Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-10 21:06 UTC

meta-pytorch / torchx

TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.

PythonCustom license★ 426 stars⑂ 156 forkssince May 2021View on GitHub ↗
KindCommand-line toolPluginhow this is determined
#pytorch#machine-learning#kubernetes#slurm#distributed-training#pipelines#components#deep-learning#python#aws-batch#ray#airflow

meta-pytorch/torchx holds a health index of 92 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (92/100) and lowest on Security (63/100). It was last updated today. 3 contributors account for most of its recent work.

92
overall / 100
Excellent

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.

92
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 78 is calibrated to 92 on the published index scale (record calibration 2026-08-02).

Ownership

Meta PyTorchOrganization · verified domain
1,420 followers60 public repossince Jun 2022

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPItorchxpoints to another repo — not scored0.7.0249,26617785 days agopytorchmachine-learning

Metrics by category

Vitality

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

78Good · 21% of overall

Development activity

95Exceptional
How it's scored
36/36Push recency — last push 0 days ago
31.2/36Commit cadence — 45/52 weeks with commits
18/18Commit volume — 239 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year239
human_commit_share0.77
days_since_last_push0
active_weeks_last_year45

Release discipline

52Moderate
How it's scored
27/27Ships releases — 15 releases published
0/36Release recency — latest release 785 days ago
19.8/27Release cadence — a release every ~111.3 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count15
latest_release_tagv0.7.0
releases_from_tagsno
days_since_latest_release785
mean_days_between_releases111.3
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

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

76Good · 17% of overall

Popularity & adoption

67Good
How it's scored
42.6/60Stars — 426 stars
18.3/25Forks — 156 forks
6.2/15Watchers — 14 watchers
Inputs used
forks156
stars426
watchers14
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

86Excellent
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateyes

Sustainability & Governance

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

78Good · 23% of overall

Maintainer resilience (bus factor)

76Good
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
16.6/22.5Commit distribution — top contributor authored 26% of commits
13.5/13.5Contributor breadth — 98 contributors
10/10OpenSSF Scorecard: Contributors — project has 21 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled98
top_contributor_share0.264

Issue & PR responsiveness

65Good
How it's scored
28.3/42Issue resolution — 67% of issues closed
13.1/30PR acceptance — 530/1,211 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs530
open_issues67
closed_issues138
prs_merged_7d1
prs_decided_7d2
prs_merged_30d57
prs_decided_30d60
issue_closed_ratio0.673
closed_unmerged_prs681
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

94Exceptional
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
22.7/25Owner reach — 1,420 followers of meta-pytorch
21.5/25Track record — 60 public repos, account ~4 yr old
Inputs used
followers1,420
owner_typeOrganization
is_verifiedyes
owner_loginmeta-pytorch
public_repos60
account_age_days1,554

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 6 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff], [tool.black])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://pytorch.org/torchx
10/10Repository description
10/10Topics — 12 topics
0/10Wiki
Inputs used
topicspytorch, machine-learning, kubernetes, slurm, distributed-training, pipelines, components, deep-learning, python, aws-batch, ray, airflow
has_wikino
homepagehttps://pytorch.org/torchx
docs_sitehttps://pytorch.org/torchx
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

63Moderate · 16% of overall

Security posture

60Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 21 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0.8/7.5Vulnerabilities — 9 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

73Good
How it's scored
14/35Direct dependencies free of known advisories — 1 affected: urllib3 1.26.20 (high 7.5)
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
33.7/40No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 449 days ago
Inputs used
sourceosv
advisories10
affected_packages1
assessed_packages17
unassessed_packages0
affected_by_severityhigh 1
direct_affected_packages1
Matched the pypi:torchx@0.7.0 runtime dependency closure — what installing the published package pulls in — 17 packages. 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.

81Excellent · 4% of overall

Agent context & guidance

100Exceptional
How it's scored
45/45Agent instructions — .claude/CLAUDE.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://pytorch.org/llms.txt)
40/40Legible commit history — 77 of 77 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://pytorch.org/llms.txt
legible_history_share1
agent_instruction_files.claude/CLAUDE.md
agent_instruction_max_bytes1,532

Verify loop (build / test / typecheck)

69Good
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff], [tool.black])
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 22 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.22

Code legibility for models

54Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
54.5/55Manageable file sizes — 2/217 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes75,743
source_files_sampled217
oversized_source_files2

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples
Inputs used
example_dirsexamples
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

426GitHub stars
98contributors
239commits, last 12 months
0days since last push
15releases
3bus factor
67open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'torchx' points at a different repository (https://github.com/pytorch/torchx); excluded from ecosystem scoring

More detail

Star and fork history 0 ★ / 156 ⇿
0Stars
156Forks
15Releases

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.

0408012016015332021-062023-122026-07
Major 0Minor 7Patch 2

Each point covers 5 days.

OpenSSF Scorecard 6.0 / 10
6.0aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-10 21:06 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 21 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
1Vulnerabilities9 existing vulnerabilities detected
Direct dependencies 7
RegistryPackageVersion constraintManifest
PyPIdocstring-parser>=0.8.1pyproject.toml
PyPIpyyaml—pyproject.toml
PyPIdocker—pyproject.toml
PyPIfilelock—pyproject.toml
PyPIfsspec>=2023.10.0pyproject.toml
PyPItabulate—pyproject.toml
PyPItyping-extensions—pyproject.toml
All dependencies 164

Full resolved dependency set from the GitHub dependency graph: 7 direct and 157 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIdocker7.1.0direct
PyPIdocstring-parser0.17.0direct
PyPIfilelock3.20.3direct
PyPIfsspec2026.2.0direct
PyPIpyyaml6.0.3direct
PyPItabulate0.9.0direct
PyPItyping-extensions4.15.0direct
PyPIabsl-py2.3.1indirect
PyPIaiobotocore3.1.2indirect
PyPIaiohappyeyeballs2.6.1indirect
PyPIaiohttp3.14.3indirect
PyPIaioitertools0.13.0indirect
PyPIaiosignal1.4.0indirect
PyPIantlr4-python3-runtime4.9.3indirect
PyPIasttokens3.0.1indirect
PyPIasync-timeout5.0.1indirect
PyPIattrs23.2.0indirect
PyPIax-platform0.2.3indirect
PyPIblack25.11.0indirect
PyPIbotocore1.42.42indirect
PyPIbotorch0.6.0indirect
PyPIcaptum0.8.0indirect
PyPIcertifi2026.1.4indirect
PyPIcharset-normalizer3.4.4indirect
PyPIclick8.1.8indirect
PyPIcolorama0.4.6indirect
PyPIcontourpy1.3.2indirect
PyPIcontourpy1.3.3indirect
PyPIcoverage7.13.1indirect
PyPIcuda-bindings13.3.1indirect
PyPIcuda-pathfinder1.5.6indirect
PyPIcuda-toolkit13.0.3.0indirect
PyPIcycler0.12.1indirect
PyPIdataclasses-json0.5.7indirect
PyPIdecorator5.2.1indirect
PyPIexceptiongroup1.3.1indirect
PyPIexecuting2.2.1indirect
PyPIfonttools4.61.1indirect
PyPIfrozenlist1.8.0indirect
PyPIgoogle-auth2.47.0indirect
PyPIgoogle-auth-oauthlib1.0.0indirect
PyPIgpytorch1.15.1indirect
PyPIgreenlet3.3.1indirect
PyPIgrpcio1.76.0indirect
PyPIhydra-core1.3.2indirect
PyPIidna3.18indirect
PyPIiniconfig2.3.0indirect
PyPIipython8.38.0indirect
PyPIipython9.9.0indirect
PyPIipython-pygments-lexers1.1.1indirect
PyPIjaxtyping0.3.6indirect
PyPIjedi0.19.2indirect
PyPIjinja2—indirect
PyPIjinja23.1.6indirect
PyPIjmespath1.1.0indirect
PyPIjoblib1.5.3indirect
PyPIkiwisolver1.4.9indirect
PyPIkubernetes25.3.0indirect
PyPIlibcst1.8.6indirect
PyPIlightning-utilities0.15.2indirect
PyPIlinear-operator0.6indirect
PyPIlintrunner0.13.0indirect
PyPIlintrunner-adapters0.13.0indirect
PyPImarkdown3.10.1indirect
PyPImarkupsafe3.0.3indirect
PyPImarshmallow3.26.2indirect
PyPImarshmallow-enum1.5.1indirect
PyPImatplotlib3.10.8indirect
PyPImatplotlib-inline0.2.1indirect
PyPImpmath1.3.0indirect
PyPImultidict6.7.0indirect
PyPImypy-extensions1.1.0indirect
PyPInarwhals2.15.0indirect
PyPInetworkx3.4.2indirect
PyPInetworkx3.6.1indirect
PyPInumpy1.26.4indirect
PyPInvidia-cublas13.1.1.3indirect
PyPInvidia-cuda-cupti13.0.85indirect
PyPInvidia-cuda-nvrtc13.0.88indirect
PyPInvidia-cuda-runtime13.0.96indirect
PyPInvidia-cudnn-cu139.20.0.48indirect
PyPInvidia-cufft12.0.0.61indirect
PyPInvidia-cufile1.15.1.6indirect
PyPInvidia-curand10.4.0.35indirect
PyPInvidia-cusolver12.0.4.66indirect
PyPInvidia-cusparse12.6.3.3indirect
PyPInvidia-cusparselt-cu130.8.1indirect
PyPInvidia-nccl-cu132.29.7indirect
PyPInvidia-nvjitlink13.3.33indirect
PyPInvidia-nvshmem-cu133.4.5indirect
PyPInvidia-nvtx13.0.85indirect
PyPIoauthlib3.3.1indirect
PyPIomegaconf2.2.3indirect
PyPIpackaging25.0indirect
PyPIpandas2.3.3indirect
PyPIparso0.8.5indirect
PyPIpexpect4.9.0indirect
PyPIpillow12.3.0indirect
PyPIpip26.1.2indirect
PyPIplotly6.5.2indirect
PyPIpluggy1.6.0indirect
PyPIprompt-toolkit3.0.52indirect
PyPIpropcache0.4.1indirect
PyPIprotobuf5.29.6indirect
PyPIpsutil7.2.1indirect
PyPIptyprocess0.7.0indirect
PyPIpure-eval0.2.3indirect
PyPIpyasn10.6.4indirect
PyPIpyasn1-modules0.4.2indirect
PyPIpygments2.19.2indirect
PyPIpyparsing3.3.2indirect
PyPIpyre-check0.9.25indirect
PyPIpyre-extensions0.0.32indirect
PyPIpytest9.0.3indirect
PyPIpytest-cov7.0.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpytorch-lightning2.5.0indirect
PyPIpytorch-sphinx-theme—indirect
PyPIpytz2025.2indirect
PyPIpywin32311indirect
PyPIpyyaml-ft8.0.0indirect
PyPIrequests2.34.2indirect
PyPIrequests-oauthlib2.0.0indirect
PyPIrsa4.9.1indirect
PyPIruff-api0.2.1indirect
PyPIs3fs2026.2.0indirect
PyPIscikit-learn1.7.2indirect
PyPIscikit-learn1.8.0indirect
PyPIscipy1.15.3indirect
PyPIscipy1.17.0indirect
PyPIsetuptools80.10.1indirect
PyPIsix1.17.0indirect
PyPIsphinx—indirect
PyPIsphinxcontrib-katex—indirect
PyPIsqlalchemy2.0.46indirect
PyPIstack-data0.6.3indirect
PyPIstdlibs2025.10.28indirect
PyPIsympy1.14.0indirect
PyPItensorboard2.14.0indirect
PyPItensorboard-data-server0.7.2indirect
PyPItestslide2.7.0indirect
PyPIthreadpoolctl3.6.0indirect
PyPItomli2.4.0indirect
PyPItomli-w1.2.0indirect
PyPItorch2.13.0indirect
PyPItorchmetrics1.6.3indirect
PyPItorchtext0.18.0indirect
PyPItorchvision0.28.0indirect
PyPItqdm4.67.1indirect
PyPItraitlets5.14.3indirect
PyPItriton3.7.1indirect
PyPItypeguard4.4.4indirect
PyPItyping-inspect0.9.0indirect
PyPItzdata2025.3indirect
PyPIufmt2.9.1indirect
PyPIurllib32.7.0indirect
PyPIusort1.1.0indirect
PyPIwadler-lindig0.1.7indirect
PyPIwcwidth0.3.3indirect
PyPIwebsocket-client1.9.0indirect
PyPIwerkzeug3.1.6indirect
PyPIwheel0.46.3indirect
PyPIwrapt1.17.3indirect
PyPIyarl1.22.0indirect
Dependency advisories 1

Installing pypi:torchx@0.7.0 pulls in 17 packages, direct and transitive: 1 carry known advisories, of which 1 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
urllib31.26.20directhigh102.7.0

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.

Related records

Inspected repositories sharing catalogue tags or ecosystems with meta-pytorch/torchx. Read them side by side →

99ray-project/rayRay is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.Exceptional100apache/airflowApache Airflow - A platform to programmatically author, schedule, and monitor workflowsExceptional100huggingface/transformers🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. Exceptional99argoproj/argo-workflowsWorkflow Engine for KubernetesExceptional99ultralytics/ultralyticsUltralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object trackingExceptional98pytorch/pytorchTensors and Dynamic neural networks in Python with strong GPU accelerationExceptional

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 v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.