pydantic

前言

pydantic是一个使用Python类型注解进行数据验证和管理的模块，它可以在代码运行时强制进行类型验证。FastAPI整合了pydantic，便于参数校验处理。

模型常见类型

from pydantic import (
    BaseModel, Field, FilePath, EmailStr, SecretStr, NameEmail, SecretBytes, HttpUrl, Json,DirectoryPath, IPvAnyAddress
)
from datetime import date
import json
from typing import Optional

class Tmp1(BaseModel):
    name: str # 字符串类型
    age: int # 整型
    age2: Optional[int] # 可选填参数。如果赋值，则必须为整型
    age3: Optional[int] = None # 可选填参数。指定了默认值为None
    enable: bool
    hobby: list
    address: dict
    birthday: date

    email: EmailStr # 电子邮件格式
    email2: NameEmail # 带有用户名的电子邮件格式
    filepath: FilePath # 文件路径类型
    directorypath: DirectoryPath # 文件目录类型
    ipaddr: IPvAnyAddress # IP地址类型
    secretstr: SecretStr # 用于敏感数据的字符串类型
    secretbyte: SecretBytes # 用于敏感数据的二进制类型
    website: HttpUrl # URL地址类型
    jsonobj: Json # JSON类型

if __name__ == '__main__':
    v1 = Tmp1(
        name="zhangsan",
        age=18,
        age2=19,
        enable=True,
        hobby=["sing","dance","basketball"],
        address={
            "Country": "China",
            "Province": "Anhui",
        },
        birthday= '2023-01-01',
        email="zhangsan@lisi.com",
        email2="zhangsan <zhangsan@lisi.com>",
        filepath="./test.txt",
        directorypath="./test",
        ipaddr="127.0.0.1",
        secretstr="123456qwerty",
        secretbyte=b"qwerty123456",
        website="https://baidu.com",
        jsonobj=json.dumps({"hello": "world"})
    )
    print(v1)
    print("-"*50)
    print(v1.model_dump()) # 旧版本可以使用 v1.dict()
    print("-"*50)
    print(v1.model_dump_json()) # 旧版本可以使用 v1.json()

测试运行输出

name='zhangsan' age=18 age2=19 age3=None enable=True hobby=['sing', 'dance', 'basketball'] address={'Country': 'China', 'Province': 'Anhui'} birthday=datetime.date(2023, 1, 1) email='zhangsan@lisi.com' email2=NameEmail(name='zhangsan', email='zhangsan@lisi.com') filepath=PosixPath('test.txt') directorypath=PosixPath('test') ipaddr=IPv4Address('127.0.0.1') secretstr=SecretStr('**********') secretbyte=SecretBytes(b'**********') website=Url('https://baidu.com/') jsonobj={'hello': 'world'}
--------------------------------------------------
{'name': 'zhangsan', 'age': 18, 'age2': 19, 'age3': None, 'enable': True, 'hobby': ['sing', 'dance', 'basketball'], 'address': {'Country': 'China', 'Province': 'Anhui'}, 'birthday': datetime.date(2023, 1, 1), 'email': 'zhangsan@lisi.com', 'email2': NameEmail(name='zhangsan', email='zhangsan@lisi.com'), 'filepath': PosixPath('test.txt'), 'directorypath': PosixPath('test'), 'ipaddr': IPv4Address('127.0.0.1'), 'secretstr': SecretStr('**********'), 'secretbyte': SecretBytes(b'**********'), 'website': Url('https://baidu.com/'), 'jsonobj': {'hello': 'world'}}
--------------------------------------------------
{"name":"zhangsan","age":18,"age2":19,"age3":null,"enable":true,"hobby":["sing","dance","basketball"],"address":{"Country":"China","Province":"Anhui"},"birthday":"2023-01-01","email":"zhangsan@lisi.com","email2":"zhangsan <zhangsan@lisi.com>","filepath":"test.txt","directorypath":"test","ipaddr":"127.0.0.1","secretstr":"**********","secretbyte":"**********","website":"https://baidu.com/","jsonobj":{"hello":"world"}}

Field类验证

from pydantic import BaseModel, ValidationError

class Tmp2(BaseModel):
    name: str = Field(..., title="姓名", description="用户姓名", max_length=10, examples=["张三"])
    age: int = Field(..., title="年龄", description="用户年龄", gt=0, lt=150, examples=[18])

if __name__ == '__main__':
    try:
        v2 = Tmp2(name="张三", age=188)
    except ValidationError as e:
        print(e.errors())
    else:
        print(v2.model_dump())

测试运行输出

[{'type': 'less_than', 'loc': ('age',), 'msg': 'Input should be less than 150', 'input': 188, 'ctx': {'lt': 150}, 'url': 'https://errors.pydantic.dev/2.5/v/less_than'}]

自定义验证

from pydantic import BaseModel, ValidationError, field_validator
class Tmp3(BaseModel):
    name: str
    age: int

    @field_validator("age") # 旧版本需要换成validator
    def valid_age(cls, v):
        if v < 0: # 自测无法用and写成一行，否则会失效
            raise ValueError("年龄必须大于0")
        elif v > 150:
            raise ValueError("年龄必须小于150")
        return v

if __name__ == '__main__':
    try:
        v2 = Tmp3(name="张三", age=188)
    except ValidationError as e:
        print(e.errors())
    else:
        print(v2.model_dump())