Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-12 08:29 UTC

holoviz / datashader

Quickly and accurately render even the largest data.

PythonBSD-3-Clause★ 3,564 stars⑂ 377 forkssince Dec 2015View on GitHub ↗

holoviz/datashader holds a health index of 91 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (95/100) and lowest on AI Readiness (52/100). It was last updated 23 days ago. 3 contributors account for most of its recent work.

91
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.

91
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)
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.

The weighted overall 77 is calibrated to 91 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

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIdatashader0.19.1303,83261116 days ago

Metrics by category

Vitality

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

67Good · 21% of overall
How it's scored
28.8/36Push recency — last push 23 days ago
13.8/36Commit cadence — 20/52 weeks with commits
15.1/18Commit volume — 47 commits in the last year
5/10OpenSSF Scorecard: Maintained — 5 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 5
Inputs used
commits_last_year47
human_commit_share1
days_since_last_push23
active_weeks_last_year20
How it's scored
27/27Ships releases — 42 releases published
27/36Release recency — latest release 115 days ago
19.8/27Release cadence — a release every ~104 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count42
latest_release_tagv0.19.1
releases_from_tagsno
days_since_latest_release115
mean_days_between_releases104

Community & Adoption

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

84Excellent · 17% of overall
How it's scored
57.6/60Stars — 3,564 stars
21.5/25Forks — 377 forks
10.8/15Watchers — 89 watchers
Inputs used
forks377
stars3,564
watchers89
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)
0/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges14
has_contributingno
has_issue_templateno
has_code_of_conductyes
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateyes
How it's scored
73.1/80Monthly downloads — 303,832 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdatashader
dependents—
ecosystemspypi
total_downloads—
monthly_downloads303,832
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?

78Good · 23% of overall
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
14.4/22.5Commit distribution — top contributor authored 36% of commits
13.5/13.5Contributor breadth — 60 contributors
10/10OpenSSF Scorecard: Contributors — project has 39 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled60
top_contributor_share0.361
How it's scored
32.8/42Issue resolution — 78% of issues closed
27.7/30PR acceptance — 812/881 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-Review — Found 7/30 approved changesets -- score normalized to 2
Inputs used
merged_prs812
open_issues134
closed_issues474
prs_merged_7d0
prs_decided_7d0
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio0.78
closed_unmerged_prs69
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
19.1/25Owner reach — 449 followers of holoviz
20.8/25Track record — 15 public repos, account ~7 yr old
Inputs used
followers449
owner_typeOrganization
is_verifiedno
owner_loginholoviz
public_repos15
account_age_days2,650

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 116 days ago
20/20Version history — 61 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdatashader
ecosystemspypi
any_deprecatedno
min_days_since_publish116

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall
How it's scored
24/24CI workflows — 6 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 27 out of 29 merged PRs checked by a CI test -- score normalized to 9
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — http://datashader.org
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicsholoviz, datashader, data-visualizations, rasterization
has_wikiyes
homepagehttp://datashader.org
docs_sitehttp://datashader.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

66Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.2/2.5CI-Tests — 27 out of 29 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-Review — Found 7/30 approved changesets -- score normalized to 2
2.5/2.5Contributors — project has 39 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
3.8/7.5Maintained — 5 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 5
5/5Packaging — packaging workflow detected
5/5Pinned-Dependencies — all dependencies are pinned
1.5/5SAST — SAST tool is not run on all commits -- score normalized to 3
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_aggregate5.8
Excluded from scoring (no data or not applicable): Branch-Protection. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages19
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:datashader@0.19.1 runtime dependency closure — what installing the published package pulls in — 19 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.

52Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 99 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.99
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
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
51.9/55Manageable file sizes — 6/108 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes152,409
source_files_sampled108
oversized_source_files6
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
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

3,564GitHub stars
60contributors
47commits, last 12 months
23days since last push
42releases
3bus factor
134open 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 ★ / 377 ⇿
0Stars
377Forks
42Releases

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.

0125250375373152016-012021-052026-08
Major 0Minor 18Patch 24

Each point covers 10 days.

OpenSSF Scorecard 5.8 / 10
5.8aggregate

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 · 2026-09-12 08:29 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
9CI-Tests27 out of 29 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 7/30 approved changesets -- score normalized to 2
10Contributorsproject has 39 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
5Maintained5 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 5
10Packagingpackaging workflow detected
10Pinned-Dependenciesall dependencies are pinned
3SASTSAST tool is not run on all commits -- score normalized to 3
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 12
RegistryPackageVersion constraintManifest
PyPIcolorcet—pyproject.toml
PyPImultipledispatch—pyproject.toml
PyPInumba—pyproject.toml
PyPInumpy—pyproject.toml
PyPIpandas—pyproject.toml
PyPIparam—pyproject.toml
PyPIpyct—pyproject.toml
PyPIrequests—pyproject.toml
PyPIscipy—pyproject.toml
PyPItoolz—pyproject.toml
PyPIpackaging—pyproject.toml
PyPIxarray—pyproject.toml
All dependencies 12

Full resolved dependency set from the GitHub dependency graph: 12 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcolorcet—direct
PyPImultipledispatch—direct
PyPInumba—direct
PyPInumpy—direct
PyPIpackaging—direct
PyPIpandas—direct
PyPIparam—direct
PyPIpyct—direct
PyPIrequests—direct
PyPIscipy—direct
PyPItoolz—direct
PyPIxarray—direct
Dependency advisories 0

Installing pypi:datashader@0.19.1 pulls in 19 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.

The message is kept through sign-in.

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.