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How to use test_numpy_data_type method in pandera

Best Python code snippet using pandera_python

test_gdal.py

Source:test_gdal.py

...232        self.assertEqual(band.GetNoDataValue(), None)233        # No data234        band = Dataset(self.nodatafile).GetRasterBand(1)235        self.assertEqual(band.GetNoDataValue(), 10)236    def test_numpy_data_type(self):237        self.assertEqual(238            Dataset(self.float32file).GetRasterBand(1).NumPyDataType,239            numpy.float32240        )241        self.assertEqual(242            Dataset(self.int16file).GetRasterBand(1).NumPyDataType,243            numpy.int16244        )245        self.assertEqual(246            Dataset(self.uint8file).GetRasterBand(1).NumPyDataType,247            numpy.uint8248        )249    def test_minimum_value(self):250        self.assertEqual(...

test_numpy_engine.py

Source:test_numpy_engine.py

...4from pandera.engines import numpy_engine5@pytest.mark.parametrize(6    "data_type", list(numpy_engine.Engine.get_registered_dtypes())7)8def test_numpy_data_type(data_type):9    """Test base numpy engine DataType."""10    numpy_engine.Engine.dtype(data_type)11    numpy_engine.Engine.dtype(data_type.type)12    numpy_engine.Engine.dtype(str(data_type.type))13    with pytest.warns(UserWarning):14        np_dtype = numpy_engine.DataType(data_type.type)15    with pytest.warns(UserWarning):16        np_dtype_from_str = numpy_engine.DataType(str(data_type.type))17    assert np_dtype == np_dtype_from_str18@pytest.mark.parametrize("data_type", ["foo", "bar", 1, 2, 3.14, np.void])19def test_numpy_engine_dtype_exceptions(data_type):20    """Test invalid inputs to numpy data-types."""21    if data_type != np.void:22        with pytest.raises(...

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