Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 00:48 UTC

PyCQA / pydocstyle

docstring style checker

PythonMIT★ 1,117 stars⑂ 190 forkssince Jan 2012archivedView on GitHub ↗
KindLibraryhow this is determined
#python#linter#docstrings

PyCQA/pydocstyle holds a health index of 19 out of 100, placing it in the Critical band. It scores highest on Engineering Quality (84/100) and lowest on Security (1/100). The repository is archived, so no further maintenance is expected.

19
overall / 100
Critical

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.

19
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 48 is calibrated to 47 on the published index scale (record calibration 2026-08-02).

Ownership

Python Code Quality AuthorityOrganization
1,013 followers29 public repossince Sep 2014

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIpydocstyle6.3.0-221276 days ago

Metrics by category

Vitality

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

21At Risk · 21% of overall

Development activity

1Critical
How it's scored
0/36Push recency — last push 986 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year0
human_commit_share—
days_since_last_push986
active_weeks_last_year0

Release discipline

52Moderate
How it's scored
27/27Ships releases — 17 releases published
0/36Release recency — latest release 1,276 days ago
19.8/27Release cadence — a release every ~97.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count17
latest_release_tag6.3.0
releases_from_tagsno
days_since_latest_release1,276
mean_days_between_releases97.6

Community & Adoption

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

63Moderate · 17% of overall

Popularity & adoption

68Good
How it's scored
49.4/60Stars — 1,117 stars
19/25Forks — 190 forks
0/15Watchers — 2 watchers
Inputs used
forks190
stars1,117
watchers2
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

57Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateyes

Sustainability & Governance

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

66Good · 23% of overall

Maintainer resilience (bus factor)

37Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
10.9/22.5Commit distribution — top contributor authored 52% of commits
13.5/13.5Contributor breadth — 85 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled85
top_contributor_share0.515

Issue & PR responsiveness

70Good
How it's scored
28/42Issue resolution — 67% of issues closed
22.7/30PR acceptance — 235/310 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs235
open_issues113
closed_issues225
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.666
closed_unmerged_prs75
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.

Ownership & stewardship

93Exceptional
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
21.6/25Owner reach — 1,013 followers of PyCQA
22.8/25Track record — 29 public repos, account ~11 yr old
Inputs used
followers1,013
owner_typeOrganization
is_verified—
owner_loginPyCQA
public_repos29
account_age_days4,325
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

69Good
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
4/35Publish recency — latest publish 1,276 days ago
20/20Version history — 22 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespydocstyle
ecosystemspypi
any_deprecatedno
min_days_since_publish1,276

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall

Engineering practices

80Excellent
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — tox.ini
0/9.6Pre-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_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — http://pydocstyle.org
10/10Repository description
10/10Topics — 3 topics
0/10Wiki
Inputs used
topicspython, linter, docstrings
has_wikino
homepagehttp://pydocstyle.org
docs_sitehttp://pydocstyle.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

1Critical · 16% of overall

Security posture

1Critical
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfilespoetry.lock
manifestspyproject.toml, requirements.txt
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. 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.

50Moderate · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

85Excellent
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile
22/22Automated tests
11/11Lint / format config — tox.ini
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configyes
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.

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/38 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes47,225
source_files_sampled38
oversized_source_files0

Key facts

1,117GitHub stars
85contributors
0commits, last 12 months
986days since last push
17releases
1bus factor
113open issues
PyPIpackage ecosystems

Data collection warnings

  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPIsnowballstemmer>=2.2.0pyproject.toml
PyPItomli>=1.2.3pyproject.toml
PyPIimportlib-metadata>=2.0.0,<5.0.0pyproject.toml
All dependencies 18

Full resolved dependency set from the GitHub dependency graph: 6 direct and 12 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIimportlib-metadata—direct
PyPIimportlib-metadata4.8.3direct
PyPIsnowballstemmer—direct
PyPIsnowballstemmer2.2.0direct
PyPItomli—direct
PyPItomli1.2.3direct
PyPI-—indirect
PyPIblack22.3indirect
PyPIisort5.4.2indirect
PyPIjinja2—indirect
PyPImypy0.930indirect
PyPIpytest6.2.5indirect
PyPIsphinx—indirect
PyPIsphinx-rtd-theme—indirect
PyPItox—indirect
PyPItypes-setuptools—indirect
PyPItyping-extensions4.1.1indirect
PyPIzipp3.6.0indirect
Raw JSON report machine-readable

Feedback

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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 v0.11.0 — full methodology · metrics wiki.

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