runtimecompare approaches one problem · two ways
Compare Approaches
The same problem solved different ways in Python, run on the same input, with what really differs and when to use each.
Wrapper without wraps vs decorator with functools.wrapsbehaves differently
Log every call to a function, then check the function's name and docstring.
what differs
@logged is exactly total = logged(total). Without functools.wraps, the result is named ‘wrapper’ and has no docstring, which confuses debuggers, help() and tools that look functions up by name.
at a glance
| approach | use it when |
|---|---|
| A · plain wrapper | Never in shared code: the wrapped function loses its identity. |
| B · @decorator + wraps | Every decorator you write. |
Watch out: wraps also sets __wrapped__, so inspect.signature and tests can reach the original function.
the outputs
Each approach runs on the same input.
concepts
decoratorsfunctools.wrapshigher-order functions
learn it
Decorators: wrap a function · functools.wraps: keep the function's identity
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