Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-27 12:42 UTC

apache / iceberg-python

PyIceberg

PythonApache-2.0★ 1,121 stars⑂ 564 forkssince Aug 2023View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

apache/iceberg-python holds a health index of 98 out of 100, placing it in the Exceptional band. It scores highest on Vitality (92/100) and lowest on Community & Adoption (82/100). It was last updated 1 day ago. 3 contributors account for most of its recent work.

98
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.

98
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 87 is calibrated to 98 on the published index scale (record calibration 2026-08-02).

Ownership

The Apache Software FoundationOrganization · verified domain
23,994 followers3,163 public repossince Jan 2009

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIpyiceberg0.11.138,788,06463177 days ago

Metrics by category

Vitality

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

92Excellent · 21% of overall
How it's scored
36/36Push recencylast push 1 days ago
34.6/36Commit cadence50/52 weeks with commits
18/18Commit volume877 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_year877
human_commit_share0.44
days_since_last_push1
active_weeks_last_year50
How it's scored
27/27Ships releases14 releases published
27/36Release recencylatest release 177 days ago
19.8/27Release cadencea release every ~62.3 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count14
latest_release_tagpyiceberg-0.11.1
releases_from_tagsno
days_since_latest_release177
mean_days_between_releases62.3
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?

82Excellent · 17% of overall
How it's scored
49.5/60Stars1,121 stars
22.9/25Forks564 forks
8/15Watchers29 watchers
Inputs used
forks564
stars1,121
watchers29
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)
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_badges0
has_contributingno
has_issue_templateno
has_code_of_conductyes
readme_badge_services
has_pull_request_templateyes
How it's scored
80/80Monthly downloads38,788,064 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagespyiceberg
dependents
ecosystemspypi
total_downloads
monthly_downloads38,788,064
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?

86Excellent · 23% of overall
How it's scored
36/54Bus factor3 contributor(s) cover half of all commits
14.5/22.5Commit distributiontop contributor authored 36% of commits
13.5/13.5Contributor breadth99 contributors
10/10OpenSSF Scorecard: Contributorsproject has 24 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled99
top_contributor_share0.355
How it's scored
35.7/42Issue resolution85% of issues closed
24.4/30PR acceptance2,278/2,801 decided PRs merged
2.2/13Newcomer PR acceptance2/12 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs2,278
open_issues145
closed_issues817
prs_merged_7d9
prs_decided_7d22
prs_merged_30d22
prs_decided_30d45
issue_closed_ratio0.849
closed_unmerged_prs523
first_time_authors_30d11
first_time_prs_merged_30d2
first_time_prs_decided_30d12
How it's scored
30/30Ownership backingorganization-owned
20/20Verified domain
25/25Owner reach23,994 followers of apache
25/25Track record3,163 public repos, account ~17 yr old
Inputs used
followers23,994
owner_typeOrganization
is_verifiedyes
owner_loginapache
public_repos3,163
account_age_days6,430

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 177 days ago
20/20Version history63 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagespyiceberg
ecosystemspypi
any_deprecatedno
min_days_since_publish177

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall
How it's scored
24/24CI workflows14 workflow(s)
24/24Tests present
16/16Linter configruff.toml
9.6/9.6Pre-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_configyes
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://py.iceberg.apache.org/
10/10Repository description
10/10Topics4 topics
10/10Wiki
Inputs used
topicsapache, hacktoberfest, iceberg, pyiceberg
has_wikiyes
homepagehttps://py.iceberg.apache.org/
docs_sitehttps://py.iceberg.apache.org/
has_readmeyes
has_docs_dirno
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-Protectionbranch protection not enabled on development/release branches
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 24 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
5/5Packagingpackaging workflow detected
4.5/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
5/5SASTSAST tool is run on all commits
5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
7.5/7.5Token-PermissionsGitHub workflow tokens follow principle of least privilege
6.8/7.5Vulnerabilities1 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate8.3
Excluded from scoring (no data or not applicable): 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_packages25
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:pyiceberg@0.11.1 runtime dependency closure — what installing the published package pulls in — 25 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.

89Excellent · 4% of overall
How it's scored
45/45Agent instructions.github/copilot-instructions.md, AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history44 of 44 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share1
agent_instruction_files.github/copilot-instructions.md, AGENTS.md, CLAUDE.md
agent_instruction_max_bytes5,923
How it's scored
18/18One-command bootstrapMakefile, vendor/Makefile
22/22Automated tests
11/11Lint / format configruff.toml
11/11Static type checkingpyiceberg/py.typed
10/10Reproducible environmentDockerfile, lockfile
2/10Demonstrated agent practice1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance56 of the last 100 commits are automated dependency updates
9/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile, vendor/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configspyiceberg/py.typed
agent_commit_share0.01
toolchain_manifests
dependency_bot_commit_share0.56
How it's scored
27/45Type-checkable codePython with type-check config (pyiceberg/py.typed)
50.5/55Manageable file sizes16/194 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes214,324
source_files_sampled194
oversized_source_files16
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

1,121GitHub stars
99contributors
877commits, last 12 months
1days since last push
14releases
3bus factor
145open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 28 authors (cap 12)

More detail

Star and fork history 0 ★ / 564 ⇿
0Stars
564Forks
14Releases

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.

010020030040050060055472023-102025-032026-08
Major 0Minor 0Patch 0

Each point covers 3 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 · 2026-08-27 12:41 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
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 24 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
10Packagingpackaging workflow detected
9Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
9Vulnerabilities1 existing vulnerabilities detected
Direct dependencies 12
RegistryPackageVersion constraintManifest
PyPImmh3>=4.0.0pyproject.toml
PyPIrequests>=2.20.0pyproject.toml
PyPIclick>=7.1.1pyproject.toml
PyPIrich>=10.11.0pyproject.toml
PyPIstrictyaml>=1.7.0pyproject.toml
PyPIpydantic>=2.0,<3.0,!=2.4.0,!=2.4.1,!=2.12.0,!=2.12.1pyproject.toml
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PyPIpyroaring>=1.0.0pyproject.toml
PyPIcachetools>=5.5pyproject.toml
PyPIzstandard>=0.13.0pyproject.toml
All dependencies 296

Full resolved dependency set from the GitHub dependency graph: 12 direct and 284 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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PyPIsix1.17.0indirect
PyPIsnowballstemmer3.1.1indirect
PyPIsoupsieve2.8.4indirect
PyPIsphinx3.5.3indirect
PyPIsphinxcontrib-applehelp2.0.0indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
PyPIsqlalchemy2.0.52indirect
PyPIstack-data0.6.3indirect
PyPIsympy1.14.0indirect
PyPIterminado0.18.1indirect
PyPIthrift0.24.0indirect
PyPIthrift-sasl0.4.3indirect
PyPItinycss21.5.1indirect
PyPItomli2.4.1indirect
PyPItornado6.5.7indirect
PyPItqdm4.67.3indirect
PyPItraitlets5.15.1indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2026.2indirect
PyPIuri-template1.3.0indirect
PyPIurllib32.7.0indirect
PyPIvirtualenv21.5.1indirect
PyPIwatchdog6.0.0indirect
PyPIwcwidth0.8.2indirect
PyPIwebcolors25.10.0indirect
PyPIwebencodings0.5.1indirect
PyPIwebsocket-client1.9.0indirect
PyPIwerkzeug3.1.8indirect
PyPIwrapt2.2.2indirect
PyPIxmltodict1.0.4indirect
PyPIyarl1.24.2indirect
PyPIzipp4.1.0indirect
Dependency advisories 0

Installing pypi:pyiceberg@0.11.1 pulls in 25 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

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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.

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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.