Public record
Software health reportschema 0.27.0 · metrics 1.13.0 · 2026-07-30 08:25 UTC

holoviz / lumen

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

PythonBSD-3-Clause★ 300 stars⑂ 36 forkssince May 2020View on GitHub ↗

holoviz/lumen holds a health index of 80 out of 100, placing it in the Good band. It scores highest on Engineering Quality (96/100) and lowest on AI Readiness (57/100). It was last updated today. 2 contributors account for most of its recent work.

80
overall / 100
Good

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At risk ceiling of 49. AI Readiness sits outside the overall score.

80
Excellent85-100Exemplary; meets essentially all checked criteria
Good70-84Healthy; minor gaps
Moderate50-69Acceptable with notable gaps; review recommended
At risk30-49Significant weaknesses; adoption warrants caution
Critical1-29Severe 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.

Ownership

HoloVizOrganization
447 followers15 public repossince Jun 2019

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIlumen1.3.0-2050 days ago

Metrics by category

Vitality

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

89Excellent · 22% of overall
How it's scored
36/36Push recency — last push 0 days ago
29.1/36Commit cadence — 42/52 weeks with commits
18/18Commit volume — 395 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 17 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year395
human_commit_share1
days_since_last_push0
active_weeks_last_year42
How it's scored
27/27Ships releases — 18 releases published
36/36Release recency — latest release 0 days ago
19.8/27Release cadence — a release every ~111.1 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count18
latest_release_tagv1.3.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases111.1

Community & Adoption

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

67Moderate · 18% of overall
How it's scored
40.2/60Stars — 300 stars
12.9/25Forks — 36 forks
5/15Watchers — 9 watchers
Inputs used
forks36
stars300
watchers9
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (BSD-3-Clause)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
has_contributingyes
has_issue_templateno
has_code_of_conductno
has_pull_request_templateyes

Sustainability & Governance

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

75Good · 24% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
11.8/22.5Commit distribution — top contributor authored 48% of commits
13.5/13.5Contributor breadth — 25 contributors
10/10OpenSSF Scorecard: Contributors — project has 11 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled25
top_contributor_share0.477
How it's scored
29.6/46.8Issue resolution — 63% of issues closed
35.3/38.3PR acceptance — 1,397/1,515 decided PRs merged
13.5/15OpenSSF Scorecard: Code-Review — Found 29/30 approved changesets -- score normalized to 9
Inputs used
merged_prs1,397
open_issues163
closed_issues281
issue_closed_ratio0.633
closed_unmerged_prs118
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
19.1/25Owner reach — 447 followers of holoviz
20.8/25Track record — 15 public repos, account ~7 yr old
Inputs used
followers447
owner_typeOrganization
is_verified
owner_loginholoviz
public_repos15
account_age_days2,606
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 205 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageslumen
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

96Excellent · 20% of overall
How it's scored
24/24CI workflows — 7 workflow(s)
24/24Tests present
16/16Linter config
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

100Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://lumen.holoviz.org
10/10Repository description
10/10Topics — 12 topics
10/10Wiki
Inputs used
topicsai-agents, conversational-ai, data-exploration, data-visualization, duckdb, holoviz, llm, panel, python, text-to-sql, xarray, rag
has_wikiyes
homepagehttps://lumen.holoviz.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

71Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
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
6.8/7.5Code-Review — Found 29/30 approved changesets -- score normalized to 9
2.5/2.5Contributors — project has 11 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 17 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
5/5Pinned-Dependencies — all dependencies are pinned
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate7.1
Excluded from scoring (no data or not applicable): branch_protection. Remaining weights renormalized.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score.

57Moderate · 0% of overall
How it's scored
45/45Agent instructions — docs/configuration/agents.md, docs/reference/api/ai/agents.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 95 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
legible_history_share0.95
agent_instruction_filesdocs/configuration/agents.md, docs/reference/api/ai/agents.md
agent_instruction_max_bytes15,454
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
10/10OpenSSF Scorecard: Pinned-Dependencies — all dependencies are pinned
Inputs used
has_nixno
has_testsyes
lockfiles
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
53.2/55Manageable file sizes — 7/212 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes119,713
source_files_sampled212
oversized_source_files7
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
0/20MCP server
40/40Runnable examples — examples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_files

Key facts

300GitHub stars
25contributors
395commits, last 12 months
0days since last push
18releases
2bus factor
163open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:lumen@1.3.0; advisories assessed against the repository dependency graph instead
  • No resolved dependencies carried a version and a supported ecosystem

More detail

Star and fork history 0 ★ / 36 ⇿
0Stars
36Forks
16Releases

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.

01325383642020-122023-092026-07
Major 1Minor 10Patch 5

Each point covers 6 days.

OpenSSF Scorecard 7.1 / 10
7.1aggregate

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 · 2026-07-30 08:24 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal 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
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
9Code-ReviewFound 29/30 approved changesets -- score normalized to 9
10Contributorsproject has 11 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 17 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
10Pinned-Dependenciesall dependencies are pinned
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 28
RegistryPackageVersion constraintManifest
PyPIbokehpyproject.toml
PyPIchardetpyproject.toml
PyPIduckdb>=1.2.0pyproject.toml
PyPIlxmlpyproject.toml
PyPIgriffepyproject.toml
PyPIholoviews>=1.17.0pyproject.toml
PyPIhvplotpyproject.toml
PyPIinstructor>=1.14.3pyproject.toml
PyPIintake<2pyproject.toml
PyPIjinja2>3.0pyproject.toml
PyPImarkitdownpyproject.toml
PyPInbformatpyproject.toml
PyPInumpypyproject.toml
PyPIpackagingpyproject.toml
PyPIpandaspyproject.toml
PyPIpanel>=1.7.5pyproject.toml
PyPIpanel-graphic-walker>=0.6.4pyproject.toml
PyPIpanel-material-ui>=0.14.0pyproject.toml
PyPIpanel-splitjs>=0.4.0pyproject.toml
PyPIparam>=2.2.1pyproject.toml
PyPIpyarrowpyproject.toml
PyPIpydantic>=2.8.0pyproject.toml
PyPIpydantic-extra-typespyproject.toml
PyPIsemchunkpyproject.toml
PyPIsqlglotpyproject.toml
PyPItabulatepyproject.toml
PyPItiktokenpyproject.toml
PyPIvl-convert-pythonpyproject.toml
All dependencies 17

Full resolved dependency set from the GitHub dependency graph: 11 direct and 6 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIduckdbdirect
PyPIholoviewsdirect
PyPIinstructordirect
PyPIintakedirect
PyPIjinja2direct
PyPIpaneldirect
PyPIpanel-graphic-walkerdirect
PyPIpanel-material-uidirect
PyPIpanel-splitjsdirect
PyPIparamdirect
PyPIpydanticdirect
PyPIboto3indirect
PyPIgoogle-genaiindirect
PyPIllama-cpp-pythonindirect
PyPIsentence-transformersindirect
PyPItransformersindirect
PyPIxarray-sqlindirect
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies carried a version and a supported ecosystem

Raw JSON report machine-readable
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                "key": "track_record",
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                "key": "fuzzing",
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                "key": "sast",
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                "key": "security_policy",
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                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "Project has not signed or included provenance with any releases.",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "GitHub workflow tokens follow principle of least privilege",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "0 existing vulnerabilities detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
            "band": "excellent",
            "name": "High-Risk Jurisdiction Exposure",
            "note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 10
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "jurisdiction_no_match",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "moderate",
        "name": "AI Readiness",
        "value": 57,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "excellent",
            "name": "Agent context & guidance",
            "note": null,
            "notes": [],
            "value": 85,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": 0.95,
              "agent_instruction_files": [
                "docs/configuration/agents.md",
                "docs/reference/api/ai/agents.md"
              ],
              "agent_instruction_max_bytes": 15454
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "docs/configuration/agents.md, docs/reference/api/ai/agents.md",
                "points": 45,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "docs/configuration/agents.md, docs/reference/api/ai/agents.md"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "95 of 100 human commits state their intent (structured subject or explanatory body)",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "legible_history",
                    "params": {
                      "legible": 95,
                      "sampled": 100
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "at_risk",
            "name": "Verify loop (build / test / typecheck)",
            "note": null,
            "notes": [],
            "value": 43,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [],
              "agent_commit_share": 0,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 18
              },
              {
                "key": "automated_tests",
                "name": "Automated tests",
                "detail": null,
                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
                "name": "Lint / format config",
                "detail": null,
                "points": 11,
                "status": "met",
                "details": [],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no agent-authored commits among the last 100",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_authored_commits",
                    "params": {
                      "sampled": 100
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "no automated dependency updates observed",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_dependency_automation",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "all dependencies are pinned",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "moderate",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 53,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 119713,
              "source_files_sampled": 212,
              "oversized_source_files": 7
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python without a type-check config",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_typecheck_config_language",
                    "params": {
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "7/212 source files over 60KB",
                "points": 53.2,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 212,
                      "oversized": 7
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "examples"
              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "examples",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "examples"
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
    "deps.dev does not index pypi:lumen@1.3.0; advisories assessed against the repository dependency graph instead",
    "No resolved dependencies carried a version and a supported ecosystem"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-30T08:25:29.022690Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/h/holoviz/lumen.svg",
  "full_name": "holoviz/lumen",
  "license_state": "standard",
  "license_spdx": "BSD-3-Clause"
}

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 v1.13.0, schema v0.27.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.