What is a Python decorator, and what can go wrong when you write one?

Explains callable decoration, closure-based configuration, metadata preservation, ordering, async behavior, and hidden control flow.

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TL;DR

A decorator takes a function or class and returns the object that should replace it. @audit above a function is roughly assignment of audit(original) to that function name when the definition executes. A function decorator often returns a wrapper closure that runs behavior before or after calling the original. functools.wraps copies important metadata and exposes the wrapped function, helping introspection, documentation, and frameworks understand it.

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The ability to describe decorator mechanics and apply them without breaking signatures, observability, or coroutine behavior.

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Overview
Decorators are concise callable transformations, but that concision can hide important runtime behavior.
A decorator takes a function or class and returns the object that should replace it. @audit above a function is roughly assignment of audit(original) to that function name when the definition executes. A function decorator often returns a wrapper closure that runs behavior before or after calling the original. functools.wraps copies important metadata and exposes the wrapped function, helping introspection, documentation, and frameworks understand it.
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Details

Describing @decorator as running on every call rather than decorating at definition time.
Forgetting functools.wraps.
Wrapping an async function with a synchronous call path.
Ignoring the order of stacked decorators.

What is a Python decorator, and what can go wrong when you write one?

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