Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-30 23:45 UTC

meta-pytorch / torchrec

Pytorch domain library for recommendation systems

Python · Jupyter NotebookBSD-3-Clause★ 2,607 stars⑂ 699 forkssince Jul 2021View on GitHub ↗

meta-pytorch/torchrec holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Vitality (100/100) and lowest on Security (42/100). It was last updated today. 10 contributors account for most of its recent work.

94
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.

94
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 80 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

Meta PyTorchOrganization · verified domain
1,433 followers61 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
PyPItorchrec1.9.110,912280 days agopytorchrecommendation-systemsshardingdistributed-training

Metrics by category

Vitality

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

100Exceptional · 21% of overall

Development activity

100Exceptional
How it's scored
36/36Push recency — last push 0 days ago
36/36Commit cadence — 52/52 weeks with commits
18/18Commit volume — 1,158 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year1,158
human_commit_share1
days_since_last_push0
active_weeks_last_year52

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 38 releases published
36/36Release recency — latest release 19 days ago
27/27Release cadence — a release every ~40.3 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count38
latest_release_tagv1.9.0-rc1
releases_from_tagsno
days_since_latest_release19
mean_days_between_releases40.3

Community & Adoption

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

82Excellent · 17% of overall
How it's scored
55.4/60Stars — 2,607 stars
23.7/25Forks — 699 forks
8.4/15Watchers — 33 watchers
Inputs used
forks699
stars2,607
watchers33
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (BSD-3-Clause)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateno
How it's scored
53.8/80Monthly downloads — 10,912 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagestorchrec
dependents—
ecosystemspypi
total_downloads—
monthly_downloads10,912
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?

81Excellent · 23% of overall
How it's scored
54/54Bus factor — 10 contributor(s) cover half of all commits
19.3/22.5Commit distribution — top contributor authored 14% of commits
13.5/13.5Contributor breadth — 100 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor10
contributors_sampled100
top_contributor_share0.141
How it's scored
29.6/42Issue resolution — 70% of issues closed
0.1/30PR acceptance — 10/4,345 decided PRs merged
0/13Newcomer PR acceptance — 0/33 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs10
open_issues79
closed_issues188
prs_merged_7d0
prs_decided_7d35
prs_merged_30d0
prs_decided_30d60
issue_closed_ratio0.704
closed_unmerged_prs4,335
first_time_authors_30d12
first_time_prs_merged_30d0
first_time_prs_decided_30d33
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
22.7/25Owner reach — 1,433 followers of meta-pytorch
21.6/25Track record — 61 public repos, account ~4 yr old
Inputs used
followers1,433
owner_typeOrganization
is_verifiedyes
owner_loginmeta-pytorch
public_repos61
account_age_days1,574

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 28 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagestorchrec
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

91Excellent · 19% of overall
How it's scored
24/24CI workflows — 13 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
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/torchrec/
10/10Repository description
10/10Topics — 7 topics
0/10Wiki
Inputs used
topicspytorch, gpu, deep-learning, cuda, recommender-system, recommendation-system, sharding
has_wikino
homepagehttps://pytorch.org/torchrec/
docs_sitehttps://pytorch.org/torchrec/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

42Weak · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
20/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestsdocs/requirements.txt, pyproject.toml, requirements.txt, setup.py
has_codeql_workflowyes
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages5
unassessed_packages26
affected_by_severitynone
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 5 resolved dependencies against OSV. 26 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.

67Good · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://pytorch.org/llms.txt)
40/40Legible commit history — 100 of 100 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—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
52.6/55Manageable file sizes — 39/877 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes237,871
source_files_sampled877
oversized_source_files39
How it's scored
40/40API schema (OpenAPI/GraphQL/proto) — torchrec/inference/inference_legacy/protos/predictor.proto, torchrec/inference/protos/predictor.proto
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_filestorchrec/inference/inference_legacy/protos/predictor.proto, torchrec/inference/protos/predictor.proto
interfaces_expected_of—
Excluded from scoring (no data or not applicable): MCP server. Remaining weights renormalized.

Key facts

2,607GitHub stars
100contributors
1,158commits, last 12 months
0days since last push
38releases
10bus factor
79open issues
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 22 authors (cap 12)
  • deps.dev does not index pypi:torchrec@1.9.1; advisories assessed against the repository dependency graph instead
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit; 2026/09/30 23:44:49 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 ★ / 699 ⇿
0Stars
699Forks
38Releases

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.

0125250375500625750690212022-022024-062026-09
Major 0Minor 10Patch 2

Each point covers 5 days.

All dependencies 31

Full resolved dependency set from the GitHub dependency graph: 0 direct and 31 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPI1-7-0a0—indirect
PyPIblack—indirect
PyPIclick—indirect
PyPIcmake—indirect
PyPIexpecttest—indirect
PyPIfbgemm-gpu—indirect
PyPIhypothesis6.70.1indirect
PyPIimportlib-metadata—indirect
PyPIiopath—indirect
PyPInumpy—indirect
PyPIpandas—indirect
PyPIparameterized—indirect
PyPIpsutil—indirect
PyPIpyre-extensions—indirect
PyPIpytorch-sphinx-theme20.3.0indirect
PyPIpyyaml—indirect
PyPIscikit-build—indirect
PyPIsphinx7.2.6indirect
PyPIsphinx-copybutton—indirect
PyPIsphinx-design—indirect
PyPIsphinx-sitemap2.7.1indirect
PyPItensorboard—indirect
PyPItensordict—indirect
PyPItorch—indirect
PyPItorchmetrics—indirect
PyPItorchmetrics1.0.3indirect
PyPItorchrec—indirect
PyPItorchx—indirect
PyPItorchx-nightly—indirect
PyPItqdm—indirect
PyPIusort—indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 5 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 26 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

No known advisories affect the assessed dependencies.

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 v0.34.0 — full methodology · metrics wiki.

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