Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 03:30 UTC

cgarciae / pypeln

Concurrent data pipelines in Python >>>

PythonMIT★ 1,596 stars⑂ 94 forkssince Sep 2018View on GitHub ↗
KindLibraryhow this is determined

cgarciae/pypeln holds a health index of 31 out of 100, placing it in the At Risk band. It scores highest on Engineering Quality (80/100) and lowest on Vitality (21/100). It was last updated 1119 days ago. A single contributor accounts for most of its recent work.

31
overall / 100
At Risk

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.

31
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

Cristian GarciaPersonal account
613 followers229 public repossince Nov 2013Google

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 publish
PyPIpypeln0.4.9-361679 days ago

Metrics by category

Vitality

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

21At Risk · 21% of overall

Development activity

1Critical
How it's scored
0/36Push recency — last push 1,119 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push1,119
active_weeks_last_year0

Release discipline

52Moderate
How it's scored
27/27Ships releases — 14 releases published
0/36Release recency — latest release 1,679 days ago
19.8/27Release cadence — a release every ~65.1 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count14
latest_release_tag0.4.9
releases_from_tagsno
days_since_latest_release1,679
mean_days_between_releases65.1
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?

64Moderate · 17% of overall

Popularity & adoption

77Good
How it's scored
52/60Stars — 1,596 stars
16.4/25Forks — 94 forks
8.7/15Watchers — 38 watchers
Inputs used
forks94
stars1,596
watchers38
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_badges1
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno

Sustainability & Governance

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

54Moderate · 23% of overall

Maintainer resilience (bus factor)

26At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
1/22.5Commit distribution — top contributor authored 95% of commits
13.5/13.5Contributor breadth — 11 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled11
top_contributor_share0.954

Issue & PR responsiveness

61Moderate
How it's scored
26.7/42Issue resolution — 64% of issues closed
22.3/30PR acceptance — 26/35 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
4.5/15OpenSSF Scorecard: Code-Review — Found 10/30 approved changesets -- score normalized to 3
Inputs used
merged_prs26
open_issues28
closed_issues49
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.636
closed_unmerged_prs9
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

69Good
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
20/25Owner reach — 613 followers of cgarciae
25/25Track record — 229 public repos, account ~12 yr old
Inputs used
followers613
owner_typeUser
is_verified—
owner_logincgarciae
public_repos229
account_age_days4,663
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

69Good
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
4/35Publish recency — latest publish 1,679 days ago
20/20Version history — 36 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespypeln
ecosystemspypi
any_deprecatedno
min_days_since_publish1,679

Engineering Quality

Are baseline engineering and documentation practices in place?

80Excellent · 19% of overall

Engineering practices

74Good
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 17 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://cgarciae.github.io/pypeln
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepagehttps://cgarciae.github.io/pypeln
docs_sitehttps://cgarciae.github.io/pypeln
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

40Weak · 16% of overall

Security posture

25At Risk
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
0/2.5CI-Tests — 0 out of 17 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-Review — Found 10/30 approved changesets -- score normalized to 3
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
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packaging — no data
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
0/7.5Vulnerabilities — 72 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate2.5
Excluded from scoring (no data or not applicable): Packaging, 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_packages1
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:pypeln@0.4.9 runtime dependency closure — what installing the published package pulls in — 1 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.

43Weak · 4% of overall

Agent context & guidance

9Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
9.1/40Legible commit history — 17 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.17
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

43Weak
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
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
lockfilespoetry.lock
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/116 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes12,763
source_files_sampled116
oversized_source_files0

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
Inputs used
example_dirsexamples
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

1,596GitHub stars
11contributors
0commits, last 12 months
1,119days since last push
14releases
1bus factor
28open 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 ★ / 94 ⇿
0Stars
94Forks
14Releases

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.

02040608010094142018-092022-072026-04
Major 0Minor 3Patch 11

Each point covers 7 days.

OpenSSF Scorecard 2.5 / 10
2.5aggregate

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 · 2026-08-13 03:29 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 17 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 10/30 approved changesets -- score normalized to 3
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
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not 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
0Vulnerabilities72 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPIstopit>=1.1.2pyproject.toml
PyPItyping_extensions>=3.7.4pyproject.toml
All dependencies 71

Full resolved dependency set from the GitHub dependency graph: 2 direct and 69 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIstopit1.1.2direct
PyPItyping-extensions4.5.0direct
PyPIaiohttp3.8.4indirect
PyPIaiosignal1.3.1indirect
PyPIastunparse1.6.3indirect
PyPIasync-timeout4.0.2indirect
PyPIasynctest0.13.0indirect
PyPIattrs22.2.0indirect
PyPIblack23.1.0indirect
PyPIcached-property1.5.2indirect
PyPIcfgv3.3.1indirect
PyPIcharset-normalizer3.1.0indirect
PyPIclick8.1.3indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.2.2indirect
PyPIcytoolz0.12.1indirect
PyPIdebugpy1.6.6indirect
PyPIdistlib0.3.6indirect
PyPIexceptiongroup1.1.1indirect
PyPIexecnet1.9.0indirect
PyPIfilelock3.10.0indirect
PyPIflaky3.7.0indirect
PyPIfrozenlist1.3.3indirect
PyPIghp-import2.1.0indirect
PyPIhypothesis6.70.0indirect
PyPIidentify2.5.21indirect
PyPIidna3.4indirect
PyPIimportlib-metadata6.1.0indirect
PyPIiniconfig2.0.0indirect
PyPIisort5.12.0indirect
PyPIjinja23.1.2indirect
PyPImarkdown3.3.7indirect
PyPImarkupsafe2.1.2indirect
PyPImergedeep1.3.4indirect
PyPImkautodoc0.1.0indirect
PyPImkdocs1.4.2indirect
PyPImkdocs-autorefs0.4.1indirect
PyPImkdocs-material4.6.3indirect
PyPImkdocstrings0.17.0indirect
PyPImultidict6.0.4indirect
PyPImypy-extensions1.0.0indirect
PyPInodeenv1.7.0indirect
PyPIpackaging23.0indirect
PyPIpathspec0.11.1indirect
PyPIplatformdirs3.1.1indirect
PyPIpluggy1.0.0indirect
PyPIpre-commit3.2.0indirect
PyPIpygments2.14.0indirect
PyPIpymdown-extensions9.10indirect
PyPIpytest7.2.2indirect
PyPIpytest-asyncio0.21.0indirect
PyPIpytest-cov4.0.0indirect
PyPIpytest-sugar0.9.6indirect
PyPIpytest-xdist3.2.1indirect
PyPIpython-dateutil2.8.2indirect
PyPIpytkdocs0.16.1indirect
PyPIpyyaml6.0indirect
PyPIpyyaml-env-tag0.1indirect
PyPIsetuptools67.6.0indirect
PyPIsix1.16.0indirect
PyPIsortedcontainers2.4.0indirect
PyPItermcolor2.2.0indirect
PyPItomli2.0.1indirect
PyPItoolz0.12.0indirect
PyPItqdm4.65.0indirect
PyPItyped-ast1.5.4indirect
PyPIvirtualenv20.21.0indirect
PyPIwatchdog3.0.0indirect
PyPIwheel0.40.0indirect
PyPIyarl1.8.2indirect
PyPIzipp3.15.0indirect
Dependency advisories 0

Installing pypi:pypeln@0.4.9 pulls in 1 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.

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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 v0.31.0 — full methodology · metrics wiki.

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