A chapter-by-chapter walkthrough of pydantic, generated from its source code and tutorial markdown.
pydantic is organized as connected concepts and components. Start broad, then drill down chapter by chapter.
Pydantic is a data validation and settings management library that uses Python type annotations to define data schemas. At its core, users define models inheriting from BaseModel with typed Fields and optional Functional Validators, which the high-performance Pydantic Core Engine (written in Rust) uses to validate and serialize data. The project also provides flexible tools like TypeAdapter for on-the-fly validation and RootModel for custom root types, all governed by a centralized Configuration system.
Source Repository: https://github.com/pydantic/pydantic
Follow sequentially or jump to any topic. Start with BaseModel.
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