Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-28 01:17 UTC

arrow-py / arrow

🏹 Better dates & times for Python

PythonApache-2.0★ 9,047 stars⑂ 774 forkssince Nov 2012View on GitHub ↗

arrow-py/arrow holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (92/100) and lowest on Vitality (45/100). It was last updated 66 days ago. 3 contributors account for most of its recent work.

83
overall / 100
Excellent

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.

83
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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

ArrowOrganization
18 followers1 public reposince Jul 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIarrow1.4.076,182,65265313 days agoarrowdatetimedatetimetimestamptimezonehumanize

Metrics by category

Vitality

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

45Weak · 21% of overall
How it's scored
18/36Push recencylast push 66 days ago
4.8/36Commit cadence7/52 weeks with commits
11.7/18Commit volume19 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_year19
human_commit_share0.91
days_since_last_push66
active_weeks_last_year7
How it's scored
27/27Ships releases46 releases published
16.2/36Release recencylatest release 307 days ago
12.6/27Release cadencea release every ~188.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count46
latest_release_tag1.4.0
releases_from_tagsno
days_since_latest_release307
mean_days_between_releases188.8
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?

83Excellent · 17% of overall
How it's scored
60/60Stars9,047 stars
24.1/25Forks774 forks
11.7/15Watchers129 watchers
Inputs used
forks774
stars9,047
watchers129
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
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateyes
How it's scored
80/80Monthly downloads76,182,652 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesarrow
dependents
ecosystemspypi
total_downloads
monthly_downloads76,182,652
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?

71Good · 23% of overall
How it's scored
36/54Bus factor3 contributor(s) cover half of all commits
16.5/22.5Commit distributiontop contributor authored 27% of commits
13.5/13.5Contributor breadth99 contributors
10/10OpenSSF Scorecard: Contributorsproject has 19 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled99
top_contributor_share0.266
How it's scored
34.1/42Issue resolution81% of issues closed
23.5/30PR acceptance561/716 decided PRs merged
0/13Newcomer PR acceptance0/1 first-time contributors' PRs merged in 30d
9/15OpenSSF Scorecard: Code-ReviewFound 17/25 approved changesets -- score normalized to 6
Inputs used
merged_prs561
open_issues96
closed_issues413
prs_merged_7d0
prs_decided_7d1
prs_merged_30d0
prs_decided_30d1
issue_closed_ratio0.811
closed_unmerged_prs155
first_time_authors_30d1
first_time_prs_merged_30d0
first_time_prs_decided_30d1
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
9.2/25Owner reach18 followers of arrow-py
14.2/25Track record1 public repos, account ~6 yr old
Inputs used
followers18
owner_typeOrganization
is_verifiedno
owner_loginarrow-py
public_repos1
account_age_days2,230
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 313 days ago
20/20Version history65 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesarrow
ecosystemspypi
any_deprecatedno
min_days_since_publish313

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
16/16Linter configtox.ini
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
12/20OpenSSF Scorecard: CI-Tests16 out of 25 merged PRs checked by a CI test -- score normalized to 6
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://arrow.readthedocs.io
10/10Repository description
10/10Topics8 topics
10/10Wiki
Inputs used
topicspython, arrow, datetime, date, time, timestamp, timezones, hacktoberfest
has_wikiyes
homepagehttps://arrow.readthedocs.io
docs_sitehttps://arrow.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

66Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
6/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
1.5/2.5CI-Tests16 out of 25 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
4.5/7.5Code-ReviewFound 17/25 approved changesets -- score normalized to 6
2.5/2.5Contributorsproject has 19 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
5/5Fuzzingproject is 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-Permissionsdetected GitHub workflow tokens with excessive permissions
6/7.5Vulnerabilities2 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.7
Excluded from scoring (no data or not applicable): 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_packages3
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:arrow@1.4.0 runtime dependency closure — what installing the published package pulls in — 3 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.

64Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt)llms.txt served by the project website (https://tox.readthedocs.io/llms.txt)
36.3/40Legible commit history62 of 91 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://tox.readthedocs.io/llms.txt
legible_history_share0.681
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile, docs/Makefile
22/22Automated tests
11/11Lint / format configtox.ini
11/11Static type checkingarrow/py.typed
0/10Reproducible environment
2/10Demonstrated agent practice1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance9 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_configsarrow/py.typed
agent_commit_share0.01
toolchain_manifests
dependency_bot_commit_share0.09
How it's scored
27/45Type-checkable codePython with type-check config (arrow/py.typed)
41.9/55Manageable file sizes5/21 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes199,250
source_files_sampled21
oversized_source_files5

Key facts

9,047GitHub stars
99contributors
19commits, last 12 months
66days since last push
46releases
3bus factor
96open 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 ★ / 774 ⇿
0Stars
774Forks
46Releases

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.

0200400600800766162012-112019-102026-08
Major 1Minor 15Patch 30

Each point covers 13 days.

OpenSSF Scorecard 5.7 / 10
5.7aggregate

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 · 2026-08-28 01:17 UTC

10Binary-Artifactsno binaries found in the repo
8Branch-Protectionbranch protection is not maximal on development and all release branches
6CI-Tests16 out of 25 merged PRs checked by a CI test -- score normalized to 6
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 17/25 approved changesets -- score normalized to 6
10Contributorsproject has 19 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
10Fuzzingproject is 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
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
8Vulnerabilities2 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPIpython-dateutil>=2.7.0pyproject.toml
PyPIbackports.zoneinfo==0.2.1pyproject.toml
PyPItzdatapyproject.toml
All dependencies 16

Full resolved dependency set from the GitHub dependency graph: 3 direct and 13 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbackports-zoneinfo0.2.1direct
PyPIpython-dateutildirect
PyPItzdatadirect
PyPIdateparser1.*indirect
PyPIdoc8indirect
PyPIpre-commitindirect
PyPIpytestindirect
PyPIpytest-covindirect
PyPIpytest-mockindirect
PyPIpytz2025.2indirect
PyPIsimplejson3.*indirect
PyPIsphinxindirect
PyPIsphinx-autobuildindirect
PyPIsphinx-autodoc-typehintsindirect
PyPIsphinx-rtd-themeindirect
PyPItypes-python-dateutilindirect
Dependency advisories 0

Installing pypi:arrow@1.4.0 pulls in 3 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.