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.