Public record
Software health reportschema 0.14.0 · metrics 2.10.0 · 2026-07-18 23:50 UTC

akaihola / darker

Apply black reformatting to Python files only in regions changed since a given commit. For a practical usage example, see the blog post at https://dev.to/akaihola/improving-python-code-incrementally-3f7a

PythonCustom license★ 685 stars⑂ 56 forkssince Feb 2020View on GitHub ↗

akaihola/darker holds a health index of 62 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (82/100) and lowest on Vitality (38/100). It was last updated 269 days ago. A single contributor accounts for most of its recent work.

62
overall / 100
Moderate

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.

62
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 58 is calibrated to 62 on the published index scale (record calibration 2026-08-02).

Ownership

Antti KaiholaPersonal account
127 followers280 public repossince Jun 2008Wärtsilä Oyj

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIdarker3.0.0-28320 days ago

Metrics by category

Vitality

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

38Weak · 21% of overall
How it's scored
3.6/36Push recencylast push 269 days ago
1.4/36Commit cadence2/52 weeks with commits
16.1/18Commit volume61 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year61
human_commit_share
days_since_last_push269
active_weeks_last_year2
How it's scored
27/27Ships releases25 releases published
16.2/36Release recencylatest release 320 days ago
19.8/27Release cadencea release every ~109.6 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count25
latest_release_tagv3.0.0
releases_from_tagsno
days_since_latest_release320
mean_days_between_releases109.6

Community & Adoption

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

65Good · 17% of overall
How it's scored
46/60Stars685 stars
14.5/25Forks56 forks
4.7/15Watchers8 watchers
Inputs used
forks56
stars685
watchers8
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
18/18CONTRIBUTING guide
0/13.5Code 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_conductno
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

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

62Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
2.2/22.5Commit distributiontop contributor authored 90% of commits
13.5/13.5Contributor breadth39 contributors
10/10OpenSSF Scorecard: Contributorsproject has 65 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled39
top_contributor_share0.9
How it's scored
34/42Issue resolution81% of issues closed
25.7/30PR acceptance392/458 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-ReviewFound 1/7 approved changesets -- score normalized to 1
Inputs used
merged_prs392
open_issues40
closed_issues171
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.81
closed_unmerged_prs66
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
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
15.1/25Owner reach127 followers of akaihola
25/25Track record280 public repos, account ~18 yr old
Inputs used
followers127
owner_typeUser
is_verified
owner_loginakaihola
public_repos280
account_age_days6,608
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 320 days ago
20/20Version history28 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesdarker
ecosystemspypi
any_deprecatedno
min_days_since_publish320

Engineering Quality

Are baseline engineering and documentation practices in place?

82Excellent · 19% of overall
How it's scored
24/24CI workflows16 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests7 out of 7 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://pypi.org/project/darker/
10/10Repository description
10/10Topics2 topics
0/10Wiki
Inputs used
topicspython, python3
has_wikino
homepagehttps://pypi.org/project/darker/
docs_sitehttps://pypi.org/project/darker/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

44Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
2.5/2.5CI-Tests7 out of 7 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-ReviewFound 1/7 approved changesets -- score normalized to 1
2.5/2.5Contributorsproject has 65 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.2/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
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-ReleasesProject has not signed or included provenance with any releases.
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_aggregate4.4
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging. 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.

46Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit historyno 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.
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
11/11Static type checkingmypy.ini, src/darker/py.typed
10/10Reproducible environmentDockerfile, Nix
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_nixyes
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configsmypy.ini, src/darker/py.typed
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
27/45Type-checkable codePython with type-check config (mypy.ini, src/darker/py.typed)
55/55Manageable file sizes0/63 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes30,141
source_files_sampled63
oversized_source_files0

Key facts

685GitHub stars
39contributors
61commits, last 12 months
269days since last push
25releases
1bus factor
40open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 4.4 / 10
4.4aggregate

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 · 2026-07-18 23:49 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests7 out of 7 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 1/7 approved changesets -- score normalized to 1
10Contributorsproject has 65 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
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
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPIdarkgraylib>=2.4.0,<3.0.dev0pyproject.toml
PyPItoml>=0.10.0pyproject.toml
PyPItyping_extensions>=4.0.1pyproject.toml
All dependencies 3

Full resolved dependency set from the GitHub dependency graph: 3 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIdarkgraylibdirect
PyPItomldirect
PyPItyping-extensionsdirect
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 v0.14.0 — full methodology · metrics wiki.

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