Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-14 09:40 UTC

pydata / sparse

Sparse multi-dimensional arrays for the PyData ecosystem

PythonBSD-3-Clause★ 666 stars⑂ 138 forkssince Apr 2017View on GitHub ↗
KindPluginLibraryhow this is determined

pydata/sparse holds a health index of 93 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (96/100) and lowest on AI Readiness (48/100). It was last updated today. 2 contributors account for most of its recent work.

93
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.

93
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 79 is calibrated to 93 on the published index scale (record calibration 2026-08-02).

Ownership

Python for DataOrganization
746 followers29 public repossince Dec 2011

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIsparse0.19.2-460 days agosparsenumpyscipydask

Metrics by category

Vitality

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

80Excellent · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
20.8/36Commit cadence30/52 weeks with commits
15.5/18Commit volume52 commits in the last year
10/10OpenSSF Scorecard: Maintained12 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year52
human_commit_share0.59
days_since_last_push0
active_weeks_last_year30
How it's scored
27/27Ships releases6 releases published
36/36Release recencylatest release 0 days ago
12.6/27Release cadencea release every ~122.6 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count6
latest_release_tag0.19.2
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases122.6

Community & Adoption

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

80Excellent · 17% of overall
How it's scored
45.8/60Stars666 stars
17.8/25Forks138 forks
6.2/15Watchers14 watchers
Inputs used
forks138
stars666
watchers14
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (BSD-3-Clause)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicescodecov.io, github.com, readthedocs.org
has_pull_request_templateyes

Sustainability & Governance

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

83Excellent · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
12.3/22.5Commit distributiontop contributor authored 45% of commits
13.5/13.5Contributor breadth60 contributors
10/10OpenSSF Scorecard: Contributorsproject has 53 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled60
top_contributor_share0.454
How it's scored
33.8/42Issue resolution80% of issues closed
26.8/30PR acceptance533/597 decided PRs merged
13/13Newcomer PR acceptance2/2 first-time contributors' PRs merged in 30d
13.5/15OpenSSF Scorecard: Code-ReviewFound 9/10 approved changesets -- score normalized to 9
Inputs used
merged_prs533
open_issues65
closed_issues269
prs_merged_7d1
prs_decided_7d1
prs_merged_30d2
prs_decided_30d2
issue_closed_ratio0.805
closed_unmerged_prs64
first_time_authors_30d1
first_time_prs_merged_30d2
first_time_prs_decided_30d2
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
20.7/25Owner reach746 followers of pydata
22.8/25Track record29 public repos, account ~14 yr old
Inputs used
followers746
owner_typeOrganization
is_verified
owner_loginpydata
public_repos29
account_age_days5,346
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 0 days ago
20/20Version history46 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagessparse
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall
How it's scored
24/24CI workflows3 workflow(s)
24/24Tests present
16/16Linter configtox.ini
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests24 out of 24 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

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://sparse.pydata.org
10/10Repository description
10/10Topics7 topics
10/10Wiki
Inputs used
topicspython, numpy, sparse-matrix, sparse-matrices, sparse-data, sparse-arrays, array-api
has_wikiyes
homepagehttps://sparse.pydata.org
docs_sitehttps://sparse.pydata.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

59Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
2.5/2.5CI-Tests24 out of 24 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6.8/7.5Code-ReviewFound 9/10 approved changesets -- score normalized to 9
2.5/2.5Contributorsproject has 53 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained12 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.9
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging. Remaining weights renormalized.

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.

48Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
33.4/40Legible commit history37 of 59 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.627
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format configtox.ini
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
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 codePython without a type-check config
53.7/55Manageable file sizes2/82 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes110,566
source_files_sampled82
oversized_source_files2
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples, 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

666GitHub stars
60contributors
52commits, last 12 months
0days since last push
6releases
2bus factor
65open 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:sparse@0.19.2; 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 ★ / 138 ⇿
0Stars
138Forks
4Releases

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.

025507510012515012732017-042021-122026-08
Major 0Minor 3Patch 0

Each point covers 9 days.

OpenSSF Scorecard 5.9 / 10
5.9aggregate

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 · 2026-08-14 09:40 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-Tests24 out of 24 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 9/10 approved changesets -- score normalized to 9
10Contributorsproject has 53 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained12 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPInumpy>=1.17pyproject.toml
PyPInumba>=0.49pyproject.toml
All dependencies 3

Full resolved dependency set from the GitHub dependency graph: 2 direct and 1 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumbadirect
PyPInumpydirect
PyPIscipyindirect
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

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 v0.31.0 — full methodology · metrics wiki.

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