Python的Pydantic概念及基本用法

pip install pydantic

from pydantic import BaseModel
class User(BaseModel):
    name: str
    age: int  # 如果不匹配，Pydantic 会尝试强制转换
    is_active: bool = True  # 可以有默认值

# 从字典创建实例
user = User(name="Alice", age="25")  # 注意：age 是字符串，但会被转为 int
print(user.name)      # Alice
print(user.age)       # 25 (int)
print(user.is_active) # True
# 访问原始数据
print(user.model_dump())  # {'name': 'Alice', 'age': 25, 'is_active': True}

from pydantic import ValidationError
try:
    User(name="Bob", age="not_a_number")
except ValidationError as e:
    print(e.json()) # 会详细列出格式错误

from pydantic import BaseModel, Field
class Product(BaseModel):
    name: str = Field(min_length=2, max_length=50)
    price: float = Field(gt=0)  # 必须大于 0
    tags: list[str] = Field(default=[], min_items=1)
# 示例
Product(name="Laptop", price=999.99, tags=["electronics"])

from typing import List, Optional
from pydantic import BaseModel, Field
# 1. 定义底层模型：商品
class Item(BaseModel):
    name: str
    price: float
    quantity: int = Field(gt=0, description="数量必须大于0")
# 2. 定义底层模型：收货地址
class Address(BaseModel):
    city: str
    street: str
    zip_code: Optional[str] = None
# 3. 定义顶层模型：订单（嵌套了 Item 和 Address）
class Order(BaseModel):
    order_id: int
    items: List[Item]  # 嵌套商品列表
    address: Address   # 嵌套地址对象
    remark: str = "无"
# --- 模拟原始数据（例如来自前端请求或数据库） ---
raw_data = {
    "order_id": 1001,
    "items": [
        {"name": "键盘", "price": 299.0, "quantity": 1},
        {"name": "鼠标", "price": 99.5, "quantity": 2}
    ],
    "address": {
        "city": "上海",
        "street": "南京东路 123 号"
    }
}
# 解析数据
order = Order(**raw_data)
# 访问嵌套数据
print(f"订单 ID: {order.order_id}")
print(f"第一件商品名称: {order.items[0].name}") # 自动补全非常爽
print(f"收货城市: {order.address.city}")

pip install pydantic-settings

from pydantic_settings import BaseSettings
class Settings(BaseSettings):
    db_url: str
    api_key: str
    class Config:
        env_file = ".env"
settings = Settings() # 自动从环境变量加载并校验