Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 23:40 UTC

zigpy / zha-device-handlers

ZHA quirks bridge the functionality gap created when manufacturers deviate from the ZCL specification, handling deviations and exceptions by parsing custom messages to and from Zigbee devices.

PythonApache-2.0★ 1,138 stars⑂ 1,185 forkssince Nov 2018View on GitHub ↗

zigpy/zha-device-handlers holds a health index of 91 out of 100, placing it in the Excellent band. It scores highest on Vitality (91/100) and lowest on AI Readiness (60/100). It was last updated 3 days ago. 3 contributors account for most of its recent work.

91
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.

91
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 77 is calibrated to 91 on the published index scale (record calibration 2026-08-02).

Ownership

zigpyOrganization
126 followers24 public repossince Jul 2017

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIzha-quirks2.2.2-1669 days ago

Metrics by category

Vitality

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

91Excellent · 21% of overall
How it's scored
36/36Push recency — last push 3 days ago
20.8/36Commit cadence — 30/52 weeks with commits
18/18Commit volume — 223 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year223
human_commit_share0.99
days_since_last_push3
active_weeks_last_year30

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 9 days ago
27/27Release cadence — a release every ~20.9 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tag2.2.2
releases_from_tagsno
days_since_latest_release9
mean_days_between_releases20.9
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?

71Good · 17% of overall
How it's scored
49.6/60Stars — 1,138 stars
25/25Forks — 1,185 forks
8.8/15Watchers — 39 watchers
Inputs used
forks1,185
stars1,138
watchers39
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges2
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com
has_pull_request_templateyes

Sustainability & Governance

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

78Good · 23% of overall
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
15.8/22.5Commit distribution — top contributor authored 30% of commits
13.5/13.5Contributor breadth — 99 contributors
10/10OpenSSF Scorecard: Contributors — project has 16 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled99
top_contributor_share0.298
How it's scored
35.4/42Issue resolution — 84% of issues closed
24.1/30PR acceptance — 1,698/2,118 decided PRs merged
1.2/13Newcomer PR acceptance — 1/11 first-time contributors' PRs merged in 30d
12/15OpenSSF Scorecard: Code-Review — Found 26/30 approved changesets -- score normalized to 8
Inputs used
merged_prs1,698
open_issues422
closed_issues2,253
prs_merged_7d0
prs_decided_7d8
prs_merged_30d6
prs_decided_30d20
issue_closed_ratio0.842
closed_unmerged_prs420
first_time_authors_30d5
first_time_prs_merged_30d1
first_time_prs_decided_30d11
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
15.1/25Owner reach — 126 followers of zigpy
22.2/25Track record — 24 public repos, account ~9 yr old
Inputs used
followers126
owner_typeOrganization
is_verifiedno
owner_loginzigpy
public_repos24
account_age_days3,346

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 9 days ago
20/20Version history — 166 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageszha-quirks
ecosystemspypi
any_deprecatedno
min_days_since_publish9

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff], [tool.pylint])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 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

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 3 topics
10/10Wiki
Inputs used
topicshome-assistant, home-automation, hacktoberfest
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

62Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6/7.5Code-Review — Found 26/30 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 16 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.2
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages40
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:zha-quirks@2.2.2 runtime dependency closure — what installing the published package pulls in — 40 packages. 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.

60Moderate · 4% of overall
How it's scored
45/45Agent instructions — .github/copilot-instructions.md, AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 93 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.939
agent_instruction_files.github/copilot-instructions.md, AGENTS.md, CLAUDE.md
agent_instruction_max_bytes26,225
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff], [tool.pylint])
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
54.4/55Manageable file sizes — 6/524 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes103,486
source_files_sampled524
oversized_source_files6

Key facts

1,138GitHub stars
99contributors
223commits, last 12 months
3days since last push
100releases
3bus factor
422open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'zha-quirks' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced

More detail

Star and fork history 0 ★ / 1,185 ⇿
0Stars
1,185Forks
100Releases

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.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

02004006008001,0001,2001,185132021-092024-032026-09
Major 2Minor 4Patch 94

Each point covers 5 days.

OpenSSF Scorecard 5.2 / 10
5.2aggregate

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 · 2026-09-17 23:39 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 26/30 approved changesets -- score normalized to 8
10Contributorsproject has 16 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 2 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
PyPIzigpy>=2.2.0pyproject.toml
PyPIzha>=2.0.0pyproject.toml
All dependencies 96

Full resolved dependency set from the GitHub dependency graph: 2 direct and 94 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIzha2.2.2direct
PyPIzigpy2.2.0direct
PyPIaiohappyeyeballs2.7.1indirect
PyPIaiohttp3.14.3indirect
PyPIaiosignal1.4.0indirect
PyPIaiospinel1.2.0indirect
PyPIaiosqlite0.21.0indirect
PyPIannotated-doc0.0.5indirect
PyPIast-serialize0.10.0indirect
PyPIastroid4.0.4indirect
PyPIattrs26.1.0indirect
PyPIbellows1.0.1indirect
PyPIcertifi2026.7.22indirect
PyPIcffi2.1.1indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.5.1indirect
PyPIclick8.5.0indirect
PyPIclick-log0.4.0indirect
PyPIcodecov2.1.13indirect
PyPIcodespell2.4.3indirect
PyPIcolorama0.4.6indirect
PyPIcoloredlogs15.0.1indirect
PyPIcolorlog6.12.0indirect
PyPIcolorzero2.0indirect
PyPIcoverage7.16.0indirect
PyPIcoveralls4.1.0indirect
PyPIcrccheck1.3.1indirect
PyPIcryptography50.0.1indirect
PyPIdill0.4.1indirect
PyPIdistlib0.4.3indirect
PyPIexecnet2.1.2indirect
PyPIfilelock3.32.5indirect
PyPIfrozendict2.4.7indirect
PyPIfrozenlist1.8.0indirect
PyPIgpiozero2.0.1.post3indirect
PyPIhumanfriendly10.0indirect
PyPIidentify2.6.19indirect
PyPIidna3.19indirect
PyPIiniconfig2.3.0indirect
PyPIisort9.0.1indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPIlibrt0.15.0indirect
PyPImarkdown-it-py4.2.0indirect
PyPImashumaro3.22indirect
PyPImccabe0.7.0indirect
PyPImdurl0.1.2indirect
PyPImultidict6.7.1indirect
PyPImypy2.1.0indirect
PyPImypy-extensions1.1.0indirect
PyPInodeenv1.10.0indirect
PyPIpackaging26.3indirect
PyPIpathspec1.1.1indirect
PyPIplatformdirs4.11.7indirect
PyPIpluggy1.6.0indirect
PyPIpre-commit4.6.2indirect
PyPIpropcache0.5.2indirect
PyPIpycparser3.0indirect
PyPIpygments2.21.0indirect
PyPIpylint4.0.8indirect
PyPIpyreadline33.5.6indirect
PyPIpytest9.1.1indirect
PyPIpytest-asyncio1.4.0indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-github-actions-annotate-failures0.4.2indirect
PyPIpytest-sugar1.1.1indirect
PyPIpytest-timeout2.4.0indirect
PyPIpytest-xdist3.8.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-discovery1.6.0indirect
PyPIpyusb1.3.1indirect
PyPIpywin32312indirect
PyPIpyyaml6.0.3indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIrich15.0.0indirect
PyPIrpds-py2026.6.3indirect
PyPIruff0.15.17indirect
PyPIserialx1.10.0indirect
PyPIsetuptools84.0.0indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPItermcolor3.3.0indirect
PyPItime-machine2.19.0indirect
PyPItomlkit0.15.1indirect
PyPItyper0.27.2indirect
PyPItyping-extensions4.16.0indirect
PyPIurllib32.7.0indirect
PyPIvirtualenv21.7.8indirect
PyPIvoluptuous0.16.0indirect
PyPIyarl1.24.5indirect
PyPIzigpy-deconz1.0.0indirect
PyPIzigpy-xbee0.22.0indirect
PyPIzigpy-zigate0.14.0indirect
PyPIzigpy-ziggurat1.1.1indirect
PyPIzigpy-znp1.1.0indirect
Dependency advisories 0

Installing pypi:zha-quirks@2.2.2 pulls in 40 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

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 v0.34.0 — full methodology · metrics wiki.

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