A simple timing decorator (wraps-preserving ergonomics)

Intermediate Accelerating numerics & developer hygiene

Created by Pavel · 29.04.2026 at 19:11 UTC

Decorators that add timing/logging should use functools.wraps so __name__, __doc__, and annotations remain intact for profilers and Sphinx. This card connects the V06 decorator lesson to performance measurement: wrap fn, record perf_counter deltas, optionally log, return the original result.

Production systems add structured logging, sampling, and async context—but the student pattern is the same: outer function, inner wrapper, preserve metadata.

functools.wraps: [1].

Sources

[1]https://docs.python.org/3/library/functools.html#functools.wraps Return to text

University approvals: 0

Tasks

Question 1

functools.wraps(fn) in a decorator mainly preserves:

Hint

Introspection-friendly wrappers.

Global interpreter lock state

Metadata like name and doc on the wrapper

NumPy array memory layout

SQL transaction isolation

Question 2

Why avoid a decorator that returns a wrapper without wraps in library code?

Hint

Observability suffers.

It breaks the import system

Stack traces and help() show misleading names/docs

It disables list comprehensions

CPython forbids it

Question 3

timed_call(f, *a, **k) returns (result, elapsed_ms) using time.perf_counter().

Hint

Return both value and timing.

import time


def timed_call(f, *a, **k):
    pass

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Card Info

Topic: Accelerating numerics & developer hygiene
Difficulty: Intermediate
Completed: 0 users

Creator

Pavel