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Pydantic
The most widely used data validation library for Python, and the de facto standard. Type-hint-driven models, fast Rust-based core (v2), and the foundation of FastAPI, LangChain, and most Python AI tooling.
Try PydanticVisit pydantic.devpydantic.dev
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Pydantic uses Python type hints to define data models with full runtime validation. v2 rewrote the core in Rust, making it one of the fastest validation libraries in any language. It is the validation layer under FastAPI, the structured-output spec for OpenAI's Python SDK, the schema layer for LangChain tools, and the backbone of Pydantic AI. If you do anything with structured data in Python, you reach for Pydantic.
Pydantic at a glance
Last verified
- Pricing
- Pydantic Validation - free and open source (MIT)
- Pydantic Logfire (separate hosted observability product) - free tier with 10M telemetry records every month, no credit card required; Enterprise plans available
- Install
pip install pydanticuv add pydanticconda install pydantic -c conda-forge- Models
- Not an AI model runner: a Python data validation library with its core logic in Rust (pydantic-core). Requires Python 3.10+ as of v2.14, which also adds Python 3.15 support; optional email and timezone extras add email-validator and tzdata.
- Recent changes
- v2.14.1 cuts allocations during model validation and fixes TypedDict closed/extra_items inheritance, Decimal max_digits enforcement, and named tuples in Sequence validation.
- v2.14.0 drops Python 3.9, adds Python 3.15, adds multiple_of for fraction and timedelta schemas and a __namespace__ parameter to create_model(), and stops mutating model_config.
Sources: Pydantic installation docs, pydantic/pydantic releases, pydantic/pydantic LICENSE, pydantic.dev
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The most widely used data validation library for Python, and the de facto standard. Type-hint-driven models, fast Rust-based core (v2), and the foundation of FastAPI, LangChain, and most Python AI tooling.
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