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Faster CPython Benchmark Infrastructure

πŸ”’ ▢️ START A BENCHMARK RUN

Results

Here are some recent and important revisions. πŸ‘‰ Complete list of results.

Most recent pystats on main (f9a5a3a)

linux x86_64 (linux)

date fork/ref hash/flags vs. 3.12.6: vs. 3.13.0rc2: vs. base:
2025-01-02 python/8eebe4e6d02bb4ad3f1c 8eebe4e (NOGIL) 1.114x ↓
πŸ“„πŸ“ˆ
1.148x ↓
πŸ“„πŸ“ˆ
1.225x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-01-02 python/8eebe4e6d02bb4ad3f1c 8eebe4e 1.145x ↑
πŸ“„πŸ“ˆ
1.101x ↑
πŸ“„πŸ“ˆ
2025-01-01 python/c810ed7c8e0a7464d197 c810ed7 (NOGIL) 1.106x ↓
πŸ“„πŸ“ˆ
1.137x ↓
πŸ“„πŸ“ˆ
1.201x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-01-01 python/c810ed7c8e0a7464d197 c810ed7 1.128x ↑
πŸ“„πŸ“ˆ
1.086x ↑
πŸ“„πŸ“ˆ
2024-12-31 python/c5438fdf4706a70bdd19 c5438fd (NOGIL) 1.104x ↓
πŸ“„πŸ“ˆ
1.136x ↓
πŸ“„πŸ“ˆ
1.214x ↓
πŸ“„πŸ“ˆπŸ§ 
2024-12-31 python/c5438fdf4706a70bdd19 c5438fd 1.145x ↑
πŸ“„πŸ“ˆ
1.100x ↑
πŸ“„πŸ“ˆ
2024-12-30 python/dafe7a44630aa32bb411 dafe7a4 1.139x ↑
πŸ“„πŸ“ˆ
1.096x ↑
πŸ“„πŸ“ˆ
2024-12-30 python/dafe7a44630aa32bb411 dafe7a4 (NOGIL) 1.106x ↓
πŸ“„πŸ“ˆ
1.139x ↓
πŸ“„πŸ“ˆ
1.213x ↓
πŸ“„πŸ“ˆπŸ§ 

linux x86_64 (vultr)

date fork/ref hash/flags vs. 3.12.6: vs. 3.13.0rc2: vs. base:
2025-01-02 python/8eebe4e6d02bb4ad3f1c 8eebe4e (NOGIL) 1.167x ↓
πŸ“„πŸ“ˆ
1.194x ↓
πŸ“„πŸ“ˆ
1.234x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-01-02 python/8eebe4e6d02bb4ad3f1c 8eebe4e 1.095x ↑
πŸ“„πŸ“ˆ
1.056x ↑
πŸ“„πŸ“ˆ
2025-01-02 mpage/gh_115999_load_attr_ 8b96368 (NOGIL) 1.060x ↓
πŸ“„πŸ“ˆ
1.091x ↓
πŸ“„πŸ“ˆ
1.123x ↑
πŸ“„πŸ“ˆπŸ§ 
2025-01-02 mpage/gh_115999_load_attr_ 8b96368 1.098x ↑
πŸ“„πŸ“ˆ
1.060x ↑
πŸ“„πŸ“ˆ
1.003x ↑
πŸ“„πŸ“ˆπŸ§ 
2025-01-01 python/c810ed7c8e0a7464d197 c810ed7 (NOGIL) 1.166x ↓
πŸ“„πŸ“ˆ
1.193x ↓
πŸ“„πŸ“ˆ
1.237x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-01-01 python/c810ed7c8e0a7464d197 c810ed7 1.099x ↑
πŸ“„πŸ“ˆ
1.060x ↑
πŸ“„πŸ“ˆ
2025-01-01 python/bb9d955e16c5578bdbc7 bb9d955 (NOGIL) 1.165x ↓
πŸ“„πŸ“ˆ
1.192x ↓
πŸ“„πŸ“ˆ
2025-01-01 kumaraditya303/asyncio_tsafe 41a86a6 (NOGIL) 1.173x ↓
πŸ“„πŸ“ˆ
1.200x ↓
πŸ“„πŸ“ˆ
1.008x ↓
πŸ“„πŸ“ˆπŸ§ 
2024-12-31 python/c5438fdf4706a70bdd19 c5438fd (NOGIL) 1.174x ↓
πŸ“„πŸ“ˆ
1.201x ↓
πŸ“„πŸ“ˆ
1.244x ↓
πŸ“„πŸ“ˆπŸ§ 
2024-12-31 python/c5438fdf4706a70bdd19 c5438fd 1.101x ↑
πŸ“„πŸ“ˆ
1.062x ↑
πŸ“„πŸ“ˆ
2024-12-30 python/dafe7a44630aa32bb411 dafe7a4 1.091x ↑
πŸ“„πŸ“ˆ
1.052x ↑
πŸ“„πŸ“ˆ
2024-12-30 python/dafe7a44630aa32bb411 dafe7a4 (NOGIL) 1.168x ↓
πŸ“„πŸ“ˆ
1.194x ↓
πŸ“„πŸ“ˆ
1.233x ↓
πŸ“„πŸ“ˆπŸ§ 

* indicates that the exact same versions of pyperformance was not used.

Longitudinal speed improvement

Improvement of the geometric mean of key merged benchmarks, computed with pyperf compare. The results have a resolution of 0.01 (1%).

Configuration speed improvement

Documentation

Running benchmarks from the GitHub web UI

Visit the πŸ”’ benchmark action and click the "Run Workflow" button.

The available parameters are:

  • fork: The fork of CPython to benchmark. If benchmarking a pull request, this would normally be your GitHub username.
  • ref: The branch, tag or commit SHA to benchmark. If a SHA, it must be the full SHA, since finding it by a prefix is not supported.
  • machine: The machine to run on. One of linux-amd64 (default), windows-amd64, darwin-arm64 or all.
  • benchmark_base: If checked, the base of the selected branch will also be benchmarked. The base is determined by running git merge-base upstream/main $ref.
  • pystats: If checked, collect the pystats from running the benchmarks.

To watch the progress of the benchmark, select it from the πŸ”’ benchmark action page. It may be canceled from there as well. To show only your benchmark workflows, select your GitHub ID from the "Actor" dropdown.

When the benchmarking is complete, the results are published to this repository and will appear in the complete table. Each set of benchmarks will have:

  • The raw .json results from pyperformance.
  • Comparisons against important reference releases, as well as the merge base of the branch if benchmark_base was selected. These include
    • A markdown table produced by pyperf compare_to.
    • A set of "violin" plots showing the distribution of results for each benchmark.

The most convenient way to get results locally is to clone this repo and git pull from it.

Running benchmarks from the GitHub CLI

To automate benchmarking runs, it may be more convenient to use the GitHub CLI. Once you have gh installed and configured, you can run benchmarks by cloning this repository and then from inside it:

gh workflow run benchmark.yml -f fork=me -f ref=my_branch

Any of the parameters described above are available at the commandline using the -f key=value syntax.

Collecting Linux perf profiling data

To collect Linux perf sampling profile data for a benchmarking run, run the _benchmark action and check the perf checkbox. Follow this by a run of the _generate action to regenerate the plots.

License

This repo is licensed under the BSD 3-Clause License, as found in the LICENSE file.

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Benchmark results for free-threaded builds of Python

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