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 数据（将转换为 JSON Schema）

每当您发现自己有任何数据可转换的 JSON 但没有 pydantic 模型时，此工具将允许您按需生成类型安全的模型层次结构。

安装 Installation¶

pip install datamodel-code-generator

例子 Example¶

在这种情况下，datamodel-code-generator 从 JSON 模式文件创建 pydantic 模型。

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

person.json:

{
  "$id": "person.json",
  "$schema": "http://json-schema.org/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:

Python 3.7 及以上版本

# generated by datamodel-codegen:
#   filename:  person.json
#   timestamp: 2020-05-19T15:07:31+00:00
from __future__ import annotations
from typing import Any, List, Optional
from pydantic import BaseModel, Field, conint


class Pet(BaseModel):
    name: Optional[str] = None
    age: Optional[int] = 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: Optional[conint(ge=0)] = Field(None, description='Age in years.')
    pets: Optional[List[Pet]] = None
    comment: Optional[Any] = None

(这个脚本是完整的，它应该“按原样”运行)

更多信息可以在官方文档中找到