Best Python code snippet using pandera_python
engine.py
Source:engine.py
...71 raise ValueError(72 f"Subclasses of {base_names} cannot be registered"73 f" with {cls.__name__}."74 )75 def _register_from_parametrized_dtype(76 cls,77 pandera_dtype_cls: Type[DataType],78 ) -> None:79 method = pandera_dtype_cls.__dict__["from_parametrized_dtype"]80 if not isinstance(method, classmethod):81 raise ValueError(82 f"{pandera_dtype_cls.__name__}.from_parametrized_dtype "83 + "must be a classmethod."84 )85 func = method.__func__86 annotations = get_type_hints(func).values()87 dtype = next(iter(annotations)) # get 1st annotation88 # parse typing.Union89 dtypes = typing_inspect.get_args(dtype) or [dtype]90 def _method(*args, **kwargs):91 return func(pandera_dtype_cls, *args, **kwargs)92 for source_dtype in dtypes:93 cls._check_source_dtype(source_dtype)94 cls._registry[cls].dispatch.register(source_dtype, _method)95 def _register_equivalents(96 cls, pandera_dtype_cls: Type[DataType], *source_dtypes: Any97 ) -> None:98 pandera_dtype = pandera_dtype_cls() # type: ignore99 for source_dtype in source_dtypes:100 cls._check_source_dtype(source_dtype)101 cls._registry[cls].equivalents[source_dtype] = pandera_dtype102 def register_dtype(103 cls: _EngineType,104 pandera_dtype_cls: Type[_DataType] = None,105 *,106 equivalents: Optional[List[Any]] = None,107 ) -> Callable:108 """Register a Pandera :class:`~pandera.dtypes.DataType` with the engine,109 as class decorator.110 :param pandera_dtype: The DataType to register.111 :param equivalents: Equivalent scalar data type classes or112 non-parametrized data type instances.113 .. note::114 The classmethod ``from_parametrized_dtype`` will also be115 registered. See :ref:`here<dtypes>` for more usage details.116 :example:117 >>> import pandera as pa118 >>>119 >>> class MyDataType(pa.DataType):120 ... pass121 >>>122 >>> class MyEngine(123 ... metaclass=pa.engines.engine.Engine,124 ... base_pandera_dtypes=MyDataType,125 ... ):126 ... pass127 >>>128 >>> @MyEngine.register_dtype(equivalents=[bool])129 ... class MyBool(MyDataType):130 ... pass131 """132 def _wrapper(pandera_dtype_cls: Type[_DataType]) -> Type[_DataType]:133 if not inspect.isclass(pandera_dtype_cls):134 raise ValueError(135 f"{cls.__name__}.register_dtype can only decorate a class,"136 f" got {pandera_dtype_cls}"137 )138 if equivalents:139 cls._register_equivalents(pandera_dtype_cls, *equivalents)140 if "from_parametrized_dtype" in pandera_dtype_cls.__dict__:141 cls._register_from_parametrized_dtype(pandera_dtype_cls)142 cls._registered_dtypes.add(pandera_dtype_cls)143 return pandera_dtype_cls144 if pandera_dtype_cls:145 return _wrapper(pandera_dtype_cls)146 return _wrapper147 def dtype(cls: _EngineType, data_type: Any) -> _DataType:148 """Convert input into a Pandera :class:`DataType` object."""149 if isinstance(data_type, cls._base_pandera_dtypes):150 return data_type151 if inspect.isclass(data_type) and issubclass(152 data_type, cls._base_pandera_dtypes153 ):154 try:155 return data_type()...
test_engine.py
Source:test_engine.py
...34 with pytest.raises(35 TypeError, match="Data type 'foo' not understood by FakeEngine"36 ):37 engine.dtype("foo")38def test_register_from_parametrized_dtype(engine: Engine):39 """Test that a dtype with from_parametrized_dtype can be registered."""40 @engine.register_dtype41 class _Dtype(BaseDataType):42 @classmethod43 def from_parametrized_dtype(cls, x: int):44 return x45 assert engine.dtype(42) == 4246 with pytest.raises(47 TypeError, match="Data type 'foo' not understood by FakeEngine"48 ):49 engine.dtype("foo")50def test_register_from_parametrized_dtype_union(engine: Engine):51 """Test that a dtype with from_parametrized_dtype and Union annotation52 can be registered.53 """54 @engine.register_dtype55 class _Dtype(BaseDataType):56 @classmethod57 def from_parametrized_dtype(cls, x: Union[int, str]):58 return x59 assert engine.dtype(42) == 4260def test_register_notclassmethod_from_parametrized_dtype(engine: Engine):61 """Test that a dtype with invalid from_parametrized_dtype62 cannot be registered.63 """64 with pytest.raises(65 ValueError,66 match="_InvalidDtype.from_parametrized_dtype must be a classmethod.",67 ):68 @engine.register_dtype69 class _InvalidDtype(BaseDataType):70 def from_parametrized_dtype( # pylint:disable=no-self-argument,no-self-use71 cls, x: int72 ):73 return x74def test_register_dtype_complete(engine: Engine, equivalents: List[Any]):75 """Test that a dtype with equivalents and from_parametrized_dtype76 can be registered.77 """78 @engine.register_dtype(equivalents=equivalents)79 class _Dtype(BaseDataType):80 @classmethod81 def from_parametrized_dtype(cls, x: Union[int, str]):82 return x83 assert engine.dtype(42) == 4284 assert engine.dtype("foo") == "foo"85 for equivalent in equivalents:86 assert engine.dtype(equivalent) == _Dtype()87 with pytest.raises(88 TypeError,89 match="Data type '<class 'str'>' not understood by FakeEngine",90 ):91 engine.dtype(str)92def test_register_dtype_overwrite(engine: Engine):93 """Test that register_dtype overwrites existing registrations."""94 @engine.register_dtype(equivalents=["foo"])95 class _DtypeA(BaseDataType):96 @classmethod97 def from_parametrized_dtype(cls, x: Union[int, str]):98 return _DtypeA()99 assert engine.dtype("foo") == _DtypeA()100 assert engine.dtype("bar") == _DtypeA()101 assert engine.dtype(42) == _DtypeA()102 @engine.register_dtype(equivalents=["foo"])103 class _DtypeB(BaseDataType):104 @classmethod105 def from_parametrized_dtype(cls, x: int):106 return _DtypeB()107 assert engine.dtype("foo") == _DtypeB()108 assert engine.dtype("bar") == _DtypeA()109 assert engine.dtype(42) == _DtypeB()110def test_register_base_pandera_dtypes():111 """Test that base datatype cannot be registered."""112 class FakeEngine( # pylint:disable=too-few-public-methods113 metaclass=Engine, base_pandera_dtypes=(BaseDataType, BaseDataType)114 ):115 pass116 with pytest.raises(117 ValueError,118 match=re.escape(119 "Subclasses of ['tests.core.test_engine.BaseDataType', "...
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