Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 21:23 UTC

yourlabs / django-autocomplete-light

A fresh approach to autocomplete implementations, specially for Django.

Python · JavaScriptMIT★ 1,870 stars⑂ 460 forkssince May 2012View on GitHub ↗

KindLibraryNetwork servicehow this is determined

yourlabs/django-autocomplete-light holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Engineering Quality (90/100) and lowest on Security (50/100). It was last updated 8 days ago. A single contributor accounts for most of its recent work.

overall / 100

Good

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 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

YourLabsOrganization

25 followers67 public repossince Sep 2011

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	Tags
PyPI	django-autocomplete-light	5.0.0	685,897	230	91 days ago	django autocomplete

Metrics by category

Vitality

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

56Moderate · 21% of overall

Development activity

64Moderate

How it's scored

28.8/36	Push recency — last push 8 days ago
7.6/36	Commit cadence — 11/52 weeks with commits
18/18	Commit volume — 133 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 18 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	133
human_commit_share	1
days_since_last_push	8
active_weeks_last_year	11

Release discipline

44Weak

How it's scored

27/27	Ships releases — 1 releases published
0/36	Release recency — latest release 4,125 days ago
12.6/27	Release cadence — cadence unknown (single release)
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	1
latest_release_tag	2.2.0
releases_from_tags	no
days_since_latest_release	4,125
mean_days_between_releases	—

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?

76Good · 17% of overall

Popularity & adoption

85Excellent

How it's scored

53.1/60	Stars — 1,870 stars
22.2/25	Forks — 460 forks
9.8/15	Watchers — 59 watchers

Inputs used

forks	460
stars	1,870
watchers	59
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

50Moderate

How it's scored

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

Inputs used

has_readme	yes
has_license	yes
readme_badges	0
has_contributing	no
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	—
has_pull_request_template	no

Ecosystem adoption (downloads)

97Exceptional

How it's scored

77.8/80	Monthly downloads — 685,897 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	django-autocomplete-light
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	685,897
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?

64Moderate · 23% of overall

Maintainer resilience (bus factor)

38Weak

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
5.1/22.5	Commit distribution — top contributor authored 77% of commits
13.5/13.5	Contributor breadth — 100 contributors
10/10	OpenSSF Scorecard: Contributors — project has 56 contributing companies or organizations

Inputs used

bus_factor	1
contributors_sampled	100
top_contributor_share	0.772

Issue & PR responsiveness

65Good

How it's scored

31.8/42	Issue resolution — 76% of issues closed
20.6/30	PR acceptance — 375/546 decided PRs merged
13/13	Newcomer PR acceptance — 1/1 first-time contributors' PRs merged in 30d
0/15	OpenSSF Scorecard: Code-Review — Found 1/19 approved changesets -- score normalized to 0

Inputs used

merged_prs	375
open_issues	211
closed_issues	662
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	2
prs_decided_30d	2
issue_closed_ratio	0.758
closed_unmerged_prs	171
first_time_authors_30d	1
first_time_prs_merged_30d	1
first_time_prs_decided_30d	1

Ownership & stewardship

65Good

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain
10.2/25	Owner reach — 25 followers of yourlabs
25/25	Track record — 67 public repos, account ~15 yr old

Inputs used

followers	25
owner_type	Organization
is_verified	no
owner_login	yourlabs
public_repos	67
account_age_days	5,486

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 91 days ago
20/20	Version history — 230 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	django-autocomplete-light
ecosystems	pypi
any_deprecated	no
min_days_since_publish	91

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall

Engineering practices

84Excellent

How it's scored

24/24	CI workflows — 1 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff]), tox.ini
0/9.6	Pre-commit hooks
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 5 out of 5 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	no

Documentation

100Exceptional

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://django-autocomplete-light.readthedocs.io
10/10	Repository description
10/10	Topics — 3 topics
10/10	Wiki

Inputs used

topics	python, django, autocomplete
has_wiki	yes
homepage	https://django-autocomplete-light.readthedocs.io
docs_site	https://django-autocomplete-light.readthedocs.io
has_readme	yes
has_docs_dir	yes
has_description	yes

Security

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

50Moderate · 16% of overall

Security posture

38Weak

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — no data
2.5/2.5	CI-Tests — 5 out of 5 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
0/7.5	Code-Review — Found 1/19 approved changesets -- score normalized to 0
2.5/2.5	Contributors — project has 56 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 — 18 commit(s) and 0 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 — 11 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	15
scorecard_version	v5.5.0
checks_inconclusive	3
scorecard_aggregate	3.8

Excluded from scoring (no data or not applicable): Branch-Protection, 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	3
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:django-autocomplete-light@5.0.0 runtime dependency closure — what installing the published package pulls in — 3 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.

73Good · 4% of overall

Agent context & guidance

85Excellent

How it's scored

45/45	Agent instructions — CLAUDE.md
0/15	Machine-readable docs (llms.txt)
40/40	Legible commit history — 85 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.85
agent_instruction_files	CLAUDE.md
agent_instruction_max_bytes	1,058

Verify loop (build / test / typecheck)

71Good

How it's scored

18/18	One-command bootstrap — docs/Makefile
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff]), tox.ini
0/11	Static type checking
10/10	Reproducible environment — lockfile
10/10	Demonstrated agent practice — 64 of the last 100 commits agent-authored or agent-credited
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	package-lock.json
has_dockerfile	no
typed_language	no
bootstrap_files	docs/Makefile
has_devcontainer	no
has_linter_config	yes
typecheck_configs	—
agent_commit_share	0.64
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

55Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
55/55	Manageable file sizes — 0/405 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	32,533
source_files_sampled	405
oversized_source_files	0

Key facts

1,870GitHub stars

100contributors

133commits, last 12 months

8days since last push

1releases

1bus factor

211open issues

npm, PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
Could not fetch npm package 'django-autocomplete-light' from its registry

More detail

Star and fork history 0 ★ / 460 ⇿

0Stars

460Forks

1Releases

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.

Major 0Minor 1Patch 0

Each point covers 14 days.

OpenSSF Scorecard 3.8 / 10

3.8aggregate

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 21:23 UTC

10	Binary-Artifacts	no binaries found in the repo
n/a	Branch-Protection	internal 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
10	CI-Tests	5 out of 5 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
0	Code-Review	Found 1/19 approved changesets -- score normalized to 0
10	Contributors	project has 56 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	18 commit(s) and 0 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	11 existing vulnerabilities detected

Direct dependencies 2

Registry	Package	Version constraint	Manifest
npm	semver	`latest`	package.json
PyPI	django	`>=5.2`	pyproject.toml

All dependencies 145

Full resolved dependency set from the GitHub dependency graph: 3 direct and 142 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
npm	semver	`5.7.2`	direct
npm	semver	`7.5.4`	direct
PyPI	django	`—`	direct
npm	ansi-regex	`5.0.1`	indirect
npm	ansi-styles	`3.2.1`	indirect
npm	ansi-styles	`4.3.0`	indirect
npm	balanced-match	`1.0.2`	indirect
npm	brace-expansion	`1.1.11`	indirect
npm	call-bind	`1.0.2`	indirect
npm	chalk	`2.4.2`	indirect
npm	cliui	`7.0.4`	indirect
npm	color-convert	`1.9.3`	indirect
npm	color-convert	`2.0.1`	indirect
npm	color-name	`1.1.3`	indirect
npm	color-name	`1.1.4`	indirect
npm	commander	`2.20.3`	indirect
npm	concat	`1.0.3`	indirect
npm	concat-map	`0.0.1`	indirect
npm	copyfiles	`2.4.1`	indirect
npm	core-util-is	`1.0.3`	indirect
npm	cross-spawn	`6.0.5`	indirect
npm	define-properties	`1.1.3`	indirect
npm	emoji-regex	`8.0.0`	indirect
npm	error-ex	`1.3.2`	indirect
npm	es-abstract	`1.19.1`	indirect
npm	es-to-primitive	`1.2.1`	indirect
npm	escalade	`3.1.1`	indirect
npm	escape-string-regexp	`1.0.5`	indirect
npm	fs.realpath	`1.0.0`	indirect
npm	function-bind	`1.1.1`	indirect
npm	get-caller-file	`2.0.5`	indirect
npm	get-intrinsic	`1.1.1`	indirect
npm	get-symbol-description	`1.0.0`	indirect
npm	glob	`7.2.0`	indirect
npm	graceful-fs	`4.2.8`	indirect
npm	has	`1.0.3`	indirect
npm	has-bigints	`1.0.1`	indirect
npm	has-flag	`3.0.0`	indirect
npm	has-symbols	`1.0.2`	indirect
npm	has-tostringtag	`1.0.0`	indirect
npm	hosted-git-info	`2.8.9`	indirect
npm	inflight	`1.0.6`	indirect
npm	inherits	`2.0.4`	indirect
npm	internal-slot	`1.0.3`	indirect
npm	is-arrayish	`0.2.1`	indirect
npm	is-bigint	`1.0.4`	indirect
npm	is-boolean-object	`1.1.2`	indirect
npm	is-callable	`1.2.4`	indirect
npm	is-core-module	`2.8.0`	indirect
npm	is-date-object	`1.0.5`	indirect
npm	is-fullwidth-code-point	`3.0.0`	indirect
npm	is-negative-zero	`2.0.1`	indirect
npm	is-number-object	`1.0.6`	indirect
npm	is-regex	`1.1.4`	indirect
npm	is-shared-array-buffer	`1.0.1`	indirect
npm	is-string	`1.0.7`	indirect
npm	is-symbol	`1.0.4`	indirect
npm	is-weakref	`1.0.1`	indirect
npm	isarray	`0.0.1`	indirect
npm	isarray	`1.0.0`	indirect
npm	isexe	`2.0.0`	indirect
npm	json-parse-better-errors	`1.0.2`	indirect
npm	load-json-file	`4.0.0`	indirect
npm	lru-cache	`6.0.0`	indirect
npm	memorystream	`0.3.1`	indirect
npm	minimatch	`3.1.2`	indirect
npm	mkdirp	`1.0.4`	indirect
npm	nice-try	`1.0.5`	indirect
npm	noms	`0.0.0`	indirect
npm	normalize-package-data	`2.5.0`	indirect
npm	npm-run-all	`4.1.5`	indirect
npm	object-inspect	`1.11.0`	indirect
npm	object-keys	`1.1.1`	indirect
npm	object.assign	`4.1.2`	indirect
npm	once	`1.4.0`	indirect
npm	parse-json	`4.0.0`	indirect
npm	path-is-absolute	`1.0.1`	indirect
npm	path-key	`2.0.1`	indirect
npm	path-parse	`1.0.7`	indirect
npm	path-type	`3.0.0`	indirect
npm	pidtree	`0.3.1`	indirect
npm	pify	`3.0.0`	indirect
npm	process-nextick-args	`2.0.1`	indirect
npm	read-pkg	`3.0.0`	indirect
npm	readable-stream	`1.0.34`	indirect
npm	readable-stream	`2.3.7`	indirect
npm	require-directory	`2.1.1`	indirect
npm	resolve	`1.20.0`	indirect
npm	safe-buffer	`5.1.2`	indirect
npm	select2	`4.1.0-rc.0`	indirect
npm	shebang-command	`1.2.0`	indirect
npm	shebang-regex	`1.0.0`	indirect
npm	shell-quote	`1.7.3`	indirect
npm	side-channel	`1.0.4`	indirect
npm	spdx-correct	`3.1.1`	indirect
npm	spdx-exceptions	`2.3.0`	indirect
npm	spdx-expression-parse	`3.0.1`	indirect
npm	spdx-license-ids	`3.0.11`	indirect
npm	string-width	`4.2.3`	indirect
npm	string.prototype.padend	`3.1.3`	indirect
npm	string.prototype.trimend	`1.0.4`	indirect
npm	string.prototype.trimstart	`1.0.4`	indirect
npm	string_decoder	`0.10.31`	indirect
npm	string_decoder	`1.1.1`	indirect
npm	strip-ansi	`6.0.1`	indirect
npm	strip-bom	`3.0.0`	indirect
npm	supports-color	`5.5.0`	indirect
npm	through2	`2.0.5`	indirect
npm	uglify-js	`3.14.3`	indirect
npm	unbox-primitive	`1.0.1`	indirect
npm	untildify	`4.0.0`	indirect
npm	util-deprecate	`1.0.2`	indirect
npm	validate-npm-package-license	`3.0.4`	indirect
npm	which	`1.3.1`	indirect
npm	which-boxed-primitive	`1.0.2`	indirect
npm	wrap-ansi	`7.0.0`	indirect
npm	wrappy	`1.0.2`	indirect
npm	xtend	`4.0.2`	indirect
npm	y18n	`5.0.8`	indirect
npm	yallist	`4.0.0`	indirect
npm	yargs	`16.2.0`	indirect
npm	yargs-parser	`20.2.9`	indirect
PyPI	coverage	`—`	indirect
PyPI	django-extensions	`—`	indirect
PyPI	django-nested-admin	`—`	indirect
PyPI	django-querysetsequence	`—`	indirect
PyPI	django-taggit	`—`	indirect
PyPI	djhacker	`—`	indirect
PyPI	furo	`—`	indirect
PyPI	idna	`—`	indirect
PyPI	pygments	`—`	indirect
PyPI	pytest	`—`	indirect
PyPI	pytest-cov	`—`	indirect
PyPI	pytest-django	`—`	indirect
PyPI	pytest-splinter	`—`	indirect
PyPI	pytest-xdist	`—`	indirect
PyPI	requests	`—`	indirect
PyPI	selenium	`—`	indirect
PyPI	setuptools	`—`	indirect
PyPI	splinter	`—`	indirect
PyPI	sqlparse	`—`	indirect
PyPI	tenacity	`—`	indirect
PyPI	urllib3	`—`	indirect
PyPI	whitenoise	`—`	indirect
PyPI	zipp	`—`	indirect

Dependency advisories 0

Installing pypi:django-autocomplete-light@5.0.0 pulls in 3 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 v0.34.0 — 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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