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pytorch GitHub Actions Analytics

GitHub Activity Summary

In November 2025, the PyTorch GitHub organization showcased a strikingly high overall success rate of 79.03%, with 14,359 successful runs out of 18,168 total runs. This remarkable performance not only underscores the reliability of their CI/CD processes but also highlights the project's commitment to high-quality development practices.

A closer look at the commit behavior reveals a notable surge in productivity, particularly on November 22, where successful action runs peaked at 1,025. This spike likely correlates with recent feature releases, reflecting a collaborative and dynamic development culture within the team.

The individual contributor patterns further affirm this collaborative spirit. Key contributors like clee2000 led the charge with 4,007 runs and a commendable success rate of 79.84%. Other contributors, such as suo and janeyx99, excelled even further with success rates of 86.07% and 87.44%, respectively. These metrics underscore a strong core team dedicated to maintaining high standards in their contributions.

However, the analysis also reveals challenges and opportunities for improvement. The presence of 3,698 failed runs indicates potential bottlenecks, particularly within the "trunk" workflow, which only achieved a success rate of 24.14%. Addressing these issues could enhance overall project efficiency.

In conclusion, PyTorch's November 2025 GitHub analytics highlight an active and engaged community, with impressive repository insights and a strong commitment to quality. These commit analysis metrics can serve as a valuable resource for developers looking to engage with or leverage PyTorch in their engineering endeavors.

GitHub Actions Key Performance Indicators
Average Execution Time (s)

1,457.58

8662.69
-0.83%
Success Rate

61.72

72.35
-0.15%
Total Runs

69,948.60

1980364
-0.96%
Successful Runs

43,185.60

1432791
-0.97%
Failed Runs

19,304.60

311480
-0.94%
Total Run Time (hrs)

28,328.54

4765355.3
-0.99%
GitHub Actions Runs Over Time
Execution Duration Over Time
Success vs Failure

Success

69%

Failure

31%
Workflow Time Distribution

pull

12%

Run Regression Tests

6%

trunk

5%

Lint

3%

Run 1xH100 Tests

3%

Others

70%
GitHub Actions by Workflow
WorkflowTotal RunsSuccessful RunsFailed RunsSuccess Rate (%)Average Duration (s)Min Duration (s)Max Duration (s)
Unit-tests on Macos CPU3030864048640186410
FFmpeg Binaries404086402.258640286403
Install tests31027075252.87086402
inductor-A100-perf-nightly98088.8928750.11238336928
inductor-perf-nightly-aarch6487187.527988.621746130557

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Workflow Duration
Workflow Success Rates
GitHub Actions by Author
AuthorTotal RunsSuccessful RunsFailed RunsSuccess Rate (%)Average Duration (s)
pytorchmergebot8852524867859.292344.57
facebook-github-bot55943501170762.582421.79
clee20004374412124094.22118.36
samanklesaria3974984293324.76719.71
GregoryComer2709759186728.021390.08

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GitHub Actions by Repository
RepositoryTotal RunsSuccessful RunsFailed RunsSuccess Rate (%)Average Duration (s)
p
pytorch
1989811412252557.351454.78
e
executorch
122096280552151.441852.63
ti
test-infra
110141045550994.92389.3
a
ao
96266216294264.581743.88
a
audio
46891241339126.47811.78

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