Pydantic 验证
类型强制和模型验证。
概述
Pydantic 允许 Python 数据类自动将根本上无类型的网络配置转变为类型化表示。
这使用稳健的类型约束来保护系统状态。
代码和执行输出
声明用于验证有效负载的严格模式用户模型。
models.py
在编辑器中尝试from pydantic import BaseModel, EmailStr, Field
from typing import List, Optional
import json
class User(BaseModel):
id: int
name: str = Field(min_length=2)
email: EmailStr
tags: List[str] = []
is_active: bool = True
# Simulating an API response with mixed types
incoming_data = {
"id": "123", # string gets coerced to int
"name": "Alice",
"email": "alice@example.com",
"tags": ("python", "developer") # tuple gets coerced to list
}
# Validate and instantiate
user = User(**incoming_data)
print("--- Validated Pydantic Model ---")
print(repr(user))
print("\n--- Exported to JSON ---")
print(user.model_dump_json(indent=2))端子输出
--- Validated Pydantic Model ---
User(id=123, name='Alice', email='alice@example.com', tags=['python', 'developer'], is_active=True)
--- Exported to JSON ---
{
"id": 123,
"name": "Alice",
"email": "alice@example.com",
"tags": [
"python",
"developer"
],
"is_active": true
}逐步实施
- API端点保护
- 配置模式验证
- 数据库接口