Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-02 11:13 UTC

Kaggle / kaggle-cli

Official Kaggle CLI

PythonApache-2.0★ 7,523 stars⑂ 1,409 forkssince Jan 2018View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

Kaggle/kaggle-cli holds a health index of 96 out of 100, placing it in the Exceptional band. It scores highest on Community & Adoption (88/100) and lowest on AI Readiness (77/100). It was last updated 11 days ago. 3 contributors account for most of its recent work.

96
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.

96
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 84 is calibrated to 96 on the published index scale (record calibration 2026-08-02).

Ownership

KaggleOrganization
2,324 followers16 public repossince Jan 2012

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIkaggle2.2.4767,1569240 days agoapikaggle

Metrics by category

Vitality

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

87Excellent · 21% of overall
How it's scored
28.8/36Push recencylast push 11 days ago
27.7/36Commit cadence40/52 weeks with commits
18/18Commit volume242 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year242
human_commit_share0.98
days_since_last_push11
active_weeks_last_year40
How it's scored
27/27Ships releases16 releases published
36/36Release recencylatest release 40 days ago
19.8/27Release cadencea release every ~59 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count16
latest_release_tagv2.2.4
releases_from_tagsno
days_since_latest_release40
mean_days_between_releases59
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?

88Excellent · 17% of overall
How it's scored
60/60Stars7,523 stars
25/25Forks1,409 forks
12.9/15Watchers209 watchers
Inputs used
forks1,409
stars7,523
watchers209
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno
How it's scored
78.5/80Monthly downloads767,156 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packageskaggle
dependents
ecosystemspypi
total_downloads
monthly_downloads767,156
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?

80Excellent · 23% of overall
How it's scored
36/54Bus factor3 contributor(s) cover half of all commits
13.3/22.5Commit distributiontop contributor authored 41% of commits
13.5/13.5Contributor breadth67 contributors
10/10OpenSSF Scorecard: Contributorsproject has 36 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled67
top_contributor_share0.409
How it's scored
32.1/42Issue resolution76% of issues closed
23.8/30PR acceptance453/571 decided PRs merged
6.5/13Newcomer PR acceptance5/10 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs453
open_issues138
closed_issues447
prs_merged_7d0
prs_decided_7d0
prs_merged_30d15
prs_decided_30d21
issue_closed_ratio0.764
closed_unmerged_prs118
first_time_authors_30d6
first_time_prs_merged_30d5
first_time_prs_decided_30d10
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
24.2/25Owner reach2,324 followers of Kaggle
21/25Track record16 public repos, account ~14 yr old
Inputs used
followers2,324
owner_typeOrganization
is_verifiedno
owner_loginKaggle
public_repos16
account_age_days5,341

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 40 days ago
20/20Version history92 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packageskaggle
ecosystemspypi
any_deprecatedno
min_days_since_publish40

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.black])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests30 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_configno
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

86Excellent · 16% of overall

Security posture

83Excellent
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
2.5/2.5CI-Tests30 out of 30 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
7.5/7.5Code-Reviewall changesets reviewed
2.5/2.5Contributorsproject has 36 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
7.5/7.5Maintained30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
1/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
2/5SASTSAST tool is not run on all commits -- score normalized to 4
5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
7.5/7.5Token-PermissionsGitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate8.3
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages31
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:kaggle@2.2.4 runtime dependency closure — what installing the published package pulls in — 31 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.

77Good · 4% of overall
How it's scored
45/45Agent instructionsGEMINI.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history98 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share1
agent_instruction_filesGEMINI.md
agent_instruction_max_bytes1,601
How it's scored
18/18One-command bootstrapdocs/Makefile
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.black])
0/11Static type checking
10/10Reproducible environmentDockerfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance2 of the last 100 commits are automated dependency updates
2/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.02
How it's scored
0/45Type-checkable codePython without a type-check config
52.7/55Manageable file sizes3/71 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes479,944
source_files_sampled71
oversized_source_files3
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 examplesnotebooks
Inputs used
example_dirsnotebooks
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

7,523GitHub stars
67contributors
242commits, last 12 months
11days since last push
16releases
3bus factor
138open 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 ★ / 1,409 ⇿
0Stars
1,409Forks
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.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

05001,0001,5001,40992019-062023-012026-09
Major 0Minor 1Patch 10

Each point covers 7 days.

OpenSSF Scorecard 8.3 / 10
8.3aggregate

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 · 2026-09-02 11:12 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
10Code-Reviewall changesets reviewed
10Contributorsproject has 36 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
2Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
4SASTSAST tool is not run on all commits -- score normalized to 4
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 11
RegistryPackageVersion constraintManifest
PyPIbleachpyproject.toml
PyPIkagglesdk>= 0.1.37, < 1.0pyproject.toml
PyPIpython-slugifypyproject.toml
PyPIrequestspyproject.toml
PyPIpython-dateutilpyproject.toml
PyPItqdmpyproject.toml
PyPIurllib3>= 1.15.1pyproject.toml
PyPIpackagingpyproject.toml
PyPIprotobufpyproject.toml
PyPIjupytextpyproject.toml
PyPIpython-dotenvpyproject.toml
All dependencies 38

Full resolved dependency set from the GitHub dependency graph: 14 direct and 24 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbleachdirect
PyPIjupytextdirect
PyPIkagglesdkdirect
PyPIpackagingdirect
PyPIpackaging24.2direct
PyPIprotobufdirect
PyPIpython-dateutildirect
PyPIpython-dotenvdirect
PyPIpython-slugifydirect
PyPIrequestsdirect
PyPIrequests2.33.0direct
PyPItqdmdirect
PyPIurllib3direct
PyPIurllib32.7.0direct
PyPIcertifi2024.7.4indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.2.0indirect
PyPIcryptography50.0.0indirect
PyPIdocutils0.20.1indirect
PyPIidna3.15indirect
PyPIimportlib-metadata6.8.0indirect
PyPIjaraco-classes3.3.0indirect
PyPIjeepney0.8.0indirect
PyPIkeyring24.2.0indirect
PyPImarkdown-it-py3.0.0indirect
PyPImdurl0.1.2indirect
PyPImore-itertools10.1.0indirect
PyPInh30.2.14indirect
PyPIpkginfo1.12.0indirect
PyPIpycparser2.21indirect
PyPIpygments2.20.0indirect
PyPIreadme-renderer42.0indirect
PyPIrequests-toolbelt1.0.0indirect
PyPIrfc39862.0.0indirect
PyPIrich13.5.2indirect
PyPIsecretstorage3.3.3indirect
PyPItwine6.0.1indirect
PyPIzipp3.19.1indirect
Dependency advisories 0

Installing pypi:kaggle@2.2.4 pulls in 31 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 statisticsPyPI.