typewire 0.1.0

A single-file utility to allow better runtime handling of types by providing a predictable way of transforming data into the shape of a given type hint.

typewire

A single-file utility to allow better runtime handling of types by providing a predictable way of transforming data into the shape of a given type hint.

Why?

Python's standard library provides tools for describing types via type hints, but it doesn't provide a unified way of actually enforcing those type hints at runtime, even buried deep in the typing module.

Our goal is to allow for x: T to behave transparently as usual whilst also allowing the user to convert to that type, regardless of whether that is x: int or x: float | None or x: dict[str, list[int | dict[float, User]]]. Just like int(x) will (to the best of its ability) turn x into an int, typewire.as_type(x, int) will do the same, but with the added benefit of working on type hints that aren't callable (like list[float]).

>>> from typewire import as_type

>>> as_type("3.2", float)
3.2

>>> as_type(78.1, int)
78

>>> as_type("3.2", int, transparent_int=True)
3

>>> as_type(["13.2", "18", "-1.2"], list[int | float])
[13.2, 18, -1.2]

>>> as_type([("a", "1"), ("b", "2"), ("c", "3"), ("z", "26")], dict[str, float])
{'a': 1.0, 'b': 2.0, 'c': 3.0, 'z': 26.0}

>>> from pathlib import Path
>>> data = {"logs": ["/tmp/app.log", "123"]}
>>> hint = dict[str, list[Path | int]]
>>> as_type(data, hint)
{'logs': [Path('/tmp/app.log'), 123]}

Installation

typewire is supported on Python 3.10 and onward and can be easily installed with a package manager such as:

# using pip
$ pip install typewire

# using uv
$ uv add typewire

typewire does not have any additional dependencies.

Documentation

TypeHint

TypeHint is provided as a top-level alias for typing.Any.

is_union, is_mapping, is_iterable

These three functions check whether a given type hint is a union type (e.g., int | str | bytes), a mapping type (e.g., dict[str, Any]), or an iterable type (e.g., list[str]).

Note that is_iterable specifically excludes str and bytes: is_iterable(str) == False as, while str does support iteration, for the purposes of type casting, it's not really an iterable/container type.

as_type

The signature is

def as_type(value: Any, to: TypeHint, *, transparent_int: bool = False, semantic_bool: False = False) -> Any:
  ...

In particular, it casts the given value to the given to type, regardless of whether to is:

# a plain type
>>> as_type(3.2, int)
3

# typing.Literal, returning the value as-is if it's a valid entry
>>> as_type("abc", Literal["abc", "def"])
'abc'

>>> as_type("80", Literal[80, 443])
ValueError(...)

# a union type, casting to the first valid type
>>> as_type("3", float | int)
3.0

>>> as_type("3", int | float)
3

# an optional type
>>> as_type(43, int | None)
43

>>> as_type(None, int | None)
None

# a mapping type
>>> as_type({"a": "1", "b": "2.0"}, dict[str, float])
{'a': 1.0, 'b': 2.0}

# a container/iterable type
>>> as_type([1.2, -3, 449], list[str])
['1.2', '-3', '449']

>>> as_type([1.2, -3, 449], tuple[str, ...])
('1.2', '-3', '449')

# typing.Annotated, treating it as the bare type
>>> as_type("3", Annotated[int, "some metadata"])
3

# an abstract collections.abc.Iterable/Mapping, cast as concrete list/dict
>>> as_type([1.2, -3, 449], Iterable[str])
['1.2', '-3', '449']

>>> as_type({"a": "1", "b": "2.0"}, Mapping[str, float])
{'a': 1.0, 'b': 2.0}

# ...unless it's a string being cast as Iterable[str]
>>> as_type("hello world", Iterable[str])
'hello world'

On a failure, ValueError is raised.

transparent_int

This flag (default = False) allows for a nonstrict cast to int.

>>> int("3.2", int)
ValueError # invalid literal for int() with base 10: '3.2'

>>> as_type("3.2", int)
ValueError # invalid literal for int() with base 10: '3.2'

>>> as_type("3.2", int, transparent_int = True)
3

In practice, this flag results in a call of int(float(value)) instead of just int(value).

semantic_bool

This flag (default = False) allows for a nonstrict cast to bool.

>>> bool("false")  # non-empty string
True

>>> as_type("false", bool)
True

>>> as_type("false", bool, semantic_bool = True)
False

In practice, if value is a string and is one of ["false", "no", "0", "off"] (case-insensitive), then it will be cast as False with this flag enabled.