使用 datamodel-code-generator 代码生成

datamodel-code-generator 项目是一个库和命令行实用程序，用于从几乎任何数据源生成 pydantic 模型，包括

• OpenAPI 3 (YAML/JSON)
• JSON Schema
• JSON/YAML/CSV 数据（将被转换为 JSON Schema）
• Python 字典（将被转换为 JSON Schema）
• GraphQL schema

无论何时您发现自己拥有任何可转换为 JSON 但没有 pydantic 模型的数据，此工具都将允许您按需生成类型安全的模型层次结构。

安装

pip install datamodel-code-generator

示例

在本例中，datamodel-code-generator 从 JSON Schema 文件创建 pydantic 模型。

datamodel-codegen  --input person.json --input-file-type jsonschema --output model.py

person.json

{
  "$id": "person.json",
  "$schema": "https://json-schema.fullstack.org.cn/draft-07/schema#",
  "title": "Person",
  "type": "object",
  "properties": {
    "first_name": {
      "type": "string",
      "description": "The person's first name."
    },
    "last_name": {
      "type": "string",
      "description": "The person's last name."
    },
    "age": {
      "description": "Age in years.",
      "type": "integer",
      "minimum": 0
    },
    "pets": {
      "type": "array",
      "items": [
        {
          "$ref": "#/definitions/Pet"
        }
      ]
    },
    "comment": {
      "type": "null"
    }
  },
  "required": [
      "first_name",
      "last_name"
  ],
  "definitions": {
    "Pet": {
      "properties": {
        "name": {
          "type": "string"
        },
        "age": {
          "type": "integer"
        }
      }
    }
  }
}

model.py

# generated by datamodel-codegen:
#   filename:  person.json
#   timestamp: 2020-05-19T15:07:31+00:00
from __future__ import annotations

from typing import Any

from pydantic import BaseModel, Field, conint


class Pet(BaseModel):
    name: str | None = None
    age: int | None = None


class Person(BaseModel):
    first_name: str = Field(description="The person's first name.")
    last_name: str = Field(description="The person's last name.")
    age: conint(ge=0) | None = Field(None, description='Age in years.')
    pets: list[Pet] | None = None
    comment: Any | None = None

更多信息可以在 官方文档 中找到