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78934db631
* Propagate`ClassVar`s to sub-models
Currently, if a `ClassVar` is defined on a model and re-defined
on a sub-model omitting the `ClassVar` annotation, Pydantic produces an
unrelated error:
NameError: Field name "..." shadows a BaseModel attribute ...
This check was introduced to prevent shadowing Pydantic's own methods
and attributes defined on the `BaseModel` class. Following this change,
class variables (that is, variables annotated with `ClassVar`)
defined on parent models will be inherited by sub-models and
will be overwritable without having to reapply the annotation.
Closes #2061.
* docs: explain how attributes are excluded and when to use `PrivateAttr`
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, Optional
from pydantic import BaseModel
class User(BaseModel):
id: int
name = 'John Doe'
signup_ts: Optional[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.
Reporting a Security Vulnerability
See our security policy.