Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-27 20:53 UTC

pudo / dataset

Easy-to-use data handling for SQL data stores with support for implicit table creation, bulk loading, and transactions.

PythonMIT★ 4,871 stars⑂ 298 forkssince Apr 2013View on GitHub ↗

pudo/dataset holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Engineering Quality (82/100) and lowest on Vitality (49/100). It was last updated 36 days ago. A single contributor accounts for most of its recent work.

78
overall / 100
Good

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.

78
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 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

Friedrich LindenbergPersonal account
996 followers49 public repossince Dec 2008@opensanctions

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdataset2.0.02,320,24056137 days agoetlloadingsqlsqlalchemyutility

Metrics by category

Vitality

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

49Weak · 21% of overall
How it's scored
18/36Push recencylast push 36 days ago
1.4/36Commit cadence2/52 weeks with commits
13.6/18Commit volume32 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year32
human_commit_share0.87
days_since_last_push36
active_weeks_last_year2
How it's scored
27/27Ships releases1 releases published
27/36Release recencylatest release 137 days ago
12.6/27Release cadencecadence unknown (single release)
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count1
latest_release_tag2.0.0
releases_from_tagsno
days_since_latest_release137
mean_days_between_releases
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?

79Good · 17% of overall
How it's scored
59.8/60Stars4,871 stars
20.6/25Forks298 forks
11/15Watchers97 watchers
Inputs used
forks298
stars4,871
watchers97
growth_stateorganic
growth_factor_pct100
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges1
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com
has_pull_request_templateno
How it's scored
80/80Monthly downloads2,320,240 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesdataset
dependents
ecosystemspypi
total_downloads
monthly_downloads2,320,240
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?

68Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
9.2/22.5Commit distributiontop contributor authored 59% of commits
13.5/13.5Contributor breadth59 contributors
10/10OpenSSF Scorecard: Contributorsproject has 27 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled59
top_contributor_share0.591
How it's scored
39.2/42Issue resolution93% of issues closed
22.1/30PR acceptance107/145 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/17 approved changesets -- score normalized to 0
Inputs used
merged_prs107
open_issues20
closed_issues279
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.933
closed_unmerged_prs38
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
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
21.6/25Owner reach996 followers of pudo
24.4/25Track record49 public repos, account ~17 yr old
Inputs used
followers996
owner_typeUser
is_verified
owner_loginpudo
public_repos49
account_age_days6,460
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 137 days ago
20/20Version history56 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesdataset
ecosystemspypi
any_deprecatedno
min_days_since_publish137

Engineering Quality

Are baseline engineering and documentation practices in place?

82Excellent · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
12/20OpenSSF Scorecard: CI-Tests2 out of 3 merged PRs checked by a CI test -- score normalized to 6
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://dataset.readthedocs.org/
10/10Repository description
10/10Topics3 topics
0/10Wiki
Inputs used
topicssql, database, python
has_wikino
homepagehttps://dataset.readthedocs.org/
docs_sitehttps://dataset.readthedocs.org/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

56Moderate · 16% of overall
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
1.5/2.5CI-Tests2 out of 3 merged PRs checked by a CI test -- score normalized to 6
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/17 approved changesets -- score normalized to 0
2.5/2.5Contributorsproject has 27 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
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
5/5Packagingpackaging workflow detected
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-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4.5
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_packages6
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:dataset@2.0.0 runtime dependency closure — what installing the published package pulls in — 6 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.

73Good · 4% of overall
How it's scored
45/45Agent instructionsCLAUDE.md
0/15Machine-readable docs (llms.txt)
22.1/40Legible commit history36 of 87 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.414
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes12,392
How it's scored
18/18One-command bootstrapMakefile, docs/Makefile
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff])
11/11Static type checkingdataset/py.typed
0/10Reproducible environment
4/10Demonstrated agent practice2 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance3 of the last 100 commits are automated dependency updates
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_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configsdataset/py.typed
agent_commit_share0.02
toolchain_manifests
dependency_bot_commit_share0.03
How it's scored
27/45Type-checkable codePython with type-check config (dataset/py.typed)
55/55Manageable file sizes0/12 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes32,767
source_files_sampled12
oversized_source_files0

Key facts

4,871GitHub stars
59contributors
32commits, last 12 months
36days since last push
1releases
1bus factor
20open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Star history carried forward from 2026-07-08: GitHub restricted the stargazers API to repository admins, so it can no longer be collected. The repository has 4871 stars today.

More detail

Star and fork history 4,868 ★ / 298 ⇿
4,868Stars
298Forks
1Releases

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.

Star history is shown as collected on 2026-07-08. GitHub restricted the stargazers API to repository administrators in July 2026, so this series can no longer be extended; the current star total above remains live.

01,0002,0003,0004,0005,0004,868291962013-042019-112026-06
Major 1Minor 0Patch 0

Each point covers 13 days.

OpenSSF Scorecard 4.5 / 10
4.5aggregate

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 20:52 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
6CI-Tests2 out of 3 merged PRs checked by a CI test -- score normalized to 6
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/17 approved changesets -- score normalized to 0
10Contributorsproject has 27 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate 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
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPIsqlalchemy>=1.4.0,<3.0.0pyproject.toml
PyPIalembic>=0.6.2pyproject.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
PyPIalembicdirect
PyPIsqlalchemydirect
PyPIfuroindirect
Dependency advisories 0

Installing pypi:dataset@2.0.0 pulls in 6 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.