{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/10"}],"enrichment":{"capability":"pyperf is a toolkit for writing, running, and analyzing Python benchmarks with automatic calibration, statistical analysis, and JSON result storage.","skillfed_tags":["benchmarking","performance-testing","statistics"],"use_cases":["Measure the performance of a code snippet or function across multiple runs and detect statistical significance.","Compare benchmark results across different Python versions or implementations to identify regressions.","Track memory usage alongside execution time using --track-memory or --tracemalloc options.","Automate performance testing in CI/CD pipelines by writing benchmark scripts that output JSON results.","Analyze historical benchmark data to spot trends or anomalies in performance over time."],"what_it_does":"pyperf is a Python benchmarking toolkit that automates the process of writing, executing, and analyzing performance tests. It handles the tedious parts of reliable benchmarking\u2014automatic calibration to a time budget, spawning multiple worker processes to reduce noise, computing statistics (mean, standard deviation, percentiles), and detecting unstable results\u2014so you can focus on the code you want to measure. Results are stored in JSON format for later analysis or comparison.\n\nYou can use it two ways: as a command-line tool (pyperf timeit) for quick one-off measurements, or by writing a benchmark script that instantiates a Runner and calls timeit() or other measurement methods. The toolkit also provides commands to analyze results (pyperf stats), compare benchmark suites across Python versions (pyperf compare_to), and tune your system for stable benchmarking (pyperf system tune). It depends only on psutil for system introspection.","worth_installing":"Yes. pyperf is a mature, actively maintained toolkit (950 stars, recent commits, MIT license) with low install friction. It solves a real problem\u2014reliable Python benchmarking with statistical rigor\u2014that most developers either skip or implement poorly. Install it if you need to measure performance seriously rather than relying on ad-hoc timeit calls."},"id":"pyperf","links":{"html":"https://skillfed.io/packages/pyperf","md":"https://skillfed.io/packages/pyperf.md","pypi":"https://pypi.org/project/pyperf/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-02-07","license_spdx":null,"license_treatment":"permissive","name":"pyperf","python_support":"supports_current","summary":"Python module to run and analyze benchmarks"},"popularity":{"monthly_downloads":646012,"position":5597,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.10.0"}