Built-in Decorators and Standard Library Decorators in Python
Built-in Decorators and Standard Library Decorators in Python
Python provides several built-in decorators and others in its standard library, particularly in the functools module. These decorators offer powerful functionality for common programming patterns.
Built-in Decorators
@property
The @property decorator is used to define methods in a class that act like attributes:
@classmethod
@classmethod is used to define methods that operate on the class rather than instances:
@staticmethod
@staticmethod is used for methods that don’t need access to the class or instance:
@dataclass
The @dataclass decorator, introduced in Python 3.7, automatically generates special methods like init(), repr(), and eq() for a class:
This decorator simplifies the creation of classes that are primarily used to store data, reducing boilerplate code significantly.
Decorators from functools
The functools module in Python’s standard library provides several useful decorators:
@functools.lru_cache
This decorator implements memoization, caching the results of a function:
@functools.cache
Introduced in Python 3.9, @cache is a simpler unbounded cache:
@functools.wraps
This decorator is used when writing custom decorators to preserve the metadata of the original function:
@functools.total_ordering
This decorator generates missing comparison methods for a class:
Conclusion
These built-in and standard library decorators provide powerful tools for Python developers. They offer efficient solutions for common programming patterns, from property management and method types to caching and comparison operations. Understanding and using these decorators can significantly enhance code readability and performance.