Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-19 09:04 UTC

PowerGridModel / power-grid-model-io

Conversion tool for various grid data formats to power-grid-model

PythonMPL-2.0★ 28 stars⑂ 16 forkssince Jul 2022View on GitHub ↗

PowerGridModel/power-grid-model-io holds a health index of 95 out of 100, placing it in the Exceptional band. It scores highest on Vitality (95/100) and lowest on Community & Adoption (64/100). It was last updated today. 3 contributors account for most of its recent work.

95
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.

95
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 82 is calibrated to 95 on the published index scale (record calibration 2026-08-02).

Ownership

Power Grid ModelOrganization
182 followers22 public repossince Mar 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpower-grid-model-io1.3.11317,5193280 days agopower-grid-modelinput-outputconversions

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 recencylast push 0 days ago
33.9/36Commit cadence49/52 weeks with commits
18/18Commit volume536 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year536
human_commit_share0.74
days_since_last_push0
active_weeks_last_year49
How it's scored
27/27Ships releases100 releases published
36/36Release recencylatest release 0 days ago
27/27Release cadencea release every ~3.3 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count100
latest_release_tagv1.3.113
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases3.3

Community & Adoption

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

64Moderate · 17% of overall
How it's scored
23.2/60Stars28 stars
9.8/25Forks16 forks
1.7/15Watchers3 watchers
Inputs used
forks16
stars28
watchers3
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 (MPL-2.0)
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_badges11
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesbadge.fury.io, github.com, readthedocs.org, shields.io, sonarcloud.io
has_pull_request_templateyes
How it's scored
56.6/80Monthly downloads17,519 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagespower-grid-model-io
dependents
ecosystemspypi
total_downloads
monthly_downloads17,519
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?

84Excellent · 23% of overall
How it's scored
36/54Bus factor3 contributor(s) cover half of all commits
16.3/22.5Commit distributiontop contributor authored 28% of commits
13.5/13.5Contributor breadth15 contributors
10/10OpenSSF Scorecard: Contributorsproject has 10 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled15
top_contributor_share0.276
How it's scored
33.1/42Issue resolution79% of issues closed
27.5/30PR acceptance361/394 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs361
open_issues16
closed_issues60
prs_merged_7d4
prs_decided_7d4
prs_merged_30d6
prs_decided_30d7
issue_closed_ratio0.789
closed_unmerged_prs33
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 backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
16.3/25Owner reach182 followers of PowerGridModel
16.7/25Track record22 public repos, account ~3 yr old
Inputs used
followers182
owner_typeOrganization
is_verified
owner_loginPowerGridModel
public_repos22
account_age_days1,247
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 history328 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagespower-grid-model-io
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall
How it's scored
24/24CI workflows8 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests11 out of 11 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

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics4 topics
10/10Wiki
Inputs used
topicsexcel, gaia, python, vision
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

79Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
3/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests11 out of 11 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
7.5/7.5Code-Reviewall changesets reviewed
2.5/2.5Contributorsproject has 10 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 4 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
5/5Pinned-Dependenciesall dependencies are pinned
5/5SASTSAST tool is run on all commits
5/5Security-Policysecurity policy file 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_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate7.4

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages123
unassessed_packages0
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 123 resolved dependencies against OSV. 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.

65Good · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
29.5/40Legible commit history41 of 74 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.554
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
11/11Static type checkingsrc/power_grid_model_io/py.typed
10/10Reproducible environmentlockfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance17 of the last 100 commits are automated dependency updates
10/10OpenSSF Scorecard: Pinned-Dependenciesall dependencies are pinned
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configssrc/power_grid_model_io/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.17
How it's scored
27/45Type-checkable codePython with type-check config (src/power_grid_model_io/py.typed)
52.6/55Manageable file sizes4/93 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes140,165
source_files_sampled93
oversized_source_files4
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples, notebooks
Inputs used
example_dirsexamples, 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

28GitHub stars
15contributors
536commits, last 12 months
0days since last push
100releases
3bus factor
16open 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:power-grid-model-io@1.3.113; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 16 ⇿
0Stars
16Forks
94Releases

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.

04812161622022-102024-092026-08
Major 0Minor 0Patch 94

Each point covers 4 days.

OpenSSF Scorecard 7.4 / 10
7.4aggregate

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 · 2026-08-19 09:04 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests11 out of 11 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 10 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 4 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
10Pinned-Dependenciesall dependencies are pinned
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file 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 8
RegistryPackageVersion constraintManifest
PyPInumpy>=2.0pyproject.toml
PyPIopenpyxlpyproject.toml
PyPIpackaging>=25.0pyproject.toml
PyPIpandaspyproject.toml
PyPIpower_grid_model>=1.8pyproject.toml
PyPIpyyamlpyproject.toml
PyPIstructlogpyproject.toml
PyPItqdmpyproject.toml
All dependencies 123

Full resolved dependency set from the GitHub dependency graph: 8 direct and 115 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpy2.5.2direct
PyPIopenpyxl3.1.5direct
PyPIpackaging25.0direct
PyPIpandas2.3.3direct
PyPIpower-grid-model1.13.142direct
PyPIpyyaml6.0.3direct
PyPIstructlog26.1.0direct
PyPItqdm4.70.0direct
PyPIalabaster1.0.0indirect
PyPIannotated-types0.8.0indirect
PyPIappnope0.1.4indirect
PyPIast-serialize0.8.0indirect
PyPIasttokens3.0.2indirect
PyPIattrs26.1.0indirect
PyPIbabel2.18.0indirect
PyPIcertifi2026.7.22indirect
PyPIcffi2.1.1indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.5.1indirect
PyPIclick8.4.2indirect
PyPIcolorama0.4.6indirect
PyPIcomm0.2.3indirect
PyPIcoverage7.15.4indirect
PyPIdebugpy1.8.21indirect
PyPIdeepdiff8.6.2indirect
PyPIdistlib0.4.3indirect
PyPIdocutils0.22.4indirect
PyPIet-xmlfile2.0.0indirect
PyPIexecuting2.2.1indirect
PyPIfastjsonschema2.22.2indirect
PyPIfilelock3.32.3indirect
PyPIgeojson3.3.0indirect
PyPIgreenlet3.5.5indirect
PyPIidentify2.6.19indirect
PyPIidna3.18indirect
PyPIimagesize2.0.0indirect
PyPIimportlib-metadata9.0.0indirect
PyPIiniconfig2.3.0indirect
PyPIipykernel7.3.0indirect
PyPIipython9.16.1indirect
PyPIipython-pygments-lexers1.1.1indirect
PyPIjedi0.20.0indirect
PyPIjinja23.1.6indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPIjupyter-cache1.0.1indirect
PyPIjupyter-client8.9.1indirect
PyPIjupyter-core5.9.1indirect
PyPIlibrt0.15.0indirect
PyPIlxml6.1.1indirect
PyPImarkdown-it-py4.2.0indirect
PyPImarkupsafe3.0.3indirect
PyPImatplotlib-inline0.2.2indirect
PyPImdit-py-plugins0.6.1indirect
PyPImdurl0.1.2indirect
PyPImypy2.3.1indirect
PyPImypy-extensions1.1.0indirect
PyPImyst-nb1.4.0indirect
PyPImyst-parser5.1.0indirect
PyPInbclient0.11.0indirect
PyPInbformat5.11.1indirect
PyPInest-asyncio21.7.2indirect
PyPInetworkx3.6.1indirect
PyPInodeenv1.10.0indirect
PyPInumpydoc1.10.0indirect
PyPIorderly-set5.5.0indirect
PyPIpandapower3.3.3indirect
PyPIpandera0.26.1indirect
PyPIparso0.8.7indirect
PyPIpathspec1.1.1indirect
PyPIpexpect4.9.0indirect
PyPIplatformdirs4.11.3indirect
PyPIpluggy1.6.0indirect
PyPIpre-commit4.6.2indirect
PyPIprompt-toolkit3.0.53indirect
PyPIpsutil7.2.2indirect
PyPIptyprocess0.7.0indirect
PyPIpure-eval0.2.3indirect
PyPIpyarrow25.0.1indirect
PyPIpycparser3.0indirect
PyPIpydantic2.13.4indirect
PyPIpydantic-core2.46.4indirect
PyPIpygments2.21.0indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-discovery1.5.2indirect
PyPIpytz2026.3.post1indirect
PyPIpyzmq27.1.0indirect
PyPIreadthedocs-sphinx-search0.3.2indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIroman-numerals4.1.0indirect
PyPIrpds-py2026.6.3indirect
PyPIruff0.16.3indirect
PyPIscipy1.16.3indirect
PyPIsix1.17.0indirect
PyPIsnowballstemmer3.1.1indirect
PyPIsphinx9.1.0indirect
PyPIsphinx-rtd-theme3.1.0indirect
PyPIsphinxcontrib-applehelp2.0.0indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jquery4.1indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
PyPIsqlalchemy2.0.52indirect
PyPIstack-data0.6.3indirect
PyPItabulate0.10.0indirect
PyPItornado6.5.8indirect
PyPItraitlets5.16.1indirect
PyPItypeguard4.6.0indirect
PyPItypes-pyyaml6.0.12.20260815indirect
PyPItypes-requests2.33.0.20260712indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspect0.9.0indirect
PyPItyping-inspection0.4.4indirect
PyPItzdata2026.3indirect
PyPIurllib32.7.0indirect
PyPIvirtualenv21.7.4indirect
PyPIwcwidth0.8.2indirect
PyPIzipp4.1.0indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 123 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct.

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 v0.31.0 — full methodology · metrics wiki.

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