Are you looking to optimize your Python codebase and make it more manageable? By incorporating decorators and applying refactoring techniques, you can significantly improve the organization, readability, and performance of your projects.
Let’s dive into understanding decorators and explore their potential impact on your refactored code.
What are Decorators?
Decorators are functions that accept another function as input, extend or modify its behavior, and then return the modified version. Using decorators enables you to apply common patterns easily and avoid repetitive boilerplate code. A popular application of decorators includes logging, caching, and authentication.
Let’s consider a real-world scenario where we need to rate limit API requests to prevent abuse. We can accomplish this using a decorator:
from functools import wraps
import time
def rate_limited(max_per_second):
"""Rate limits the wrapped function to max_per_second calls per second."""
min_interval = 1 / float(max_per_second)
def decorate(func):
last_time_called = [0.0]…
