Python pyperf moduleΒΆ
The Python pyperf
module is a toolkit to write, run and analyze benchmarks.
Documentation:
Features of the pyperf
module:
Simple API to run reliable benchmarks: see examples.
Automatically calibrate a benchmark for a time budget.
Spawn multiple worker processes.
Compute the mean and standard deviation.
Detect if a benchmark result seems unstable: see the pyperf check command.
pyperf stats command to analyze the distribution of benchmark results (min/max, mean, median, percentiles, etc.).
pyperf compare_to command tests if a difference if significant. It supports comparison between multiple benchmark suites (made of multiple benchmarks)
pyperf timeit command line tool for quick but reliable Python microbenchmarks
pyperf system tune command to tune your system to run stable benchmarks.
Automatically collect metadata on the computer and the benchmark: use the pyperf metadata command to display them, or the pyperf collect_metadata command to manually collect them.
--track-memory
and--tracemalloc
options to track the memory usage of a benchmark.JSON format to store benchmark results.
Support multiple units: seconds, bytes and integer.
Quick Links:
pyperf documentation (this documentation)
pyperf project homepage at GitHub (code, bugs)
Download latest pyperf release at the Python Cheeseshop (PyPI)
Other Python benchmark projects:
pyperformance: the Python benchmark suite which uses
pyperf
Airspeed Velocity: A simple Python benchmarking tool with web-based reporting
The pyperf project is covered by the PSF Code of Conduct.