The pyperformance project is intended to be an authoritative source of benchmarks for all Python implementations.

A set of benchmark problems and implementations for Python - numfocus/python-benchmarks

Save apalala/3fbbeb5305584d2abe05 to your computer and use it in GitHub Desktop. ... This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode characters ... Apple M1 MacBook Air 16GB gets: python -OO bench.py 0.645364999771 0.645573139191 0.646193981171 python3 -OO bench.py 0.6115190000000004 0.6118404580000001 0.611904

August 24, 2016 - This project is intended to be ... than synthetic benchmarks, using whole applications when possible. GitHub: https://github.com/python/benchmarks (source code, issues)...

A simple Python Benchmark Library. Contribute to Karlheinzniebuhr/pythonbenchmark development by creating an account on GitHub.

To run a benchmark use the pyperf timeit command (result written into bench.json): $ python3 -m pyperf timeit '[1,2]*1000' -o bench.json .....................

A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket: - dionhaefner/pyhpc-benchmarks

So the test does not only mesure the performance of Python itself, but also the performance of the lib2to3 module which can change depending on the Python version. ... Files are called .py.txt instead of .py to not run PEP 8 checks on them, and more generally to not modify them. Async workload benchmark, which calls asyncio.gather() on a tree (6 levels deep, 6 branches per level) with the leaf nodes simulating some [potentially] async work (depending on the benchmark variant).

To collect Linux perf sampling profile data for a benchmarking run, run the _benchmark action and check the perf checkbox. The results will be available as "artifacts" on the run page after the run -- they are not committed directly to the repository. The python -m bench_runner profiling_plot command can be used to turn the raw perf results into tables and graphs.

> python3 bench.py Compress using BZ2 algorithm: [========================================] 100.0% 0:00:15 Compress using LZMA algorithm: [========================================] 100.0% 0:00:16 Calculate Pi using Wallis product: ...

You can use it to measure speed of various Python versions, compilers/interpreters or to measure speed of various hosting providers. git clone https://github.com/vprelovac/python-speed.git cd python-speed python3 bench.py

Note that all the releases that are available here: https://github.com/OWASP/BenchmarkPython/releases, are historical. The latest release is always available live by simply cloning or pulling the head of this repository (i.e., git pull). ... runRemoteAccessibleBenchmark.sh - like the above but allows port 8443 to be accessible outside the machine the Python Benchmark is running on.

Performance benchmarks of Python, Numpy, etc. vs. other languages such as Matlab, Julia, Fortran. - scivision/python-performance

A little Python benchmarking tool.

To run a benchmark use the pyperf timeit command (result written into bench.json): $ python3 -m pyperf timeit '[1,2]*1000' -o bench.json .....................

An ongoing project for benchmarking different Python approaches - ideally one per day!

To build a wheel directly from source, you can follow these steps: git clone https://github.com/google/benchmark.git cd benchmark # create a virtual environment and activate it python3 -m venv venv --system-site-packages source venv/bin/activate # .\venv\Scripts\Activate.ps1 on Windows # upgrade ...

A pytest fixture for benchmarking code.

The focus is on real-world benchmarks, rather than synthetic benchmarks, using whole applications when possible. GitHub: https://github.com/python/performance (source code, issues)

Benchmarks for Intel Distribution for Python.