Public record
Software health reportschema 0.15.0 · metrics 2.10.0 · 2026-07-19 13:55 UTC

PyAutoLabs / PyAutoLens

PyAutoLens: Open-Source Strong Gravitational Lensing

PythonMIT★ 184 stars⑂ 36 forkssince Oct 2017View on GitHub ↗

PyAutoLabs/PyAutoLens holds a health index of 87 out of 100, placing it in the Excellent band. It scores highest on Vitality (96/100) and lowest on Security (51/100). It was last updated today. A single contributor accounts for most of its recent work.

87
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.

87
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 73 is calibrated to 87 on the published index scale (record calibration 2026-08-02).

Ownership

PyAutoLabsOrganization
4 followers40 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
PyPIautolens2026.7.19.17,9974090 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 recencylast push 0 days ago
29.8/36Commit cadence43/52 weeks with commits
18/18Commit volume610 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 29 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year610
human_commit_share
days_since_last_push0
active_weeks_last_year43

Release discipline

100Exceptional
How it's scored
27/27Ships releases51 releases published
36/36Release recencylatest release 0 days ago
27/27Release cadencea release every ~10.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count51
latest_release_tag2026.7.19.1
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases10.8
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?

70Good · 17% of overall
How it's scored
36.7/60Stars184 stars
12.9/25Forks36 forks
5.6/15Watchers11 watchers
Inputs used
forks36
stars184
watchers11
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized 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_badges
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services
has_pull_request_templateyes
How it's scored
52/80Monthly downloads7,997 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesautolens
dependents
ecosystemspypi
total_downloads
monthly_downloads7,997
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?

68Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
10.5/22.5Commit distributiontop contributor authored 53% of commits
13.5/13.5Contributor breadth15 contributors
10/10OpenSSF Scorecard: Contributorsproject has 4 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled15
top_contributor_share0.534
How it's scored
40.7/42Issue resolution97% of issues closed
28.7/30PR acceptance388/405 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/17 approved changesets -- score normalized to 0
Inputs used
merged_prs388
open_issues7
closed_issues223
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.97
closed_unmerged_prs17
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
5/25Owner reach4 followers of PyAutoLabs
12.3/25Track record40 public repos, account ~0 yr old
Inputs used
followers4
owner_typeOrganization
is_verified
owner_loginPyAutoLabs
public_repos40
account_age_days106
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 0 days ago
20/20Version history409 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesautolens
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests16 out of 17 merged PRs checked by a CI test -- score normalized to 9
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 sitehttps://pyautolens.readthedocs.io/
10/10Repository description
10/10Topics7 topics
10/10Wiki
Inputs used
topicsastronomy, gravitational-lensing, cosmology, galaxy, astrophysics, python, bayesian-inference
has_wikiyes
homepagehttps://pyautolens.readthedocs.io/
docs_sitehttps://pyautolens.readthedocs.io/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

51Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
2.2/2.5CI-Tests16 out of 17 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/17 approved changesets -- score normalized to 0
2.5/2.5Contributorsproject has 4 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 29 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 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.

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.

58Moderate · 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
0/40Legible commit historyno data
Inputs used
has_llms_txtyes
llms_txt_url
legible_history_share
agent_instruction_files.github/copilot-instructions.md, AGENTS.md, CLAUDE.md
agent_instruction_max_bytes5,251
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno data
0/8Automated maintenanceno data
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/227 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes57,729
source_files_sampled227
oversized_source_files0

Key facts

184GitHub stars
15contributors
610commits, last 12 months
0days since last push
51releases
1bus factor
7open issues
PyPIpackage ecosystems

More detail

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 · 2026-07-19 13:55 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
9CI-Tests16 out of 17 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/17 approved changesets -- score normalized to 0
10Contributorsproject has 4 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 29 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 2
RegistryPackageVersion constraintManifest
PyPIautogalaxypyproject.toml
PyPInautilus-sampler==1.0.5pyproject.toml
All dependencies 4

Full resolved dependency set from the GitHub dependency graph: 1 direct and 3 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInautilus-sampler1.0.5direct
PyPIgetdist1.4indirect
PyPIsetuptoolsindirect
PyPIzeus-mcmc2.5.4indirect
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 v0.15.0 — full methodology · metrics wiki.

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