Public record
Software health reportschema 0.14.0 · metrics 2.10.0 · 2026-07-18 23:16 UTC

HiDiHo01 / python-frank-energie

Asynchronous Python package for Frank Energie. Retrieve energy prices for Frank energie.

PythonApache-2.0★ 10 stars⑂ 3 forkssince Apr 2025View on GitHub ↗

HiDiHo01/python-frank-energie holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Vitality (92/100) and lowest on AI Readiness (32/100). It was last updated today. 2 contributors account for most of its recent work.

83
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.

83
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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

RoyPersonal account
12 followers39 public repossince Dec 2021

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 publishTags
PyPIpython-frank-energie2026.7.18-570 days agohome-assistantenergyasyncasyncioapifrank-energie

Metrics by category

Vitality

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

92Excellent · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
22.8/36Commit cadence33/52 weeks with commits
18/18Commit volume327 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year327
human_commit_share
days_since_last_push0
active_weeks_last_year33

Release discipline

100Exceptional
How it's scored
27/27Ships releases28 releases published
36/36Release recencylatest release 0 days ago
27/27Release cadencea release every ~8.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count28
latest_release_tagv2026.7.18-beta.7
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases8.8
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?

33At Risk · 17% of overall
How it's scored
15.5/60Stars10 stars
2.5/25Forks3 forks
0/15Watchers1 watchers
Inputs used
forks3
stars10
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno

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
25.2/54Bus factor2 contributor(s) cover half of all commits
11.7/22.5Commit distributiontop contributor authored 48% of commits
13.5/13.5Contributor breadth10 contributors
3/10OpenSSF Scorecard: Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor2
contributors_sampled10
top_contributor_share0.481
How it's scored
42/42Issue resolution100% of issues closed
26.5/30PR acceptance105/119 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 7/26 approved changesets -- score normalized to 2
Inputs used
merged_prs105
open_issues0
closed_issues6
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio1
closed_unmerged_prs14
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
8/25Owner reach12 followers of HiDiHo01
20.8/25Track record39 public repos, account ~4 yr old
Inputs used
followers12
owner_typeUser
is_verified
owner_loginHiDiHo01
public_repos39
account_age_days1,660
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 history57 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagespython-frank-energie
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 workflows10 workflow(s)
24/24Tests present
16/16Linter config.flake8, .pylintrc
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests12 out of 12 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
10/10Topics5 topics
10/10Wiki
Inputs used
topicsautomation, homeassistant, homeassistant-integration, python, python3
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?

67Good · 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-Tests12 out of 12 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
1.5/7.5Code-ReviewFound 7/26 approved changesets -- score normalized to 2
0.8/2.5Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
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 5 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
2.5/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 5
5/5SASTSAST tool is run on all commits
2/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
6/7.5Vulnerabilities2 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.7
Excluded from scoring (no data or not applicable): Branch-Protection, 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.

32At Risk · 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.flake8, .pylintrc
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno data
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
5/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 5
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
51.1/55Manageable file sizes2/28 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes173,122
source_files_sampled28
oversized_source_files2

Key facts

10GitHub stars
10contributors
327commits, last 12 months
0days since last push
28releases
2bus factor
0open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 6.7 / 10
6.7aggregate

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 23:15 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-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 7/26 approved changesets -- score normalized to 2
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 5
10SASTSAST tool is run on all commits
4Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
8Vulnerabilities2 existing vulnerabilities detected
Direct dependencies 6
RegistryPackageVersion constraintManifest
PyPIaiohttp>=3.13.5pyproject.toml
PyPIPyJWT>=2.10.1pyproject.toml
PyPIcryptography>=44.0.1pyproject.toml
PyPItyping-extensions>=4.10.0pyproject.toml
PyPIpydantic>=2.0.0pyproject.toml
PyPIidna>=3.7pyproject.toml
All dependencies 94

Full resolved dependency set from the GitHub dependency graph: 6 direct and 88 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaiohttp3.14.1direct
PyPIcryptography49.0.0direct
PyPIidna3.18direct
PyPIpydantic2.13.4direct
PyPIpyjwt2.13.0direct
PyPItyping-extensions4.16.0direct
PyPIaiohappyeyeballs2.7.1indirect
PyPIaiosignal1.4.0indirect
PyPIannotated-doc0.0.4indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.14.2indirect
PyPIaresponsesindirect
PyPIaresponses3.0.0indirect
PyPIattrs26.1.0indirect
PyPIauthlib1.7.2indirect
PyPIbandit1.9.4indirect
PyPIblack26.5.1indirect
PyPIblacken-docs1.20.0indirect
PyPIcertifi2026.6.17indirect
PyPIcffi2.1.0indirect
PyPIcfgv3.5.0indirect
PyPIclick8.4.2indirect
PyPIcodespell2.4.3indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.15.2indirect
PyPIdefusedxml0.7.1indirect
PyPIdistlib0.4.3indirect
PyPIdparse0.6.4indirect
PyPIfilelock3.31.0indirect
PyPIfreezegunindirect
PyPIfreezegun1.5.5indirect
PyPIfrozenlist1.8.0indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIidentify2.6.19indirect
PyPIiniconfig2.3.0indirect
PyPIjinja23.1.6indirect
PyPIjoblib1.5.3indirect
PyPIjoserfc1.7.3indirect
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PyPImarshmallow4.3.0indirect
PyPImdurl0.1.2indirect
PyPImultidict6.7.1indirect
PyPImypyindirect
PyPImypy-extensions1.1.0indirect
PyPInltk3.10.0indirect
PyPInodeenv1.10.0indirect
PyPIpackaging26.2indirect
PyPIpathspec1.1.1indirect
PyPIpip26.1.2indirect
PyPIplatformdirs4.10.1indirect
PyPIpluggy1.6.0indirect
PyPIpoetry2.4.1indirect
PyPIpre-commit4.6.0indirect
PyPIpre-commit-hooks6.0.0indirect
PyPIpropcache0.5.2indirect
PyPIpycparser3.0indirect
PyPIpydantic-core2.46.4indirect
PyPIpygments2.20.0indirect
PyPIpytestindirect
PyPIpytest9.1.1indirect
PyPIpytest-asyncioindirect
PyPIpytest-asyncio1.4.0indirect
PyPIpytest-covindirect
PyPIpytest-cov7.1.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-discovery1.4.4indirect
PyPIpython-frank-energieindirect
PyPIpytokens0.4.1indirect
PyPIpyyaml6.0.3indirect
PyPIregex2026.7.10indirect
PyPIrequests2.34.2indirect
PyPIrich15.0.0indirect
PyPIruamel-yaml0.19.1indirect
PyPIruffindirect
PyPIruff0.15.22indirect
PyPIsafety3.8.1indirect
PyPIsafety-schemas0.0.16indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPIstevedore5.9.0indirect
PyPIsyrupyindirect
PyPIsyrupy5.5.3indirect
PyPItenacity9.1.4indirect
PyPItomlkit0.15.1indirect
PyPItqdm4.69.0indirect
PyPItruststore0.10.4indirect
PyPItyper0.25.1indirect
PyPItyping-inspection0.4.2indirect
PyPIvirtualenv21.6.1indirect
PyPIvulture2.16indirect
PyPIyarl1.24.2indirect
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.