Python Decorators

Also Known As

TL;DR

Explanation

A decorator is a callable that takes a function and returns a modified version. @functools.wraps preserves the original function's name and docstring. Built-in decorators: @property (computed attribute), @staticmethod (no self/cls), @classmethod (receives cls), @functools.cache (memoisation), @functools.lru_cache(maxsize=128). Decorator factories take arguments: @lru_cache(maxsize=256). Class decorators: @dataclass generates __init__, __repr__, __eq__ from class annotations — Python's equivalent of PHP 8.1 readonly classes. Stacking: @app.route('/') @login_required applies inside-out. PHP's equivalent is attribute-based annotations (#[Route]) or middleware patterns — Python decorators are more powerful because they execute arbitrary code, not just metadata.

Diagram

flowchart LR
    subgraph Decorator_Mechanics
        ORIG[def my_func]
        WRAP[def decorator wraps func]
        APPLIED[my_func = decorator my_func]
        ORIG --> WRAP --> APPLIED
    end
    subgraph Common_Uses
        TIMING[measure_time decorator<br/>log execution duration]
        CACHE2[functools.lru_cache<br/>memoize results]
        AUTH2[require_auth decorator<br/>check before running]
        RETRY2[retry decorator<br/>retry on exception]
    end
    subgraph Syntax
        AT[at symbol decorator<br/>above function definition<br/>syntactic sugar]
    end
style APPLIED fill:#238636,color:#fff
style CACHE2 fill:#1f6feb,color:#fff
style AUTH2 fill:#f85149,color:#fff

Common Misconception

Why It Matters

Common Mistakes

• Not using functools.wraps — the decorated function loses its __name__ and __doc__.
• Decorators that do not handle the wrapped function's arguments correctly — use *args, **kwargs.
• Stateful decorators without thread safety — mutable state in a decorator is shared across calls.
• Stacking too many decorators — execution order is bottom-up for application and top-down for stacking.

Code Examples

# Decorator without functools.wraps — loses metadata:
def log_call(func):
    def wrapper(*args, **kwargs):
        print(f'Calling {func.__name__}')
        return func(*args, **kwargs)
    return wrapper  # wrapper.__name__ is 'wrapper', not 'original'

# Fixed:
import functools
def log_call(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs): ...
    return wrapper

import functools

def retry(times=3):
    def decorator(fn):
        @functools.wraps(fn)
        def wrapper(*args, **kwargs):
            for i in range(times):
                try: return fn(*args, **kwargs)
                except Exception:
                    if i == times - 1: raise
        return wrapper
    return decorator

@retry(times=5)
def fetch_data(): ...

References

• ↗ https://docs.python.org/3/glossary.html#term-decorator

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