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How to use extract_metadata method in lisa

Best Python code snippet using lisa_python

test_extract_metadata.py

Source:test_extract_metadata.py

...93                                         (time, 2)])94        return cube95    @staticmethod96    def test_return_type_cube(cube_1):97        cube_metadata = data.extract_metadata.extract_metadata(98            cube_1, 1, [], ['cube'], ['netCDF'])99        assert isinstance(cube_metadata, CollectionMetadata)100    @staticmethod101    def test_return_type_cubelist(cube_1, cube_2):102        cubelist_metadata = data.extract_metadata.extract_metadata(103            CubeList([cube_1, cube_2]), 1, [], ['cube'], ['netCDF'], 'title', 'desc')104        assert isinstance(cubelist_metadata, CollectionMetadata)105    @staticmethod106    def test_title_cube(cube_1):107        cube_metadata = data.extract_metadata.extract_metadata(108            cube_1, 1, [], ['cube'], ['netCDF'])109        assert cube_metadata.title == "mass_concentration_of_ozone_in_air"110    @staticmethod111    def test_title_cubelist(cube_1, cube_2):112        cubelist_metadata = data.extract_metadata.extract_metadata(113            CubeList([cube_1, cube_2]), 1, [], ['cube'], ['netCDF'], 'title', 'desc')114        assert cubelist_metadata.title == "title"115    @staticmethod116    def test_total_time_extent(cube_1):117        cube_metadata = data.extract_metadata.extract_metadata(118            cube_1, 1, [], ['cube'], ['netCDF'])119        assert np.allclose(cube_metadata.extent.temporal.values, np.linspace(1, 24, 24))120    @staticmethod121    def test_total_time_extent_gap(cube_3):122        cube_metadata = data.extract_metadata.extract_metadata(123            cube_3, 1, [], ['cube'], ['netCDF'])124        assert np.allclose(cube_metadata.extent.temporal.values, [1, 2, 3, 7, 8, 9])125    @staticmethod126    def test_total_vertical_extent(cube_1):127        cube_metadata = data.extract_metadata.extract_metadata(128            cube_1, 1, [], ['cube'], ['netCDF'])129        assert cube_metadata.extent.vertical.values == pytest.approx(3.5)130    @staticmethod131    def test_parameters_length_cube(cube_1):132        cube_metadata = data.extract_metadata.extract_metadata(133            cube_1, 1, [], ['cube'], ['netCDF'])134        assert len(cube_metadata.parameters) == 1135    @staticmethod136    def test_parameters_length_cubelist(cube_1, cube_2):137        cubelist_metadata = data.extract_metadata.extract_metadata(138            CubeList([cube_1, cube_2]), 1, [], ['cube'], ['netCDF'], 'title', 'desc')139        assert len(cubelist_metadata.parameters) == 2140    @staticmethod141    def test_containing_polygon_cube(cube_1):142        cube_metadata = data.extract_metadata.extract_metadata(143            cube_1, 1, [], ['cube'], ['netCDF'])144        assert cube_metadata.extent.spatial.bbox.bounds == (45, -90, 360, 90)145    @staticmethod146    def test_containing_polygon_equal(cube_1):147        # two equal polygons148        cubelist_metadata = data.extract_metadata.extract_metadata(149            CubeList([cube_1, cube_1]), 1, [], ['cube'], ['netCDF'], 'title', 'desc')150        assert cubelist_metadata.extent.spatial.bbox.bounds == (45, -90, 360, 90)151    @staticmethod152    def test_containing_polygon_overlapping(cube_1, cube_2):153        # two partially overlapping polygons154        cubelist_metadata = data.extract_metadata.extract_metadata(155            CubeList([cube_1, cube_2]), 1, [], ['cube'], ['netCDF'], 'title', 'desc')156        assert cubelist_metadata.extent.spatial.bbox.bounds == (1, -90, 360, 100)157    @staticmethod158    def test_containing_polygon_within(cube_1, cube_3):159        # one polygon completely within another polygon160        cubelist_metadata = data.extract_metadata.extract_metadata(161            CubeList([cube_1, cube_3]), 1, [], ['cube'], ['netCDF'], 'title', 'desc')162        assert cubelist_metadata.extent.spatial.bbox.bounds == (-10, -150, 400, 150)163    @staticmethod164    def test_containing_polygon_overlapping_and_within(cube_1, cube_2, cube_3):165        # two partially overlapping polygons completely within a third polygon166        cubelist_metadata = data.extract_metadata.extract_metadata(167            CubeList([cube_1, cube_2, cube_3]), 1, [], ['cube'], ['netCDF'], 'title', 'desc')168        assert cubelist_metadata.extent.spatial.bbox.bounds == (-10, -150, 400, 150)169    @staticmethod170    def test_containing_polygon_separate(cube_1, cube_4):171        # two completely separate polygons172        cubelist_metadata = data.extract_metadata.extract_metadata(173            CubeList([cube_1, cube_4]), 1, [], ['cube'], ['netCDF'], 'title', 'desc')174        assert cubelist_metadata.extent.spatial.bbox.bounds == (45, -90, 430, 175)175    @staticmethod176    def test_containing_polygon_overlap_within_separate(cube_1, cube_2, cube_3, cube_4):177        # two partially overlapping polygons completely within a third polygon, and a completely separate fourth polygon178        cubelist_metadata = data.extract_metadata.extract_metadata(179            CubeList([cube_1, cube_2, cube_3, cube_4]), 1, [], ['cube'], ['netCDF'], 'title', 'desc')180        assert cubelist_metadata.extent.spatial.bbox.bounds == (-10, -150, 430, 175)181class errorTest(unittest.TestCase):182    def test_dimensionless_cube_error(self):183        time = DimCoord(np.linspace(1, 24, 24),184                        standard_name='time',185                        units="hours since 1970-01-01 00:00:00")186        cube = Cube(np.zeros((24), np.float32),187                    standard_name="mass_concentration_of_ozone_in_air",188                    units="ug/m3",189                    dim_coords_and_dims=[(time, 0)])190        with self.assertRaisesRegex(ValueError, 'The dataset must contain at least one variable with x and y axes.'):191            data.extract_metadata.extract_metadata(...

security.py

Source:security.py

...17        if scheme in ("http", "https"):18            return hostname19    return urlunsplit((scheme, hostname, "", None, None))20class SecurityEvent(BaseEvent):21    def extract_metadata(self, data):22        # Relay normalizes the message for security reports into the log entry23        # field, so we grab the message from there.24        # (https://github.com/getsentry/relay/pull/558)25        message = strip(26            get_path(data, "logentry", "formatted") or get_path(data, "logentry", "message")27        )28        return {"message": message}29    def get_title(self, metadata):30        # Due to a regression (https://github.com/getsentry/sentry/pull/19794)31        # some events did not have message persisted but title. Because of this32        # the title code has to take these into account.33        return metadata.get("message") or metadata.get("title") or "<untitled>"34    def get_location(self, metadata):35        # Try to get location by preferring URI over origin.  This covers36        # all the cases below where CSP sets URI and others set origin.37        return metadata.get("uri") or metadata.get("origin")38class CspEvent(SecurityEvent):39    key = "csp"40    def extract_metadata(self, data):41        metadata = SecurityEvent.extract_metadata(self, data)42        metadata["uri"] = _normalize_uri(data["csp"].get("blocked_uri") or "")43        metadata["directive"] = data["csp"].get("effective_directive")44        return metadata45class HpkpEvent(SecurityEvent):46    key = "hpkp"47    def extract_metadata(self, data):48        metadata = SecurityEvent.extract_metadata(self, data)49        metadata["origin"] = data["hpkp"].get("hostname")50        return metadata51class ExpectCTEvent(SecurityEvent):52    key = "expectct"53    def extract_metadata(self, data):54        metadata = SecurityEvent.extract_metadata(self, data)55        metadata["origin"] = data["expectct"].get("hostname")56        return metadata57class ExpectStapleEvent(SecurityEvent):58    key = "expectstaple"59    def extract_metadata(self, data):60        metadata = SecurityEvent.extract_metadata(self, data)61        metadata["origin"] = data["expectstaple"].get("hostname")...

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