",
"0.60631007",
"0.60592574",
"0.6... | 0.0 | -1 |
Find exports for a given account | def get_exports(client, bucket, prefix, latest=True):
keys = client.list_objects_v2(
Bucket=bucket, Prefix=prefix, Delimiter='/').get('CommonPrefixes', [])
found = []
years = []
for y in keys:
part = y['Prefix'].rsplit('/', 2)[-2]
if not part.isdigit():
continue
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def find_by_account(cls,account):\n for credentials in cls.credential_list:\n if credentials.account == account:\n return credentials",
"def export_accounts(self):\n print('=== Exporting all account data...')\n\n for account in self.client.tenant.accounts:\n ... | [
"0.59281385",
"0.58018434",
"0.569227",
"0.5647005",
"0.5508856",
"0.54309577",
"0.54309577",
"0.54139084",
"0.5381647",
"0.5355028",
"0.5352831",
"0.5346433",
"0.534154",
"0.5332681",
"0.5287703",
"0.52789176",
"0.5235002",
"0.5224027",
"0.51786953",
"0.5165503",
"0.51365143... | 0.46468973 | 74 |
export a given log group to s3 | def export(group, bucket, prefix, start, end, role, poll_period=120,
session=None, name="", region=None):
start = start and isinstance(start, str) and parse(start) or start
end = (end and isinstance(start, str) and
parse(end) or end or datetime.now())
start = start.replace(tzinfo=tzloc... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def export_cw_logs_to_s3(global_vars, log_group_name, retention_days, bucket_name, obj_prefix = None):\n resp_data = {'status': False, 'task_info':{}, 'error_message': ''}\n if not retention_days: retention_days = 90\n if not obj_prefix: obj_prefix = log_group_name.split('/')[-1]\n now_time = dat... | [
"0.7299515",
"0.6354688",
"0.609733",
"0.5968771",
"0.5890701",
"0.57919425",
"0.5719376",
"0.5693675",
"0.5673941",
"0.5615103",
"0.55705446",
"0.55546635",
"0.5508692",
"0.5500976",
"0.5415052",
"0.53872406",
"0.5381192",
"0.5351819",
"0.5333531",
"0.5318828",
"0.52851784",... | 0.76097655 | 0 |
With the option of having multiple layouts on one screen, it must be the app.py program that assigns the dimensions of the layout as the layout itself is unaware of other layouts | def assign_dimensions(self, dimensions):
if self.real_size < 1:
raise Layout_Error("Real size must be larger than the layout itself (hence must be more than 1)")
if not self.scroll_enabled:
self.real_size = 1
self._dimensions = dimensions
self._layout_width = s... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_layout( self ):",
"def _do_layout(self):\n return",
"def _generate_layout(self):\n\n pass",
"def test_multiple_layouts(self):\n\n # site.py\n\n self.app.layout('page.html', 'sub-layout.html', 'layout.html')\n self.app.run()\n\n # tests\n\n with open... | [
"0.69394404",
"0.6680851",
"0.66320705",
"0.6573839",
"0.6544663",
"0.6506498",
"0.63752866",
"0.6340171",
"0.6315905",
"0.6302106",
"0.62825966",
"0.61903805",
"0.6170804",
"0.6136268",
"0.61278975",
"0.610944",
"0.6046649",
"0.60361177",
"0.59862",
"0.59726304",
"0.5966327"... | 0.5796929 | 32 |
With the option of having multiple layouts on one screen, it must be the app.py program that assigns the position of the layout (based on the top left corner) as the layout itself is unaware of other layouts | def assign_position(self, position):
self._actual_position = list(position)
self._position = [0, 0]
if not self._widget_assigned:
self._align()
self._update_widgets()
self._widget_assigned = True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_layout( self ):",
"def _do_layout(self):\n return",
"def layout(self):\n pass",
"def set_layout(layout):\r\n # Get active window and set reference to active view\r\n window = sublime.active_window()\r\n previous_active = window.active_view()\r\n\r\n # Do not set layout wh... | [
"0.6937658",
"0.6772835",
"0.6771903",
"0.67105615",
"0.66829115",
"0.6522903",
"0.6515964",
"0.6487785",
"0.6432114",
"0.62702847",
"0.62645257",
"0.62606627",
"0.62567633",
"0.6252418",
"0.62371427",
"0.6232333",
"0.62201405",
"0.62193847",
"0.61550915",
"0.6131667",
"0.611... | 0.0 | -1 |
Open a text file & return a list of lowercase strings. | def load(filename: str) -> list:
try:
with open(filename) as in_file:
loaded_txt = in_file.read().strip().split("\n")
loaded_txt = [x.lower() for x in loaded_txt]
return loaded_txt
except IOError as e:
print("{}\nError opening {}. Terminating program.".format(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def read_text_file(filename):\n try:\n file = open(filename, 'r')\n except:\n print('Cannot read file ' + filename + '. Please check the path', file=sys.stderr)\n sys.exit(1)\n output = []\n \n for line in file:\n line = line.strip().lower(... | [
"0.7791968",
"0.76199895",
"0.7393152",
"0.7225327",
"0.7197625",
"0.7197625",
"0.71210194",
"0.70748514",
"0.69804806",
"0.6914742",
"0.6905123",
"0.6821919",
"0.67699254",
"0.6751201",
"0.66823953",
"0.66470754",
"0.6636171",
"0.66317534",
"0.6623684",
"0.6623684",
"0.66015... | 0.76761186 | 1 |
The constructor takes in sender, receiver and a signature. | def __init__(self, sender: str, receiver: str, signature: str) -> None:
super().__init__(sender, receiver)
self.signature = signature | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, method, receiver):\n self.method = method\n if type(receiver) == Class:\n self.receiver = cast(receiver, objc_id)\n else:\n self.receiver = receiver",
"def __init__(self, sender):\r\n\t\tself.sender = sender",
"def __init__(self, sig, *args, **kwarg... | [
"0.6864943",
"0.68118566",
"0.6798293",
"0.6582685",
"0.6582685",
"0.6582685",
"0.64841205",
"0.6334486",
"0.6323883",
"0.6277131",
"0.60506815",
"0.6022045",
"0.6010426",
"0.60057503",
"0.5989921",
"0.5977475",
"0.5931117",
"0.59037286",
"0.59037286",
"0.5903544",
"0.5898120... | 0.8604357 | 0 |
This is the same as the parent except it also prints out the signature. | def __str__(self) -> str:
return_string = super().__str__()
return_string += f"\n{self.signature}"
return return_string | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def signature(self, p_int): # real signature unknown; restored from __doc__\n return \"\"",
"def __repr__(self):\n args = map(repr, [self.sig] + self[1:])\n return \"%s(%s)\" % (type(self).__name__, \", \".join(args))",
"def signature(self) -> global___SnippetSignature:",
"def signature(... | [
"0.7024263",
"0.6887671",
"0.6639112",
"0.6414004",
"0.6403797",
"0.62989455",
"0.6291004",
"0.6219402",
"0.6180741",
"0.6180741",
"0.6180741",
"0.61282855",
"0.60823816",
"0.60823816",
"0.6053541",
"0.6053541",
"0.60462373",
"0.59927696",
"0.59856004",
"0.5964969",
"0.596038... | 0.6861111 | 2 |
Search `docstr` for a type of `param_str`. | def _search_param_in_docstr(docstr, param_str):
# look at #40 to see definitions of those params
patterns = [re.compile(p % re.escape(param_str))
for p in DOCSTRING_PARAM_PATTERNS]
for pattern in patterns:
match = pattern.search(docstr)
if match:
return _strip_res... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_doc(cls, type_str):\n do_doc_test(cls, type_str)",
"def string_check(param, name):\n\tif not isinstance(param, strcomp):\n\t\traise TypeError(\"Keyword arg '%s' must be of type string. Got: %s\" % (\n\t\t\tname, type(param)))\n\telse:\n\t\tpass",
"def findType(*args, deep: bool=True, exact: bool=Tr... | [
"0.63382846",
"0.598061",
"0.58747685",
"0.5833059",
"0.57483447",
"0.56994957",
"0.56646067",
"0.56259286",
"0.5518372",
"0.54818416",
"0.54810244",
"0.5438783",
"0.5408456",
"0.5370847",
"0.53659624",
"0.5362474",
"0.5314391",
"0.528517",
"0.528517",
"0.5272139",
"0.5266672... | 0.75555766 | 0 |
Strip off the part looks like a ReST role in `type_str`. | def _strip_rest_role(type_str):
match = REST_ROLE_PATTERN.match(type_str)
if match:
return match.group(1)
else:
return type_str | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def strip_action_str(string: str) -> str:",
"def keep_types_s(s, types):\n patt = \"(?s)\" + \"|\".join(\"(?<=\\n)\" + s + \"\\n.+?\\n(?=\\S+|$)\" for s in types)\n return \"\".join(re.findall(patt, \"\\n\" + s.strip() + \"\\n\")).rstrip()",
"def remove_rt(token):\n if token == 'rt' or tok... | [
"0.63687265",
"0.614773",
"0.5987192",
"0.5897323",
"0.58686006",
"0.5840779",
"0.58221066",
"0.57654697",
"0.57208276",
"0.5631733",
"0.55604565",
"0.55465204",
"0.5546396",
"0.54754424",
"0.5445958",
"0.5437278",
"0.543659",
"0.5418817",
"0.54181844",
"0.5377318",
"0.536126... | 0.80957615 | 0 |
SmartNvmeSize a model defined in Swagger | def __init__(self, blocks: int=None, bytes: int=None): # noqa: E501
self.swagger_types = {
'blocks': int,
'bytes': int
}
self.attribute_map = {
'blocks': 'blocks',
'bytes': 'bytes'
}
self._blocks = blocks
self._bytes = by... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_representation_size(self):\n raise NotImplementedError()",
"def getSize(self) -> int:\n ...",
"def getSize(self) -> int:\n ...",
"def from_dict(cls, dikt) -> 'SmartNvmeSize':\n return util.deserialize_model(dikt, cls)",
"def getSize(self):\n return 1",
"def ... | [
"0.6321575",
"0.62322617",
"0.62322617",
"0.61111945",
"0.6077867",
"0.6034471",
"0.5993694",
"0.59876543",
"0.59714866",
"0.5971163",
"0.5907662",
"0.58435166",
"0.5779695",
"0.57618344",
"0.5730992",
"0.5667128",
"0.56641084",
"0.5624955",
"0.5622476",
"0.56101996",
"0.5598... | 0.0 | -1 |
Returns the dict as a model | def from_dict(cls, dikt) -> 'SmartNvmeSize':
return util.deserialize_model(dikt, cls) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def from_dict(cls, dikt) -> 'ModelClass':\n return util.deserialize_model(dikt, cls)",
"def to_dict_model(self) -> dict:\n return dict((key, getattr(self, key)) for key in self.__mapper__.c.keys())",
"def from_dict(cls, dikt):\n return util.deserialize_model(dikt, cls)",
"def from_dict(cls, ... | [
"0.6941054",
"0.68435305",
"0.6772809",
"0.6772809",
"0.6772809",
"0.6772809",
"0.6772809",
"0.6772809",
"0.6740629",
"0.66985685",
"0.66985685",
"0.6644842",
"0.6639277",
"0.6602594",
"0.6600973",
"0.66003793",
"0.65941405",
"0.6579801",
"0.65626",
"0.6414536",
"0.64143956",... | 0.0 | -1 |
Gets the blocks of this SmartNvmeSize. | def blocks(self) -> int:
return self._blocks | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getBlocks(self) -> List[ghidra.program.model.mem.MemoryBlock]:\n ...",
"def get_blocks(self):\n block_positions = product(range(self.block_size), range(self.block_size))\n return [self._get_block(i, j) for i, j in block_positions]",
"def blocks(self): # (list of size: block_period_numb... | [
"0.7196433",
"0.71351993",
"0.685585",
"0.6758741",
"0.6666133",
"0.6553506",
"0.65312415",
"0.6421771",
"0.6336547",
"0.6319847",
"0.6311347",
"0.629077",
"0.6184365",
"0.6114867",
"0.6088489",
"0.60132515",
"0.60027033",
"0.5997864",
"0.599185",
"0.5951994",
"0.59188086",
... | 0.654431 | 6 |
Sets the blocks of this SmartNvmeSize. | def blocks(self, blocks: int):
self._blocks = blocks | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _set_x_block_size(self):\n self._scene_gen.block_dimensions = (self._block_size_x_spinbox.value(),\n self._scene_gen.block_dimensions[Y],\n self._scene_gen.block_dimensions[Z])\n self._refresh_view()",
"def bl... | [
"0.6569442",
"0.64330506",
"0.6303345",
"0.60803413",
"0.6073872",
"0.6004342",
"0.5976128",
"0.59371215",
"0.58781767",
"0.58410674",
"0.5803466",
"0.5743724",
"0.5650272",
"0.56428427",
"0.5577154",
"0.5539702",
"0.553863",
"0.55320626",
"0.55199337",
"0.55170935",
"0.54881... | 0.71460104 | 0 |
Gets the bytes of this SmartNvmeSize. | def bytes(self) -> int:
return self._bytes | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def size(self):\r\n return self.size.data",
"def size_bytes(self) -> int:\n return pulumi.get(self, \"size_bytes\")",
"def readBytes(self, size=1):\n return self.bytes",
"def getSize(self):\r\n return self.size",
"def getSize(self):\n return self.size",
"def getSize(sel... | [
"0.7371811",
"0.71968883",
"0.6981857",
"0.695602",
"0.6946972",
"0.69296885",
"0.6893996",
"0.687236",
"0.68668884",
"0.67658156",
"0.6764008",
"0.6752757",
"0.67525524",
"0.67525524",
"0.67525524",
"0.673711",
"0.66910815",
"0.66758984",
"0.6666385",
"0.6661358",
"0.6634040... | 0.70552576 | 3 |
Sets the bytes of this SmartNvmeSize. | def bytes(self, bytes: int):
self._bytes = bytes | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_data_size(self, num_bytes):\n self.model.data_size = num_bytes\n self.refresh_memory()",
"def setsize(self, size):\n self.__size = size",
"def __set_size(self, size):\n if not isinstance(size, int):\n raise TypeError('The size should be an integer')\n if si... | [
"0.65401167",
"0.65033114",
"0.6215887",
"0.6185418",
"0.61283857",
"0.6123741",
"0.61116976",
"0.6108987",
"0.60780287",
"0.6022307",
"0.6020796",
"0.59437305",
"0.59437305",
"0.59437305",
"0.59437305",
"0.5898609",
"0.5884375",
"0.5875178",
"0.5854943",
"0.5837582",
"0.5769... | 0.62403035 | 2 |
Return query for get inforamtions about sides in order. | def client_supplier_query(order_id: int) -> Products:
Clients = aliased(Businesses)
Suppliers = aliased(Businesses)
ClientSupplier = join(Orders, Clients, Orders.client_name == Clients.name)\
.join(Suppliers, Suppliers.name == Orders.supplier_name)
query = aliased(select([Clients.name.label("Cl... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sides(self):\n\n return Finger.side_choices",
"def sides(self) -> Iterable['Side']:\n for solid in self.solids:\n yield from solid",
"def queryset(self, request):\n qs = super(AdRepOrderAdmin, self).queryset(request)\n qs = AdRepOrder.objects.select_related().filter(id__i... | [
"0.5445523",
"0.52991235",
"0.52020675",
"0.5064588",
"0.50240153",
"0.49783623",
"0.49547517",
"0.49403247",
"0.4938608",
"0.49364024",
"0.49066815",
"0.48336706",
"0.4826701",
"0.48130545",
"0.48010692",
"0.4798074",
"0.47941858",
"0.4783131",
"0.4774379",
"0.4741319",
"0.4... | 0.0 | -1 |
Return query for proucts on storage. | def types_query(owner_name):
query = Products.query.with_entities(Products.type_name.label('Type'))\
.filter_by(owner_name=owner_name)\
.distinct()
return query | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_queries() -> List[str]:\n\n logging.info(\"getting query files\")\n gcs = storage.Client(project=GCP_PROJECT)\n bucket = gcs.bucket(GCS_BUCKET)\n blobs = bucket.list_blobs(prefix='layered_gis')\n queries = {}\n for blob in blobs:\n blob_name = blob.name\n if '.sh' in blob_na... | [
"0.5889063",
"0.5862815",
"0.57291085",
"0.5719271",
"0.56243545",
"0.5602135",
"0.5601193",
"0.5601193",
"0.55706",
"0.5535134",
"0.55129355",
"0.5473278",
"0.54587007",
"0.54570323",
"0.5442046",
"0.54395086",
"0.54321676",
"0.5399316",
"0.5397061",
"0.53956485",
"0.5373300... | 0.0 | -1 |
Query to describe current storage. | def statistics_query(owner_name):
"""
WITH p_count AS (
SELECT
type_name,
owner_name,
COUNT(type_name) product_count
FROM products
GROUP BY (owner_name, type_name)
),
"""
p_count = db.session.query(
Products.type_name,
Prod... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_storage(isamAppliance, statistics_duration, check_mode=False, force=False):\n return isamAppliance.invoke_get(\n \"Retrieving the Storage Usage Statistics\",\n \"/statistics/systems/storage.json{0}\".format(\n tools.create_query_string(\n timespan=statistics_durat... | [
"0.65683",
"0.65081173",
"0.6428925",
"0.6336974",
"0.6310956",
"0.62664115",
"0.6209134",
"0.61565226",
"0.61411303",
"0.6129979",
"0.61074126",
"0.6100042",
"0.60946625",
"0.60684484",
"0.6000856",
"0.59938955",
"0.5965352",
"0.5947011",
"0.58958423",
"0.5844806",
"0.584081... | 0.0 | -1 |
Return query, where provide detaled info about available products for this type. | def expand_type_query(owner_name: str, type_name: []) -> 'session query':
critical_level = get_critical_level(owner_name, type_name)
ordered = db.session.query(
func.sum(SpecificOrders.quantity).label('number')
)\
.join(Orders, Orders.order_id == SpecificOrders.order_id)\
.filter(
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def available_products(self):\n # TODO - take into account bands, and what bands available in input products, etc\n return {k: self.__products__[k].description for k in self.__products__.keys()}",
"def show_available_products(): # {{{\n products_available = {}\n try:\n with MONGO:\n ... | [
"0.6795268",
"0.67284316",
"0.6657121",
"0.665529",
"0.664184",
"0.6528742",
"0.650293",
"0.6398634",
"0.6362628",
"0.6306756",
"0.6292385",
"0.62119484",
"0.621097",
"0.619985",
"0.6145081",
"0.6114483",
"0.6106502",
"0.61019003",
"0.604602",
"0.6039854",
"0.60307074",
"0.... | 0.53904986 | 64 |
Return query, where provide detaled info about available products for this type. | def expand_types_order(owner_name: str, type_name: [], order_id) -> 'session query':
query = select([Products.type_name.label('Type'),
Products.serial_number.label('Serial number'),
Products.producent.label('Producent'),
Products.model.label('Model'),
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def available_products(self):\n # TODO - take into account bands, and what bands available in input products, etc\n return {k: self.__products__[k].description for k in self.__products__.keys()}",
"def show_available_products(): # {{{\n products_available = {}\n try:\n with MONGO:\n ... | [
"0.67935586",
"0.6727523",
"0.66559565",
"0.6652261",
"0.66405725",
"0.6528544",
"0.6502141",
"0.6398148",
"0.6359407",
"0.6306457",
"0.6289251",
"0.62108374",
"0.6210161",
"0.6200407",
"0.6142485",
"0.61146283",
"0.6102825",
"0.60975516",
"0.60435545",
"0.60386443",
"0.60282... | 0.0 | -1 |
Create new product, from provided dict. | def create_product(new_product, owner_name):
if not isinstance(new_product, dict):
raise ValueError(f"New product {new_product} is not a dict")
new_instance = Products(
serial_number=new_product['serial_number'],
type_name=new_product['type_name'],
owner_name=owner_name,
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create(cls, dictionary):\n return cls(**dictionary)",
"def create(cls, dictionary):\n return cls(**dictionary)",
"def from_dict(cls, dct):\n return cls(**dct)",
"def create(cls, **kwargs):\n response = cls.get_client().create_product(**kwargs)\n object_details = cls._fl... | [
"0.71715415",
"0.71715415",
"0.65444577",
"0.65245855",
"0.6505505",
"0.643091",
"0.64308983",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",
"0.6385321",... | 0.6412352 | 7 |
Create query object to get all orderrs from storage. Return Query | def get_orders_query(history, business_id):
Clients = aliased(Businesses)
Suppliers = aliased(Businesses)
query = db.session.query(
Orders.order_id.label("Order id"),
Orders.order_date.label("Order date"),
Clients.name.label("Client"),
Suppliers.name.label("Supplier"),
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_all_orders():",
"def query_orders(self):\n return self._call_txtrader_api('query_orders', {})",
"def get(self):\n return DAO.orders",
"def get_query(self):\n q = db.Query(self.KIND,keys_only=self.KEYS_ONLY)\n for prop, value in self.FILTERS:\n q.filter(\"%s =\" ... | [
"0.6642401",
"0.6619481",
"0.639662",
"0.6373416",
"0.63626057",
"0.6110864",
"0.60644734",
"0.60009384",
"0.5964549",
"0.5941906",
"0.59289455",
"0.5920785",
"0.58526146",
"0.58117765",
"0.5804008",
"0.5788778",
"0.57617706",
"0.57590115",
"0.5752011",
"0.5750678",
"0.574840... | 0.562002 | 33 |
Return query, with all existing models. | def get_models_query():
query = db.session.query(Products.model).distinct()
return query | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def models(self, model=None):\n for query in self.__queries:\n if isinstance(query, orb.Query):\n yield query.model(model)\n else:\n for model in query.models(model):\n yield model",
"def _get_all_records(self) -> List[DBModelInstance]... | [
"0.69336724",
"0.67575055",
"0.6741291",
"0.6721403",
"0.66756815",
"0.66453505",
"0.65904415",
"0.6569294",
"0.65680003",
"0.6514055",
"0.6467715",
"0.64061546",
"0.64025044",
"0.6397078",
"0.6390089",
"0.6326347",
"0.6288563",
"0.6265645",
"0.6263423",
"0.62535185",
"0.6227... | 0.75393826 | 0 |
Return query, on all existing producents. | def get_producents_query():
query = db.session.query(Products.producent).distinct()
return query | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _getAllProvas(self):\n return self.execSql(\"select_all_provas\")",
"def generate_query(self):\n return",
"def make_query(self):",
"def query(self):\n pass",
"def get_query(self):\n q = db.Query(self.KIND,keys_only=self.KEYS_ONLY)\n for prop, value in self.FILTERS... | [
"0.70404816",
"0.60729134",
"0.603747",
"0.5846816",
"0.58360267",
"0.58090544",
"0.58018607",
"0.5783798",
"0.57318574",
"0.5725078",
"0.56661415",
"0.5665614",
"0.56622094",
"0.56526935",
"0.5649819",
"0.56355524",
"0.56053555",
"0.55854297",
"0.55686235",
"0.55618703",
"0.... | 0.7525649 | 0 |
Set a minimum relative uncertainty for the HirexSr signals. | def set_min_uncertainty(signal, threshold=0.05):
# Increase Hirex-Sr uncertainties to be a rel error of 5% minimum (JUST FOR TESTING)
corrected_unc=signal.std_y/signal.y<=0.05
signal.std_y[corrected_unc]=0.05*signal.y[corrected_unc]
# correction for normalized uncertainties
if signal.s/signal.m<=0.... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_min_confidence(self, new_min):\n self.__min_confidence = new_min",
"def set_Ec_min(self, x):\n x = float(x)\n if self.Ec_min != x:\n self.Ec_min = x\n self.Ec[0] = x",
"def setUncertainty(self, uncertainty):\n self.uncertainty = uncertainty",
"def... | [
"0.6703387",
"0.63027465",
"0.6177287",
"0.5665198",
"0.56195945",
"0.56136763",
"0.55630547",
"0.55627656",
"0.555593",
"0.555593",
"0.54854083",
"0.54678583",
"0.54263455",
"0.5422868",
"0.54227537",
"0.5412941",
"0.5385455",
"0.5342574",
"0.53386",
"0.53296685",
"0.5296957... | 0.69471943 | 0 |
Calculate the impurity confinement time, defined as the time constant obtained from an exponential fit of the spectroscopic signal after peaking. If signal is an array of signals, finds the impurity confinement time for each, then provides the mean and standard deviation within the set. | def get_tau_imp(signal, plots=True):
tau_imp=np.zeros((signal.y.shape[1],1))
time=signal.t
if plots==True:
f1 = plt.figure()
ax1 = f1.add_subplot(2,1,1)
ax2 = f1.add_subplot(2,1,2)
for i in range(signal.y.shape[1]):
sig=signal.y[:,i]
# Subtract the m... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def mean_squared_error_time(input_signalorspectrum, output_signalorspectrum):\n if isinstance(input_signalorspectrum, list) != True:\n observed_l = []\n observed_l.append(input_signalorspectrum)\n else:\n observed_l = input_signalorspectrum\n if isinstance(output_signalorspectrum, lis... | [
"0.5298134",
"0.51132464",
"0.5097189",
"0.5064602",
"0.50354946",
"0.50028414",
"0.49787804",
"0.49409816",
"0.49381432",
"0.4925306",
"0.49154824",
"0.49072072",
"0.49028787",
"0.4901111",
"0.4873843",
"0.48637593",
"0.48314908",
"0.4823539",
"0.4823539",
"0.48046473",
"0.4... | 0.5672792 | 0 |
Spoofs given MAC address | def spoof(self, mac, air=False):
if air:
os.system(
'sudo '
'/System/Library/PrivateFrameworks'
'/Apple80211.framework/Versions'
'/Current/Resources/airport -z'
)
_status = os.system('sudo ifconfig %s ether %s' % (self.id, mac))
return 'Interface %s (%s) => (%s)' % (self.id, self.ma... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _get_mac_address():\n if not sys.platform.startswith('linux'):\n raise RuntimeError(\n 'Cannot get the MAC address on non-Linux platforms'\n )\n ifname = get_default_iface_name_linux()\n s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n info... | [
"0.7184662",
"0.71231216",
"0.6886774",
"0.68855536",
"0.6876342",
"0.6869648",
"0.68631303",
"0.68411386",
"0.6823506",
"0.67871636",
"0.6784512",
"0.6739386",
"0.67346317",
"0.67322683",
"0.6722954",
"0.6696346",
"0.6696346",
"0.6696346",
"0.6696346",
"0.66954273",
"0.66713... | 0.6054331 | 68 |
Returns a list of interfaces objects. | def fetch():
_interfaces = [Interface(iface) for iface in netifaces.interfaces()]
for iface in _interfaces:
if (iface.id in BLACK_ID) or (iface.mac in BLACK_MAC) or (len(iface.mac) < 5):
_interfaces.remove(iface)
return _interfaces | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def interfaces(self):\n if self._interfaces is None:\n self._interfaces = list(x[\"interface\"] for x in self._interfaces_detailed_list())\n\n return self._interfaces",
"def list():\n\n\treturn netifaces.interfaces()",
"def _get_interfaces(self):\n return self.__interfaces",
"def ... | [
"0.81987125",
"0.8083309",
"0.78065586",
"0.78065586",
"0.78065586",
"0.7573135",
"0.75322247",
"0.7481535",
"0.72989315",
"0.69569594",
"0.6890868",
"0.68131423",
"0.6807769",
"0.678631",
"0.67372656",
"0.6702418",
"0.66673565",
"0.66494524",
"0.66494524",
"0.6603068",
"0.66... | 0.62256 | 29 |
Lists available interface names. | def list():
return netifaces.interfaces() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def interface_list() -> List[str]:\n cmd_ip = system_command('ip')\n command = f\"{cmd_ip} -o addr show up primary scope global\".split()\n result = SUDO.execute_unit(command)\n result.assert_return()\n line_list = result.stdout.splitlines()\n pattern = re.compile(r\"^\\d+[:]\\s+(\\S+)\\s+(.+)$\"... | [
"0.7411383",
"0.7232032",
"0.72114456",
"0.6973412",
"0.69043547",
"0.68619394",
"0.679673",
"0.6740396",
"0.6686123",
"0.6686123",
"0.6661291",
"0.66574144",
"0.6648544",
"0.65959096",
"0.65669006",
"0.65150845",
"0.64693594",
"0.64693594",
"0.64693594",
"0.6445497",
"0.6410... | 0.7836606 | 0 |
build weixin JSApi.chooseWXPay params | def build_jspay_params(paysign_key, appid, prepay_id):
_params = {
"nonceStr": sign.random_nonce_str(32),
"timeStamp": int(time.time()),
"package": 'prepay_id={}'.format(prepay_id),
"signType": "MD5",
"appId": appid
}
_params['paySign'] = sign.sign_for_pay(paysign_key... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_parameters(pobj):\n ViscosityWilke.build_parameters(pobj)",
"def initialize(public_api_key, default_wak=None, params=None):\n\n if params is None:\n params = {}\n\n print('initializing lnpay..')\n\n global __VERSION__\n global __PUBLIC_API_KEY__\n global __ENDPOINT_URL_... | [
"0.5316788",
"0.5219171",
"0.49018717",
"0.48517498",
"0.48473987",
"0.4843703",
"0.47966686",
"0.4786458",
"0.4684021",
"0.46805087",
"0.46547464",
"0.46540335",
"0.46333072",
"0.46102008",
"0.46095118",
"0.46002406",
"0.45881376",
"0.45822966",
"0.4577122",
"0.4576725",
"0.... | 0.5701106 | 0 |
Change the urls in all content pages. Also changes the urls that begin with this url. | def rename_url(self, old_url, new_url):
def rename_html(html):
return re.sub(
r"""(\s)href=(["'])%s""" % old_url,
r'\1href=\2%s' % new_url,
html
)
def rename_markup(markup):
if not 'rename_url_expressions' in editor.edi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def urls(self, urls):\n\n self._urls = urls",
"def _update_urls(self):\n\n to_fix = [\n # We fix the urls in the README file.\n PyFunceble.CONFIG_DIRECTORY + \"README.rst\",\n # We fix the urls in the configuration file.\n PyFunceble.CONFIG_DIRECTORY + \"... | [
"0.66469926",
"0.64842045",
"0.64342177",
"0.64010423",
"0.6328618",
"0.61935735",
"0.61853534",
"0.6152363",
"0.61477363",
"0.61453766",
"0.6060277",
"0.6017771",
"0.59222454",
"0.5780527",
"0.5741267",
"0.5735124",
"0.5707387",
"0.56970894",
"0.56782633",
"0.5617779",
"0.56... | 0.6101035 | 10 |
Return sorted content items for this block. | def get_content_for_block(self, block_name):
return self.page_content_items.filter(block_name=block_name).order_by('sort') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_items(self, instance):\n sorted_items = instance.items.order_by('contentitemonpage__sort_by').all()\n return ContentItemSerializer(sorted_items, read_only=True, many=True).data",
"def __get_items(self, sort_keys_function=None):\n if sort_keys_function:\n return sorted(list... | [
"0.7203827",
"0.65020275",
"0.6405821",
"0.6380889",
"0.6337046",
"0.6282616",
"0.62138516",
"0.6061105",
"0.5986232",
"0.5945387",
"0.59096706",
"0.5909197",
"0.57804215",
"0.5760349",
"0.57546836",
"0.5749722",
"0.57332176",
"0.57332176",
"0.57321185",
"0.57300663",
"0.5728... | 0.7341322 | 0 |
Load an object given its absolute object path, and return it. object can be a class, function, variable or an instance. | def import_object(path):
try:
dot = path.rindex('.')
except ValueError:
raise ValueError("Error loading object '%s': not a full path" % path)
module, name = path[:dot], path[dot+1:]
mod = import_module(module)
try:
obj = getattr(mod, name)
except AttributeError:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_object(path):\n try:\n dot = path.rindex('.')\n except ValueError:\n raise ValueError(\"Error loading object '%s': not a full path\" % path)\n\n module, name = path[:dot], path[dot+1:]\n mod = import_module(module)\n\n try:\n obj = getattr(mod, name)\n except Attribu... | [
"0.87203074",
"0.8714351",
"0.86193395",
"0.80881464",
"0.76507956",
"0.7540539",
"0.75298196",
"0.7481483",
"0.7424371",
"0.733665",
"0.73353285",
"0.7264761",
"0.72388357",
"0.7229578",
"0.7178961",
"0.69940937",
"0.69565845",
"0.6937031",
"0.69023806",
"0.6859193",
"0.6791... | 0.83069754 | 3 |
Indicates whether specific platform is need to be built | def has_platform(self, platform_name):
return platform_name in self.platform_list | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def platform_supported(self):\n return platform.system().lower() in self.platforms if self.platforms else False",
"def check_platform():\n system = platform.system()\n distro = platform.platform()\n is_raspberry_pi = False\n try:\n info = open(\"/proc/cpuinfo\").read()\n except FileN... | [
"0.71212935",
"0.70436865",
"0.6949426",
"0.6933144",
"0.68413055",
"0.6644802",
"0.664328",
"0.6630137",
"0.6541337",
"0.6534053",
"0.65173113",
"0.64472014",
"0.6441205",
"0.64278555",
"0.6403306",
"0.6343476",
"0.6329101",
"0.6326767",
"0.63261914",
"0.63257444",
"0.632147... | 0.6023522 | 59 |
Fetches repos from config.json | def fetch_repos(self):
for repo in self.json_repos['repos']:
title = str(repo["title"])
repo_url = str(repo['repo'])
self.repos[title] = repo_url | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fetch_repos(connection):\n\n try:\n response = connection.get_json('repository')\n except HTTPRequestError as ex:\n raise exception_from_http_error(ex) from ex\n\n result = response.get('result', [])\n return [Repository(connection, repo['rid'], data=repo) for repo in result]",
"def... | [
"0.69072866",
"0.68005025",
"0.6771198",
"0.6725589",
"0.66690826",
"0.6660223",
"0.6563224",
"0.6562054",
"0.6532253",
"0.6429869",
"0.6419862",
"0.6401692",
"0.63973206",
"0.62876177",
"0.6262754",
"0.62594336",
"0.6254202",
"0.6254202",
"0.6208351",
"0.6194637",
"0.6191547... | 0.78047276 | 0 |
Fetches branches for each repo from config.json | def fetch_branches(self):
for jrepo in self.json_repos['repos']:
title = str(jrepo["title"])
self.branches[title] = str(jrepo['current']) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def branches_full(config, args):\n for b in config.repo.branches():\n yield config.repo.branch(b.name)",
"def show_branches(config, args):\n for item in lib.input_json_lines():\n yield config.repo.branch(item)",
"def make_branches(self, api_json=None):\n if api_json is None:\n return ... | [
"0.69463867",
"0.68368787",
"0.6707363",
"0.6653876",
"0.6577588",
"0.65272236",
"0.6501614",
"0.64859295",
"0.64772815",
"0.6438882",
"0.64305085",
"0.6258769",
"0.62371534",
"0.6195701",
"0.6190658",
"0.61512154",
"0.6114853",
"0.60720813",
"0.60627514",
"0.60360074",
"0.59... | 0.7710535 | 0 |
Returns a list of initial environment setup steps | def init_workspace_steps(self):
return [
InstallShellJS(),
RMCommand(path="~/.cordova/" + self.platform, workdir='build', haltOnFailure=False, description='Remove cache'),
RMCommand(path="*", workdir='build', haltOnFailure=False, description='Clean workdir'),
Shel... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def envs():\n\n # update and grab the envs from the metadata keys\n metadata = _init()\n return list(metadata.keys())",
"def SetupEnvironment(self):\n pass",
"def _get_install_steps(self):\n\n content = self._get_yaml_content()\n\n return self._fix_install_steps(content['install'])",
... | [
"0.66229904",
"0.6526401",
"0.63138646",
"0.6217128",
"0.6208876",
"0.61686397",
"0.60309076",
"0.6027222",
"0.59644306",
"0.5938788",
"0.58808476",
"0.58711517",
"0.5822204",
"0.581619",
"0.5760303",
"0.57595754",
"0.575318",
"0.5719677",
"0.5706185",
"0.56916517",
"0.568056... | 0.6193221 | 5 |
Returns a list of steps for cloning necessary repos | def repos_clone_steps(self):
platform = self.platform
# required by coho tools to correctly resolve repo location
if platform == "blackberry10":
platform = "blackberry"
return [
ShellCommand(command=["node", "medic/checkout.js", "--path=medic/repos.json", "--cat=C... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def clone_all_repo(self):\n repo_path = self.cfg['paths']['repo']\n since = datetime.datetime.strptime(self.cfg['filters']['since'], self.cfg['filters']['date_format'])\n threads = []\n # INITIALIZE ALL REPOS\n for repo in self.cfg[\"repos\"]:\n if (not self.cfg['repla... | [
"0.6446149",
"0.6382948",
"0.6273487",
"0.6116369",
"0.59837794",
"0.59746057",
"0.58794206",
"0.5857089",
"0.5844229",
"0.5772935",
"0.572115",
"0.5718577",
"0.57020026",
"0.56601727",
"0.56417",
"0.5637879",
"0.5619802",
"0.56186646",
"0.5604742",
"0.5546208",
"0.55187005",... | 0.79946405 | 0 |
Returns a list of steps for CLI setup | def cli_steps(self):
return [
ShellCommand(command=["git", "clone", "-b", CONFIG.branches['CLI'], CONFIG.repos['CLI'], "cordova-cli"], workdir='build', haltOnFailure=True, description='Clone CLI'),
ShellCommand(command=["git", "clone", "--depth", "1", "-b", CONFIG.branches['CORDOVA-LIB']... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setup_commands(self):\n return self.get_data(\"setup_commands\")",
"def _get_install_steps(self):\n\n content = self._get_yaml_content()\n\n return self._fix_install_steps(content['install'])",
"def get_all_steps(self):\n steps = []\n steps.extend(self.init_workspace_step... | [
"0.6651091",
"0.6479719",
"0.6409983",
"0.6366993",
"0.6313349",
"0.6267738",
"0.6155656",
"0.6142456",
"0.6105375",
"0.60354024",
"0.5895893",
"0.5795892",
"0.57458186",
"0.56846845",
"0.567229",
"0.5646961",
"0.5621909",
"0.56113553",
"0.5608341",
"0.55730104",
"0.5529855",... | 0.7070678 | 0 |
Returns a list of steps for CLI setup Should not be used in common case, only for common slave tests | def plugman_steps(self):
return [
ShellCommand(command=["rm", "-rf", "cordova-*"], workdir='build', haltOnFailure=False, description='Cordova Clean'),
ShellCommand(command=["git", "clone", CONFIG.repos['PLUGMAN'], "cordova-plugman"], workdir='build', haltOnFailure=True, description='Get ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cli_steps(self):\n return [\n ShellCommand(command=[\"git\", \"clone\", \"-b\", CONFIG.branches['CLI'], CONFIG.repos['CLI'], \"cordova-cli\"], workdir='build', haltOnFailure=True, description='Clone CLI'),\n ShellCommand(command=[\"git\", \"clone\", \"--depth\", \"1\", \"-b\", CONF... | [
"0.7121964",
"0.66414857",
"0.6590362",
"0.6503794",
"0.6442164",
"0.6309476",
"0.6200637",
"0.60921854",
"0.6006797",
"0.58807784",
"0.5764678",
"0.5671883",
"0.56505984",
"0.56240004",
"0.5579277",
"0.55354774",
"0.55034655",
"0.54971015",
"0.546893",
"0.5453238",
"0.544851... | 0.61514026 | 7 |
Returns a list of steps for mobilespec app setup | def prepare_mobilespec_steps(self):
platform = self.platform
# required by coho tools to correctly resolve repo location
if platform == "blackberry10":
platform = "blackberry"
return [
NPMInstall(workdir='build/cordova-mobile-spec/createmobilespec', haltOnFailure=... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def deploy_steps(self):\n return [ShellCommand(command=[\"node\", \"medic/build_\" + self.platform + \".js\"], workdir='build', timeout=CONFIG.build_timeout, description='Run tests', name='Run tests')]",
"def init_workspace_steps(self):\n return [\n InstallShellJS(),\n RMComma... | [
"0.65084136",
"0.642119",
"0.6384407",
"0.63580227",
"0.6311263",
"0.62183255",
"0.59461796",
"0.56012833",
"0.555745",
"0.55543995",
"0.5514638",
"0.54713285",
"0.54269874",
"0.54202676",
"0.53925604",
"0.5366822",
"0.53609735",
"0.5345367",
"0.5297906",
"0.5297146",
"0.5282... | 0.760149 | 0 |
Returns a list of steps for deploying mobilespec application to test device | def deploy_steps(self):
return [ShellCommand(command=["node", "medic/build_" + self.platform + ".js"], workdir='build', timeout=CONFIG.build_timeout, description='Run tests', name='Run tests')] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def prepare_mobilespec_steps(self):\n platform = self.platform\n # required by coho tools to correctly resolve repo location\n if platform == \"blackberry10\":\n platform = \"blackberry\"\n return [\n NPMInstall(workdir='build/cordova-mobile-spec/createmobilespec',... | [
"0.75590795",
"0.63454",
"0.6130196",
"0.6108414",
"0.5982014",
"0.58221376",
"0.5818699",
"0.56397694",
"0.5596652",
"0.55899227",
"0.5447674",
"0.54173493",
"0.5405188",
"0.5400062",
"0.53762925",
"0.53739935",
"0.53050184",
"0.5303761",
"0.5242022",
"0.5242022",
"0.5223853... | 0.75774807 | 0 |
Returns a list of steps for building mobilespec application | def build_platform_step(self):
return [ShellCommand(command=["../cordova-cli/bin/cordova", "build", self.platform], workdir='build/mobilespec', timeout=CONFIG.build_timeout, description='Build', name='Build')] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def prepare_mobilespec_steps(self):\n platform = self.platform\n # required by coho tools to correctly resolve repo location\n if platform == \"blackberry10\":\n platform = \"blackberry\"\n return [\n NPMInstall(workdir='build/cordova-mobile-spec/createmobilespec',... | [
"0.779069",
"0.67776674",
"0.64382553",
"0.624265",
"0.60818905",
"0.6052851",
"0.6028818",
"0.57117945",
"0.56699735",
"0.5631484",
"0.5578449",
"0.5562804",
"0.5509476",
"0.5509476",
"0.5501834",
"0.5475979",
"0.5436348",
"0.53203976",
"0.5319532",
"0.5312754",
"0.5293944",... | 0.6734113 | 2 |
Returns a list of all steps current platform | def get_all_steps(self):
steps = []
steps.extend(self.init_workspace_steps())
steps.extend(self.repos_clone_steps())
steps.extend(self.cli_steps())
steps.extend(self.prepare_mobilespec_steps())
steps.extend(self.deploy_steps())
return steps | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def availableSteps( self ):\n assert isinstance( self._level, int )\n assert isinstance( self._steps, list )\n assert isinstance( self._outter, Env ) or ( self._outter is None )\n\n lst = [ ]\n self._availableSteps( lst )\n return lst",
"def Platforms():\n return platforms",
... | [
"0.6643733",
"0.6476299",
"0.6185028",
"0.59915143",
"0.5967349",
"0.59573674",
"0.5938493",
"0.5935553",
"0.59315646",
"0.5929291",
"0.5864497",
"0.58506036",
"0.58318293",
"0.58021766",
"0.5801714",
"0.57479554",
"0.5633305",
"0.5621189",
"0.56003636",
"0.55945224",
"0.5584... | 0.7025099 | 0 |
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