Profilers measure the performance of a whole program to identify where most of the time is spent. But once you’ve found a target function, re-profiling the whole program to see if your changes helped can be slow and cumbersome. The profiler introduces overhead to execution and you have to pick out the stats for the one function you care about from the report. I have often gone through this loop while optimizing client or open source projects, such as when I optimized Django’s system checks framework (previous post).

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Adam Johnson

tprof is a new targeting profiler for Python 3.12+ that measures performance of specific functions rather than entire programs. Unlike traditional profilers that add overhead across the whole codebase, tprof uses sys.monitoring to track only designated target functions, providing quick command-line reports with timing statistics. It supports comparison mode to benchmark "before" and "after" versions of optimized code, showing percentage improvements. The tool offers both CLI and Python API interfaces, with timing done in C to minimize overhead.

Python: introducing tprof, a targeting profiler

<p>Interesting, will definitely check it out!</p>
