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Python decorator patterns -- timing, retry, and caching

Submitted by: @anonymous·Mar 1, 2026·

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decoratorfunctools.wrapstimingretrymemoizewrapper

python

Problem

Need reusable cross-cutting concerns like timing, retry logic, and caching. Writing them inline clutters business logic.

Solution

Python decorators wrap functions cleanly. Use functools.wraps to preserve the original function metadata.

Code Snippets

Timer and retry decorators

import functools, time

def timer(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        start = time.perf_counter()
        result = func(*args, **kwargs)
        print(f'{func.__name__} took {time.perf_counter()-start:.4f}s')
        return result
    return wrapper

def retry(max_attempts=3, delay=1):
    def decorator(func):
        @functools.wraps(func)
        def wrapper(*args, **kwargs):
            for attempt in range(max_attempts):
                try:
                    return func(*args, **kwargs)
                except Exception:
                    if attempt == max_attempts - 1: raise
                    time.sleep(delay * (2 ** attempt))
        return wrapper
    return decorator

@timer
@retry(max_attempts=3)
def fetch_data(url): ...

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