Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-04 22:23 UTC

pytorch / pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Python · C++Custom license★ 102,182 stars⑂ 28,709 forkssince Aug 2016View on GitHub ↗
KindPluginLibraryCommand-line toolMobile applicationhow this is determined

pytorch/pytorch holds a health index of 98 out of 100, placing it in the Exceptional band. It scores highest on Vitality (97/100) and lowest on Security (64/100). It was last updated today. 21 contributors account for most of its recent work.

98
overall / 100
Exceptional

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

98
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 87 is calibrated to 98 on the published index scale (record calibration 2026-08-02).

Ownership

pytorchOrganization
13,462 followers70 public repossince Aug 2016

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPItorch2.13.095,610,8644927 days agopytorchmachine-learning

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

97Exceptional · 21% of overall

Development activity

100Exceptional
How it's scored
36/36Push recencylast push 0 days ago
36/36Commit cadence52/52 weeks with commits
18/18Commit volume17,228 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year17,228
human_commit_share1
days_since_last_push0
active_weeks_last_year52
How it's scored
27/27Ships releases68 releases published
36/36Release recencylatest release 27 days ago
19.8/27Release cadencea release every ~49 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count68
latest_release_tagv2.13.0
releases_from_tagsno
days_since_latest_release27
mean_days_between_releases49

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

93Exceptional · 17% of overall

Popularity & adoption

100Exceptional
How it's scored
60/60Stars102,182 stars
25/25Forks28,709 forks
15/15Watchers1,807 watchers
Inputs used
forks28,709
stars102,182
watchers1,807
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services
has_pull_request_templateno
How it's scored
80/80Monthly downloads95,610,864 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagestorch
dependents
ecosystemspypi
total_downloads
monthly_downloads95,610,864
unverified_packages_excluded
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

84Excellent · 23% of overall
How it's scored
54/54Bus factor21 contributor(s) cover half of all commits
20.4/22.5Commit distributiontop contributor authored 9% of commits
13.5/13.5Contributor breadth100 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor21
contributors_sampled100
top_contributor_share0.094
How it's scored
31.2/42Issue resolution74% of issues closed
1.5/30PR acceptance6,574/128,305 decided PRs merged
0/13Newcomer PR acceptance0/12 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs6,574
open_issues15,438
closed_issues44,736
prs_merged_7d0
prs_decided_7d43
prs_merged_30d0
prs_decided_30d45
issue_closed_ratio0.743
closed_unmerged_prs121,731
first_time_authors_30d9
first_time_prs_merged_30d0
first_time_prs_decided_30d12
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
25/25Owner reach13,462 followers of pytorch
25/25Track record70 public repos, account ~9 yr old
Inputs used
followers13,462
owner_typeOrganization
is_verified
owner_loginpytorch
public_repos70
account_age_days3,643
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 27 days ago
20/20Version history49 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagestorch
ecosystemspypi
any_deprecatedno
min_days_since_publish27

Engineering Quality

Are baseline engineering and documentation practices in place?

93Exceptional · 19% of overall
How it's scored
24/24CI workflows146 workflow(s)
24/24Tests present
16/16Linter config.flake8
0/9.6Pre-commit hooks
6.4/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://pytorch.org
10/10Repository description
10/10Topics8 topics
10/10Wiki
Inputs used
topicsneural-network, autograd, gpu, numpy, deep-learning, tensor, python, machine-learning
has_wikiyes
homepagehttps://pytorch.org
docs_sitehttps://pytorch.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

64Moderate · 16% of overall
How it's scored
30/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfiles
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifests.github/requirements-gha-cache.txt, android/build.gradle, docs/requirements.txt, pyproject.toml, requirements-build.txt, requirements.txt, setup.py
has_codeql_workflowno
has_security_policyyes
has_dependabot_configyes

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories20
affected_packages6
assessed_packages100
unassessed_packages39
affected_by_severityhigh 1, moderate 5
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 100 resolved dependencies against OSV. 39 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

91Excellent · 4% of overall
How it's scored
45/45Agent instructions.github/copilot-instructions.md, AGENTS.md, CLAUDE.md, docs/source/elastic/agent.md, torch/_dynamo/CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history100 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share1
agent_instruction_files.github/copilot-instructions.md, AGENTS.md, CLAUDE.md, docs/source/elastic/agent.md, torch/_dynamo/CLAUDE.md
agent_instruction_max_bytes14,189
How it's scored
18/18One-command bootstrap.ci/magma-rocm/Makefile, .ci/magma/Makefile, Makefile, benchmarks/dynamo/Makefile, docs/Makefile, docs/cpp/Makefile, functorch/docs/Makefile
22/22Automated tests
11/11Lint / format config.flake8
11/11Static type checkingmypy.ini, torch/py.typed
10/10Reproducible environmentdevcontainer, Dockerfile
10/10Demonstrated agent practice6 of the last 100 commits agent-authored or agent-credited
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_files.ci/magma-rocm/Makefile, .ci/magma/Makefile, Makefile, benchmarks/dynamo/Makefile, docs/Makefile, docs/cpp/Makefile, functorch/docs/Makefile
has_devcontaineryes
has_linter_configyes
typecheck_configsmypy.ini, torch/py.typed
agent_commit_share0.06
toolchain_manifestsandroid/build.gradle, android/pytorch_android/build.gradle, android/pytorch_android/host/build.gradle, android/pytorch_android_torchvision/build.gradle
dependency_bot_commit_share0
How it's scored
27/45Type-checkable codePython with type-check config (mypy.ini, torch/py.typed)
52.1/55Manageable file sizes511/9,655 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes2,171,256
source_files_sampled9,655
oversized_source_files511
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexample, examples, notebooks
Inputs used
example_dirsexample, examples, notebooks
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

102,182GitHub stars
100contributors
17,228commits, last 12 months
0days since last push
68releases
21bus factor
15,438open issues
Maven, PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 30 authors (cap 12)
  • OpenSSF Scorecard did not return a usable result (2026/08/04 22:21:34 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 28,709 ⇿
0Stars
28,709Forks
2Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

27,50027,75028,00028,25028,50028,75028,709542026-062026-072026-08
Major 0Minor 1Patch 1
All dependencies 139

Full resolved dependency set from the GitHub dependency graph: 0 direct and 139 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaiohttp3.14.1indirect
PyPIboto31.35.42indirect
PyPIbreathe4.36.0indirect
PyPIbs40.0.1indirect
PyPIbuildindirect
PyPIbuild1.3.0indirect
PyPIclickindirect
PyPIcmakeindirect
PyPIcmake3.31.6indirect
PyPIcoverxygen1.8.1indirect
PyPIdataclasses-json0.6.7indirect
PyPIdill0.3.7indirect
PyPIdocker7.1.0indirect
PyPIdocutils0.20indirect
PyPIexhale0.3.7indirect
PyPIexpecttestindirect
PyPIexpecttest0.3.0indirect
PyPIfbscribelogger0.1.7indirect
PyPIfilelockindirect
PyPIfilelock3.20.3indirect
PyPIflatbuffers24.12.23indirect
PyPIfsspecindirect
PyPIghstack0.8.0indirect
PyPIgitpython3.1.54indirect
PyPIhypothesisindirect
PyPIhypothesis6.56.4indirect
PyPIipython8.12.0indirect
PyPIjax0.9.0indirect
PyPIjaxlib0.9.0indirect
PyPIjaxtyping0.3.2indirect
PyPIjinja2indirect
PyPIjinja23.1.6indirect
PyPIjunitparser2.1.1indirect
PyPIlark0.12.0indirect
PyPIlibtpu0.0.34indirect
PyPIliger-kernelindirect
PyPIlintrunnerindirect
PyPIlintrunner0.12.7indirect
PyPIlintrunner0.13.0indirect
PyPIlxml6.1.0indirect
PyPImatplotlibindirect
PyPImatplotlib3.6.3indirect
PyPImkl-include2024.2.0indirect
PyPImkl-static2024.2.0indirect
PyPImypy1.16.0indirect
PyPImyst-nb1.3.0indirect
PyPImyst-parser4.0.1indirect
PyPInetworkxindirect
PyPInetworkx2.8.8indirect
PyPIninjaindirect
PyPIninja1.10.0.post1indirect
PyPIninja1.13.0indirect
PyPInumpyindirect
PyPInumpy2.3.4indirect
PyPInvidia-cutlass-dsl4.1.0.dev0indirect
PyPInvidia-ml-py11.525.84indirect
PyPIonnx1.21.0indirect
PyPIonnx-ir0.1.16indirect
PyPIonnxscript0.6.2indirect
PyPIopt-einsumindirect
PyPIopt-einsum3.3indirect
PyPIoptreeindirect
PyPIoptree0.17.0indirect
PyPIpackagingindirect
PyPIpackaging24.2indirect
PyPIpandasindirect
PyPIpandas2.3.3indirect
PyPIparameterized0.8.1indirect
PyPIpillow12.3.0indirect
PyPIpipindirect
PyPIpip26.1.2indirect
PyPIprotobuf6.33.5indirect
PyPIpsutilindirect
PyPIpulp2.9.0indirect
PyPIpwlf2.2.1indirect
PyPIpygithubindirect
PyPIpygithub2.3.0indirect
PyPIpygments2.20.0indirect
PyPIpyre-extensions0.0.32indirect
PyPIpytest7.3.2indirect
PyPIpytest9.0.3indirect
PyPIpytest-cpp2.3.0indirect
PyPIpytest-flakefinder1.1.0indirect
PyPIpytest-rerunfailuresindirect
PyPIpytest-subtests0.13.1indirect
PyPIpytest-xdist3.3.1indirect
PyPIpython-etcd0.4.5indirect
PyPIpytorch-sphinx-theme20.4.11indirect
PyPIpywavelets1.7.0indirect
PyPIpyyamlindirect
PyPIpyyaml6.0.2indirect
PyPIpyyaml6.0.3indirect
PyPIpyzstdindirect
PyPIquack-kernelsindirect
PyPIredisindirect
PyPIrequestsindirect
PyPIrequests2.33.0indirect
PyPIrich14.1.0indirect
PyPIscikit-build0.18.1indirect
PyPIscikit-build-coreindirect
PyPIscikit-build-core1.0.0indirect
PyPIscikit-image0.22.0indirect
PyPIscikit-learnindirect
PyPIscipy1.16.2indirect
PyPIscons4.5.2indirect
PyPIsetuptoolsindirect
PyPIsetuptools78.1.1indirect
PyPIsetuptools80.10.2indirect
PyPIsetuptools83.0.0indirect
PyPIsetuptools-git-versioning2.1.0indirect
PyPIsixindirect
PyPIsoxr0.5.0indirect
PyPIsphinx7.2.6indirect
PyPIsphinx-copybutton0.5.0indirect
PyPIsphinx-design0.6.1indirect
PyPIsphinx-reredirects0.1.4indirect
PyPIsphinx-sitemap2.6.0indirect
PyPIsphinxcontrib-katex0.9.11indirect
PyPIsphinxcontrib-mermaid1.0.0indirect
PyPIsphinxext-opengraph0.9.1indirect
PyPIspinindirect
PyPIspin0.17indirect
PyPIsympyindirect
PyPIsympy1.13.3indirect
PyPItabulate0.9.0indirect
PyPItensorboard2.18.0indirect
PyPItlparse0.4.0indirect
PyPItorchindirect
PyPItpu-info0.7.1indirect
PyPItqdmindirect
PyPItransformers5.13.0indirect
PyPItyping-extensionsindirect
PyPItyping-extensions4.15.0indirect
PyPIunittest-xml-reportingindirect
PyPIuvindirect
PyPIuv0.11.15indirect
PyPIwheelindirect
PyPIxdoctest1.3.0indirect
PyPIz3-solver4.15.1.0indirect
Dependency advisories 6

This repository publishes no package the index resolves, so its own dependency graph was assessed — 100 packages, which also include development and test pins that never ship: 6 carry known advisories, of which 0 are direct. 39 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
gitpython3.1.54indirecthigh43.1.57
aiohttp3.14.1indirectmoderate63.14.3
onnx1.21.0indirectmoderate41.22.0
pytest7.3.2indirectmoderate29.0.3
setuptools78.1.1indirectmoderate283.0.0
setuptools80.10.2indirectmoderate283.0.0

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.