Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-16 04:52 UTC

jr200-labs / polars-hist-db

(jetstream | file) --> polars dataframe <--> mariadb (bitemporal)

PythonMIT★ 1 star⑂ 1 forksince Mar 2025View on GitHub ↗
KindLibraryhow this is determined
#bitemporal#mariadb#polars#scraper#dsv#nats#nats-jetstream

jr200-labs/polars-hist-db holds a health index of 71 out of 100, placing it in the Good band. It scores highest on Engineering Quality (96/100) and lowest on Community & Adoption (34/100). It was last updated today. 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

jr200-labsOrganization
1 follower14 public repossince Apr 2026

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIpolars-hist-db0.12.486,870960 days ago

Metrics by category

Vitality

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

87Excellent · 21% of overall

Development activity

79Good
How it's scored
36/36Push recency — last push 0 days ago
15.2/36Commit cadence — 22/52 weeks with commits
18/18Commit volume — 262 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year262
human_commit_share—
days_since_last_push0
active_weeks_last_year22

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 96 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~0.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count96
latest_release_tagv0.12.48
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases0.4
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?

34At Risk · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 1 stars
0/25Forks — 1 forks
0/15Watchers — 1 watchers
Inputs used
forks1
stars1
watchers1
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_badges—
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

64Moderate
How it's scored
51.2/80Monthly downloads — 6,870 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespolars-hist-db
dependents—
ecosystemspypi
total_downloads—
monthly_downloads6,870
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?

47Weak · 23% of overall

Maintainer resilience (bus factor)

19Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
7.3/22.5Commit distribution — top contributor authored 68% of commits
2.7/13.5Contributor breadth — 2 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.677

Issue & PR responsiveness

33At Risk
How it's scored
0/42Issue resolution — 0% of issues closed
28.5/30PR acceptance — 195/205 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/14 approved changesets -- score normalized to 0
Inputs used
merged_prs195
open_issues2
closed_issues0
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0
closed_unmerged_prs10
first_time_authors_30d—
first_time_prs_merged_30d—
first_time_prs_decided_30d—
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

52Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
2.2/25Owner reach — 1 followers of jr200-labs
9.1/25Track record — 14 public repos, account ~0 yr old
Inputs used
followers1
owner_typeOrganization
is_verified—
owner_loginjr200-labs
public_repos14
account_age_days101
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 0 days ago
20/20Version history — 96 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespolars-hist-db
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 13 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.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_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://jr200-labs.github.io/polars-hist-db/
10/10Repository description
10/10Topics — 7 topics
10/10Wiki
Inputs used
topicsbitemporal, mariadb, polars, scraper, dsv, nats, nats-jetstream
has_wikiyes
homepagehttps://jr200-labs.github.io/polars-hist-db/
docs_sitehttps://jr200-labs.github.io/polars-hist-db/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

48Weak · 16% of overall

Security posture

48Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all 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 0/14 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
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 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
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
0/7.5Vulnerabilities — 25 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4.8
Excluded from scoring (no data or not applicable): Packaging, 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.

63Moderate · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

88Excellent
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config
11/11Static type checking — polars_hist_db/py.typed
10/10Reproducible environment — Dockerfile, lockfile
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configspolars_hist_db/py.typed
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.

Code legibility for models

81Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (polars_hist_db/py.typed)
53.9/55Manageable file sizes — 3/150 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes96,397
source_files_sampled150
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 — examples, notebooks
Inputs used
example_dirsexamples, notebooks
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

1GitHub stars
2contributors
262commits, last 12 months
0days since last push
96releases
1bus factor
2open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 4.8 / 10
4.8aggregate

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 · 2026-07-16 04:51 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all 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 0/14 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities25 existing vulnerabilities detected
Direct dependencies 10
RegistryPackageVersion constraintManifest
PyPInats-py>=2.15.0pyproject.toml
PyPIpandas>=3.0.3pyproject.toml
PyPIpolars>=1.42.1pyproject.toml
PyPIpyarrow>=25.0.0pyproject.toml
PyPIpymysql>=1.2.0pyproject.toml
PyPIpytz>=2026.2pyproject.toml
PyPIpyyaml>=6.0.3pyproject.toml
PyPIscandir-rs>=2.9.9pyproject.toml
PyPIsql-metadata>=3.0.1pyproject.toml
PyPIsqlalchemy>=2.0.51pyproject.toml
All dependencies 137

Full resolved dependency set from the GitHub dependency graph: 10 direct and 127 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInats-py2.15.0direct
PyPIpandas3.0.3direct
PyPIpolars1.42.1direct
PyPIpyarrow25.0.0direct
PyPIpymysql1.2.0direct
PyPIpytz2026.2direct
PyPIpyyaml6.0.3direct
PyPIscandir-rs2.9.9direct
PyPIsql-metadata3.0.1direct
PyPIsqlalchemy2.0.51direct
PyPIadbc-driver-flightsql1.11.0indirect
PyPIadbc-driver-manager1.11.0indirect
PyPIanyio4.13.0indirect
PyPIappnope0.1.4indirect
PyPIargon2-cffi25.1.0indirect
PyPIargon2-cffi-bindings25.1.0indirect
PyPIarrow1.4.0indirect
PyPIast-serialize0.6.0indirect
PyPIasttokens3.0.1indirect
PyPIasync-lru2.3.0indirect
PyPIattrs26.1.0indirect
PyPIbabel2.18.0indirect
PyPIbeautifulsoup44.14.3indirect
PyPIbleach6.3.0indirect
PyPIcertifi2026.2.25indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.4.7indirect
PyPIcolorama0.4.6indirect
PyPIcomm0.2.3indirect
PyPIcoverage7.15.1indirect
PyPIdebugpy1.8.20indirect
PyPIdecorator5.2.1indirect
PyPIdefusedxml0.7.1indirect
PyPIexecuting2.2.1indirect
PyPIfastjsonschema2.21.2indirect
PyPIfqdn1.5.1indirect
PyPIgreenlet3.4.0indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIidna3.11indirect
PyPIimportlib-resources7.1.0indirect
PyPIiniconfig2.3.0indirect
PyPIipykernel7.3.0indirect
PyPIipython9.12.0indirect
PyPIipython-pygments-lexers1.1.1indirect
PyPIipywidgets8.1.8indirect
PyPIisoduration20.11.0indirect
PyPIjedi0.19.2indirect
PyPIjinja23.1.6indirect
PyPIjson50.14.0indirect
PyPIjsonpointer3.1.1indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPIjupyter1.1.1indirect
PyPIjupyter-client8.9.1indirect
PyPIjupyter-console6.6.3indirect
PyPIjupyter-core5.9.1indirect
PyPIjupyter-events0.12.0indirect
PyPIjupyter-lsp2.3.1indirect
PyPIjupyter-server2.18.2indirect
PyPIjupyter-server-terminals0.5.4indirect
PyPIjupyterlab4.5.7indirect
PyPIjupyterlab-pygments0.3.0indirect
PyPIjupyterlab-server2.28.0indirect
PyPIjupyterlab-widgets3.0.16indirect
PyPIlark1.3.1indirect
PyPIlibrt0.13.0indirect
PyPImarkupsafe3.0.3indirect
PyPImatplotlib-inline0.2.1indirect
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PyPImypy2.3.0indirect
PyPImypy-extensions1.1.0indirect
PyPInbclient0.10.4indirect
PyPInbconvert7.17.1indirect
PyPInbformat5.10.4indirect
PyPInest-asyncio21.7.2indirect
PyPInotebook7.5.6indirect
PyPInotebook-shim0.2.4indirect
PyPInumpy2.4.4indirect
PyPIpackaging26.0indirect
PyPIpandocfilters1.5.1indirect
PyPIparso0.8.6indirect
PyPIpathspec1.0.4indirect
PyPIpexpect4.9.0indirect
PyPIplatformdirs4.9.6indirect
PyPIpluggy1.6.0indirect
PyPIpolars-hist-db0.12.48indirect
PyPIpolars-runtime-321.42.1indirect
PyPIprometheus-client0.25.0indirect
PyPIprompt-toolkit3.0.52indirect
PyPIpsutil7.2.2indirect
PyPIpsycopg3.3.4indirect
PyPIpsycopg-binary3.3.4indirect
PyPIptyprocess0.7.0indirect
PyPIpure-eval0.2.3indirect
PyPIpyarrow-stubs20.0.0.20260625indirect
PyPIpycparser3.0indirect
PyPIpycrdt0.14.1indirect
PyPIpygments2.20.0indirect
PyPIpytest9.1.1indirect
PyPIpytest-asyncio1.4.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-json-logger4.1.0indirect
PyPIpywinpty3.0.3indirect
PyPIpyzmq27.1.0indirect
PyPIquarto-cli1.10.15indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.33.1indirect
PyPIrfc3339-validator0.1.4indirect
PyPIrfc3986-validator0.1.1indirect
PyPIrfc3987-syntax1.1.0indirect
PyPIrpds-py0.30.0indirect
PyPIruff0.15.21indirect
PyPIsend2trash2.1.0indirect
PyPIsetuptools82.0.1indirect
PyPIsix1.17.0indirect
PyPIsoupsieve2.8.3indirect
PyPIsqlglot30.12.0indirect
PyPIstack-data0.6.3indirect
PyPIterminado0.18.1indirect
PyPItinycss21.4.0indirect
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PyPItyping-extensions4.15.0indirect
PyPItzdata2026.1indirect
PyPIuri-template1.3.0indirect
PyPIurllib32.6.3indirect
PyPIwcwidth0.6.0indirect
PyPIwebcolors25.10.0indirect
PyPIwebencodings0.5.1indirect
PyPIwebsocket-client1.9.0indirect
PyPIwheel0.46.3indirect
PyPIwidgetsnbextension4.0.15indirect
Raw JSON report machine-readable

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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 v0.11.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.