Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-10 18:57 UTC

Jebel-Quant / jquantstats

Time series and portfolio analytics for quantitative finance.

PythonMIT★ 44 stars⑂ 10 forkssince May 2025View on GitHub ↗

Jebel-Quant/jquantstats holds a health index of 93 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (100/100) and lowest on Sustainability & Governance (60/100). It was last updated 2 days ago. A single contributor accounts for most of its recent work.

93
overall / 100
Exceptional

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.

93
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 79 is calibrated to 93 on the published index scale (record calibration 2026-08-02).

Ownership

Jebel QuantOrganization
25 followers30 public repossince Jun 2025

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIjquantstats0.11.021,8716510 days ago

Metrics by category

Vitality

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

98Exceptional · 21% of overall

Development activity

100Exceptional
How it's scored
36/36Push recency — last push 2 days ago
36/36Commit cadence — 52/52 weeks with commits
18/18Commit volume — 1,083 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 28 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year1,083
human_commit_share0.78
days_since_last_push2
active_weeks_last_year52

Release discipline

96Exceptional
How it's scored
27/27Ships releases — 69 releases published
36/36Release recency — latest release 10 days ago
27/27Release cadence — a release every ~11.8 days
6/10OpenSSF Scorecard: Signed-Releases — 3 out of the last 5 releases have a total of 6 signed artifacts.
Inputs used
releases_count69
latest_release_tagv0.11.0
releases_from_tagsno
days_since_latest_release10
mean_days_between_releases11.8

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

61Moderate · 17% of overall
How it's scored
26.5/60Stars — 44 stars
8/25Forks — 10 forks
0/15Watchers — 1 watchers
Inputs used
forks10
stars44
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges8
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesbadge.fury.io, github.com, shields.io
has_pull_request_templateno
How it's scored
57.9/80Monthly downloads — 21,871 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesjquantstats
dependents—
ecosystemspypi
total_downloads—
monthly_downloads21,871
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?

60Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.2/22.5Commit distribution — top contributor authored 99% of commits
5.4/13.5Contributor breadth — 4 contributors
10/10OpenSSF Scorecard: Contributors — project has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled4
top_contributor_share0.993
How it's scored
42/42Issue resolution — 100% of issues closed
26.6/30PR acceptance — 634/714 decided PRs merged
8.7/13Newcomer PR acceptance — 2/3 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — Found 2/21 approved changesets -- score normalized to 0
Inputs used
merged_prs634
open_issues0
closed_issues267
prs_merged_7d3
prs_decided_7d3
prs_merged_30d42
prs_decided_30d44
issue_closed_ratio1
closed_unmerged_prs80
first_time_authors_30d1
first_time_prs_merged_30d2
first_time_prs_decided_30d3
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
10.2/25Owner reach — 25 followers of Jebel-Quant
13.3/25Track record — 30 public repos, account ~1 yr old
Inputs used
followers25
owner_typeOrganization
is_verifiedno
owner_loginJebel-Quant
public_repos30
account_age_days450

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 10 days ago
20/20Version history — 65 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesjquantstats
ecosystemspypi
any_deprecatedno
min_days_since_publish10

Engineering Quality

Are baseline engineering and documentation practices in place?

100Exceptional · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows — 9 workflow(s)
24/24Tests present
16/16Linter config — .ruff.toml, ruff.toml
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://jebel-quant.github.io/jquantstats/
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicsanalytics, dashboard, plotly, polars
has_wikiyes
homepagehttps://jebel-quant.github.io/jquantstats/
docs_sitehttps://jebel-quant.github.io/jquantstats/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

71Good · 16% of overall
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 — 30 out of 30 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 2/21 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 3 contributing companies or organizations -- score normalized to 10
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 28 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
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
4.5/7.5Signed-Releases — 3 out of the last 5 releases have a total of 6 signed artifacts.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate6.4

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_packages9
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:jquantstats@0.11.0 runtime dependency closure — what installing the published package pulls in — 9 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.

87Excellent · 4% of overall
How it's scored
45/45Agent instructions — CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 76 of 78 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.974
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes4,351
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — .ruff.toml, ruff.toml
11/11Static type checking — src/jquantstats/py.typed
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 42 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 22 of the last 100 commits are automated dependency updates
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_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configssrc/jquantstats/py.typed
agent_commit_share0.42
toolchain_manifests—
dependency_bot_commit_share0.22
How it's scored
27/45Type-checkable code — Python with type-check config (src/jquantstats/py.typed)
54.6/55Manageable file sizes — 1/157 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes75,079
source_files_sampled157
oversized_source_files1

Key facts

44GitHub stars
4contributors
1,083commits, last 12 months
2days since last push
69releases
1bus 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 ★ / 10 ⇿
0Stars
10Forks
42Releases

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.

02468101012025-072026-012026-08
Major 0Minor 9Patch 33

Each point covers 2 days.

OpenSSF Scorecard 6.4 / 10
6.4aggregate

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 · 2026-09-10 18:56 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests30 out of 30 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 2/21 approved changesets -- score normalized to 0
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 28 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
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
6Signed-Releases3 out of the last 5 releases have a total of 6 signed artifacts.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 6
RegistryPackageVersion constraintManifest
PyPIjinja2>=3.1.0pyproject.toml
PyPInarwhals>=2.0.0pyproject.toml
PyPInumpy>=2.0.0pyproject.toml
PyPIplotly>=6.1.1pyproject.toml
PyPIpolars>=1.43.0pyproject.toml
PyPIscipy>=1.14.1pyproject.toml
All dependencies 88

Full resolved dependency set from the GitHub dependency graph: 6 direct and 82 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIjinja23.1.6direct
PyPInarwhals2.25.0direct
PyPInumpy2.4.6direct
PyPIplotly6.9.0direct
PyPIpolars1.44.1direct
PyPIscipy1.17.1direct
PyPIannotated-doc0.0.4indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.13.0indirect
PyPIbeautifulsoup44.14.3indirect
PyPIcertifi2026.4.22indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.4.7indirect
PyPIchoreographer1.3.0indirect
PyPIclick8.3.3indirect
PyPIcolorama0.4.6indirect
PyPIcontourpy1.3.3indirect
PyPIcurl-cffi0.15.0indirect
PyPIcycler0.12.1indirect
PyPIdocutils0.22.4indirect
PyPIfastapi0.141.1indirect
PyPIfonttools4.62.1indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIhypothesis6.167.1indirect
PyPIidna3.15indirect
PyPIiniconfig2.3.0indirect
PyPIitsdangerous2.2.0indirect
PyPIjedi0.19.2indirect
PyPIkaleido1.4.0indirect
PyPIkiwisolver1.5.0indirect
PyPIlogistro2.0.1indirect
PyPIloro1.10.3indirect
PyPIlxml6.1.1indirect
PyPImarimo0.24.0indirect
PyPImarkdown3.10.2indirect
PyPImarkdown-it-py4.0.0indirect
PyPImarkupsafe3.0.3indirect
PyPImatplotlib3.11.1indirect
PyPImdurl0.1.2indirect
PyPImsgspec0.21.1indirect
PyPImultitasking0.0.13indirect
PyPIorjson3.11.8indirect
PyPIpackaging26.2indirect
PyPIpandas3.0.5indirect
PyPIparso0.8.7indirect
PyPIpeewee4.0.5indirect
PyPIpillow12.3.0indirect
PyPIplatformdirs4.9.6indirect
PyPIpluggy1.6.0indirect
PyPIpolars-runtime-321.44.1indirect
PyPIprotobuf7.34.1indirect
PyPIpsutil7.2.2indirect
PyPIpyarrow24.0.0indirect
PyPIpycparser3.0indirect
PyPIpydantic2.13.3indirect
PyPIpydantic-core2.46.3indirect
PyPIpygments2.20.0indirect
PyPIpymdown-extensions11.0.1indirect
PyPIpyparsing3.3.2indirect
PyPIpytest9.1.1indirect
PyPIpytest-timeout2.4.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-dotenv1.2.3indirect
PyPIpython-multipart0.0.32indirect
PyPIpytz2026.2indirect
PyPIpyyaml6.0.3indirect
PyPIpyzmq27.1.0indirect
PyPIquantstats0.0.81indirect
PyPIrequests2.33.1indirect
PyPIrich15.0.0indirect
PyPIseaborn0.13.2indirect
PyPIsimplejson4.1.1indirect
PyPIsix1.17.0indirect
PyPIsortedcontainers2.4.0indirect
PyPIsoupsieve2.8.4indirect
PyPIstarlette1.3.1indirect
PyPIsyrupy5.5.3indirect
PyPItabulate0.10.0indirect
PyPItomlkit0.15.0indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2026.2indirect
PyPIurllib32.7.0indirect
PyPIuvicorn0.52.4indirect
PyPIwebsockets16.0indirect
PyPIyfinance1.7.0indirect
Dependency advisories 0

Installing pypi:jquantstats@0.11.0 pulls in 9 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 statistics — PyPI.