Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-19 10:34 UTC

tidy-finance / py-tidyfinance

Python package with helper functions for developers and researchers familiar with Tidy Finance

PythonMIT★ 20 stars⑂ 7 forkssince Dec 2024View on GitHub ↗

tidy-finance/py-tidyfinance holds a health index of 77 out of 100, placing it in the Good band. It scores highest on Vitality (79/100) and lowest on Community & Adoption (38/100). It was last updated 4 days ago. 2 contributors account for most of its recent work.

77
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.

77
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 66 is calibrated to 77 on the published index scale (record calibration 2026-08-02).

Ownership

Tidy FinanceOrganization
104 followers9 public repossince Jan 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPItidyfinance0.5.1-1017 days ago

Metrics by category

Vitality

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

79Good · 21% of overall
How it's scored
36/36Push recencylast push 4 days ago
11.8/36Commit cadence17/52 weeks with commits
18/18Commit volume263 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year263
human_commit_share1
days_since_last_push4
active_weeks_last_year17
How it's scored
27/27Ships releases5 releases published
36/36Release recencylatest release 17 days ago
12.6/27Release cadencea release every ~132.3 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count5
latest_release_tagv0.5.1
releases_from_tagsno
days_since_latest_release17
mean_days_between_releases132.3
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?

38Weak · 17% of overall
How it's scored
20.7/60Stars20 stars
6.5/25Forks7 forks
0/15Watchers2 watchers
Inputs used
forks7
stars20
watchers2
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_badges5
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateno

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
25.2/54Bus factor2 contributor(s) cover half of all commits
12.5/22.5Commit distributiontop contributor authored 44% of commits
9.5/13.5Contributor breadth7 contributors
10/10OpenSSF Scorecard: Contributorsproject has 4 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled7
top_contributor_share0.445
How it's scored
42/42Issue resolution100% of issues closed
26.7/30PR acceptance49/55 decided PRs merged
6.5/13Newcomer PR acceptance1/2 first-time contributors' PRs merged in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 2/7 approved changesets -- score normalized to 2
Inputs used
merged_prs49
open_issues0
closed_issues23
prs_merged_7d0
prs_decided_7d0
prs_merged_30d3
prs_decided_30d4
issue_closed_ratio1
closed_unmerged_prs6
first_time_authors_30d1
first_time_prs_merged_30d1
first_time_prs_decided_30d2
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
14.5/25Owner reach104 followers of tidy-finance
14.6/25Track record9 public repos, account ~3 yr old
Inputs used
followers104
owner_typeOrganization
is_verifiedno
owner_logintidy-finance
public_repos9
account_age_days1,338

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 17 days ago
20/20Version history10 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagestidyfinance
ecosystemspypi
any_deprecatedno
min_days_since_publish17

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall
How it's scored
24/24CI workflows3 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests7 out of 7 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://python.tidy-finance.org/
10/10Repository description
10/10Topics2 topics
0/10Wiki
Inputs used
topicsfinance, python
has_wikino
homepagehttps://python.tidy-finance.org/
docs_sitehttps://python.tidy-finance.org/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

57Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
3/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests7 out of 7 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
1.5/7.5Code-ReviewFound 2/7 approved changesets -- score normalized to 2
2.5/2.5Contributorsproject has 4 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
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
3/7.5Vulnerabilities6 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4.6
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_packages21
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:tidyfinance@0.5.1 runtime dependency closure — what installing the published package pulls in — 21 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.

66Good · 4% of overall
How it's scored
45/45Agent instructionsCLAUDE.md
15/15Machine-readable docs (llms.txt)llms.txt served by the project website (https://python.tidy-finance.org/llms.txt)
30.4/40Legible commit history57 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://python.tidy-finance.org/llms.txt
legible_history_share0.57
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes4,241
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environmentlockfile
10/10Demonstrated agent practice31 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0.31
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
51.1/55Manageable file sizes4/57 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes104,205
source_files_sampled57
oversized_source_files4

Key facts

20GitHub stars
7contributors
263commits, last 12 months
4days since last push
5releases
2bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'tidyfinance' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced

More detail

Star and fork history 0 ★ / 7 ⇿
0Stars
7Forks
3Releases

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.

1234567712025-042025-122026-08
Major 0Minor 3Patch 0

Each point covers 2 days.

OpenSSF Scorecard 4.6 / 10
4.6aggregate

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 · 2026-09-19 10:34 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests7 out of 7 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 2/7 approved changesets -- score normalized to 2
10Contributorsproject has 4 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
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
4Vulnerabilities6 existing vulnerabilities detected
Direct dependencies 9
RegistryPackageVersion constraintManifest
PyPIpolars>=1.0.0pyproject.toml
PyPIpandas>=2.2.0pyproject.toml
PyPIpyarrow>=19.0.1pyproject.toml
PyPInumpy>=1.26.0pyproject.toml
PyPIcurl_cffi>=0.10.0pyproject.toml
PyPIsqlalchemy>=2.0.21pyproject.toml
PyPIpsycopg2-binary>=2.9.9pyproject.toml
PyPIpython-dotenv>=1.0.0pyproject.toml
PyPIformulaic>=1.0.0pyproject.toml
All dependencies 136

Full resolved dependency set from the GitHub dependency graph: 10 direct and 126 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPIformulaic1.2.2direct
PyPInumpy2.4.6direct
PyPInumpy2.5.0direct
PyPIpandas3.0.3direct
PyPIpolars1.42.0direct
PyPIpsycopg2-binary2.9.12direct
PyPIpyarrow24.0.0direct
PyPIpython-dotenv1.2.2direct
PyPIsqlalchemy2.0.51direct
PyPIanyio4.14.1indirect
PyPIappnope0.1.4indirect
PyPIargon2-cffi25.1.0indirect
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PyPIarrow1.4.0indirect
PyPIasttokens3.0.1indirect
PyPIasync-lru2.3.0indirect
PyPIattrs26.1.0indirect
PyPIbabel2.18.0indirect
PyPIbeautifulsoup44.15.0indirect
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PyPIpyzmq27.1.0indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIrfc3339-validator0.1.4indirect
PyPIrfc3986-validator0.1.1indirect
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PyPIrpds-py2026.5.1indirect
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PyPIscipy1.17.1indirect
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PyPIsix1.17.0indirect
PyPIsoupsieve2.8.4indirect
PyPIstack-data0.6.3indirect
PyPIterminado0.18.1indirect
PyPItidyfinance0.5.1indirect
PyPItinycss21.5.1indirect
PyPItomli2.4.1indirect
PyPItornado6.5.8indirect
PyPItraitlets5.15.1indirect
PyPItyping-extensions4.15.0indirect
PyPItzdata2026.2indirect
PyPIuri-template1.3.0indirect
PyPIurllib32.7.0indirect
PyPIwcwidth0.8.1indirect
PyPIwebcolors25.10.0indirect
PyPIwebencodings0.5.1indirect
PyPIwebsocket-client1.9.0indirect
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Dependency advisories 0

Installing pypi:tidyfinance@0.5.1 pulls in 21 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.