Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-22 08:36 UTC

ray-project / deltacat

A portable Multimodal Lakehouse powered by Ray that brings exabyte-level scalability and fast, ACID-compliant, change-data-capture to your ML and analytics workloads.

PythonApache-2.0★ 285 stars⑂ 48 forkssince Aug 2021View on GitHub ↗

ray-project/deltacat holds a health index of 57 out of 100, placing it in the Moderate band. It scores highest on Sustainability & Governance (79/100) and lowest on Security (44/100). It was last updated 187 days ago. 3 contributors account for most of its recent work.

57
overall / 100
Moderate

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.

57
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 61 is calibrated to 67 on the published index scale (record calibration 2026-08-02).

Ownership

ray-projectOrganization
1,859 followers127 public repossince Sep 2016

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIdeltacat2.0.0.post4218107392 days ago

Metrics by category

Vitality

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

45Weak · 21% of overall
How it's scored
3.6/36Push recency — last push 187 days ago
7.6/36Commit cadence — 11/52 weeks with commits
11.7/18Commit volume — 19 commits in the last year
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year19
human_commit_share1
days_since_last_push187
active_weeks_last_year11
How it's scored
27/27Ships releases — 100 releases published
16.2/36Release recency — latest release 187 days ago
27/27Release cadence — a release every ~25.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tag1.1.42
releases_from_tagsno
days_since_latest_release187
mean_days_between_releases25.8
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?

53Moderate · 17% of overall
How it's scored
39.8/60Stars — 285 stars
13.9/25Forks — 48 forks
5/15Watchers — 9 watchers
Inputs used
forks48
stars285
watchers9
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateyes
How it's scored
31.2/80Monthly downloads — 218 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdeltacat
dependents—
ecosystemspypi
total_downloads—
monthly_downloads218
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?

79Good · 23% of overall
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
17.1/22.5Commit distribution — top contributor authored 24% of commits
13.5/13.5Contributor breadth — 24 contributors
10/10OpenSSF Scorecard: Contributors — project has 6 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled24
top_contributor_share0.242
How it's scored
34.6/42Issue resolution — 82% of issues closed
25.1/30PR acceptance — 349/417 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
10.5/15OpenSSF Scorecard: Code-Review — Found 22/30 approved changesets -- score normalized to 7
Inputs used
merged_prs349
open_issues22
closed_issues104
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.825
closed_unmerged_prs68
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
23.5/25Owner reach — 1,859 followers of ray-project
25/25Track record — 127 public repos, account ~10 yr old
Inputs used
followers1,859
owner_typeOrganization
is_verifiedno
owner_loginray-project
public_repos127
account_age_days3,693
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
14/35Publish recency — latest publish 392 days ago
20/20Version history — 107 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdeltacat
ecosystemspypi
any_deprecatedno
min_days_since_publish392

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
16/16Linter config — .flake8
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 22 out of 22 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

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

44Weak · 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 — 22 out of 22 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
5.2/7.5Code-Review — Found 22/30 approved changesets -- score normalized to 7
2.5/2.5Contributors — project has 6 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
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 184 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate3.9
Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.
How it's scored
15.4/35Direct dependencies free of known advisories — 1 affected: pyarrow 16.0.0 (high 7.0)
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
34/40No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 692 days ago
Inputs used
sourceosv
advisories3
affected_packages1
assessed_packages13
unassessed_packages6
affected_by_severityhigh 1
direct_affected_packages1
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories. Remaining weights renormalized. Matched 13 resolved dependencies against OSV. 6 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

64Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.ray.io/llms.txt)
40/40Legible commit history — 77 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.ray.io/llms.txt
legible_history_share0.77
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — .flake8
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
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
53/55Manageable file sizes — 17/460 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes561,421
source_files_sampled460
oversized_source_files17
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

285GitHub stars
24contributors
19commits, last 12 months
187days since last push
100releases
3bus factor
22open 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 ★ / 48 ⇿
0Stars
48Forks
100Releases

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.

010203040504722021-112024-042026-09
Major 1Minor 2Patch 60

Each point covers 5 days.

OpenSSF Scorecard 3.9 / 10
3.9aggregate

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 · 2026-10-22 08:35 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during GetBranch(main): error during branchesHandler.query: 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-Tests22 out of 22 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7Code-ReviewFound 22/30 approved changesets -- score normalized to 7
10Contributorsproject has 6 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
10Packagingpackaging workflow 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
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities184 existing vulnerabilities detected
Direct dependencies 18
RegistryPackageVersion constraintManifest
PyPIaws-embedded-metrics==3.2.0pyproject.toml
PyPIboto3~=1.34pyproject.toml
PyPIgoogle-cloud-storage—pyproject.toml
PyPIgcsfs==2025.3.2pyproject.toml
PyPIdaft==0.5.22pyproject.toml
PyPIintervaltree==3.1.0pyproject.toml
PyPImsgpack~=1.0.7pyproject.toml
PyPInumpy==1.23.2pyproject.toml
PyPIpandas==2.2.3pyproject.toml
PyPIpolars==1.28.1pyproject.toml
PyPIpyarrow==16.0.0pyproject.toml
PyPIpydantic!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,<2.10.0pyproject.toml
PyPIpymemcache==4.0.0pyproject.toml
PyPIray==2.46.0pyproject.toml
PyPItenacity==8.2.3pyproject.toml
PyPItyping-extensions>=4.6.1pyproject.toml
PyPIredis==5.0.0pyproject.toml
PyPIschedule==1.2.0pyproject.toml
All dependencies 19

Full resolved dependency set from the GitHub dependency graph: 18 direct and 1 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaws-embedded-metrics3.2.0direct
PyPIboto3—direct
PyPIdaft0.5.22direct
PyPIgcsfs2025.3.2direct
PyPIgoogle-cloud-storage—direct
PyPIintervaltree3.1.0direct
PyPImsgpack—direct
PyPInumpy1.23.2direct
PyPIpandas2.2.3direct
PyPIpolars1.28.1direct
PyPIpyarrow16.0.0direct
PyPIpydantic—direct
PyPIpymemcache4.0.0direct
PyPIray—direct
PyPIredis5.0.0direct
PyPIschedule1.2.0direct
PyPItenacity8.2.3direct
PyPItyping-extensions—direct
PyPIpytest-benchmark4.0.0indirect
Dependency advisories 1

This repository publishes no package the index resolves, so its own dependency graph was assessed — 13 packages, which also include development and test pins that never ship: 1 carry known advisories, of which 1 are direct. 6 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
pyarrow16.0.0directhigh323.0.1

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.