pythonwrench.typing package

class pythonwrench.typing.DataclassInstance(*args, **kwargs)[source]

Bases: Protocol

pythonwrench.typing.EllipsisType

alias of EllipsisType

class pythonwrench.typing.NamedTupleInstance(*args, **kwargs)[source]

Bases: Protocol

class pythonwrench.typing.NoneType

Bases: object

The type of the None singleton.

class pythonwrench.typing.SupportsAdd(*args, **kwargs)[source]

Bases: Protocol[_T_Other]

Protocol that support __add__ (+) method.

class pythonwrench.typing.SupportsAnd(*args, **kwargs)[source]

Bases: Protocol[_T_Other]

Protocol that support __and__ (&) method.

class pythonwrench.typing.SupportsBool(*args, **kwargs)[source]

Bases: Protocol

Protocol that support __bool__ method.

class pythonwrench.typing.SupportsDiv(*args, **kwargs)[source]

Bases: Protocol[_T_Other]

Protocol that support __div__ (/) method.

class pythonwrench.typing.SupportsGetitem(*args, **kwargs)[source]

Bases: Protocol[_T_Item, _T_Index]

Protocol that support __getitem__ method.

class pythonwrench.typing.SupportsGetitem2(*args, **kwargs)[source]

Bases: Protocol[_T_Index2, _T_Item]

Protocol that support __getitem__ method.

Same than SupportsGetitem except that generic parameters are in reversed order: [T_Index, T_Item].

class pythonwrench.typing.SupportsGetitemIterLen(*args, **kwargs)[source]

Bases: Protocol[_T_Item, _T_Index]

Protocol that support __getitem__, __iter__ and __len__ methods.

class pythonwrench.typing.SupportsGetitemIterLen2(*args, **kwargs)[source]

Bases: Protocol[_T_Index2, _T_Item]

Protocol that support __getitem__, __iter__ and __len__ methods.

Same than SupportsGetitemIterLen except that generic parameters are in reversed order: [T_Index, T_Item].

class pythonwrench.typing.SupportsGetitemLen(*args, **kwargs)[source]

Bases: Protocol[_T_Item, _T_Index]

Protocol that support __getitem__ and __len__ methods.

class pythonwrench.typing.SupportsGetitemLen2(*args, **kwargs)[source]

Bases: Protocol[_T_Index2, _T_Item]

Protocol that support __getitem__ and __len__ methods.

Same than SupportsGetitemLen except that generic parameters are in reversed order: [T_Index, T_Item].

class pythonwrench.typing.SupportsIterLen(*args, **kwargs)[source]

Bases: Protocol[_T_Item]

Protocol that support __iter__ and __len__ methods.

class pythonwrench.typing.SupportsLen(*args, **kwargs)[source]

Bases: Protocol

Protocol that support __len__ method.

class pythonwrench.typing.SupportsMatmul(*args, **kwargs)[source]

Bases: Protocol[_T_Other]

Protocol that support __matmul__ (@) method.

class pythonwrench.typing.SupportsMul(*args, **kwargs)[source]

Bases: Protocol[_T_Other]

Protocol that support __mul__ (*) method.

class pythonwrench.typing.SupportsOr(*args, **kwargs)[source]

Bases: Protocol[_T_Other]

Protocol that support __or__ (|) method.

pythonwrench.typing.check_args_types(fn: Callable[[P], T]) → Callable[[P], T][source]

Decorator to check argument types before call to a function.

Example

>>> import pythonwrench as pw
>>> @pw.check_args_types
>>> def f(a: int, b: str) -> str:
>>>     return a * b
>>> f(1, "a")  # pass check
>>> f(1, 2)  # raises TypeError from decorator
pythonwrench.typing.is_builtin_collection(x: Any, *, strict: bool = False) → TypeIs[list | tuple | dict | set | frozenset][source]

Returns True if x is an instance of a builtin collection type (list, tuple, dict, set, frozenset).

Args:

x: Object to check. strict: If True, it will not consider custom subtypes of builtins as builtin collections. defaults to False.

pythonwrench.typing.is_builtin_number(x: Any, *, strict: bool = False) → TypeIs[bool | int | float | complex][source]

Returns True if x is an instance of a builtin number type (int, float, bool, complex).

Args:

x: Object to check. strict: If True, it will not consider custom subtypes of builtins as builtin numbers. defaults to False.

pythonwrench.typing.is_builtin_obj(x: Any) → bool[source]

Returns True if object is an instance of a builtin object.

Note: If the object is an instance of a custom subtype of a builtin object, this function returns False.

pythonwrench.typing.is_builtin_scalar(x: Any, *, strict: bool = False) → TypeIs[bool | int | float | complex | None | str | bytes][source]

Returns True if x is an instance of a builtin scalar type (int, float, bool, complex, NoneType, str, bytes).

Args:

x: Object to check. strict: If True, it will not consider subtypes of builtins as builtin scalars. defaults to False.

pythonwrench.typing.is_dataclass_instance(x: Any) → TypeIs[DataclassInstance][source]

Returns True if argument is a dataclass.

Unlike function dataclasses.is_dataclass, this function returns False for a dataclass type.

pythonwrench.typing.is_iterable_bool(x: Any, *, accept_generator: bool = True) → TypeIs[Iterable[bool]][source]
pythonwrench.typing.is_iterable_bytes_or_list(x: Any, *, accept_generator: bool = True) → TypeIs[Iterable[bytes | list]][source]
pythonwrench.typing.is_iterable_float(x: Any, *, accept_generator: bool = True) → TypeIs[Iterable[float]][source]
pythonwrench.typing.is_iterable_int(x: Any, *, accept_bool: bool = True, accept_generator: bool = True) → TypeIs[Iterable[int]][source]
pythonwrench.typing.is_iterable_integral(x: Any, *, accept_generator: bool = True) → TypeIs[Iterable[Integral]][source]
pythonwrench.typing.is_iterable_str(x: Any, *, accept_str: bool = True, accept_generator: bool = True) → TypeGuard[Iterable[str]][source]
pythonwrench.typing.is_namedtuple_instance(x: Any) → TypeIs[NamedTupleInstance][source]

Returns True if argument is a NamedTuple.

pythonwrench.typing.is_sequence_str(x: Any, *, accept_str: bool = True) → TypeGuard[Sequence[str]][source]
pythonwrench.typing.is_typed_dict(x: Any) → TypeGuard[type][source]
pythonwrench.typing.isinstance_generic(obj: Any, class_or_tuple: type[T] | None | tuple[type[T], ...] | Any, *, check_only_first: bool = False) → TypeIs[T][source]

Improved isinstance(…) function that supports parametrized Union, TypedDict, Literal, Mapping or Iterable.

Args:

obj: Object to check. class_or_tuple: Type to check. Can be a parametrized type from typing. check_only_first: If True, check only if first element when checking for Iterable[type]. defaults to False.

Example 1

>>> isinstance_generic({"a": 1, "b": 2}, dict)
... True
>>> isinstance_generic({"a": 1, "b": 2}, dict[str, int])
... True
>>> isinstance_generic({"a": 1, "b": 2}, dict[str, str])
... False
>>> from typing import Literal
>>> isinstance_generic({"a": 1, "b": 2}, dict[str, Literal[1, 2]])
... True

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