How to use assert_examples method in hypothesis

Best Python code snippet using hypothesis

test_tasks.py

Source:test_tasks.py

...18        kwargs = kwargs or {}19        return import_dataset(self.user.id, self.project.item.id, filenames, file_format, **kwargs)20class TestImportClassificationData(TestImportData):21    task = DOCUMENT_CLASSIFICATION22    def assert_examples(self, dataset):23        self.assertEqual(Example.objects.count(), len(dataset))24        for text, expected_labels in dataset:25            example = Example.objects.get(text=text)26            labels = set(cat.label.text for cat in example.categories.all())27            self.assertEqual(labels, set(expected_labels))28    def assert_parse_error(self, response):29        self.assertGreaterEqual(len(response['error']), 1)30        self.assertEqual(Example.objects.count(), 0)31        self.assertEqual(CategoryType.objects.count(), 0)32        self.assertEqual(Category.objects.count(), 0)33    def test_jsonl(self):34        filename = 'text_classification/example.jsonl'35        file_format = 'JSONL'36        kwargs = {'column_label': 'labels'}37        dataset = [38            ('exampleA', ['positive']),39            ('exampleB', ['positive', 'negative']),40            ('exampleC', [])41        ]42        self.import_dataset(filename, file_format, kwargs)43        self.assert_examples(dataset)44    def test_csv(self):45        filename = 'text_classification/example.csv'46        file_format = 'CSV'47        dataset = [48            ('exampleA', ['positive']),49            ('exampleB', [])50        ]51        self.import_dataset(filename, file_format)52        self.assert_examples(dataset)53    def test_csv_out_of_order_columns(self):54        filename = 'text_classification/example_out_of_order_columns.csv'55        file_format = 'CSV'56        dataset = [57            ('exampleA', ['positive']),58            ('exampleB', [])59        ]60        self.import_dataset(filename, file_format)61        self.assert_examples(dataset)62    def test_fasttext(self):63        filename = 'text_classification/example_fasttext.txt'64        file_format = 'fastText'65        dataset = [66            ('exampleA', ['positive']),67            ('exampleB', ['positive', 'negative']),68            ('exampleC', [])69        ]70        self.import_dataset(filename, file_format)71        self.assert_examples(dataset)72    def test_excel(self):73        filename = 'text_classification/example.xlsx'74        file_format = 'Excel'75        dataset = [76            ('exampleA', ['positive']),77            ('exampleB', [])78        ]79        self.import_dataset(filename, file_format)80        self.assert_examples(dataset)81    def test_json(self):82        filename = 'text_classification/example.json'83        file_format = 'JSON'84        dataset = [85            ('exampleA', ['positive']),86            ('exampleB', ['positive', 'negative']),87            ('exampleC', [])88        ]89        self.import_dataset(filename, file_format)90        self.assert_examples(dataset)91    def test_textfile(self):92        filename = 'example.txt'93        file_format = 'TextFile'94        dataset = [95            ('exampleA\nexampleB\n\nexampleC\n', [])96        ]97        self.import_dataset(filename, file_format)98        self.assert_examples(dataset)99    def test_textline(self):100        filename = 'example.txt'101        file_format = 'TextLine'102        dataset = [103            ('exampleA', []),104            ('exampleB', []),105            ('exampleC', [])106        ]107        self.import_dataset(filename, file_format)108        self.assert_examples(dataset)109    def test_wrong_jsonl(self):110        filename = 'text_classification/example.json'111        file_format = 'JSONL'112        response = self.import_dataset(filename, file_format)113        self.assert_parse_error(response)114    def test_wrong_json(self):115        filename = 'text_classification/example.jsonl'116        file_format = 'JSON'117        response = self.import_dataset(filename, file_format)118        self.assert_parse_error(response)119    def test_wrong_excel(self):120        filename = 'text_classification/example.jsonl'121        file_format = 'Excel'122        response = self.import_dataset(filename, file_format)123        self.assert_parse_error(response)124    def test_wrong_csv(self):125        filename = 'text_classification/example.jsonl'126        file_format = 'CSV'127        response = self.import_dataset(filename, file_format)128        self.assert_parse_error(response)129class TestImportSequenceLabelingData(TestImportData):130    task = SEQUENCE_LABELING131    def assert_examples(self, dataset):132        self.assertEqual(Example.objects.count(), len(dataset))133        for text, expected_labels in dataset:134            example = Example.objects.get(text=text)135            labels = [[span.start_offset, span.end_offset, span.label.text] for span in example.spans.all()]136            self.assertEqual(labels, expected_labels)137    def assert_parse_error(self, response):138        self.assertGreaterEqual(len(response['error']), 1)139        self.assertEqual(Example.objects.count(), 0)140        self.assertEqual(SpanType.objects.count(), 0)141        self.assertEqual(Span.objects.count(), 0)142    def test_jsonl(self):143        filename = 'sequence_labeling/example.jsonl'144        file_format = 'JSONL'145        dataset = [146            ('exampleA', [[0, 1, 'LOC']]),147            ('exampleB', [])148        ]149        self.import_dataset(filename, file_format)150        self.assert_examples(dataset)151    def test_conll(self):152        filename = 'sequence_labeling/example.conll'153        file_format = 'CoNLL'154        dataset = [155            ('JAPAN GET', [[0, 5, 'LOC']]),156            ('Nadim Ladki', [[0, 11, 'PER']])157        ]158        self.import_dataset(filename, file_format)159        self.assert_examples(dataset)160    def test_wrong_conll(self):161        filename = 'sequence_labeling/example.jsonl'162        file_format = 'CoNLL'163        response = self.import_dataset(filename, file_format)164        self.assert_parse_error(response)165    def test_jsonl_with_overlapping(self):166        filename = 'sequence_labeling/example_overlapping.jsonl'167        file_format = 'JSONL'168        response = self.import_dataset(filename, file_format)169        self.assertEqual(len(response['error']), 1)170class TestImportSeq2seqData(TestImportData):171    task = SEQ2SEQ172    def assert_examples(self, dataset):173        self.assertEqual(Example.objects.count(), len(dataset))174        for text, expected_labels in dataset:175            example = Example.objects.get(text=text)176            labels = set(text_label.text for text_label in example.texts.all())177            self.assertEqual(labels, set(expected_labels))178    def test_jsonl(self):179        filename = 'seq2seq/example.jsonl'180        file_format = 'JSONL'181        dataset = [182            ('exampleA', ['label1']),183            ('exampleB', [])184        ]185        self.import_dataset(filename, file_format)186        self.assert_examples(dataset)187    def test_json(self):188        filename = 'seq2seq/example.json'189        file_format = 'JSON'190        dataset = [191            ('exampleA', ['label1']),192            ('exampleB', [])193        ]194        self.import_dataset(filename, file_format)195        self.assert_examples(dataset)196    def test_csv(self):197        filename = 'seq2seq/example.csv'198        file_format = 'CSV'199        dataset = [200            ('exampleA', ['label1']),201            ('exampleB', [])202        ]203        self.import_dataset(filename, file_format)204        self.assert_examples(dataset)205class TextImportIntentDetectionAndSlotFillingData(TestImportData):206    task = INTENT_DETECTION_AND_SLOT_FILLING207    def assert_examples(self, dataset):208        self.assertEqual(Example.objects.count(), len(dataset))209        for text, expected_labels in dataset:210            example = Example.objects.get(text=text)211            cats = set(cat.label.text for cat in example.categories.all())212            entities = [(span.start_offset, span.end_offset, span.label.text) for span in example.spans.all()]213            self.assertEqual(cats, set(expected_labels['cats']))214            self.assertEqual(entities, expected_labels['entities'])215    def test_entities_and_cats(self):216        filename = 'intent/example.jsonl'217        file_format = 'JSONL'218        dataset = [219            ('exampleA', {'cats': ['positive'], 'entities': [(0, 1, 'LOC')]}),220            ('exampleB', {'cats': ['positive'], 'entities': []}),221            ('exampleC', {'cats': [], 'entities': [(0, 1, 'LOC')]}),222            ('exampleD', {'cats': [], 'entities': []}),223        ]224        self.import_dataset(filename, file_format)...

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