Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-19 09:20 UTC

chemosim-lab / ProLIF

Interaction Fingerprints for protein-ligand complexes and more

PythonApache-2.0★ 540 stars⑂ 104 forkssince Jan 2020View on GitHub ↗

#molecular-dynamics #rdkit #drug-design #docking #cheminformatics #mdanalysis #drug-discovery

chemosim-lab/ProLIF holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Engineering Quality (86/100) and lowest on Security (50/100). It was last updated 48 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

ChemSenSim LabOrganization

31 followers14 public repossince Jul 2019

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	prolif	2.2.1	78,934	30	53 days ago	science chemistry drug-design cheminformatics chemoinformatics molecular-dynamics interaction-fingerprint

Metrics by category

Vitality

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

62Moderate · 21% of overall

Development activity

48Weak

How it's scored

18/36	Push recency — last push 48 days ago
7.6/36	Commit cadence — 11/52 weeks with commits
13.4/18	Commit volume — 30 commits in the last year
9/10	OpenSSF Scorecard: Maintained — 9 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 9

Inputs used

commits_last_year	30
human_commit_share	1
days_since_last_push	48
active_weeks_last_year	11

Release discipline

84Excellent

How it's scored

27/27	Ships releases — 16 releases published
36/36	Release recency — latest release 53 days ago
12.6/27	Release cadence — a release every ~149.8 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	16
latest_release_tag	v2.2.1
releases_from_tags	no
days_since_latest_release	53
mean_days_between_releases	149.8

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?

72Good · 17% of overall

Popularity & adoption

67Good

How it's scored

44.3/60	Stars — 540 stars
16.8/25	Forks — 104 forks
6/15	Watchers — 13 watchers

Inputs used

forks	104
stars	540
watchers	13
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

70Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (Apache-2.0)
18/18	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	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	—
has_pull_request_template	no

Ecosystem adoption (downloads)

82Excellent

How it's scored

65.3/80	Monthly downloads — 78,934 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	prolif
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	78,934
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)

35Weak

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
2.7/22.5	Commit distribution — top contributor authored 88% of commits
13.5/13.5	Contributor breadth — 18 contributors
10/10	OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations

Inputs used

bus_factor	1
contributors_sampled	18
top_contributor_share	0.882

Issue & PR responsiveness

75Good

How it's scored

38.2/42	Issue resolution — 91% of issues closed
23.7/30	PR acceptance — 87/110 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
3/15	OpenSSF Scorecard: Code-Review — Found 6/28 approved changesets -- score normalized to 2

Inputs used

merged_prs	87
open_issues	18
closed_issues	183
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	0
prs_decided_30d	0
issue_closed_ratio	0.91
closed_unmerged_prs	23
first_time_authors_30d	0
first_time_prs_merged_30d	0
first_time_prs_decided_30d	0

Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

61Moderate

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain
10.8/25	Owner reach — 31 followers of chemosim-lab
20.6/25	Track record — 14 public repos, account ~7 yr old

Inputs used

followers	31
owner_type	Organization
is_verified	no
owner_login	chemosim-lab
public_repos	14
account_age_days	2,614

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 53 days ago
20/20	Version history — 30 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	prolif
ecosystems	pypi
any_deprecated	no
min_days_since_publish	53

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall

Engineering practices

84Excellent

How it's scored

24/24	CI workflows — 6 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff], [tool.black], [tool.isort])
0/9.6	Pre-commit hooks
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 20 out of 20 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

90Excellent

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://prolif.readthedocs.io
10/10	Repository description
10/10	Topics — 7 topics
0/10	Wiki

Inputs used

topics	molecular-dynamics, rdkit, drug-design, docking, cheminformatics, mdanalysis, drug-discovery
has_wiki	no
homepage	https://prolif.readthedocs.io
docs_site	https://prolif.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

37Weak

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
3/7.5	Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5	CI-Tests — 20 out of 20 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
1.5/7.5	Code-Review — Found 6/28 approved changesets -- score normalized to 2
2.5/2.5	Contributors — project has 5 contributing companies or organizations
0/10	Dangerous-Workflow — 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
6.8/7.5	Maintained — 9 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 9
5/5	Packaging — packaging workflow detected
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5	SAST — SAST tool is run on all commits
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 — 54 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	17
scorecard_version	v5.5.0
checks_inconclusive	1
scorecard_aggregate	3.7

Excluded from scoring (no data or not applicable): 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	29
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:prolif@2.2.1 runtime dependency closure — what installing the published package pulls in — 29 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.

57Moderate · 4% of overall

Agent context & guidance

27At Risk

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
26.7/40	Legible commit history — 50 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.5
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

54Moderate

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff], [tool.black], [tool.isort])
11/11	Static type checking — prolif/py.typed
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	prolif/py.typed
agent_commit_share	0
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

82Excellent

How it's scored

27/45	Type-checkable code — Python with type-check config (prolif/py.typed)
55/55	Manageable file sizes — 0/53 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	54,761
source_files_sampled	53
oversized_source_files	0

Machine-readable interfaces

100Exceptional

How it's scored

0/40	API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20	MCP server — not applicable to this kind of software
40/40	Runnable examples — notebooks

Inputs used

example_dirs	notebooks
has_mcp_signal	no
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

540GitHub stars

18contributors

30commits, last 12 months

48days since last push

16releases

1bus factor

18open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 104 ⇿

0Stars

104Forks

15Releases

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 2Minor 3Patch 8

Each point covers 6 days.

OpenSSF Scorecard 3.7 / 10

3.7aggregate

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 · 2026-09-19 09:19 UTC

10	Binary-Artifacts	no binaries found in the repo
4	Branch-Protection	branch protection is not maximal on development and all release branches
10	CI-Tests	20 out of 20 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
2	Code-Review	Found 6/28 approved changesets -- score normalized to 2
10	Contributors	project has 5 contributing companies or organizations
0	Dangerous-Workflow	dangerous workflow patterns detected
0	Dependency-Update-Tool	no update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
9	Maintained	9 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 9
10	Packaging	packaging workflow detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
10	SAST	SAST tool is run on all commits
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	54 existing vulnerabilities detected

Direct dependencies 11

Registry	Package	Version constraint	Manifest
PyPI	pandas	`>=1.1.0`	pyproject.toml
PyPI	numpy	`>=1.13.3`	pyproject.toml
PyPI	scipy	`>=1.3.0`	pyproject.toml
PyPI	mdanalysis	`>=2.2.0,<3`	pyproject.toml
PyPI	mdanalysis	`>=2.7.0,<3`	pyproject.toml
PyPI	networkx	`>=2.5.0`	pyproject.toml
PyPI	tqdm	`—`	pyproject.toml
PyPI	multiprocess	`—`	pyproject.toml
PyPI	dill	`—`	pyproject.toml
PyPI	psutil	`—`	pyproject.toml
PyPI	gemmi	`>=0.7.5`	pyproject.toml

All dependencies 161

Full resolved dependency set from the GitHub dependency graph: 13 direct and 148 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	dill	`0.3.9`	direct
PyPI	gemmi	`0.7.5`	direct
PyPI	mdanalysis	`2.5.0`	direct
PyPI	mdanalysis	`2.8.0`	direct
PyPI	multiprocess	`0.70.17`	direct
PyPI	networkx	`3.2.1`	direct
PyPI	networkx	`3.4.2`	direct
PyPI	numpy	`1.26.4`	direct
PyPI	pandas	`2.2.3`	direct
PyPI	psutil	`7.0.0`	direct
PyPI	scipy	`1.13.1`	direct
PyPI	scipy	`1.15.2`	direct
PyPI	tqdm	`4.67.1`	direct
PyPI	accessible-pygments	`0.0.5`	indirect
PyPI	alabaster	`0.7.16`	indirect
PyPI	anyio	`4.14.2`	indirect
PyPI	appnope	`0.1.4`	indirect
PyPI	asttokens	`3.0.0`	indirect
PyPI	attrs	`25.1.0`	indirect
PyPI	babel	`2.17.0`	indirect
PyPI	beautifulsoup4	`4.13.3`	indirect
PyPI	biopython	`1.85`	indirect
PyPI	black	`25.1.0`	indirect
PyPI	certifi	`2025.1.31`	indirect
PyPI	cffi	`1.17.1`	indirect
PyPI	charset-normalizer	`3.4.1`	indirect
PyPI	click	`8.1.8`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	comm	`0.2.2`	indirect
PyPI	commonmark	`0.9.1`	indirect
PyPI	contourpy	`1.3.0`	indirect
PyPI	contourpy	`1.3.1`	indirect
PyPI	coverage	`7.6.12`	indirect
PyPI	cycler	`0.12.1`	indirect
PyPI	debugpy	`1.8.12`	indirect
PyPI	decorator	`5.2.1`	indirect
PyPI	docutils	`0.19`	indirect
PyPI	exceptiongroup	`1.2.2`	indirect
PyPI	executing	`2.2.0`	indirect
PyPI	fasteners	`0.19`	indirect
PyPI	fastjsonschema	`2.21.1`	indirect
PyPI	fonttools	`4.56.0`	indirect
PyPI	greenlet	`3.1.1`	indirect
PyPI	griddataformats	`1.0.2`	indirect
PyPI	gsd	`3.4.2`	indirect
PyPI	h11	`0.16.0`	indirect
PyPI	idna	`3.10`	indirect
PyPI	imagesize	`1.4.1`	indirect
PyPI	importlib-metadata	`8.6.1`	indirect
PyPI	iniconfig	`2.0.0`	indirect
PyPI	ipykernel	`6.29.5`	indirect
PyPI	ipython	`8.18.1`	indirect
PyPI	ipywidgets	`8.1.5`	indirect
PyPI	jedi	`0.19.2`	indirect
PyPI	jinja2	`3.1.5`	indirect
PyPI	joblib	`1.4.2`	indirect
PyPI	jsonpickle	`4.0.2`	indirect
PyPI	jsonschema	`4.23.0`	indirect
PyPI	jsonschema-specifications	`2024.10.1`	indirect
PyPI	jupyter-cache	`0.6.1`	indirect
PyPI	jupyter-client	`8.6.3`	indirect
PyPI	jupyter-core	`5.7.2`	indirect
PyPI	jupyterlab-widgets	`3.0.13`	indirect
PyPI	kiwisolver	`1.4.7`	indirect
PyPI	kiwisolver	`1.4.8`	indirect
PyPI	markdown-it-py	`2.2.0`	indirect
PyPI	markupsafe	`3.0.2`	indirect
PyPI	matplotlib	`3.10.1`	indirect
PyPI	matplotlib	`3.9.4`	indirect
PyPI	matplotlib-inline	`0.1.7`	indirect
PyPI	mda-xdrlib	`0.2.0`	indirect
PyPI	mdahole2	`0.5.0`	indirect
PyPI	mdit-py-plugins	`0.3.5`	indirect
PyPI	mdurl	`0.1.2`	indirect
PyPI	mmtf-python	`1.1.3`	indirect
PyPI	mrcfile	`1.5.4`	indirect
PyPI	msgpack	`1.1.0`	indirect
PyPI	mypy	`1.15.0`	indirect
PyPI	mypy-extensions	`1.0.0`	indirect
PyPI	myst-nb	`0.17.2`	indirect
PyPI	myst-parser	`0.18.1`	indirect
PyPI	nbclient	`0.7.4`	indirect
PyPI	nbformat	`5.10.4`	indirect
PyPI	nest-asyncio	`1.6.0`	indirect
PyPI	optype	`0.9.2`	indirect
PyPI	packaging	`24.2`	indirect
PyPI	pandas-stubs	`2.2.3.250308`	indirect
PyPI	parso	`0.8.4`	indirect
PyPI	pastel	`0.2.1`	indirect
PyPI	pathsimanalysis	`1.2.0`	indirect
PyPI	pathspec	`0.12.1`	indirect
PyPI	pexpect	`4.9.0`	indirect
PyPI	pillow	`11.1.0`	indirect
PyPI	platformdirs	`4.3.6`	indirect
PyPI	pluggy	`1.5.0`	indirect
PyPI	poethepoet	`0.33.0`	indirect
PyPI	prolif	`0.0.0`	indirect
PyPI	prompt-toolkit	`3.0.50`	indirect
PyPI	ptyprocess	`0.7.0`	indirect
PyPI	pure-eval	`0.2.3`	indirect
PyPI	py3dmol	`2.4.2`	indirect
PyPI	pycparser	`2.22`	indirect
PyPI	pydata-sphinx-theme	`0.15.4`	indirect
PyPI	pygments	`2.19.1`	indirect
PyPI	pyparsing	`3.2.1`	indirect
PyPI	pytest	`8.3.5`	indirect
PyPI	pytest-cov	`6.0.0`	indirect
PyPI	python-dateutil	`2.9.0.post0`	indirect
PyPI	pytz	`2025.1`	indirect
PyPI	pyvis	`0.3.2`	indirect
PyPI	pywin32	`308`	indirect
PyPI	pyyaml	`6.0.2`	indirect
PyPI	pyzmq	`26.2.1`	indirect
PyPI	rdkit	`2024.9.6`	indirect
PyPI	recommonmark	`0.7.1`	indirect
PyPI	referencing	`0.36.2`	indirect
PyPI	requests	`2.32.3`	indirect
PyPI	rpds-py	`0.23.1`	indirect
PyPI	ruff	`0.11.2`	indirect
PyPI	scipy-stubs	`1.15.2.1`	indirect
PyPI	seaborn	`0.13.2`	indirect
PyPI	setuptools	`78.1.0`	indirect
PyPI	six	`1.17.0`	indirect
PyPI	snowballstemmer	`2.2.0`	indirect
PyPI	soupsieve	`2.6`	indirect
PyPI	sphinx	`5.3.0`	indirect
PyPI	sphinx-autobuild	`2024.10.3`	indirect
PyPI	sphinx-autobuild	`2025.8.25`	indirect
PyPI	sphinx-book-theme	`1.1.3`	indirect
PyPI	sphinx-copybutton	`0.5.2`	indirect
PyPI	sphinxcontrib-applehelp	`2.0.0`	indirect
PyPI	sphinxcontrib-devhelp	`2.0.0`	indirect
PyPI	sphinxcontrib-htmlhelp	`2.1.0`	indirect
PyPI	sphinxcontrib-jsmath	`1.0.1`	indirect
PyPI	sphinxcontrib-qthelp	`2.0.0`	indirect
PyPI	sphinxcontrib-serializinghtml	`2.0.0`	indirect
PyPI	sqlalchemy	`2.0.38`	indirect
PyPI	stack-data	`0.6.3`	indirect
PyPI	starlette	`1.3.1`	indirect
PyPI	tabulate	`0.9.0`	indirect
PyPI	threadpoolctl	`3.5.0`	indirect
PyPI	tokenize-rt	`6.1.0`	indirect
PyPI	tomli	`2.2.1`	indirect
PyPI	tornado	`6.4.2`	indirect
PyPI	traitlets	`5.14.3`	indirect
PyPI	types-networkx	`3.4.2.20250426`	indirect
PyPI	types-psutil	`7.2.1.20251231`	indirect
PyPI	types-pytz	`2025.2.0.20250326`	indirect
PyPI	types-requests	`2.32.0.20250328`	indirect
PyPI	types-setuptools	`78.1.0.20250329`	indirect
PyPI	types-tqdm	`4.67.0.20250319`	indirect
PyPI	typing-extensions	`4.12.2`	indirect
PyPI	tzdata	`2025.1`	indirect
PyPI	urllib3	`2.3.0`	indirect
PyPI	uvicorn	`0.51.0`	indirect
PyPI	watchfiles	`1.2.0`	indirect
PyPI	waterdynamics	`1.2.0`	indirect
PyPI	wcwidth	`0.2.13`	indirect
PyPI	websockets	`16.1.1`	indirect
PyPI	widgetsnbextension	`4.0.13`	indirect
PyPI	zipp	`3.21.0`	indirect

Dependency advisories 0

Installing pypi:prolif@2.2.1 pulls in 29 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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