email = models.CharField(max_length=100, default="", validators=[EmailValidator(message="email不合法")]) count = models.IntegerField(default=8, validators=[MaxValueValidator(limit_value=20), MinValueValidator(limit_value=5)]) char_str = models.CharField(max_length=100, validators=[MaxLengthVal...
from pydantic import BaseModel, ValidationError, EmailStr, field_validator, model_validator def check_name(v: str) -> str: """Validator to be used throughout""" if not v.startswith("小"): raise ValueError("must be startswith 小") return v class User(BaseModel): id: int name: str ...
from django.core.validators import EmailValidator, URLValidator, DecimalValidator from django.core.validators import MaxValueValidator, MinValueValidator from django.core.validators import MaxLengthValidator, MinLengthValidator class Regex(models.Model): name = models.CharField(max_length=32, error_messages=...
from django.core.validators import RegexValidator from django.core.validators import EmailValidator,URLValidator,DecimalValidator,\ MaxLengthValidator,MinLengthValidator,MaxValueValidator,MinValueValidator 如: test=models.CharField( max_length=32, error_messages={'c1': '优先错信息1','c2': '优先错信息2'...
validatorsimportEmailValidator,URLValidator,DecimalValidator,\27MaxLengthValidator,MinLengthValidator,MaxValueValidator,MinValueValidator28如:29test =models.CharField(30max_length=32,31error_messages={32'c1':'优先错信息1',33'c2':'优先错信息2',34'c3':'优先错信息3',35},36validators=[37RegexValidator...
class MyModel(models.Model): even_field = models.IntegerField(validators=[validate_even]) 验证器的作用很重要,需求也很广泛,Django为此内置了一些验证器,我们直接拿来使用即可: RegexValidator 这是正则匹配验证器。用于对输入的值进行正则搜索,如果命中,则平安无事,如果没命中则弹出 ValidationError 异常。 数字...
MaxLengthValidator,MinLengthValidator,MaxValueValidator,MinValueValidator 如: test = models.CharField( max_length=32, error_messages={ 'c1': '优先错信息1', 'c2': '优先错信息2', 'c3': '优先错信息3', }, validators=[ RegexValidator(regex='root_\d+', message='错误了', code='c1'), ...
2.validators校验(RegexValidator校验器或自定义校验函数) 3.局部钩子(类中定义的以clean_字段名命名的函数,校验正常必须返回该字段的值self.cleaned_data.get(‘name’)) 4.全局钩子(类中定义的函数名clean,校验正常必须返回该对象的校验结果值return self.cleaned_data) 5.每一步通过校验单结果都以字典形式保存在...
validator = ValidateQA( cross_check_sources=True, llm=AnthropicLLM(model="claude-3-haiku") ) doc_processor >> qa_gen >> validator # 运行配置 results = pipe.run( input_files=["technical_manual.pdf","product_specs.doc...
pydantic本身提供了上述基本类型的数据检查方法,但是,除此之外,我们也可以使用validator和config方法来实现更为复杂的数据类型定义以及检查。 1. validator用法考察 使用validator方法,我们可以对数据进行更为复杂的数据检查。 下面,我们给出一个代码实现样例如下: ...