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How to use _get_entry method in localstack

Best Python code snippet using localstack_python

evaluation_test.py

Source:evaluation_test.py

...29      constants.DATE: np.repeat(dates, len(sites)),30      constants.SITE_ID: np.tile(sites, len(dates)),31      constants.PREDICTION: np.random.rand(len(dates) * len(sites)) * 10,32  })33def _get_entry(last_observation_date="2020-05-07",34               dataset_index_key="dset_index_1", cadence=1):35  return forecast_indexing.build_entry(36      forecast_id="",37      file_location="",38      dataset_name=_TEST_DATASET,39      creation_timestamp="",40      dataset_index_key=dataset_index_key,41      dataset_location="",42      last_observation_date=last_observation_date,43      cadence=cadence,44      extra_info={})45def _get_dataset(eval_dates, sites, target="new_confirmed", cadence=1):46  training_datetime = (47      datetime.datetime.strptime(eval_dates[0], "%Y-%m-%d") -48      datetime.timedelta(days=1))49  return dataset_factory.Dataset(50      training_targets=np.random.randint(0, 10, (1, len(sites), 1)),51      training_features=[],52      evaluation_targets=np.random.randint(0, 10,53                                           (len(eval_dates), len(sites), 1)),54      sum_past_targets=np.random.randint(0, 10, (len(sites), 1)),55      target_names=[target],56      feature_names=[],57      training_dates=[58          datetime.datetime.strftime(training_datetime, "%Y-%m-%d")59      ],60      evaluation_dates=eval_dates,61      sites=np.array(sites),62      dataset_index_key="test_dset_index_1",63      cadence=cadence)64class EvaluationTest(absltest.TestCase):65  def setUp(self):66    super().setUp()67    self._default_dates = ["2020-05-07", "2020-05-08", "2020-05-09"]68    self._default_sites = ["site_1", "site_2"]69  def test_comparable_forecasts_subset_sites(self):70    """Check that validation fails for forecasts with different sites."""71    forecasts_1 = _get_forecasts(self._default_dates, self._default_sites)72    forecasts_2 = _get_forecasts(self._default_dates, ["site_1", "site_3"])73    all_forecast_arrays = evaluation._convert_forecasts_to_arrays(74        [forecasts_1, forecasts_2])75    _, sites_to_eval, sites_to_drop, updated_data_arrays = (76        evaluation._get_forecast_spec_and_comparable_predictions(77            all_forecast_arrays))78    np.testing.assert_array_equal(sites_to_eval, ["site_1"])79    np.testing.assert_array_equal(sites_to_drop, ["site_2", "site_3"])80    np.testing.assert_array_equal(81        updated_data_arrays, np.array(82            [arr.data_array for arr in all_forecast_arrays])[:, :, 0:1, :])83    np.testing.assert_array_equal(updated_data_arrays[0].shape,84                                  updated_data_arrays[1].shape)85  def test_incomparable_forecasts_subset_dates(self):86    """Check that validation fails for forecasts with different start dates."""87    forecasts_1 = _get_forecasts(self._default_dates, self._default_sites)88    forecasts_2 = _get_forecasts(["2020-05-06", "2020-05-07"],89                                 self._default_sites)90    all_forecast_arrays = evaluation._convert_forecasts_to_arrays(91        [forecasts_1, forecasts_2])92    dates_to_eval, _, _, updated_data_arrays = (93        evaluation._get_forecast_spec_and_comparable_predictions(94            all_forecast_arrays))95    np.testing.assert_array_equal(dates_to_eval, ["2020-05-07"])96    np.testing.assert_array_equal(97        updated_data_arrays[0], all_forecast_arrays[0].data_array[0:1])98    np.testing.assert_array_equal(99        updated_data_arrays[1], all_forecast_arrays[1].data_array[1:2])100    np.testing.assert_array_equal(updated_data_arrays[0].shape,101                                  updated_data_arrays[1].shape)102  def test_valid_different_forecast_horizons(self):103    """Check that validation passes for forecasts with different horizons."""104    forecasts_1 = _get_forecasts(self._default_dates, self._default_sites)105    forecasts_2 = _get_forecasts(["2020-05-07", "2020-05-08"],106                                 self._default_sites)107    all_forecast_arrays = evaluation._convert_forecasts_to_arrays(108        [forecasts_1, forecasts_2])109    evaluation._get_forecast_spec_and_comparable_predictions(110        all_forecast_arrays)111  def test_badly_formatted_forecasts(self):112    """Checks that forecasts with unexpected format fail evaluation."""113    forecasts = _get_forecasts(self._default_dates, self._default_sites)114    forecasts["extra_column"] = ""115    all_forecast_arrays = evaluation._convert_forecasts_to_arrays([forecasts])116    with self.assertRaisesRegex(AssertionError,117                                "Unexpected columns in forecasts:*"):118      evaluation._get_forecast_spec_and_comparable_predictions(119          all_forecast_arrays)120  def test_incomparable_last_observation_dates(self):121    """Checks that validation fails for different last_observation_dates."""122    entry_1 = _get_entry(last_observation_date="2020-05-06")123    entry_2 = _get_entry(last_observation_date="2020-05-07")124    with self.assertRaisesRegex(125        ValueError,126        "Models can only be compared if they have the same "127        "last_observation_date. *"):128      evaluation._get_last_observation_date_and_validate_comparable(129          [entry_1, entry_2])130  def test_incomparable_forecast_cadences(self):131    """Checks that validation fails for forecasts with different cadences."""132    entry_1 = _get_entry(cadence=1)133    entry_2 = _get_entry(cadence=7)134    with self.assertRaisesRegex(135        ValueError,136        "Models can only be compared if they have the same forecast cadence *"):137      evaluation._get_last_observation_date_and_validate_comparable(138          [entry_1, entry_2])139  def test_incomparable_forecast_sources(self):140    """Checks validation fails for forecasts trained on different datasets."""141    entry_1 = _get_entry(dataset_index_key="dset_index_1")142    entry_2 = _get_entry(dataset_index_key="dset_index_2")143    with self.assertRaisesRegex(144        ValueError,145        "Models can only be compared if they were trained using the same "146        "dataset.*"):147      evaluation._get_last_observation_date_and_validate_comparable(148          [entry_1, entry_2])149  def test_incomparable_eval_dset_missing_sites(self):150    """Checks that validation fails when the dataset is missing sites."""151    dataset = _get_dataset(self._default_dates, ["site_1", "site_3"])152    with self.assertRaisesRegex(153        ValueError, "Not all of the sites in the forecasts are present in the "154        "evaluation dataset*"):155      evaluation._validate_eval_dataset_comparable(dataset, self._default_dates,156                                                   self._default_sites)...

test_vdocs.py

Source:test_vdocs.py

...43            file_2.close()44            self.assertNotEqual(md5_1, md5_2)45        shutil.rmtree(f_dir1)46        shutil.rmtree(f_dir2)47    def test_get_entry(self):48        """Objective: Test if the entries generated by the '_get_entry()'different.49        Input: Return value from GlastopfHoneypot._get_entry()50        Expected Result: Two runs of GlastopfHoneypot._get_entry() generate different results51        Notes:"""52        user_id1 = random.randint(1000, 1500)  # Realistic user ID53        pwd_entry1, shd_entry1, grp_entry1 = vdocs._get_entry(user_id1)54        user_id2 = random.randint(1000, 1500)55        pwd_entry2, shd_entry2, grp_entry2 = vdocs._get_entry(user_id2)56        self.assertNotEqual(pwd_entry1, pwd_entry2)57        self.assertNotEqual(shd_entry1, shd_entry2)58        self.assertNotEqual(grp_entry1, grp_entry2)59if __name__ == '__main__':...

config.py

Source:config.py

...16CONFIG_DST_MAPPING_FIELD_STROKE_COUNT = 'strokeCount'17class ConfigWrapper:18    def __init__(self) -> None:19        config: Optional[Dict[str, Any]] = mw.addonManager.getConfig(__name__)20        self.noteTypes = self._get_entry(config, CONFIG_NOTE_TYPES, ['Japanese::Kanji'])21        self.field_kanji = self._get_entry(config, CONFIG_FIELD_SRC, 'kanji')22        self.skipTags = self._get_entry(config, CONFIG_SKIP_TAGS, ['kanji_skip'])23        self.addTags = self._get_entry(config, CONFIG_ADD_TAGS, ['kanji_auto_filled'])24        self.targetDeck = self._get_entry(config, CONFIG_TARGET_DECK, 'Japanese::Kanji')25        self.targetNoteType = self._get_entry(config, CONFIG_TARGET_NOTE_TYPE, 'Japanese::Kanji')26        self.targetTag = self._get_entry(config, CONFIG_TARGET_TAG, 'auto_created')27        dst_mapping = config.get(CONFIG_DST_MAPPING)28        self.field_kun_yomi = self._get_entry(dst_mapping, CONFIG_DST_MAPPING_FIELD_KUNYOMI, 'kun_yomi')29        self.field_on_yomi = self._get_entry(dst_mapping, CONFIG_DST_MAPPING_FIELD_ONYOMI, 'on_yomi')30        self.field_english = self._get_entry(dst_mapping, CONFIG_DST_MAPPING_FIELD_ENGLISH, 'meanings')31        self.field_jlpt = self._get_entry(dst_mapping, CONFIG_DST_MAPPING_FIELD_JLPT, 'jlpt')32        self.field_grade = self._get_entry(dst_mapping, CONFIG_DST_MAPPING_FIELD_GRADE, 'grade')33        self.field_stroke_count = self._get_entry(dst_mapping, CONFIG_DST_MAPPING_FIELD_STROKE_COUNT, 'stroke_count')34    @staticmethod35    def _get_entry(src: Optional[Dict[str, Any]], field_name: str, default: Union[str, List[str]]) -> Union[str, List[str]]:36        if not src:37            return default38        return src.get(field_name, default)39# TODO probably replace with ConfigWrapper singleton...

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