Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-11 02:31 UTC

paulomtts / pyjinhx

A framework for template-based python web apps. Powered by Pydantic, Jinja2 and HTMX!

PythonMIT★ 10 stars⑂ 0 forkssince Dec 2025View on GitHub ↗
KindLibraryhow this is determined
#html#htmx#jinja2#pydantic#python#templates

paulomtts/pyjinhx holds a health index of 71 out of 100, placing it in the Good band. It scores highest on Vitality (83/100) and lowest on Community & Adoption (39/100). It was last updated 12 days ago. A single contributor accounts for most of its recent work.

71
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.

71
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 63 is calibrated to 71 on the published index scale (record calibration 2026-08-02).

Ownership

PauloPersonal account
16 followers11 public repossince Nov 2021Nubank

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
PyPIpyjinhx1.9.84,86410212 days agocomponentsjinja2pydantictemplatesui

Metrics by category

Vitality

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

83Excellent · 21% of overall

Development activity

72Good
How it's scored
28.8/36Push recency — last push 12 days ago
15.2/36Commit cadence — 22/52 weeks with commits
18/18Commit volume — 1,182 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year1,182
human_commit_share1
days_since_last_push12
active_weeks_last_year22

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 12 days ago
27/27Release cadence — a release every ~0.7 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tagv1.9.8
releases_from_tagsno
days_since_latest_release12
mean_days_between_releases0.7
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?

39Weak · 17% of overall

Popularity & adoption

16Critical
How it's scored
15.5/60Stars — 10 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars10
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized 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_badges3
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

62Moderate
How it's scored
49.2/80Monthly downloads — 4,864 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespyjinhx
dependents—
ecosystemspypi
total_downloads—
monthly_downloads4,864
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?

56Moderate · 23% of overall

Maintainer resilience (bus factor)

15Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.1/22.5Commit distribution — top contributor authored 100% of commits
2.7/13.5Contributor breadth — 2 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.997

Issue & PR responsiveness

80Excellent
How it's scored
40.4/42Issue resolution — 96% of issues closed
29.1/30PR acceptance — 503/518 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/28 approved changesets -- score normalized to 0
Inputs used
merged_prs503
open_issues20
closed_issues525
prs_merged_7d0
prs_decided_7d0
prs_merged_30d35
prs_decided_30d38
issue_closed_ratio0.963
closed_unmerged_prs15
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.

Ownership & stewardship

45Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
8.8/25Owner reach — 16 followers of paulomtts
17.5/25Track record — 11 public repos, account ~4 yr old
Inputs used
followers16
owner_typeUser
is_verified—
owner_loginpaulomtts
public_repos11
account_age_days1,767
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 12 days ago
20/20Version history — 102 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespyjinhx
ecosystemspypi
any_deprecatedno
min_days_since_publish12

Engineering Quality

Are baseline engineering and documentation practices in place?

81Excellent · 19% of overall

Engineering practices

68Good
How it's scored
24/24CI workflows — 5 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 11 out of 11 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://paulomtts.github.io/pyjinhx/
10/10Repository description
10/10Topics — 6 topics
10/10Wiki
Inputs used
topicshtml, htmx, jinja2, pydantic, python, templates
has_wikiyes
homepagehttps://paulomtts.github.io/pyjinhx/
docs_sitehttps://paulomtts.github.io/pyjinhx/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

53Moderate · 16% of overall

Security posture

41Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5CI-Tests — 11 out of 11 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/28 approved changesets -- score normalized to 0
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
4.5/7.5Vulnerabilities — 4 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4.1
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 advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages7
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:pyjinhx@1.9.8 runtime dependency closure — what installing the published package pulls in — 7 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

Agent context & guidance

52Moderate
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.pydantic.dev/llms.txt)
37.3/40Legible commit history — 70 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.pydantic.dev/llms.txt
legible_history_share0.7
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

53Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
11/11Static type checking — pyjinhx/py.typed
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 57 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency 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_configno
typecheck_configspyjinhx/py.typed
agent_commit_share0.57
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (pyjinhx/py.typed)
54.6/55Manageable file sizes — 3/441 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes329,767
source_files_sampled441
oversized_source_files3

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — demos, examples
Inputs used
example_dirsdemos, examples
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

10GitHub stars
2contributors
1,182commits, last 12 months
12days since last push
100releases
1bus factor
20open issues
PyPIpackage ecosystems

Data collection warnings

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

More detail

OpenSSF Scorecard 4.1 / 10
4.1aggregate

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 · 2026-09-11 02:31 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests11 out of 11 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/28 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 30 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
6Vulnerabilities4 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPIjinja2>=3.1.6pyproject.toml
PyPImarkupsafe>=3.0.3pyproject.toml
PyPIpydantic>=2.12.5pyproject.toml
All dependencies 62

Full resolved dependency set from the GitHub dependency graph: 3 direct and 59 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIjinja23.1.6direct
PyPImarkupsafe3.0.3direct
PyPIpydantic2.13.4direct
PyPIannotated-doc0.0.4indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.14.0indirect
PyPIbabel2.18.0indirect
PyPIbackrefs7.0indirect
PyPIcertifi2026.6.17indirect
PyPIcharset-normalizer3.4.7indirect
PyPIclick8.4.1indirect
PyPIcolorama0.4.6indirect
PyPIdiskcache5.6.3indirect
PyPIfakeredis2.36.2indirect
PyPIfastapi0.138.0indirect
PyPIghp-import2.1.0indirect
PyPIgreenlet3.5.2indirect
PyPIgriffelib2.1.0indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIidna3.18indirect
PyPIiniconfig2.3.0indirect
PyPImarkdown3.10.2indirect
PyPImergedeep1.3.4indirect
PyPImkdocs1.6.1indirect
PyPImkdocs-autorefs1.4.4indirect
PyPImkdocs-get-deps0.2.2indirect
PyPImkdocs-material9.7.6indirect
PyPImkdocs-material-extensions1.3.1indirect
PyPImkdocstrings1.0.4indirect
PyPImkdocstrings-python2.0.5indirect
PyPIpackaging26.2indirect
PyPIpaginate0.5.7indirect
PyPIpathspec1.1.1indirect
PyPIplatformdirs4.10.0indirect
PyPIplaywright1.60.0indirect
PyPIpluggy1.6.0indirect
PyPIpydantic-core2.46.4indirect
PyPIpyee13.0.1indirect
PyPIpygments2.20.0indirect
PyPIpyjinhx1.9.8indirect
PyPIpymdown-extensions10.21.3indirect
PyPIpytest9.1.1indirect
PyPIpytest-base-url2.1.0indirect
PyPIpytest-playwright0.8.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-multipart0.0.32indirect
PyPIpython-slugify8.0.4indirect
PyPIpyyaml6.0.3indirect
PyPIpyyaml-env-tag1.1indirect
PyPIredis8.0.0indirect
PyPIrequests2.34.2indirect
PyPIsix1.17.0indirect
PyPIsortedcontainers2.4.0indirect
PyPIstarlette1.3.1indirect
PyPItext-unidecode1.3indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPIurllib32.7.0indirect
PyPIuvicorn0.49.0indirect
PyPIwatchdog6.0.0indirect
Dependency advisories 0

Installing pypi:pyjinhx@1.9.8 pulls in 7 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

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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 statistics — PyPI.