Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 03:01 UTC

rspeer / wordfreq

Access a database of word frequencies, in various natural languages.

PythonCustom license★ 1,726 stars⑂ 115 forkssince Oct 2013View on GitHub ↗

rspeer/wordfreq holds a health index of 26 out of 100, placing it in the At Risk band. It scores highest on Community & Adoption (63/100) and lowest on Vitality (15/100). It was last updated 585 days ago. A single contributor accounts for most of its recent work.

26
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.

26
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 46 is calibrated to 44 on the published index scale (record calibration 2026-08-02).

Ownership

Elia Robyn LakePersonal account
302 followers64 public repossince Mar 2010Tarro

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 publish
PyPIwordfreq3.1.1-31995 days ago

Metrics by category

Vitality

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

15Critical · 21% of overall
How it's scored
0/36Push recencylast push 585 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_push585
active_weeks_last_year0
How it's scored
27/27Ships releases6 releases published
0/36Release recencylatest release 1,416 days ago
5.4/27Release cadencea release every ~441.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count6
latest_release_tagv3.0.2
releases_from_tagsno
days_since_latest_release1,416
mean_days_between_releases441.8
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?

63Moderate · 17% of overall
How it's scored
52.5/60Stars1,726 stars
17.1/25Forks115 forks
9.3/15Watchers49 watchers
Inputs used
forks115
stars1,726
watchers49
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

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

56Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
6.7/22.5Commit distributiontop contributor authored 70% of commits
8.1/13.5Contributor breadth6 contributors
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled6
top_contributor_share0.703
How it's scored
30.7/42Issue resolution73% of issues closed
27.8/30PR acceptance74/80 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs74
open_issues10
closed_issues27
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.73
closed_unmerged_prs6
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
17.8/25Owner reach302 followers of rspeer
25/25Track record64 public repos, account ~16 yr old
Inputs used
followers302
owner_typeUser
is_verified
owner_loginrspeer
public_repos64
account_age_days5,978
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 995 days ago
20/20Version history31 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packageswordfreq
ecosystemspypi
any_deprecatedno
min_days_since_publish995

Engineering Quality

Are baseline engineering and documentation practices in place?

50Moderate · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config.flake8, tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

46Weak · 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
0/2.5CI-Testsno data
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/30 approved changesets -- score normalized to 0
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
0/10Dangerous-Workflowno data
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.2/2.5Licenselicense 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-Dependenciesno data
0/5SASTno SAST tool detected
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsno data
3.8/7.5Vulnerabilities5 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated12
scorecard_versionv5.5.0
checks_inconclusive6
scorecard_aggregate3.3
Excluded from scoring (no data or not applicable): CI-Tests, Dangerous-Workflow, Packaging, Pinned-Dependencies, 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
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:wordfreq@3.1.1 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.

52Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
13.5/40Legible commit history25 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.253
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config.flake8, tox.ini
11/11Static type checkingmypy.ini, wordfreq/py.typed
10/10Reproducible environmentlockfile
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-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configsmypy.ini, wordfreq/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.01
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
27/45Type-checkable codePython with type-check config (mypy.ini, wordfreq/py.typed)
55/55Manageable file sizes0/19 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes14,794
source_files_sampled19
oversized_source_files0

Key facts

1,726GitHub stars
6contributors
0commits, last 12 months
585days since last push
6releases
1bus factor
10open 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 ★ / 115 ⇿
0Stars
115Forks
6Releases

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.

020406080100120114222015-092021-022026-07
Major 0Minor 0Patch 3

Each point covers 10 days.

OpenSSF Scorecard 3.3 / 10
3.3aggregate

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 · 2026-08-13 03:01 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
n/aDangerous-Workflowno workflows found
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
5Vulnerabilities5 existing vulnerabilities detected
Direct dependencies 9
RegistryPackageVersion constraintManifest
PyPImsgpack^1.0.7pyproject.toml
PyPIlangcodes>= 3.0pyproject.toml
PyPIregex>= 2023.10.3pyproject.toml
PyPIftfy>= 6.3pyproject.toml
PyPImecab-python3^1.0.5pyproject.toml
PyPIipadic^1.0.0pyproject.toml
PyPImecab-ko-dic^1.0.0pyproject.toml
PyPIjieba>=0.42pyproject.toml
PyPIlocate^1.1.1pyproject.toml
All dependencies 41

Full resolved dependency set from the GitHub dependency graph: 9 direct and 32 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIftfy6.3.1direct
PyPIipadic1.0.0direct
PyPIjieba0.42.1direct
PyPIlangcodes3.5.0direct
PyPIlocate1.1.1direct
PyPImecab-ko-dic1.0.0direct
PyPImecab-python31.0.10direct
PyPImsgpack1.1.0direct
PyPIregex2024.11.6direct
PyPIasttokens3.0.0indirect
PyPIcolorama0.4.6indirect
PyPIdecorator5.1.1indirect
PyPIexceptiongroup1.2.2indirect
PyPIexecuting2.1.0indirect
PyPIgprof2dot2024.6.6indirect
PyPIiniconfig2.0.0indirect
PyPIipython8.18.1indirect
PyPIjedi0.19.2indirect
PyPIlanguage-data1.3.0indirect
PyPImarisa-trie1.2.1indirect
PyPImatplotlib-inline0.1.7indirect
PyPImypy1.14.1indirect
PyPImypy-extensions1.0.0indirect
PyPIpackaging24.2indirect
PyPIparso0.8.4indirect
PyPIpexpect4.9.0indirect
PyPIpluggy1.5.0indirect
PyPIprompt-toolkit3.0.48indirect
PyPIptyprocess0.7.0indirect
PyPIpure-eval0.2.3indirect
PyPIpygments2.18.0indirect
PyPIpytest7.4.4indirect
PyPIpytest-profiling1.8.1indirect
PyPIruff0.1.15indirect
PyPIsetuptools75.6.0indirect
PyPIsix1.17.0indirect
PyPIstack-data0.6.3indirect
PyPItomli2.2.1indirect
PyPItraitlets5.14.3indirect
PyPItyping-extensions4.12.2indirect
PyPIwcwidth0.2.13indirect
Dependency advisories 0

Installing pypi:wordfreq@3.1.1 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 v0.31.0 — full methodology · metrics wiki.

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