Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 01:33 UTC

jmcarpenter2 / swifter

A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner

PythonMIT★ 2,638 stars⑂ 104 forkssince Apr 2018View on GitHub ↗

jmcarpenter2/swifter holds a health index of 27 out of 100, placing it in the At Risk band. It scores highest on Community & Adoption (66/100) and lowest on Vitality (17/100). It was last updated 875 days ago. 3 contributors account for most of its recent work.

27
overall / 100
At Risk

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.

27
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 47 is calibrated to 45 on the published index scale (record calibration 2026-08-02).

Ownership

Jason CarpenterPersonal account
90 followers13 public repossince Jun 2017

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
PyPIswifter1.4.0-861108 days agopandasdaskapplyfunctionparallelizevectorize

Metrics by category

Vitality

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

17Critical · 21% of overall
How it's scored
0/36Push recencylast push 875 days ago
0/36Commit cadence0/52 weeks with commits
0/18Commit volume0 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_year0
human_commit_share0.99
days_since_last_push875
active_weeks_last_year0
How it's scored
16.2/27Ships releases22 version tags (no GitHub releases)
0/36Release recencylatest release 1,108 days ago
19.8/27Release cadencea release every ~52.7 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count22
latest_release_tag1.4.0
releases_from_tagsyes
days_since_latest_release1,108
mean_days_between_releases52.7
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?

66Good · 17% of overall
How it's scored
55.5/60Stars2,638 stars
16.8/25Forks104 forks
8/15Watchers28 watchers
Inputs used
forks104
stars2,638
watchers28
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
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_badges6
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, circleci.com, shields.io
has_pull_request_templateno

Sustainability & Governance

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

65Good · 23% of overall
How it's scored
36/54Bus factor3 contributor(s) cover half of all commits
15.4/22.5Commit distributiontop contributor authored 32% of commits
13.5/13.5Contributor breadth11 contributors
0/10OpenSSF Scorecard: Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor3
contributors_sampled11
top_contributor_share0.316
How it's scored
35.4/42Issue resolution84% of issues closed
26/30PR acceptance72/83 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-ReviewFound 1/8 approved changesets -- score normalized to 1
Inputs used
merged_prs72
open_issues24
closed_issues128
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.842
closed_unmerged_prs11
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
14.1/25Owner reach90 followers of jmcarpenter2
20.3/25Track record13 public repos, account ~9 yr old
Inputs used
followers90
owner_typeUser
is_verified
owner_loginjmcarpenter2
public_repos13
account_age_days3,340
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
4/35Publish recencylatest publish 1,108 days ago
20/20Version history86 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesswifter
ecosystemspypi
any_deprecatedno
min_days_since_publish1,108

Engineering Quality

Are baseline engineering and documentation practices in place?

44Weak · 19% of overall
How it's scored
0/24CI workflows
0/24Tests present
16/16Linter configtox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 8 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsno
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics6 topics
10/10Wiki
Inputs used
topicspandas, pandas-dataframe, parallel-computing, parallelization, dask, modin
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?

42Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0/2.5CI-Tests0 out of 8 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-ReviewFound 1/8 approved changesets -- score normalized to 1
0/2.5Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
0/10Dangerous-Workflowno data
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
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-Releasesno data
0/7.5Token-Permissionsno data
0/7.5Vulnerabilities13 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate2.7
Excluded from scoring (no data or not applicable): Branch-Protection, Dangerous-Workflow, Packaging, Signed-Releases, Token-Permissions. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories19
affected_packages3
assessed_packages5
unassessed_packages10
affected_by_severitycritical 2, moderate 1
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 5 resolved dependencies against OSV. 10 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.

47Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
18.3/40Legible commit history34 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.343
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile
0/22Automated tests
11/11Lint / format configtox.ini
0/11Static type checking
10/10Reproducible environmentDockerfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance1 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_testsno
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.01
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/7 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes48,584
source_files_sampled7
oversized_source_files0
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

2,638GitHub stars
11contributors
0commits, last 12 months
875days since last push
22releases
3bus factor
24open 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 ★ / 104 ⇿
0Stars
104Forks
22Releases

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.

02040608010012010442018-042022-012025-10
Major 1Minor 4Patch 17

Each point covers 7 days.

OpenSSF Scorecard 2.7 / 10
2.7aggregate

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 · 2026-08-13 01:32 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
0CI-Tests0 out of 8 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 1/8 approved changesets -- score normalized to 1
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
n/aDangerous-Workflowno workflows found
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
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
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
0Vulnerabilities13 existing vulnerabilities detected
All dependencies 15

Full resolved dependency set from the GitHub dependency graph: 0 direct and 15 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIblack22.3.0indirect
PyPIcodecovindirect
PyPIcoverageindirect
PyPIdaskindirect
PyPIflake83.7.7indirect
PyPIipywidgetsindirect
PyPIjupyterlab3.6.7indirect
PyPImodinindirect
PyPInoseindirect
PyPIpandasindirect
PyPIperfplot0.7.3indirect
PyPIpsutilindirect
PyPIpytest6.2.2indirect
PyPIrayindirect
PyPItqdmindirect
Dependency advisories 3

This repository publishes no package the index resolves, so its own dependency graph was assessed — 5 packages, which also include development and test pins that never ship: 3 carry known advisories, of which 0 are direct. 10 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
black22.3.0indirectcritical426.3.1
jupyterlab3.6.7indirectcritical137.5.6
pytest6.2.2indirectmoderate29.0.3

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 v0.31.0 — full methodology · metrics wiki.

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