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How to use _register_numpy_numbers method in pandera

Best Python code snippet using pandera_python

pandas_engine.py

Source:pandas_engine.py

...159    type = pd.BooleanDtype()160###############################################################################161# number162###############################################################################163def _register_numpy_numbers(164    builtin_name: str, pandera_name: str, sizes: List[int]165) -> None:166    """Register pandera.engines.numpy_engine DataTypes167    with the pandas engine."""168    builtin_type = getattr(builtins, builtin_name, None)  # uint doesn't exist169    # default to int64 regardless of OS170    default_pd_dtype = {171        "int": np.dtype("int64"),172        "uint": np.dtype("uint64"),173    }.get(builtin_name, pd.Series([1], dtype=builtin_name).dtype)174    for bit_width in sizes:175        # e.g.: numpy.int64176        np_dtype = getattr(np, f"{builtin_name}{bit_width}")177        equivalents = set(178            (179                np_dtype,180                # e.g.: pandera.dtypes.Int64181                getattr(dtypes, f"{pandera_name}{bit_width}"),182                getattr(dtypes, f"{pandera_name}{bit_width}")(),183            )184        )185        if np_dtype == default_pd_dtype:186            equivalents |= set(187                (188                    default_pd_dtype,189                    builtin_name,190                    getattr(dtypes, pandera_name),191                    getattr(dtypes, pandera_name)(),192                )193            )194            if builtin_type:195                equivalents.add(builtin_type)196            # results from pd.api.types.infer_dtype197            if builtin_type is float:198                equivalents.add("floating")199                equivalents.add("mixed-integer-float")200            elif builtin_type is int:201                equivalents.add("integer")202        numpy_data_type = getattr(numpy_engine, f"{pandera_name}{bit_width}")203        Engine.register_dtype(numpy_data_type, equivalents=list(equivalents))204###############################################################################205# signed integer206###############################################################################207_register_numpy_numbers(208    builtin_name="int",209    pandera_name="Int",210    sizes=[64, 32, 16, 8],211)212@Engine.register_dtype(equivalents=[pd.Int64Dtype, pd.Int64Dtype()])213@immutable214class INT64(DataType, dtypes.Int):215    """Semantic representation of a :class:`pandas.Int64Dtype`."""216    type = pd.Int64Dtype()217    bit_width: int = 64218@Engine.register_dtype(equivalents=[pd.Int32Dtype, pd.Int32Dtype()])219@immutable220class INT32(INT64):221    """Semantic representation of a :class:`pandas.Int32Dtype`."""222    type = pd.Int32Dtype()223    bit_width: int = 32224@Engine.register_dtype(equivalents=[pd.Int16Dtype, pd.Int16Dtype()])225@immutable226class INT16(INT32):227    """Semantic representation of a :class:`pandas.Int16Dtype`."""228    type = pd.Int16Dtype()229    bit_width: int = 16230@Engine.register_dtype(equivalents=[pd.Int8Dtype, pd.Int8Dtype()])231@immutable232class INT8(INT16):233    """Semantic representation of a :class:`pandas.Int8Dtype`."""234    type = pd.Int8Dtype()235    bit_width: int = 8236###############################################################################237# unsigned integer238###############################################################################239_register_numpy_numbers(240    builtin_name="uint",241    pandera_name="UInt",242    sizes=[64, 32, 16, 8],243)244@Engine.register_dtype(equivalents=[pd.UInt64Dtype, pd.UInt64Dtype()])245@immutable246class UINT64(DataType, dtypes.UInt):247    """Semantic representation of a :class:`pandas.UInt64Dtype`."""248    type = pd.UInt64Dtype()249    bit_width: int = 64250@Engine.register_dtype(equivalents=[pd.UInt32Dtype, pd.UInt32Dtype()])251@immutable252class UINT32(UINT64):253    """Semantic representation of a :class:`pandas.UInt32Dtype`."""254    type = pd.UInt32Dtype()255    bit_width: int = 32256@Engine.register_dtype(equivalents=[pd.UInt16Dtype, pd.UInt16Dtype()])257@immutable258class UINT16(UINT32):259    """Semantic representation of a :class:`pandas.UInt16Dtype`."""260    type = pd.UInt16Dtype()261    bit_width: int = 16262@Engine.register_dtype(equivalents=[pd.UInt8Dtype, pd.UInt8Dtype()])263@immutable264class UINT8(UINT16):265    """Semantic representation of a :class:`pandas.UInt8Dtype`."""266    type = pd.UInt8Dtype()267    bit_width: int = 8268# ###############################################################################269# # float270# ###############################################################################271_register_numpy_numbers(272    builtin_name="float",273    pandera_name="Float",274    sizes=[128, 64, 32, 16] if FLOAT_128_AVAILABLE else [64, 32, 16],275)276if PANDAS_1_2_0_PLUS:277    @Engine.register_dtype(equivalents=[pd.Float64Dtype, pd.Float64Dtype()])278    @immutable279    class FLOAT64(DataType, dtypes.Float):280        """Semantic representation of a :class:`pandas.Float64Dtype`."""281        type = pd.Float64Dtype()282        bit_width: int = 64283    @Engine.register_dtype(equivalents=[pd.Float32Dtype, pd.Float32Dtype()])284    @immutable285    class FLOAT32(FLOAT64):286        """Semantic representation of a :class:`pandas.Float32Dtype`."""287        type = pd.Float32Dtype()288        bit_width: int = 32289# ###############################################################################290# # complex291# ###############################################################################292_register_numpy_numbers(293    builtin_name="complex",294    pandera_name="Complex",295    sizes=[256, 128, 64] if FLOAT_128_AVAILABLE else [128, 64],296)297# ###############################################################################298# # nominal299# ###############################################################################300@Engine.register_dtype(301    equivalents=[302        "category",303        "categorical",304        dtypes.Category,305        pd.CategoricalDtype,306    ]...

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