Pydantic is a data validation library for Python.
Define how data should be in pure, canonical Python 3.7+; validate it with Pydantic.
This is free and open source software.
Features include:
- Type hints powering schema validation. The schema that Pydantic validates against is generally defined by Python type hints.
- Core validation logic is implemented in separate package pydantic-core, where validation for most types is implemented in Rust.
- Provides functionality to serialize model in three ways:
- To a Python dict made up of the associated Python objects.
- To a Python dict made up only of “jsonable” types.
- To a JSON string.
- JSON Schema can be generated for any Pydantic schema — allowing self-documenting APIs and integration with a wide variety of tools which support JSON Schema.
- Strict mode and data coercion.
- Provides four ways to create schemas and perform validation and serialization:
- BaseModel — Pydantic’s own super class with many common utilities available via instance methods.
- pydantic.dataclasses.dataclass – a wrapper around standard dataclasses which performs validation when a dataclass is initialized.
- TypeAdapter – a general way to adapt any type for validation and serialization. This allows types like TypedDict and NampedTuple to be validated as well as simple scalar values like int or timedelta – all types supported can be used with TypeAdapter.
- validate_call – a decorator to perform validation when calling a function.
- Customisation
Website: docs.pydantic.dev/latest
Support: GitHub Code Repository
Developer: Pydantic Services Inc. and individual contributors
License: MIT License
Pydantic is written in Python. Learn Python with our recommended free books and free tutorials.
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