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How to use _set_test_name method in gabbi

Best Python code snippet using gabbi_python

suitemaker.py

Source:suitemaker.py

...65            else:66                # NOTE(cdent): Not clear this can happen but just in case.67                raise GabbiFormatError(68                    'malformed test chunk "%s": %s' % (test_dict, exc))69        test_name = self._set_test_name(test)70        self._set_test_method_and_url(test, test_name)71        self._validate_keys(test, test_name)72        # Set server hostname in http request if host header is set.73        if 'request_headers' in test and 'host' in test['request_headers']:74            hostname = test['request_headers']['host']75        else:76            hostname = None77        http_class = httpclient.get_http(verbose=test['verbose'],78                                         caption=test['name'],79                                         cert_validate=test['cert_validate'],80                                         hostname=hostname)81        if prior_test:82            history = prior_test.history83        else:84            history = {}85        test_method_name = 'test_request'86        test_method = getattr(case.HTTPTestCase, test_method_name)87        @unittest.skipIf(self.host == '', 'No host configured')88        @functools.wraps(test_method)89        def do_test(*args, **kwargs):90            return test_method(*args, **kwargs)91        # Use metaclasses to build a class of the necessary type92        # and name with relevant arguments.93        klass = TestBuilder(test_name, (case.HTTPTestCase,),94                            {'test_data': test,95                             'test_directory': self.test_directory,96                             'fixtures': self.fixture_classes,97                             'inner_fixtures': self.inner_fixtures,98                             'http': http_class,99                             'host': self.host,100                             'intercept': self.intercept,101                             'content_handlers': self.content_handlers,102                             'response_handlers': self.response_handlers,103                             'port': self.port,104                             'prefix': self.prefix,105                             'prior': prior_test,106                             'history': history,107                             'test_base_name': self.test_base_name,108                             test_method_name: do_test,109                             })110        # We've been asked to, make this test class think it comes111        # from a different module.112        if self.test_loader_name:113            klass.__module__ = self.test_loader_name114        tests = self.loader.loadTestsFromTestCase(klass)115        history[test['name']] = tests._tests[0]116        # Return the first (and only) test in the klass.117        return tests._tests[0]118    def _set_test_name(self, test):119        """Set the name of the test120        The original name is lowercased and spaces are replaces with '_'.121        The result is appended to the test_base_name, which is based on the122        name of the input data file.123        """124        if not test['name']:125            raise GabbiFormatError('Test name missing in a test in %s.'126                                   % self.test_base_name)127        return '%s_%s' % (self.test_base_name,128                          test['name'].lower().replace(' ', '_'))129    @staticmethod130    def _set_test_method_and_url(test, test_name):131        """Extract the base URL and method for this test.132        If there is an upper case key in the test, that is used as the...

test_common.py

Source:test_common.py

...44    # properly45    assert_greater(len(estimators), 0)46    for name, Estimator in estimators:47        # some can just not be sensibly default constructed48        yield (_set_test_name(check_parameters_default_constructible, name),49               name, Estimator)50def test_non_meta_estimators():51    # input validation etc for non-meta estimators52    estimators = all_estimators()53    for name, Estimator in estimators:54        if issubclass(Estimator, BiclusterMixin):55            continue56        if name.startswith("_"):57            continue58        for check in _yield_all_checks(name, Estimator):59            if issubclass(Estimator, ProjectedGradientNMF):60                # The ProjectedGradientNMF class is deprecated61                with ignore_warnings():62                    yield _set_test_name(check, name), name, Estimator63            else:64                yield _set_test_name(check, name), name, Estimator65def test_configure():66    # Smoke test the 'configure' step of setup, this tests all the67    # 'configure' functions in the setup.pys in the scikit68    cwd = os.getcwd()69    setup_path = os.path.abspath(os.path.join(sklearn.__path__[0], '..'))70    setup_filename = os.path.join(setup_path, 'setup.py')71    if not os.path.exists(setup_filename):72        return73    try:74        os.chdir(setup_path)75        old_argv = sys.argv76        sys.argv = ['setup.py', 'config']77        clean_warning_registry()78        with warnings.catch_warnings():79            # The configuration spits out warnings when not finding80            # Blas/Atlas development headers81            warnings.simplefilter('ignore', UserWarning)82            if PY3:83                with open('setup.py') as f:84                    exec(f.read(), dict(__name__='__main__'))85            else:86                execfile('setup.py', dict(__name__='__main__'))87    finally:88        sys.argv = old_argv89        os.chdir(cwd)90def test_class_weight_balanced_linear_classifiers():91    classifiers = all_estimators(type_filter='classifier')92    clean_warning_registry()93    with warnings.catch_warnings(record=True):94        linear_classifiers = [95            (name, clazz)96            for name, clazz in classifiers97            if ('class_weight' in clazz().get_params().keys() and98                issubclass(clazz, LinearClassifierMixin))]99    for name, Classifier in linear_classifiers:100        yield _set_test_name(check_class_weight_balanced_linear_classifier,101                             name), name, Classifier102@ignore_warnings103def test_import_all_consistency():104    # Smoke test to check that any name in a __all__ list is actually defined105    # in the namespace of the module or package.106    pkgs = pkgutil.walk_packages(path=sklearn.__path__, prefix='sklearn.',107                                 onerror=lambda _: None)108    submods = [modname for _, modname, _ in pkgs]109    for modname in submods + ['sklearn']:110        if ".tests." in modname:111            continue112        package = __import__(modname, fromlist="dummy")113        for name in getattr(package, '__all__', ()):114            if getattr(package, name, None) is None:115                raise AttributeError(116                    "Module '{0}' has no attribute '{1}'".format(117                        modname, name))118def test_root_import_all_completeness():119    EXCEPTIONS = ('utils', 'tests', 'base', 'setup')120    for _, modname, _ in pkgutil.walk_packages(path=sklearn.__path__,121                                               onerror=lambda _: None):122        if '.' in modname or modname.startswith('_') or modname in EXCEPTIONS:123            continue124        assert_in(modname, sklearn.__all__)125def test_all_tests_are_importable():126    # Ensure that for each contentful subpackage, there is a test directory127    # within it that is also a subpackage (i.e. a directory with __init__.py)128    HAS_TESTS_EXCEPTIONS = re.compile(r'''(?x)129                                      \.externals(\.|$)|130                                      \.tests(\.|$)|131                                      \._132                                      ''')133    lookup = dict((name, ispkg)134                  for _, name, ispkg135                  in pkgutil.walk_packages(sklearn.__path__,136                                           prefix='sklearn.'))137    missing_tests = [name for name, ispkg in lookup.items()138                     if ispkg139                     and not HAS_TESTS_EXCEPTIONS.search(name)140                     and name + '.tests' not in lookup]141    assert_equal(missing_tests, [],142                 '{0} do not have `tests` subpackages. Perhaps they require '143                 '__init__.py or an add_subpackage directive in the parent '144                 'setup.py'.format(missing_tests))145def test_non_transformer_estimators_n_iter():146    # Test that all estimators of type which are non-transformer147    # and which have an attribute of max_iter, return the attribute148    # of n_iter atleast 1.149    for est_type in ['regressor', 'classifier', 'cluster']:150        regressors = all_estimators(type_filter=est_type)151        for name, Estimator in regressors:152            # LassoLars stops early for the default alpha=1.0 for153            # the iris dataset.154            if name == 'LassoLars':155                estimator = Estimator(alpha=0.)156            else:157                estimator = Estimator()158            if hasattr(estimator, "max_iter"):159                # These models are dependent on external solvers like160                # libsvm and accessing the iter parameter is non-trivial.161                if name in (['Ridge', 'SVR', 'NuSVR', 'NuSVC',162                             'RidgeClassifier', 'SVC', 'RandomizedLasso',163                             'LogisticRegressionCV']):164                    continue165                # Tested in test_transformer_n_iter below166                elif (name in CROSS_DECOMPOSITION or167                      name in ['LinearSVC', 'LogisticRegression']):168                    continue169                else:170                    # Multitask models related to ENet cannot handle171                    # if y is mono-output.172                    yield (_set_test_name(173                        check_non_transformer_estimators_n_iter, name),174                        name, estimator, 'Multi' in name)175def test_transformer_n_iter():176    transformers = all_estimators(type_filter='transformer')177    for name, Estimator in transformers:178        if issubclass(Estimator, ProjectedGradientNMF):179            # The ProjectedGradientNMF class is deprecated180            with ignore_warnings():181                estimator = Estimator()182        else:183            estimator = Estimator()184        # Dependent on external solvers and hence accessing the iter185        # param is non-trivial.186        external_solver = ['Isomap', 'KernelPCA', 'LocallyLinearEmbedding',187                           'RandomizedLasso', 'LogisticRegressionCV']188        if hasattr(estimator, "max_iter") and name not in external_solver:189            if isinstance(estimator, ProjectedGradientNMF):190                # The ProjectedGradientNMF class is deprecated191                with ignore_warnings():192                    yield _set_test_name(193                        check_transformer_n_iter, name), name, estimator194            else:195                yield _set_test_name(196                    check_transformer_n_iter, name), name, estimator197def test_get_params_invariance():198    # Test for estimators that support get_params, that199    # get_params(deep=False) is a subset of get_params(deep=True)200    # Related to issue #4465201    estimators = all_estimators(include_meta_estimators=False,202                                include_other=True)203    for name, Estimator in estimators:204        if hasattr(Estimator, 'get_params'):205            # If class is deprecated, ignore deprecated warnings206            if hasattr(Estimator.__init__, "deprecated_original"):207                with ignore_warnings():208                    yield _set_test_name(209                        check_get_params_invariance, name), name, Estimator210            else:211                yield _set_test_name(...

bc_factory.py

Source:bc_factory.py

...64                self._set_result(vertex)65            elif vertex.role.lower() == "topic":66                self._set_test_code(vertex)67            elif vertex.role.lower() == "qualifier.synonym.name":68                self._set_test_name(vertex)69            elif vertex.role.lower() == "qualifier.synonym.loinc":70                self._set_loinc_code(vertex)71            elif vertex.role.lower() == "qualifier.record" or vertex.role.lower() == "qualifier.variable" or \72                vertex.role.lower() == "qualifier.grouping":73                self._set_qualifier(vertex)74            else:75                #TODO check to see if it's an invalid role76                print(f"not processing role: {vertex.role}")77        except AttributeError:78            print(f"Concept {vertex.label} is missing the role attribute")79    def _set_qualifier(self, vertex):80        """81        for DECs with role qualifier set the BC attributes82        :param vertex: node object from the graph created using the CMAP83        """84        for node in vertex.target:85            if node[0].type == "Conceptual Domain":86                if node[0].ct_subset:87                    self._qualifiers[vertex.label] = self._set_qualifier_subset(node[0].ct_subset)88                else:89                    self._qualifiers[vertex.label] = node[0].label90                break91    def _set_qualifier_subset(self, subset):92        """93        return the name, c-code, and terms for a CT subset that defines a DEC CD (conceptual domain)94        :param subset: CT subset object that includes the list of terms95        :return: qualifier CT subset dictionary96        """97        qualifier_subset = {"name": subset.name, "c_code": subset.c_code}98        terms = []99        for term in subset.terms:100            term_label = term.label101            if term.is_default:102                term_label = term_label + " default"103            terms.append(term_label)104            qualifier_subset["terms"] = terms105        return qualifier_subset106    def _set_test_code(self, vertex):107        """108        sets the TESTCD and associated c-code for findings domain BCs; set to one value for the BC109        :param vertex: node object from the graph created using the CMAP110        """111        for node in vertex.target:112            if node[0].type == "Conceptual Domain":113                self.kwargs["test_cd"] = node[0].label.split("(")[0].strip()114                self.kwargs["test_c_code"] = node[0].label.split("(")[1].strip()[:-1]115                break116    def _set_test_name(self, vertex):117        """118        sets the test name for findings domain BCs; set to one value for the BC119        :param vertex: node object from the graph created using the CMAP120        """121        for node in vertex.target:122            if node[0].type == "Conceptual Domain":123                self.kwargs["test_name"] = node[0].label.split("(")[0].strip()124                break125    def _set_loinc_code(self, vertex):126        """127        sets the loinc code for findings domain BCs; set to one value for the BC128        :param vertex: node object from the graph created using the CMAP129        """130        for node in vertex.target:...

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