Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-14 18:02 UTC

holoviz / lumen

Illuminate your data. Agent framework turning natural language into SQL, charts, dashboards and reports.

PythonBSD-3-Clause★ 311 stars⑂ 44 forkssince May 2020View on GitHub ↗

KindLibraryCommand-line toolPluginhow this is determined

#ai-agents #conversational-ai #data-exploration #data-visualization #duckdb #holoviz #llm #panel #python #text-to-sql #xarray #rag

holoviz/lumen holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (96/100) and lowest on AI Readiness (66/100). It was last updated 3 days ago. 2 contributors account for most of its recent work.

overall / 100

Exceptional

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 80 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

HoloVizOrganization

449 followers15 public repossince Jun 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
PyPI	lumen	1.3.0	-	205	46 days ago

Metrics by category

Vitality

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

89Excellent · 21% of overall

Development activity

93Exceptional

How it's scored

36/36	Push recency — last push 3 days ago
29.1/36	Commit cadence — 42/52 weeks with commits
18/18	Commit volume — 405 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 23 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	405
human_commit_share	1
days_since_last_push	3
active_weeks_last_year	42

Release discipline

83Excellent

How it's scored

27/27	Ships releases — 18 releases published
36/36	Release recency — latest release 46 days ago
19.8/27	Release cadence — a release every ~111.1 days
0/10	OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.

Inputs used

releases_count	18
latest_release_tag	v1.3.0
releases_from_tags	no
days_since_latest_release	46
mean_days_between_releases	111.1

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

67Good · 17% of overall

Popularity & adoption

59Moderate

How it's scored

40.4/60	Stars — 311 stars
13.6/25	Forks — 44 forks
5/15	Watchers — 9 watchers

Inputs used

forks	44
stars	311
watchers	9
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

77Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (BSD-3-Clause)
18/18	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	12
has_contributing	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	codecov.io, github.com, shields.io
has_pull_request_template	yes

Sustainability & Governance

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

77Good · 23% of overall

Maintainer resilience (bus factor)

61Moderate

How it's scored

25.2/54	Bus factor — 2 contributor(s) cover half of all commits
12.2/22.5	Commit distribution — top contributor authored 46% of commits
13.5/13.5	Contributor breadth — 34 contributors
10/10	OpenSSF Scorecard: Contributors — project has 11 contributing companies or organizations

Inputs used

bus_factor	2
contributors_sampled	34
top_contributor_share	0.459

Issue & PR responsiveness

83Excellent

How it's scored

28.7/42	Issue resolution — 68% of issues closed
27.7/30	PR acceptance — 1,459/1,581 decided PRs merged
11.6/13	Newcomer PR acceptance — 17/19 first-time contributors' PRs merged in 30d
15/15	OpenSSF Scorecard: Code-Review — all changesets reviewed

Inputs used

merged_prs	1,459
open_issues	150
closed_issues	325
prs_merged_7d	4
prs_decided_7d	4
prs_merged_30d	40
prs_decided_30d	43
issue_closed_ratio	0.684
closed_unmerged_prs	122
first_time_authors_30d	6
first_time_prs_merged_30d	17
first_time_prs_decided_30d	19

Ownership & stewardship

70Good

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain
19.1/25	Owner reach — 449 followers of holoviz
20.8/25	Track record — 15 public repos, account ~7 yr old

Inputs used

followers	449
owner_type	Organization
is_verified	no
owner_login	holoviz
public_repos	15
account_age_days	2,652

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 46 days ago
20/20	Version history — 205 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	lumen
ecosystems	pypi
any_deprecated	no
min_days_since_publish	46

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional

How it's scored

24/24	CI workflows — 7 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff], [tool.isort])
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

100Exceptional

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://lumen.holoviz.org
10/10	Repository description
10/10	Topics — 12 topics
10/10	Wiki

Inputs used

topics	ai-agents, conversational-ai, data-exploration, data-visualization, duckdb, holoviz, llm, panel, python, text-to-sql, xarray, rag
has_wiki	yes
homepage	https://lumen.holoviz.org
docs_site	https://lumen.holoviz.org
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?

71Good · 16% of overall

Security posture

72Good

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 — 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
7.5/7.5	Code-Review — all changesets reviewed
2.5/2.5	Contributors — project has 11 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 23 issue activity found in the last 90 days -- score normalized to 10
5/5	Packaging — packaging workflow detected
5/5	Pinned-Dependencies — all dependencies are pinned
5/5	SAST — SAST tool is run on all commits
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — Project has not signed or included provenance with any releases.
7.5/7.5	Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5	Vulnerabilities — 0 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	17
scorecard_version	v5.5.0
checks_inconclusive	1
scorecard_aggregate	7.2

Excluded from scoring (no data or not applicable): Branch-Protection. Remaining weights renormalized.

Dependency advisories

68Good

How it's scored

10.4/35	Direct dependencies free of known advisories — 1 affected: intake 2.0.0a2 (high 8.8)
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
32.8/40	No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 179 days ago

Inputs used

source	osv
advisories	2
affected_packages	1
assessed_packages	141
unassessed_packages	0
affected_by_severity	high 1
direct_affected_packages	1

Matched the pypi:lumen@1.3.0 runtime dependency closure — what installing the published package pulls in — 141 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.

66Good · 4% of overall

Agent context & guidance

85Excellent

How it's scored

45/45	Agent instructions — docs/configuration/agents.md, docs/reference/api/ai/agents.md
0/15	Machine-readable docs (llms.txt)
40/40	Legible commit history — 97 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.97
agent_instruction_files	docs/configuration/agents.md, docs/reference/api/ai/agents.md
agent_instruction_max_bytes	17,795

Verify loop (build / test / typecheck)

43Weak

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff], [tool.isort])
0/11	Static type checking
0/10	Reproducible environment
0/10	Demonstrated agent practice — no agent-authored commits among the last 100
0/8	Automated maintenance — no automated dependency updates observed
10/10	OpenSSF Scorecard: Pinned-Dependencies — all dependencies are pinned

Inputs used

has_nix	no
has_tests	yes
lockfiles	—
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

53Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
52.6/55	Manageable file sizes — 10/226 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	145,474
source_files_sampled	226
oversized_source_files	10

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 — examples

Inputs used

example_dirs	examples
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

311GitHub stars

34contributors

405commits, last 12 months

3days since last push

18releases

2bus factor

150open issues

PyPIpackage ecosystems

Data collection warnings

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

More detail

Star and fork history 0 ★ / 44 ⇿

0Stars

44Forks

17Releases

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 1Minor 11Patch 5

Each point covers 6 days.

OpenSSF Scorecard 7.2 / 10

7.2aggregate

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 · 2026-09-14 18:01 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	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
10	Code-Review	all changesets reviewed
10	Contributors	project has 11 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 23 issue activity found in the last 90 days -- score normalized to 10
10	Packaging	packaging workflow detected
10	Pinned-Dependencies	all dependencies are pinned
10	SAST	SAST tool is run on all commits
0	Security-Policy	security policy file not detected
0	Signed-Releases	Project has not signed or included provenance with any releases.
10	Token-Permissions	GitHub workflow tokens follow principle of least privilege
10	Vulnerabilities	0 existing vulnerabilities detected

Direct dependencies 29

Registry	Package	Version constraint	Manifest
PyPI	bokeh	`>=3.9.0`	pyproject.toml
PyPI	chardet	`—`	pyproject.toml
PyPI	duckdb	`>=1.2.0`	pyproject.toml
PyPI	lxml	`—`	pyproject.toml
PyPI	griffe	`<2`	pyproject.toml
PyPI	holoviews	`>=1.17.0`	pyproject.toml
PyPI	hvplot	`—`	pyproject.toml
PyPI	instructor	`>=1.14.3`	pyproject.toml
PyPI	intake	`<2`	pyproject.toml
PyPI	jinja2	`>3.0`	pyproject.toml
PyPI	markitdown	`—`	pyproject.toml
PyPI	narwhals	`>=2`	pyproject.toml
PyPI	nbformat	`—`	pyproject.toml
PyPI	numpy	`—`	pyproject.toml
PyPI	packaging	`—`	pyproject.toml
PyPI	pandas	`—`	pyproject.toml
PyPI	panel	`>=1.9.0`	pyproject.toml
PyPI	panel-graphic-walker	`>=0.6.4`	pyproject.toml
PyPI	panel-material-ui	`>=0.14.0`	pyproject.toml
PyPI	panel-splitjs	`>=0.4.0`	pyproject.toml
PyPI	param	`>=2.2.1,<2.5.0`	pyproject.toml
PyPI	pyarrow	`—`	pyproject.toml
PyPI	pydantic	`>=2.8.0`	pyproject.toml
PyPI	pydantic-extra-types	`—`	pyproject.toml
PyPI	semchunk	`—`	pyproject.toml
PyPI	sqlglot	`—`	pyproject.toml
PyPI	tabulate	`—`	pyproject.toml
PyPI	tiktoken	`—`	pyproject.toml
PyPI	vl-convert-python	`—`	pyproject.toml

All dependencies 20

Full resolved dependency set from the GitHub dependency graph: 14 direct and 6 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	bokeh	`—`	direct
PyPI	duckdb	`—`	direct
PyPI	griffe	`—`	direct
PyPI	holoviews	`—`	direct
PyPI	instructor	`—`	direct
PyPI	intake	`—`	direct
PyPI	jinja2	`—`	direct
PyPI	narwhals	`—`	direct
PyPI	panel	`—`	direct
PyPI	panel-graphic-walker	`—`	direct
PyPI	panel-material-ui	`—`	direct
PyPI	panel-splitjs	`—`	direct
PyPI	param	`—`	direct
PyPI	pydantic	`—`	direct
PyPI	boto3	`—`	indirect
PyPI	google-genai	`—`	indirect
PyPI	llama-cpp-python	`—`	indirect
PyPI	sentence-transformers	`—`	indirect
PyPI	transformers	`—`	indirect
PyPI	xarray-sql	`—`	indirect

Dependency advisories 1

Installing pypi:lumen@1.3.0 pulls in 141 packages, direct and transitive: 1 carry known advisories, of which 1 are direct dependencies.

Package	Version	Relation	Severity	Advisories	Fixed in
intake	`2.0.0a2`	direct	high	2	`2.0.9`

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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