Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-14 21:06 UTC

meta-pytorch / botorch

Bayesian optimization in PyTorch

Jupyter Notebook · PythonMIT★ 3,598 stars⑂ 495 forkssince Jul 2018View on GitHub ↗
KindLibraryWeb interfacehow this is determined

meta-pytorch/botorch holds a health index of 96 out of 100, placing it in the Exceptional band. It scores highest on Vitality (95/100) and lowest on AI Readiness (67/100). It was last updated 5 days ago. 2 contributors account for most of its recent work.

96
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.

96
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 84 is calibrated to 96 on the published index scale (record calibration 2026-08-02).

Ownership

Meta PyTorchOrganization · verified domain
1,422 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
PyPIbotorch0.18.1462,5625797 days agobayesian-optimizationpytorch

Metrics by category

Vitality

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

95Exceptional · 21% of overall
How it's scored
36/36Push recency — last push 5 days ago
34.6/36Commit cadence — 50/52 weeks with commits
18/18Commit volume — 254 commits in the last year
10/10OpenSSF Scorecard: Maintained — 28 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year254
human_commit_share0.95
days_since_last_push5
active_weeks_last_year50
How it's scored
27/27Ships releases — 57 releases published
27/36Release recency — latest release 97 days ago
27/27Release cadence — a release every ~44.3 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count57
latest_release_tagv0.18.1
releases_from_tagsno
days_since_latest_release97
mean_days_between_releases44.3
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?

91Excellent · 17% of overall
How it's scored
57.7/60Stars — 3,598 stars
22.5/25Forks — 495 forks
9.2/15Watchers — 47 watchers
Inputs used
forks495
stars3,598
watchers47
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
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_badges7
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateyes
How it's scored
75.5/80Monthly downloads — 462,562 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesbotorch
dependents—
ecosystemspypi
total_downloads—
monthly_downloads462,562
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?

76Good · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
14.9/22.5Commit distribution — top contributor authored 34% of commits
13.5/13.5Contributor breadth — 99 contributors
10/10OpenSSF Scorecard: Contributors — project has 16 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled99
top_contributor_share0.336
How it's scored
38.2/42Issue resolution — 91% of issues closed
0.1/30PR acceptance — 7/2,329 decided PRs merged
0/13Newcomer PR acceptance — 0/5 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs7
open_issues57
closed_issues570
prs_merged_7d0
prs_decided_7d3
prs_merged_30d0
prs_decided_30d8
issue_closed_ratio0.909
closed_unmerged_prs2,322
first_time_authors_30d2
first_time_prs_merged_30d0
first_time_prs_decided_30d5
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
22.7/25Owner reach — 1,422 followers of meta-pytorch
21.5/25Track record — 60 public repos, account ~4 yr old
Inputs used
followers1,422
owner_typeOrganization
is_verifiedyes
owner_loginmeta-pytorch
public_repos60
account_age_days1,558

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 97 days ago
20/20Version history — 57 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesbotorch
ecosystemspypi
any_deprecatedno
min_days_since_publish97

Engineering Quality

Are baseline engineering and documentation practices in place?

87Excellent · 19% of overall
How it's scored
24/24CI workflows — 11 workflow(s)
24/24Tests present
16/16Linter config — .flake8
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
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

80Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://botorch.org/
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics—
has_wikino
homepagehttps://botorch.org/
docs_sitehttps://botorch.org/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

73Good · 16% of overall
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
0/2.5CI-Tests — no data
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 16 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
2.5/2.5License — license file detected
7.5/7.5Maintained — 28 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — no SAST tool detected
4.5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
6/7.5Vulnerabilities — 2 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.6
Excluded from scoring (no data or not applicable): CI-Tests, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages43
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:botorch@0.18.1 runtime dependency closure — what installing the published package pulls in — 43 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.

67Good · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 95 of 95 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — sphinx/Makefile
22/22Automated tests
11/11Lint / format config — .flake8
11/11Static type checking — botorch/py.typed
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 5 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
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filessphinx/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configsbotorch/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.05
How it's scored
27/45Type-checkable code — Jupyter Notebook with type-check config (botorch/py.typed)
53.8/55Manageable file sizes — 11/492 source files over 60KB
Inputs used
primary_languageJupyter Notebook
largest_source_bytes139,762
source_files_sampled492
oversized_source_files11
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 — example, notebooks
Inputs used
example_dirsexample, 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

3,598GitHub stars
99contributors
254commits, last 12 months
5days since last push
57releases
2bus factor
57open issues
npm, PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 495 ⇿
0Stars
495Forks
57Releases

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.

0100200300400500486312019-052022-122026-08
Major 0Minor 18Patch 38

Each point covers 7 days.

OpenSSF Scorecard 6.6 / 10
6.6aggregate

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 · 2026-09-14 21:06 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 16 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained28 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTno SAST tool detected
9Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
8Vulnerabilities2 existing vulnerabilities detected
Direct dependencies 19
RegistryPackageVersion constraintManifest
PyPItyping_extensions—pyproject.toml
PyPIpyre_extensions—pyproject.toml
PyPIgpytorch>=1.15.2pyproject.toml
PyPIlinear_operator>=0.6.1pyproject.toml
PyPItorch>=2.4pyproject.toml
PyPIscipy—pyproject.toml
PyPImultipledispatch—pyproject.toml
PyPIthreadpoolctl—pyproject.toml
PyPIninja—pyproject.toml
npm@docusaurus/core~3.9.0website/package.json
npm@docusaurus/preset-classic~3.9.0website/package.json
npmclsx^1.1.1website/package.json
npmplotly.js^2.8.1website/package.json
npmreact^18.3.1website/package.json
npmreact-dom^18.3.1website/package.json
npmreact-plotly.js^2.5.1website/package.json
npmrehype-katex7website/package.json
npmremark-math6website/package.json
npmwebpack5.104.1website/package.json
All dependencies 29

Full resolved dependency set from the GitHub dependency graph: 19 direct and 10 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
npm@docusaurus/core~3.9.0direct
npm@docusaurus/preset-classic~3.9.0direct
npmclsx^1.1.1direct
npmplotly.js^2.8.1direct
npmreact^18.3.1direct
npmreact-dom^18.3.1direct
npmreact-plotly.js^2.5.1direct
npmrehype-katex7direct
npmremark-math6direct
npmwebpack5.104.1direct
PyPIgpytorch—direct
PyPIlinear-operator—direct
PyPImultipledispatch—direct
PyPIninja—direct
PyPIpyre-extensions—direct
PyPIscipy—direct
PyPIthreadpoolctl—direct
PyPItorch—direct
PyPItyping-extensions—direct
npm@docusaurus/module-type-aliases~3.9.0indirect
npm@docusaurus/types~3.9.0indirect
PyPIblack25.11.0indirect
PyPIjax—indirect
PyPIjaxlib—indirect
PyPInumpyro—indirect
PyPIruff-api0.2.1indirect
PyPIstdlibs2025.10.28indirect
PyPIufmt2.9.1indirect
PyPIusort1.1.0indirect
Dependency advisories 0

Installing pypi:botorch@0.18.1 pulls in 43 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

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.