Python pyperf module

The Python pyperf module is a toolkit to write, run and analyze benchmarks.

Documenation:

• Perf User Guide
  • Run a benchmark
  • Analyze benchmark results
  • pyperf commands
  • Runner CLI
  • Tune the system for benchmarks
• Perf Developer Guide
  • Examples
  • API
  • Metadata
  • pyperf JSON format
  • Changelog

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
• Python speed mailing list
• Airspeed Velocity: A simple Python benchmarking tool with web-based reporting
• pytest-benchmark
• boltons.statsutils

The pyperf project is covered by the PSF Code of Conduct.