锚文本对网站,十堰优化seo,网站建设公司有哪些,酒店管理专业建设规划使用Flask和Pydantic实现参数验证
1 简介
Pydantic是一个用于数据验证和解析的 Python 库#xff0c;版本2的性能有较大提升#xff0c;很多框架使用Pydantic做数据校验。
# 官方参考文档
https://docs.pydantic.dev/latest/# Github地址
https://github.com/pydantic/pyd…使用Flask和Pydantic实现参数验证
1 简介
Pydantic是一个用于数据验证和解析的 Python 库版本2的性能有较大提升很多框架使用Pydantic做数据校验。
# 官方参考文档
https://docs.pydantic.dev/latest/# Github地址
https://github.com/pydantic/pydantic2 使用Flask自定义参数校验
2.1 结构 2.2 源代码
app_result.py
import jsonfrom flask import jsonifydef result(data: object None, code: int 200, msg: str success):Set the result of web:param data: It is data of status:param code: It is code of status:param msg: It is a message of status:return: dict# 将对象转化为json字符串data_json_str json.dumps(data, ensure_asciiFalse, defaultlambda obj: obj.__dict__)# 将json字符串转化为json字典data_json_dict json.loads(data_json_str)# 设置返回值字典result_dict {code: code,msg: msg,data: data_json_dict}return jsonify(result_dict)
validate_request.py
from flask import request
from pydantic import ValidationErrorfrom entity.app.app_result import resultdef validate_form(form_object):# 设置含有请求参数的装饰器def inner(fun):def inner_sub():try:# 获取Content-Typecontent_type request.content_typeif content_type is None:return result(code400, msgNo parameters)# 验证参数form_instance None# 获取 “application/json” 请求if application/json in content_type:# 获取json字典数据parameters request.get_json(silentTrue)# 将字典转化为对象form_instance form_object(**parameters)else:# 获取 application/x-www-form-urlencoded 或者 multipart/form-data 请求等parameters request.form.to_dict()# 将字典转化为对象form_instance form_object(**parameters)# print(parameters)return fun(form_instance)except ValidationError as e:print(e.json())# 存储错误参数列表parameters_invalid list()# 处理参数for error in e.errors():parameters_invalid.append({attr: error.get(loc)[0],msg: error.get(msg)})return result(parameters_invalid, code400, msgThe parameter is invalid)# 更改视图名称inner_sub.__name__ fun.__name__return inner_subreturn inner
data_form.py
from typing import Optionalfrom pydantic import BaseModel, Field, field_validatorclass DataForm(BaseModel):# Python中...3个点是Ellipsis对象主要用于切片操作和类型注解# pydantic中Field的...3个点表示必填项name: str Field(..., titleThe name of the item, descriptiondeldldlddl, max_length5)desc: Optional[str] Field(..., titleThe description of the item, max_length2)price: float Field(..., titleThe price of the item, ge0.01)# 如果不使用Field设置验证参数可以使用field_validator注解# 自定义验证器field_validator(price)# cls是一个用于类方法的参数代表类本身def age_must_be_positive(cls, v):if v 0:raise ValueError(年龄不能为负数)return vindex.py
from flask import Flask, Blueprintfrom test.data_form import DataForm
from entity.form.validate_request import validate_formapp Flask(__name__)# 构建蓝本
admin Blueprint(admin, __name__)admin.route(/info)
validate_form(DataForm)
def info(info_form: DataForm):print(info_form.name)print(info_form.desc)return Hello Adminadmin.route(/msg)
validate_form(DataForm)
def msg(msg_form: DataForm):print(msg_form)return Hello Admin# 注册蓝本
app.register_blueprint(admin, url_prefix/admin)if __name__ __main__:app.run(host0.0.0.0, debugTrue)2.3 返回值
