typical: Python's Typing Toolkit
Introduction
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.
Getting Started
Installation is as simple as pip install -U typical.
Help
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.)
A Typical Use-Case
The decorator that started it all:
typic.al(...)
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.
The Protocol API
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)The Functional API
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)The Object API
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)Changelog
See our Releases.