pythonwrench.typing.checks module¶

pythonwrench.typing.checks.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.checks.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.checks.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.checks.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.checks.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.checks.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.checks.is_iterable_bool(x: Any, *, accept_generator: bool = True) → TypeIs[Iterable[bool]][source]¶

pythonwrench.typing.checks.is_iterable_bytes_or_list(x: Any, *, accept_generator: bool = True) → TypeIs[Iterable[bytes | list]][source]¶

pythonwrench.typing.checks.is_iterable_float(x: Any, *, accept_generator: bool = True) → TypeIs[Iterable[float]][source]¶

pythonwrench.typing.checks.is_iterable_int(x: Any, *, accept_bool: bool = True, accept_generator: bool = True) → TypeIs[Iterable[int]][source]¶

pythonwrench.typing.checks.is_iterable_integral(x: Any, *, accept_generator: bool = True) → TypeIs[Iterable[Integral]][source]¶

pythonwrench.typing.checks.is_iterable_str(x: Any, *, accept_str: bool = True, accept_generator: bool = True) → TypeGuard[Iterable[str]][source]¶

pythonwrench.typing.checks.is_namedtuple_instance(x: Any) → TypeIs[NamedTupleInstance][source]¶

Returns True if argument is a NamedTuple.

pythonwrench.typing.checks.is_sequence_str(x: Any, *, accept_str: bool = True) → TypeGuard[Sequence[str]][source]¶

pythonwrench.typing.checks.is_typed_dict(x: Any) → TypeGuard[type][source]¶

pythonwrench.typing.checks.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