Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 05:21 UTC

zigpy / zha-device-handlers

ZHA device handlers 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★ 1,124 stars⑂ 1,154 forkssince Nov 2018View on GitHub ↗

KindLibraryhow this is determined

#home-assistant #home-automation #hacktoberfest

zigpy/zha-device-handlers holds a health index of 91 out of 100, placing it in the Excellent band. It scores highest on Vitality (92/100) and lowest on Security (55/100). It was last updated today. 3 contributors account for most of its recent work.

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.

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)

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

120 followers24 public repossince Jul 2017

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

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish
PyPI	zha-quirks	2.2.0	-	164	15 days ago

Metrics by category

Vitality

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

92Excellent · 21% of overall

Development activity

86Excellent

How it's scored

36/36	Push recency — last push 0 days ago
21.5/36	Commit cadence — 31/52 weeks with commits
18/18	Commit volume — 238 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	238
human_commit_share	0.99
days_since_last_push	0
active_weeks_last_year	31

Release discipline

100Exceptional

How it's scored

27/27	Ships releases — 100 releases published
36/36	Release recency — latest release 15 days ago
27/27	Release cadence — a release every ~18.5 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	100
latest_release_tag	2.2.0
releases_from_tags	no
days_since_latest_release	15
mean_days_between_releases	18.5

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

Popularity & adoption

83Excellent

How it's scored

49.5/60	Stars — 1,124 stars
25/25	Forks — 1,154 forks
8.8/15	Watchers — 39 watchers

Inputs used

forks	1,154
stars	1,124
watchers	39
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

57Moderate

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (Apache-2.0)
0/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
6.3/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	2
has_contributing	no
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	codecov.io, github.com
has_pull_request_template	yes

Sustainability & Governance

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

84Excellent · 23% of overall

Maintainer resilience (bus factor)

75Good

How it's scored

36/54	Bus factor — 3 contributor(s) cover half of all commits
15.8/22.5	Commit distribution — top contributor authored 30% of commits
13.5/13.5	Contributor breadth — 99 contributors
10/10	OpenSSF Scorecard: Contributors — project has 16 contributing companies or organizations

Inputs used

bus_factor	3
contributors_sampled	99
top_contributor_share	0.299

Issue & PR responsiveness

80Excellent

How it's scored

35.6/42	Issue resolution — 85% of issues closed
24.2/30	PR acceptance — 1,692/2,097 decided PRs merged
8.1/13	Newcomer PR acceptance — 5/8 first-time contributors' PRs merged in 30d
12/15	OpenSSF Scorecard: Code-Review — Found 25/30 approved changesets -- score normalized to 8

Inputs used

merged_prs	1,692
open_issues	403
closed_issues	2,249
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	19
prs_decided_30d	26
issue_closed_ratio	0.848
closed_unmerged_prs	405
first_time_authors_30d	8
first_time_prs_merged_30d	5
first_time_prs_decided_30d	8

Ownership & stewardship

84Excellent

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain — verified-domain status not read for this organization
15/25	Owner reach — 120 followers of zigpy
22.2/25	Track record — 24 public repos, account ~9 yr old

Inputs used

followers	120
owner_type	Organization
is_verified	—
owner_login	zigpy
public_repos	24
account_age_days	3,311

Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 15 days ago
20/20	Version history — 164 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	zha-quirks
ecosystems	pypi
any_deprecated	no
min_days_since_publish	15

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall

Engineering practices

94Exceptional

How it's scored

24/24	CI workflows — 3 workflow(s)
24/24	Tests present
16/16	Linter config
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

60Moderate

How it's scored

30/30	README
0/25	Documentation directory
0/15	Documentation / homepage site
10/10	Repository description
10/10	Topics — 3 topics
10/10	Wiki

Inputs used

topics	home-assistant, home-automation, hacktoberfest
has_wiki	yes
homepage	—
docs_site	—
has_readme	yes
has_docs_dir	no
has_description	yes

Security

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

55Moderate · 16% of overall

Security posture

44Weak

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
2.2/7.5	Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5	CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6/7.5	Code-Review — Found 25/30 approved changesets -- score normalized to 8
2.5/2.5	Contributors — project has 16 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5	Dependency-Update-Tool — no update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
0/5	Packaging — no data
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 38 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	16
scorecard_version	v5.5.0
checks_inconclusive	2
scorecard_aggregate	4.4

Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	40
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:zha-quirks@2.2.0 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

Agent context & guidance

85Excellent

How it's scored

45/45	Agent instructions — .github/copilot-instructions.md, AGENTS.md, CLAUDE.md
0/15	Machine-readable docs (llms.txt)
40/40	Legible commit history — 94 of 99 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.949
agent_instruction_files	.github/copilot-instructions.md, AGENTS.md, CLAUDE.md
agent_instruction_max_bytes	26,225

Verify loop (build / test / typecheck)

43Weak

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
11/11	Lint / format config
0/11	Static type checking
10/10	Reproducible environment — lockfile
0/10	Demonstrated agent practice — no agent-authored commits among the last 100
0/8	Automated maintenance — no automated dependency updates observed
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Inputs used

has_nix	no
has_tests	yes
lockfiles	uv.lock
has_dockerfile	no
typed_language	no
bootstrap_files	—
has_devcontainer	no
has_linter_config	yes
typecheck_configs	—
agent_commit_share	0
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

54Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
54.4/55	Manageable file sizes — 6/524 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	103,486
source_files_sampled	524
oversized_source_files	6

Key facts

1,124GitHub stars

99contributors

238commits, last 12 months

0days since last push

100releases

3bus factor

403open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
First-time contributor figures cover 12 of 22 authors (cap 12)

More detail

Star and fork history 0 ★ / 1,154 ⇿

0Stars

1,154Forks

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.

Major 2Minor 4Patch 94

Each point covers 5 days.

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 · 2026-08-13 05:20 UTC

10	Binary-Artifacts	no binaries found in the repo
3	Branch-Protection	branch protection is not maximal on development and all release branches
10	CI-Tests	30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
8	Code-Review	Found 25/30 approved changesets -- score normalized to 8
10	Contributors	project has 16 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
0	Dependency-Update-Tool	no update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
n/a	Packaging	packaging workflow not detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
0	SAST	SAST tool is not run on all commits -- score normalized to 0
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	38 existing vulnerabilities detected

Direct dependencies 2

Registry	Package	Version constraint	Manifest
PyPI	zigpy	`>=2.0.0`	pyproject.toml
PyPI	zha	`>=2.0.0`	pyproject.toml

All dependencies 95

Full resolved dependency set from the GitHub dependency graph: 2 direct and 93 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	zha	`2.0.0`	direct
PyPI	zigpy	`2.0.0`	direct
PyPI	aiohappyeyeballs	`2.6.1`	indirect
PyPI	aiohttp	`3.13.3`	indirect
PyPI	aiosignal	`1.4.0`	indirect
PyPI	aiosqlite	`0.21.0`	indirect
PyPI	annotated-doc	`0.0.4`	indirect
PyPI	ast-serialize	`0.5.0`	indirect
PyPI	astroid	`4.0.4`	indirect
PyPI	attrs	`26.1.0`	indirect
PyPI	bellows	`0.49.2`	indirect
PyPI	certifi	`2026.2.25`	indirect
PyPI	cffi	`2.0.0`	indirect
PyPI	cfgv	`3.5.0`	indirect
PyPI	charset-normalizer	`3.4.6`	indirect
PyPI	click	`8.3.1`	indirect
PyPI	click-log	`0.4.0`	indirect
PyPI	codecov	`2.1.13`	indirect
PyPI	codespell	`2.4.2`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	coloredlogs	`15.0.1`	indirect
PyPI	colorlog	`6.10.1`	indirect
PyPI	colorzero	`2.0`	indirect
PyPI	coverage	`7.13.5`	indirect
PyPI	coveralls	`4.1.0`	indirect
PyPI	crccheck	`1.3.1`	indirect
PyPI	cryptography	`46.0.5`	indirect
PyPI	dill	`0.4.1`	indirect
PyPI	distlib	`0.4.0`	indirect
PyPI	execnet	`2.1.2`	indirect
PyPI	filelock	`3.25.2`	indirect
PyPI	frozendict	`2.4.7`	indirect
PyPI	frozenlist	`1.8.0`	indirect
PyPI	gpiozero	`2.0.1`	indirect
PyPI	humanfriendly	`10.0`	indirect
PyPI	identify	`2.6.18`	indirect
PyPI	idna	`3.11`	indirect
PyPI	iniconfig	`2.3.0`	indirect
PyPI	isort	`8.0.1`	indirect
PyPI	jsonschema	`4.26.0`	indirect
PyPI	jsonschema-specifications	`2025.9.1`	indirect
PyPI	librt	`0.11.0`	indirect
PyPI	markdown-it-py	`4.0.0`	indirect
PyPI	mashumaro	`3.22`	indirect
PyPI	mccabe	`0.7.0`	indirect
PyPI	mdurl	`0.1.2`	indirect
PyPI	multidict	`6.7.1`	indirect
PyPI	mypy	`2.1.0`	indirect
PyPI	mypy-extensions	`1.1.0`	indirect
PyPI	nodeenv	`1.10.0`	indirect
PyPI	packaging	`26.0`	indirect
PyPI	pathspec	`1.1.1`	indirect
PyPI	platformdirs	`4.9.4`	indirect
PyPI	pluggy	`1.6.0`	indirect
PyPI	pre-commit	`4.5.1`	indirect
PyPI	propcache	`0.4.1`	indirect
PyPI	pycparser	`3.0`	indirect
PyPI	pygments	`2.19.2`	indirect
PyPI	pylint	`4.0.5`	indirect
PyPI	pyreadline3	`3.5.6`	indirect
PyPI	pytest	`9.0.2`	indirect
PyPI	pytest-asyncio	`1.3.0`	indirect
PyPI	pytest-cov	`7.1.0`	indirect
PyPI	pytest-github-actions-annotate-failures	`0.4.0`	indirect
PyPI	pytest-sugar	`1.1.1`	indirect
PyPI	pytest-timeout	`2.4.0`	indirect
PyPI	pytest-xdist	`3.8.0`	indirect
PyPI	python-dateutil	`2.9.0.post0`	indirect
PyPI	python-discovery	`1.2.0`	indirect
PyPI	pyusb	`1.3.1`	indirect
PyPI	pywin32	`312`	indirect
PyPI	pyyaml	`6.0.3`	indirect
PyPI	referencing	`0.37.0`	indirect
PyPI	requests	`2.32.5`	indirect
PyPI	rich	`14.3.3`	indirect
PyPI	rpds-py	`0.30.0`	indirect
PyPI	ruff	`0.15.17`	indirect
PyPI	serialx	`1.8.2`	indirect
PyPI	setuptools	`82.0.1`	indirect
PyPI	shellingham	`1.5.4`	indirect
PyPI	six	`1.17.0`	indirect
PyPI	termcolor	`3.3.0`	indirect
PyPI	time-machine	`2.19.0`	indirect
PyPI	tomlkit	`0.14.0`	indirect
PyPI	typer	`0.24.1`	indirect
PyPI	typing-extensions	`4.15.0`	indirect
PyPI	urllib3	`2.6.3`	indirect
PyPI	virtualenv	`21.2.0`	indirect
PyPI	voluptuous	`0.16.0`	indirect
PyPI	yarl	`1.23.0`	indirect
PyPI	zigpy-deconz	`0.25.5`	indirect
PyPI	zigpy-xbee	`0.21.1`	indirect
PyPI	zigpy-zigate	`0.14.0`	indirect
PyPI	zigpy-ziggurat	`1.0.1`	indirect
PyPI	zigpy-znp	`1.1.0`	indirect

Dependency advisories 0

Installing pypi:zha-quirks@2.2.0 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.

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 statistics — PyPI.

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

More detail

Feedback

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