🖥Pydantic имеет встроенную функцию #DataValidation , но она потребляет много памяти.
Attrs не имеет встроенной проверки данных и обеспечивает более высокую производительность и меньшее использование памяти, что идеально подходит для внутренних структур данных и простого создания классов в #Python.
from attrs import define, field
@define class UserAttrs: name: str age: int = field()
@age.validator def check_age(self, attribute, value): if value < 0: raise ValueError("Age can't be negative") return value # accepts any positive age
try: user = UserAttrs(name="Bob", age=-1) except ValueError as e: print("ValueError:", e)
🖥Pydantic имеет встроенную функцию #DataValidation , но она потребляет много памяти.
Attrs не имеет встроенной проверки данных и обеспечивает более высокую производительность и меньшее использование памяти, что идеально подходит для внутренних структур данных и простого создания классов в #Python.
from attrs import define, field
@define class UserAttrs: name: str age: int = field()
@age.validator def check_age(self, attribute, value): if value < 0: raise ValueError("Age can't be negative") return value # accepts any positive age
try: user = UserAttrs(name="Bob", age=-1) except ValueError as e: print("ValueError:", e)
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