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How to use _datetime_strategy method in pandera

Best Python code snippet using pandera_python

strategies.py

Source:strategies.py

...180MAX_DT_VALUE = 2**63 - 1181def _is_datetime_tz(pandera_dtype: DataType) -> bool:182    native_type = getattr(pandera_dtype, "type", None)183    return isinstance(native_type, pd.DatetimeTZDtype)184def _datetime_strategy(185    dtype: Union[np.dtype, pd.DatetimeTZDtype], strategy186) -> SearchStrategy:187    if isinstance(dtype, pd.DatetimeTZDtype):188        def _to_datetime(value) -> pd.DatetimeTZDtype:189            if isinstance(value, pd.Timestamp):190                return value.tz_convert(tz=dtype.tz)  # type: ignore[union-attr]191            return pd.Timestamp(value, unit=dtype.unit, tz=dtype.tz)  # type: ignore[union-attr]192        return st.builds(_to_datetime, strategy)193    else:194        res = (195            st.just(dtype.str.split("[")[-1][:-1])196            if "[" in dtype.str197            else st.sampled_from(npst.TIME_RESOLUTIONS)198        )199        return st.builds(dtype.type, strategy, res)200def numpy_time_dtypes(201    dtype: Union[np.dtype, pd.DatetimeTZDtype], min_value=None, max_value=None202):203    """Create numpy strategy for datetime and timedelta data types.204    :param dtype: numpy datetime or timedelta datatype205    :param min_value: minimum value of the datatype to create206    :param max_value: maximum value of the datatype to create207    :returns: ``hypothesis`` strategy208    """209    def _to_unix(value: Any) -> int:210        if dtype.type is np.timedelta64:211            return pd.Timedelta(value).value212        return pd.Timestamp(value).value213    min_value = MIN_DT_VALUE if min_value is None else _to_unix(min_value)214    max_value = MAX_DT_VALUE if max_value is None else _to_unix(max_value)215    return _datetime_strategy(dtype, st.integers(min_value, max_value))216def numpy_complex_dtypes(217    dtype,218    min_value: complex = complex(0, 0),219    max_value: Optional[complex] = None,220    allow_infinity: bool = None,221    allow_nan: bool = None,222):223    """Create numpy strategy for complex numbers.224    :param dtype: numpy complex number datatype225    :param min_value: minimum value, must be complex number226    :param max_value: maximum value, must be complex number227    :returns: ``hypothesis`` strategy228    """229    max_real: Optional[float]230    max_imag: Optional[float]231    if max_value:232        max_real = max_value.real233        max_imag = max_value.imag234    else:235        max_real = max_imag = None236    if dtype.itemsize == 8:237        width = 32238    else:239        width = 64240    # switch min and max values for imaginary if min value > max value241    if max_imag is not None and min_value.imag > max_imag:242        min_imag = max_imag243        max_imag = min_value.imag244    else:245        min_imag = min_value.imag246    strategy = st.builds(247        complex,248        st.floats(249            min_value=min_value.real,250            max_value=max_real,251            width=width,252            allow_infinity=allow_infinity,253            allow_nan=allow_nan,254        ),255        st.floats(256            min_value=min_imag,257            max_value=max_imag,258            width=width,259            allow_infinity=allow_infinity,260            allow_nan=allow_nan,261        ),262    ).map(dtype.type)263    @st.composite264    def build_complex(draw):265        value = draw(strategy)266        hypothesis.assume(min_value <= value)267        if max_value is not None:268            hypothesis.assume(max_value >= value)269        return value270    return build_complex()271def to_numpy_dtype(pandera_dtype: DataType):272    """Convert a :class:`~pandera.dtypes.DataType` to numpy dtype compatible273    with hypothesis."""274    try:275        np_dtype = pandas_engine.Engine.numpy_dtype(pandera_dtype)276    except TypeError as err:277        if is_datetime(pandera_dtype):278            return np.dtype("datetime64[ns]")279        raise TypeError(280            f"Data generation for the '{pandera_dtype}' data type is "281            "currently unsupported."282        ) from err283    if np_dtype == np.dtype("object") or str(pandera_dtype) == "str":284        np_dtype = np.dtype(str)285    return np_dtype286def pandas_dtype_strategy(287    pandera_dtype: DataType,288    strategy: Optional[SearchStrategy] = None,289    **kwargs,290) -> SearchStrategy:291    # pylint: disable=line-too-long,no-else-raise292    """Strategy to generate data from a :class:`pandera.dtypes.DataType`.293    :param pandera_dtype: :class:`pandera.dtypes.DataType` instance.294    :param strategy: an optional hypothesis strategy. If specified, the295        pandas dtype strategy will be chained onto this strategy.296    :kwargs: key-word arguments passed into297        `hypothesis.extra.numpy.from_dtype <https://hypothesis.readthedocs.io/en/latest/numpy.html#hypothesis.extra.numpy.from_dtype>`_ .298        For datetime, timedelta, and complex number datatypes, these arguments299        are passed into :func:`~pandera.strategies.numpy_time_dtypes` and300        :func:`~pandera.strategies.numpy_complex_dtypes`.301    :returns: ``hypothesis`` strategy302    """303    def compat_kwargs(*args):304        return {k: v for k, v in kwargs.items() if k in args}305    # hypothesis doesn't support categoricals or objects, so we'll will need to306    # build a pandera-specific solution.307    if is_category(pandera_dtype):308        raise TypeError(309            "data generation for the Category dtype is currently "310            "unsupported. Consider using a string or int dtype and "311            "Check.isin(values) to ensure a finite set of values."312        )313    np_dtype = to_numpy_dtype(pandera_dtype)314    if strategy:315        if _is_datetime_tz(pandera_dtype):316            return _datetime_strategy(pandera_dtype.type, strategy)  # type: ignore317        return strategy.map(np_dtype.type)318    elif is_datetime(pandera_dtype) or is_timedelta(pandera_dtype):319        return numpy_time_dtypes(320            pandera_dtype.type if _is_datetime_tz(pandera_dtype) else np_dtype,  # type: ignore321            **compat_kwargs("min_value", "max_value"),322        )323    elif is_complex(pandera_dtype):324        return numpy_complex_dtypes(325            np_dtype,326            **compat_kwargs(327                "min_value", "max_value", "allow_infinity", "allow_nan"328            ),329        )330    return npst.from_dtype(...

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