datetime:2022/09/24 15:44
author:nzb
pydantic 基础使用
from datetime import datetime, date
from pathlib import Path
from typing import Optional, List
from pydantic import BaseModel, ValidationError, constr
from sqlalchemy import Column, Integer, String
from sqlalchemy.dialects.postgresql import ARRAY
from sqlalchemy.ext.declarative import declarative_base
"""
Data validation and settings management using python type annotations.
使用Python的类型注解来进行数据校验和settings管理
pydantic enforces type hints at runtime, and provides user friendly errors when data is invalid.
Pydantic可以在代码运行时提供类型提示,数据校验失败时提供友好的错误提示
Define how data should be in pure, canonical python; validate it with pydantic.
定义数据应该如何在纯规范的Python代码中保存,并用Pydantic验证它
"""
class User(BaseModel):
id: int
name: str = "Jack"
signup_ts: Optional[datetime] = None
friends: List[int] = []
external_data = {
"id": "123",
"signup_ts": "2022-07-06 10:45",
"friends": [1, 2, "3"]
}
print("\033[31m1. --- Pydantic的基本用法。Pycharm可以安装Pydantic插件 ---\033[0m")
user = User(**external_data)
print(user.id, user.friends)
print(user.signup_ts)
print(user.dict())
print("\033[31m2. --- 校验失败处理 ---\033[0m")
try:
User(id=1, signup_ts=datetime.today(), friends=[1, 2, 'not number'])
except ValidationError as e:
print(e.json())
print("\033[31m3. --- 模型类的的属性和方法 ---\033[0m")
print(user.dict())
print(user.json())
print(user.copy())
print(User.parse_obj(external_data))
print(User.parse_raw('{"id": "123", "signup_ts": "2020-12-22 12:22", "friends": [1, 2, "3"]}'))
path = Path("pydantic_tutorial.json")
path.write_text('{"id": "123", "signup_ts": "2020-12-22 12:22", "friends": [1, 2, "3"]}')
print(User.parse_file(path))
print(user.schema())
print(user.schema_json())
user_data = {"id": "error", "signup_ts": "2020-12-22 12:22", "friends": [1, 2, 3]}
print(User.construct(**user_data))
print(User.__fields__.keys())
print("\033[31m4. --- 递归模型 ---\033[0m")
class Sound(BaseModel):
sound: str
class Dog(BaseModel):
birthday: date
weight: float = Optional[None]
sound: List[Sound]
dogs = Dog(birthday=date.today(), weight=6.66, sound=[{"sound": "wang wang ~"}, {"sound": "ying ying ~"}])
print(dogs.dict())
print("\033[31m5. --- ORM模型:从类实例创建符合ORM对象的模型 ---\033[0m")
Base = declarative_base()
class ComanyOrm(Base):
__tablename__ = "companies"
id = Column(Integer, primary_key=True, nullable=True)
public_key = Column(String(20), index=True, nullable=True, unique=True)
name = Column(String(64), unique=True)
domains = Column(ARRAY(String(255)))
class ComanyModel(BaseModel):
id: int
public_key: constr(max_length=20)
name: constr(max_length=64)
domains: List[constr(max_length=255)]
class Config:
orm_mode = True
company_orm = ComanyOrm(
id=123,
public_key="foobar",
name="Testing",
domains=["demo.com", "example.com"]
)
print(ComanyModel.from_orm(company_orm))
print("\033[31m6. --- Pydantic支撑的字段类型,官方文档:https://pydantic-docs.helpmanual.io/usage/types/ ---\033[0m")
1. --- Pydantic的基本用法。Pycharm可以安装Pydantic插件 ---
123 [1, 2, 3]
2022-07-06 10:45:00
{'id': 123, 'name': 'Jack', 'signup_ts': datetime.datetime(2022, 7, 6, 10, 45), 'friends': [1, 2, 3]}
2. --- 校验失败处理 ---
[
{
"loc": [
"friends",
2
],
"msg": "value is not a valid integer",
"type": "type_error.integer"
}
]
3. --- 模型类的的属性和方法 ---
{'id': 123, 'name': 'Jack', 'signup_ts': datetime.datetime(2022, 7, 6, 10, 45), 'friends': [1, 2, 3]}
{"id": 123, "name": "Jack", "signup_ts": "2022-07-06T10:45:00", "friends": [1, 2, 3]}
id=123 name='Jack' signup_ts=datetime.datetime(2022, 7, 6, 10, 45) friends=[1, 2, 3]
id=123 name='Jack' signup_ts=datetime.datetime(2022, 7, 6, 10, 45) friends=[1, 2, 3]
id=123 name='Jack' signup_ts=datetime.datetime(2020, 12, 22, 12, 22) friends=[1, 2, 3]
id=123 name='Jack' signup_ts=datetime.datetime(2020, 12, 22, 12, 22) friends=[1, 2, 3]
{'title': 'User', 'type': 'object', 'properties': {'id': {'title': 'Id', 'type': 'integer'}, 'name': {'title': 'Name', 'default': 'Jack', 'type': 'string'}, 'signup_ts': {'title': 'Signup Ts', 'type': 'string', 'format': 'date-time'}, 'friends': {'title': 'Friends', 'default': [], 'type': 'array', 'items': {'type': 'integer'}}}, 'required': ['id']}
{"title": "User", "type": "object", "properties": {"id": {"title": "Id", "type": "integer"}, "name": {"title": "Name", "default": "Jack", "type": "string"}, "signup_ts": {"title": "Signup Ts", "type": "string", "format": "date-time"}, "friends": {"title": "Friends", "default": [], "type": "array", "items": {"type": "integer"}}}, "required": ["id"]}
name='Jack' signup_ts='2020-12-22 12:22' friends=[1, 2, 3] id='error'
dict_keys(['id', 'name', 'signup_ts', 'friends'])
4. --- 递归模型 ---
{'birthday': datetime.date(2022, 9, 24), 'sound': [{'sound': 'wang wang ~'}, {'sound': 'ying ying ~'}]}
5. --- ORM模型:从类实例创建符合ORM对象的模型 ---
id=123 public_key='foobar' name='Testing' domains=['demo.com', 'example.com']
6. --- Pydantic支撑的字段类型,官方文档:https://pydantic-docs.helpmanual.io/usage/types/ ---