🚀 从模式定义中几秒钟内生成 Python 数据模型。

📚 文献资料· 🧪 游乐场· 💼 首席维护员可工作

[!注] Playground 隐私：生成程序在你的浏览器中本地运行，使用 Pyodide。你的模式和选项不会发送到 后端。共享复制URL会将其编码在URL片段（#state=...），浏览器不会将这些片段发送到服务器; 完整的网址仍然可以存储在你的浏览器历史或你分享的任何地方。

✨ 它的作用

选择任何支持的输入，并选择你想要的 Python 模型样式作为输出。 --input-model path/to/file.py:ClassName 甚至可以重新定位已定义的 Pydantic、dataclass 或 TypedDict 类 在另一个Python文件中转换为不同的输出类型。

• 📄 将 OpenAPI 3、AsyncAPI、**JSON 模式、Apache Avro、XML 模式、协议缓冲区/gRPC、GraphQL、MCP 工具模式以及原始数据（JSON/YAML/CSV）转换为 Python 模型
• 🐍 通过[[T2]从现有的Python类型（Pydantic、dataclass、TypedDict）生成
• 🎯 生成Pydantic v2、Pydantic v2数据类、dataclasses、TypedDict或msgspec输出

datamodel-code-generator

🚀 Generate Python data models from schema definitions in seconds.

📚 Documentation · 🧪 Playground · 💼 Lead maintainer available for work

[!NOTE] Playground privacy: Generation runs locally in your browser with Pyodide. Your schema and options are not sent to a backend. Shared repro URLs encode them in the URL fragment (#state=...), which browsers do not send to the server; the full URL can still be stored in your browser history or wherever you share it.

✨ What it does

Pick any one of the supported inputs and pick the Python model style you want as output. --input-model path/to/file.py:ClassName can even retarget an existing Pydantic, dataclass, or TypedDict class defined in another Python file to a different output type.

• 📄 Converts OpenAPI 3, AsyncAPI, JSON Schema, Apache Avro, XML Schema, Protocol Buffers/gRPC, GraphQL, MCP tool schemas, and raw data (JSON/YAML/CSV) into Python models
• 🐍 Generates from existing Python types (Pydantic, dataclass, TypedDict) via --input-model
• 🎯 Generates Pydantic v2, Pydantic v2 dataclass, dataclasses, TypedDict, or msgspec output
• 🔗 Handles complex schemas: $ref, allOf, oneOf, anyOf, enums, and nested types
• ✅ Produces type-safe, validated code ready for your IDE and type checker