Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-27 08:58 UTC

PyAutoLabs / PyAutoFit

PyAutoFit: Classy Probabilistic Programming

PythonMIT★ 65 stars⑂ 15 forkssince Nov 2018View on GitHub ↗

PyAutoLabs/PyAutoFit holds a health index of 88 out of 100, placing it in the Excellent band. It scores highest on Vitality (96/100) and lowest on Security (61/100). It was last updated today. A single contributor accounts for most of its recent work.

88
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.

88
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 74 is calibrated to 88 on the published index scale (record calibration 2026-08-02).

Ownership

PyAutoLabsOrganization
5 followers46 public repossince Apr 2026

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIautofit2026.9.27.17,5333650 days agocli

Metrics by category

Vitality

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

96Exceptional · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
29.1/36Commit cadence — 42/52 weeks with commits
18/18Commit volume — 820 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year820
human_commit_share0.95
days_since_last_push0
active_weeks_last_year42

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 56 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~3.9 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count56
latest_release_tag2026.9.27.1
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases3.9
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?

65Good · 17% of overall
How it's scored
29.3/60Stars — 65 stars
9.6/25Forks — 15 forks
3.3/15Watchers — 5 watchers
Inputs used
forks15
stars65
watchers5
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_badges5
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, readthedocs.org, shields.io
has_pull_request_templateyes
How it's scored
51.7/80Monthly downloads — 7,533 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesautofit
dependents—
ecosystemspypi
total_downloads—
monthly_downloads7,533
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?

65Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
9.3/22.5Commit distribution — top contributor authored 59% of commits
13.5/13.5Contributor breadth — 11 contributors
10/10OpenSSF Scorecard: Contributors — project has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled11
top_contributor_share0.588
How it's scored
41.2/42Issue resolution — 98% of issues closed
29.2/30PR acceptance — 1,005/1,034 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/18 approved changesets -- score normalized to 0
Inputs used
merged_prs1,005
open_issues11
closed_issues601
prs_merged_7d4
prs_decided_7d4
prs_merged_30d50
prs_decided_30d50
issue_closed_ratio0.982
closed_unmerged_prs29
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.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
5.6/25Owner reach — 5 followers of PyAutoLabs
13.1/25Track record — 46 public repos, account ~0 yr old
Inputs used
followers5
owner_typeOrganization
is_verifiedno
owner_loginPyAutoLabs
public_repos46
account_age_days176

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 — 365 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesautofit
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

81Excellent · 19% of overall
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 10 out of 10 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://pyautofit.readthedocs.io/
10/10Repository description
10/10Topics — 11 topics
10/10Wiki
Inputs used
topicsprobabilistic-programming, statistics, bayesian-inference, bayesian-methods, model, astronomy, statistical-analysis, stats, mcmc, graphical-models, python
has_wikiyes
homepagehttps://pyautofit.readthedocs.io/
docs_sitehttps://pyautofit.readthedocs.io/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

61Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5CI-Tests — 10 out of 10 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
0/7.5Code-Review — Found 0/18 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 3 contributing companies or organizations -- score normalized to 10
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 — 30 commit(s) and 30 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
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
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
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.1
Excluded from scoring (no data or not applicable): Packaging, 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
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_packages11
unassessed_packages18
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 11 resolved dependencies against OSV. 18 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.

73Good · 4% of overall
How it's scored
45/45Agent instructions — .github/copilot-instructions.md, AGENTS.md, CLAUDE.md
15/15Machine-readable docs (llms.txt) — llms.txt present
40/40Legible commit history — 88 of 95 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_url—
legible_history_share0.926
agent_instruction_files.github/copilot-instructions.md, AGENTS.md, CLAUDE.md
agent_instruction_max_bytes5,036
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
10/10Demonstrated agent practice — 46 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
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_filesdocs/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0.46
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
54.5/55Manageable file sizes — 5/611 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes111,511
source_files_sampled611
oversized_source_files5
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, samples
Inputs used
example_dirsexample, samples
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

65GitHub stars
11contributors
820commits, last 12 months
0days since last push
56releases
1bus factor
11open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:autofit@2026.9.27.1; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 15 ⇿
0Stars
15Forks
43Releases

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.

03581013151522021-022023-112026-08
Major 0Minor 0Patch 0

Each point covers 6 days.

OpenSSF Scorecard 5.1 / 10
5.1aggregate

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 · 2026-09-27 08:57 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests10 out of 10 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/18 approved changesets -- score normalized to 0
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 30 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
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 23
RegistryPackageVersion constraintManifest
PyPIautonerves>=2026.8.22.1pyproject.toml
PyPIoptax>=0.2.5pyproject.toml
PyPIarray_api_compat—pyproject.toml
PyPIanesthetic>=2.9.0pyproject.toml
PyPIcorner==2.2.2pyproject.toml
PyPIdecorator>=4.2.1pyproject.toml
PyPIdill>=0.3.1.1pyproject.toml
PyPIdynesty==2.1.5pyproject.toml
PyPItyping-inspect>=0.4.0pyproject.toml
PyPIemcee>=3.1.6pyproject.toml
PyPIgprof2dot==2021.2.21pyproject.toml
PyPImatplotlib—pyproject.toml
PyPInumpydoc>=1.0.0pyproject.toml
PyPIh5py>=3.11.0pyproject.toml
PyPISQLAlchemy>=2.0.32,<2.1.0pyproject.toml
PyPIscipy<=1.17.1pyproject.toml
PyPIastunparse==1.6.3pyproject.toml
PyPIthreadpoolctl>=3.1.0pyproject.toml
PyPItimeout-decorator==0.5.0pyproject.toml
PyPIxxhash<=3.4.1pyproject.toml
PyPInetworkx==3.1pyproject.toml
PyPIpyvis==0.3.2pyproject.toml
PyPIpsutil==6.1.0pyproject.toml
All dependencies 29

Full resolved dependency set from the GitHub dependency graph: 23 direct and 6 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIanesthetic—direct
PyPIarray-api-compat—direct
PyPIastunparse1.6.3direct
PyPIautonerves—direct
PyPIcorner2.2.2direct
PyPIdecorator—direct
PyPIdill—direct
PyPIdynesty2.1.5direct
PyPIemcee—direct
PyPIgprof2dot2021.2.21direct
PyPIh5py—direct
PyPImatplotlib—direct
PyPInetworkx3.1direct
PyPInumpydoc—direct
PyPIoptax—direct
PyPIpsutil6.1.0direct
PyPIpyvis0.3.2direct
PyPIscipy—direct
PyPIsqlalchemy—direct
PyPIthreadpoolctl—direct
PyPItimeout-decorator0.5.0direct
PyPItyping-inspect—direct
PyPIxxhash—direct
PyPIastropy—indirect
PyPIblackjax—indirect
PyPIgetdist1.4indirect
PyPInautilus-sampler1.0.5indirect
PyPIsetuptools—indirect
PyPIzeus-mcmc2.5.4indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 11 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 18 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.