Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-19 15:20 UTC

tortoise / pypika-tortoise

Forked from pypika and streamline just for tortoise-orm

PythonApache-2.0★ 10 stars⑂ 12 forkssince Mar 2021View on GitHub ↗

tortoise/pypika-tortoise holds a health index of 51 out of 100, placing it in the Moderate band. It scores highest on Sustainability & Governance (80/100) and lowest on Security (33/100). It was last updated 158 days ago. 2 contributors account for most of its recent work.

51
overall / 100
Moderate

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.

51
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 51 is calibrated to 51 on the published index scale (record calibration 2026-08-02).

Ownership

TortoiseOrganization
94 followers9 public repossince Aug 2018

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpypika-tortoise0.6.5-21158 days agopostgresqltortoise-ormmysqlsqlitesql

Metrics by category

Vitality

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

45Weak · 21% of overall
How it's scored
9.9/36Push recencylast push 158 days ago
2.8/36Commit cadence4/52 weeks with commits
8.6/18Commit volume8 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_year8
human_commit_share1
days_since_last_push158
active_weeks_last_year4
How it's scored
27/27Ships releases21 releases published
27/36Release recencylatest release 158 days ago
19.8/27Release cadencea release every ~52.3 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count21
latest_release_tagv0.6.5
releases_from_tagsno
days_since_latest_release158
mean_days_between_releases52.3
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?

36Weak · 17% of overall
How it's scored
15.5/60Stars10 stars
8.7/25Forks12 forks
0/15Watchers1 watchers
Inputs used
forks12
stars10
watchers1
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
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno

Sustainability & Governance

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

80Excellent · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
14.9/22.5Commit distributiontop contributor authored 34% of commits
10.8/13.5Contributor breadth8 contributors
10/10OpenSSF Scorecard: Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor2
contributors_sampled8
top_contributor_share0.339
How it's scored
42/42Issue resolution100% of issues closed
27.2/30PR acceptance29/32 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
7.5/15OpenSSF Scorecard: Code-ReviewFound 10/18 approved changesets -- score normalized to 5
Inputs used
merged_prs29
open_issues0
closed_issues8
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio1
closed_unmerged_prs3
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
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
14.2/25Owner reach94 followers of tortoise
19.3/25Track record9 public repos, account ~7 yr old
Inputs used
followers94
owner_typeOrganization
is_verified
owner_logintortoise
public_repos9
account_age_days2,916
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 158 days ago
20/20Version history21 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagespypika-tortoise
ecosystemspypi
any_deprecatedno
min_days_since_publish158

Engineering Quality

Are baseline engineering and documentation practices in place?

51Moderate · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
4/20OpenSSF Scorecard: CI-Tests5 out of 19 merged PRs checked by a CI test -- score normalized to 2
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

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?

33At Risk · 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
0.5/2.5CI-Tests5 out of 19 merged PRs checked by a CI test -- score normalized to 2
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3.8/7.5Code-ReviewFound 10/18 approved changesets -- score normalized to 5
2.5/2.5Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
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
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
0/7.5Vulnerabilities16 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate3.3
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

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.

54Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
26.7/40Legible commit history50 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.5
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
0/11Lint / format config
11/11Static type checkingpypika_tortoise/py.typed
10/10Reproducible environmentlockfile
4/10Demonstrated agent practice2 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_filesMakefile
has_devcontainerno
has_linter_configno
typecheck_configspypika_tortoise/py.typed
agent_commit_share0.02
toolchain_manifests
dependency_bot_commit_share0
How it's scored
27/45Type-checkable codePython with type-check config (pypika_tortoise/py.typed)
52.8/55Manageable file sizes2/51 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes78,085
source_files_sampled51
oversized_source_files2

Key facts

10GitHub stars
8contributors
8commits, last 12 months
158days since last push
21releases
2bus factor
0open 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 ★ / 12 ⇿
0Stars
12Forks
19Releases

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.

0246810121212021-052023-112026-06
Major 0Minor 5Patch 14

Each point covers 5 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 · 2026-08-19 15:20 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
2CI-Tests5 out of 19 merged PRs checked by a CI test -- score normalized to 2
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
5Code-ReviewFound 10/18 approved changesets -- score normalized to 5
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update 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
0Vulnerabilities16 existing vulnerabilities detected
All dependencies 0

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

RegistryPackageVersionRelation
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies to assess

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.