See python-typelib for a modern successor to this library by the same author.
For an more extensive alternative, see mashumaro.
Typical is a library devoted to runtime analysis, inference, validation, and enforcement of Python types, PEP 484 Type Hints, and custom user-defined data-types.
Typical is fully compliant with the following Python Typing PEPs:
- PEP 484 -- Type Hints
- PEP 563 -- Postponed Evaluation of Annotations
- PEP 585 -- Type Hinting Generics In Standard Collections
- PEP 586 -- Literal Types
- PEP 589 -- TypedDict: Type Hints for Dictionaries with a Fixed Set of Keys
- PEP 604 -- Allow writing union types as X | Y
It provides a high-level Protocol API, Functional API, and Object API to suit most any occasion.
Installation is as simple as pip install -U typical.
The latest documentation is hosted at python-typical.org.
Starting with version 2.0, All documentation is hand-crafted markdown & versioned documentation can be found at typical's Git Repo. (Versioned documentation is still in-the-works directly on our domain.)
The decorator that started it all:
import typic @typic.al def hard_math(a: int, b: int, *c: int) -> int: return a + b + sum(c) hard_math(1, "3") #> 4 @typic.al(strict=True) def strict_math(a: int, b: int, *c: int) -> int: return a + b + sum(c) strict_math(1, 2, 3, "4") #> Traceback (most recent call last): #> ... #> typic.constraints.error.ConstraintValueError: Given value <'4'> fails constraints: (type=int, nullable=False, coerce=False) Typical has both a high-level Object API and high-level Functional API. In general, any method registered to one API is also available to the other.
import dataclasses from typing import Iterable import typic @typic.constrained(ge=1) class ID(int): ... @typic.constrained(max_length=280) class Tweet(str): ... @dataclasses.dataclass # or typing.TypedDict or typing.NamedTuple or annotated class... class Tweeter: id: ID tweets: Iterable[Tweet] json = '{"id":1,"tweets":["I don\'t understand Twitter"]}' protocol = typic.protocol(Tweeter) t = protocol.transmute(json) print(t) #> Tweeter(id=1, tweets=["I don't understand Twitter"]) print(protocol.tojson(t)) #> '{"id":1,"tweets":["I don\'t understand Twitter"]}' protocol.validate({"id": 0, "tweets": []}) #> Traceback (most recent call last): #> ... #> typic.constraints.error.ConstraintValueError: Tweeter.id: value <0> fails constraints: (type=int, nullable=False, coerce=False, ge=1)import dataclasses from typing import Iterable import typic @typic.constrained(ge=1) class ID(int): ... @typic.constrained(max_length=280) class Tweet(str): ... @dataclasses.dataclass # or typing.TypedDict or typing.NamedTuple or annotated class... class Tweeter: id: ID tweets: Iterable[Tweet] json = '{"id":1,"tweets":["I don\'t understand Twitter"]}' t = typic.transmute(Tweeter, json) print(t) #> Tweeter(id=1, tweets=["I don't understand Twitter"]) print(typic.tojson(t)) #> '{"id":1,"tweets":["I don\'t understand Twitter"]}' typic.validate(Tweeter, {"id": 0, "tweets": []}) #> Traceback (most recent call last): #> ... #> typic.constraints.error.ConstraintValueError: Tweeter.id: value <0> fails constraints: (type=int, nullable=False, coerce=False, ge=1)from typing import Iterable import typic @typic.constrained(ge=1) class ID(int): ... @typic.constrained(max_length=280) class Tweet(str): ... @typic.klass class Tweeter: id: ID tweets: Iterable[Tweet] json = '{"id":1,"tweets":["I don\'t understand Twitter"]}' t = Tweeter.transmute(json) print(t) #> Tweeter(id=1, tweets=["I don't understand Twitter"]) print(t.tojson()) #> '{"id":1,"tweets":["I don\'t understand Twitter"]}' Tweeter.validate({"id": 0, "tweets": []}) #> Traceback (most recent call last): #> ... #> typic.constraints.error.ConstraintValueError: Given value <0> fails constraints: (type=int, nullable=False, coerce=False, ge=1)See our Releases.