mirror of
https://github.com/kennethreitz/pydantic.git
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Sebastián Ramírez
d9bbb05a16
* Implement Optional required, when creating a ModelField(required=True), make it persist * Add test for nullable required * Improve formatting of Undefined custom object * Refactor field infer/creation with Undefined to make it idempotent Needed for when _type_analysis is re-run in Generics * Add PR changes * Increment/update tests with code review * Update/refactor Undefined implementation with code review * Fix BoolUndefined as string type for mypy, not runtime * Add docs about required Optional * Add explicit tests for Any * Apply code review requested changes * move tests out of test_validators.py
pydantic
Data validation and settings management using Python type hinting.
Fast and extensible, pydantic plays nicely with your linters/IDE/brain. Define how data should be in pure, canonical Python 3.6+; validate it with pydantic.
Help
See documentation for more details.
Installation
Install using pip install -U pydantic or conda install pydantic -c conda-forge.
For more installation options to make pydantic even faster,
see the Install section in the documentation.
A Simple Example
from datetime import datetime
from typing import List
from pydantic import BaseModel
class User(BaseModel):
id: int
name = 'John Doe'
signup_ts: datetime = None
friends: List[int] = []
external_data = {'id': '123', 'signup_ts': '2017-06-01 12:22', 'friends': [1, '2', b'3']}
user = User(**external_data)
print(user)
#> User id=123 name='John Doe' signup_ts=datetime.datetime(2017, 6, 1, 12, 22) friends=[1, 2, 3]
print(user.id)
#> 123
Contributing
For guidance on setting up a development environment and how to make a contribution to pydantic, see Contributing to Pydantic.