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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 (cf4c4ec)

linux x86_64 (linux)

date fork/ref hash/flags vs. 3.12.6: vs. 3.13.0rc2: vs. base:
2025-02-03 python/bb5c6875d6e84bf2b4e1 bb5c687 1.104x ↑
πŸ“„πŸ“ˆ
1.059x ↑
πŸ“„πŸ“ˆ
2025-02-03 python/bb5c6875d6e84bf2b4e1 bb5c687 (NOGIL) 1.040x ↓
πŸ“„πŸ“ˆ
1.073x ↓
πŸ“„πŸ“ˆ
1.125x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-02-02 python/ae4788809d674f8e27fa ae47888 1.101x ↑
πŸ“„πŸ“ˆ
1.057x ↑
πŸ“„πŸ“ˆ
2025-02-02 python/ae4788809d674f8e27fa ae47888 (NOGIL) 1.037x ↓
πŸ“„πŸ“ˆ
1.072x ↓
πŸ“„πŸ“ˆ
1.123x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-02-02 python/a29a9c0f3890fec843b7 a29a9c0 1.096x ↑
πŸ“„πŸ“ˆ
1.054x ↑
πŸ“„πŸ“ˆ
2025-02-02 python/a29a9c0f3890fec843b7 a29a9c0 (NOGIL) 1.034x ↓
πŸ“„πŸ“ˆ
1.070x ↓
πŸ“„πŸ“ˆ
1.112x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-02-01 python/cf4c4ecc26c7e3b89f2e cf4c4ec (NOGIL) 1.056x ↓
πŸ“„πŸ“ˆ
1.091x ↓
πŸ“„πŸ“ˆ
1.133x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-02-01 python/cf4c4ecc26c7e3b89f2e cf4c4ec 1.096x ↑
πŸ“„πŸ“ˆ
1.055x ↑
πŸ“„πŸ“ˆ
2025-01-31 python/c3ae5c9e4ad121f8ba60 c3ae5c9 (NOGIL) 1.044x ↓
πŸ“„πŸ“ˆ
1.078x ↓
πŸ“„πŸ“ˆ
1.011x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-01-31 python/31c82c28f927b7e55c7d 31c82c2 (NOGIL) 1.032x ↓
πŸ“„πŸ“ˆ
1.066x ↓
πŸ“„πŸ“ˆ
2025-01-31 python/d89a5f6a6e65511a5f6e d89a5f6 (NOGIL) 1.035x ↓
πŸ“„πŸ“ˆ
1.072x ↓
πŸ“„πŸ“ˆ
1.100x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-01-31 python/d89a5f6a6e65511a5f6e d89a5f6 1.074x ↑
πŸ“„πŸ“ˆ
1.035x ↑
πŸ“„πŸ“ˆ

linux x86_64 (vultr)

date fork/ref hash/flags vs. 3.12.6: vs. 3.13.0rc2: vs. base:
2025-02-03 python/bb5c6875d6e84bf2b4e1 bb5c687 1.100x ↑
πŸ“„πŸ“ˆ
1.061x ↑
πŸ“„πŸ“ˆ
2025-02-03 python/bb5c6875d6e84bf2b4e1 bb5c687 (NOGIL) 1.043x ↓
πŸ“„πŸ“ˆ
1.074x ↓
πŸ“„πŸ“ˆ
1.130x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-02-02 corona10/gh_129533 d36c349 (NOGIL) 1.021x ↓
πŸ“„πŸ“ˆ
1.053x ↓
πŸ“„πŸ“ˆ
1.003x ↑
πŸ“„πŸ“ˆπŸ§ 
2025-02-02 python/ae4788809d674f8e27fa ae47888 1.100x ↑
πŸ“„πŸ“ˆ
1.061x ↑
πŸ“„πŸ“ˆ
2025-02-02 python/ae4788809d674f8e27fa ae47888 (NOGIL) 1.027x ↓
πŸ“„πŸ“ˆ
1.059x ↓
πŸ“„πŸ“ˆ
1.117x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-02-02 python/a29a9c0f3890fec843b7 a29a9c0 1.101x ↑
πŸ“„πŸ“ˆ
1.062x ↑
πŸ“„πŸ“ˆ
2025-02-02 python/a29a9c0f3890fec843b7 a29a9c0 (NOGIL) 1.024x ↓
πŸ“„πŸ“ˆ
1.055x ↓
πŸ“„πŸ“ˆ
1.115x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-02-01 python/cf4c4ecc26c7e3b89f2e cf4c4ec (NOGIL) 1.024x ↓
πŸ“„πŸ“ˆ
1.056x ↓
πŸ“„πŸ“ˆ
1.117x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-02-01 python/cf4c4ecc26c7e3b89f2e cf4c4ec 1.104x ↑
πŸ“„πŸ“ˆ
1.065x ↑
πŸ“„πŸ“ˆ
2025-02-01 mpage/revert_c3ae5c9 3edc57c (NOGIL) 1.051x ↓
πŸ“„πŸ“ˆ
1.082x ↓
πŸ“„πŸ“ˆ
1.027x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-01-31 nascheme/gh_129201_gc_mark_pr abfc49a (NOGIL) 1.043x ↓
πŸ“„πŸ“ˆ
1.074x ↓
πŸ“„πŸ“ˆ
1.005x ↑
πŸ“„πŸ“ˆπŸ§ 
2025-01-31 python/54f74b80aef8b581f2b1 54f74b8 (NOGIL) 1.026x ↓
πŸ“„πŸ“ˆ
1.058x ↓
πŸ“„πŸ“ˆ
1.000x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-01-31 python/9ba281d871c4df3a3ac4 9ba281d (NOGIL) 1.025x ↓
πŸ“„πŸ“ˆ
1.057x ↓
πŸ“„πŸ“ˆ
2025-01-31 python/c3ae5c9e4ad121f8ba60 c3ae5c9 (NOGIL) 1.029x ↓
πŸ“„πŸ“ˆ
1.061x ↓
πŸ“„πŸ“ˆ
1.029x ↑
πŸ“„πŸ“ˆπŸ§ 
2025-01-31 python/31c82c28f927b7e55c7d 31c82c2 (NOGIL) 1.057x ↓
πŸ“„πŸ“ˆ
1.087x ↓
πŸ“„πŸ“ˆ
2025-01-31 python/d89a5f6a6e65511a5f6e d89a5f6 (NOGIL) 1.027x ↓
πŸ“„πŸ“ˆ
1.059x ↓
πŸ“„πŸ“ˆ
1.106x ↓
πŸ“„πŸ“ˆπŸ§ 
2025-01-31 python/d89a5f6a6e65511a5f6e d89a5f6 1.086x ↑
πŸ“„πŸ“ˆ
1.047x ↑
πŸ“„πŸ“ˆ

* 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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