Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-12 05:49 UTC

scaleoutsystems / scaleout-client

Scaleout Edge: Sovereign Edge AI orchestration and Federated Learning

PythonApache-2.0★ 169 stars⑂ 42 forkssince Jul 2020View on GitHub ↗
KindCommand-line toolLibraryhow this is determined
#federated-machine-learning#fedml#federated-learning#edge-ml#fleet-learning#keras-tensorflow#pytorch#scikit-learn#tensorflow#edge-ai

scaleoutsystems/scaleout-client holds a health index of 63 out of 100, placing it in the Moderate band. It scores highest on Sustainability & Governance (72/100) and lowest on AI Readiness (36/100). It was last updated 63 days ago. 2 contributors account for most of its recent work.

63
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.

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

Ownership

ScaleoutOrganization
58 followers47 public repossince Nov 2018

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIscaleoututil1.0.5-763 days ago
PyPIscaleout1.0.5223863 days ago

Metrics by category

Vitality

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

63Moderate · 21% of overall

Development activity

38Weak
How it's scored
18/36Push recency — last push 63 days ago
6.9/36Commit cadence — 10/52 weeks with commits
11.7/18Commit volume — 19 commits in the last year
1/10OpenSSF Scorecard: Maintained — 2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
Inputs used
commits_last_year19
human_commit_share—
days_since_last_push63
active_weeks_last_year10

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 75 releases published
36/36Release recency — latest release 63 days ago
27/27Release cadence — a release every ~43.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count75
latest_release_tagv1.0.5
releases_from_tagsno
days_since_latest_release63
mean_days_between_releases43.6
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?

68Good · 17% of overall

Popularity & adoption

53Moderate
How it's scored
36.1/60Stars — 169 stars
13.4/25Forks — 42 forks
3.3/15Watchers — 5 watchers
Inputs used
forks42
stars169
watchers5
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 (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateno

Sustainability & Governance

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

72Good · 23% of overall

Maintainer resilience (bus factor)

54Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
13/22.5Commit distribution — top contributor authored 42% 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_factor2
contributors_sampled4
top_contributor_share0.421

Issue & PR responsiveness

78Good
How it's scored
41.2/42Issue resolution — 98% of issues closed
24/30PR acceptance — 735/917 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-Review — Found 4/19 approved changesets -- score normalized to 2
Inputs used
merged_prs735
open_issues2
closed_issues107
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.982
closed_unmerged_prs182
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

67Good
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
12.7/25Owner reach — 58 followers of scaleoutsystems
24.2/25Track record — 47 public repos, account ~7 yr old
Inputs used
followers58
owner_typeOrganization
is_verifiedno
owner_loginscaleoutsystems
public_repos47
account_age_days2,857

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 2 package(s) on pypi
35/35Publish recency — latest publish 63 days ago
20/20Version history — 8 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesscaleoututil, scaleout
ecosystemspypi
any_deprecatedno
min_days_since_publish63

Engineering Quality

Are baseline engineering and documentation practices in place?

40Weak · 19% of overall

Engineering practices

24At Risk
How it's scored
0/24CI workflows
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 9 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

65Good
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://www.scaleoutsystems.com
10/10Repository description
10/10Topics — 10 topics
0/10Wiki
Inputs used
topicsfederated-machine-learning, fedml, federated-learning, edge-ml, fleet-learning, keras-tensorflow, pytorch, scikit-learn, tensorflow, edge-ai
has_wikino
homepagehttps://www.scaleoutsystems.com
docs_sitehttps://www.scaleoutsystems.com
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

52Moderate · 16% of overall

Security posture

40Weak
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 9 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
1.5/7.5Code-Review — Found 4/19 approved changesets -- score normalized to 2
2.5/2.5Contributors — project has 3 contributing companies or organizations -- score normalized to 10
0/10Dangerous-Workflow — no data
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0.8/7.5Maintained — 2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
0/5Packaging — no data
0/5Pinned-Dependencies — no data
0.5/5SAST — SAST tool is not run on all commits -- score normalized to 1
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — no data
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate4
Excluded from scoring (no data or not applicable): Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. 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_packages20
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:scaleoututil@1.0.5 runtime dependency closure — what installing the published package pulls in — 20 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.

36Weak · 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)

31At Risk
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance, OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/99 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes47,137
source_files_sampled99
oversized_source_files0

Machine-readable interfaces

100Exceptional
How it's scored
40/40API schema (OpenAPI/GraphQL/proto) — scaleout-util/scaleout.proto
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_filesscaleout-util/scaleout.proto
interfaces_expected_of—
Excluded from scoring (no data or not applicable): MCP server. Remaining weights renormalized.

Key facts

169GitHub stars
4contributors
19commits, last 12 months
63days since last push
75releases
2bus factor
2open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch pypi package 'scaleout-client-workspace' from its registry
  • pypi download statistics for 'scaleoututil' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced

More detail

Star and fork history 0 ★ / 42 ⇿
0Stars
42Forks
70Releases

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.

0102030404022020-102023-072026-04
Major 0Minor 32Patch 31

Each point covers 6 days.

OpenSSF Scorecard 4.0 / 10
4.0aggregate

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 · 2026-09-12 05:49 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 9 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 4/19 approved changesets -- score normalized to 2
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
1Maintained2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
1SASTSAST tool is not run on all commits -- score normalized to 1
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 17
RegistryPackageVersion constraintManifest
PyPIscaleoututil—pyproject.toml
PyPIscaleout—pyproject.toml
PyPInumpy>=1.21.6scaleout-client-python/pyproject.toml
PyPIpsutil—scaleout-client-python/pyproject.toml
PyPIscaleoututil==1.0.5scaleout-client-python/pyproject.toml
PyPIclick==8.3.1scaleout-client-python/pyproject.toml
PyPIurllib3>=2.6.0scaleout-client-python/pyproject.toml
PyPIgrpcio==1.78.0scaleout-util/pyproject.toml
PyPIgrpcio-tools==1.78.0scaleout-util/pyproject.toml
PyPIprotobuf==6.33.5scaleout-util/pyproject.toml
PyPInumpy>=2.2.6scaleout-util/pyproject.toml
PyPIrequests>=2.31scaleout-util/pyproject.toml
PyPIurllib3>=2.6.0scaleout-util/pyproject.toml
PyPIpyjwt>=2.12.0scaleout-util/pyproject.toml
PyPIvirtualenv==20.36.1scaleout-util/pyproject.toml
PyPIcryptography>=46.0.5scaleout-util/pyproject.toml
PyPIPyYAML~=6.0scaleout-util/pyproject.toml
All dependencies 47

Full resolved dependency set from the GitHub dependency graph: 16 direct and 31 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIclick8.3.1direct
PyPIcryptography—direct
PyPIgrpcio1.78.0direct
PyPIgrpcio-tools1.78.0direct
PyPInumpy—direct
PyPInumpy1.24.4direct
PyPInumpy1.26.4direct
PyPIprotobuf6.33.5direct
PyPIpyjwt—direct
PyPIpyyaml—direct
PyPIrequests—direct
PyPIscaleout—direct
PyPIscaleoututil—direct
PyPIscaleoututil1.0.5direct
PyPIurllib3—direct
PyPIvirtualenv20.36.1direct
PyPIchart-studio—indirect
PyPIdash1.12.0indirect
PyPIdocker—indirect
PyPIdocker5.0.2indirect
PyPIdocker6.1.1indirect
PyPIfedn—indirect
PyPIfire0.3.1indirect
PyPIflask1.0indirect
PyPImonai—indirect
PyPImypy—indirect
PyPIpandas—indirect
PyPIplotly—indirect
PyPIpyloudnorm0.1.1indirect
PyPIpymongo3.7.1indirect
PyPIpytest—indirect
PyPIpytest-cov—indirect
PyPIpytest-order—indirect
PyPIresponses—indirect
PyPIscikit-learn—indirect
PyPIscipy—indirect
PyPIsphinx-code-tabs—indirect
PyPIsphinx-copybutton—indirect
PyPIsphinx-rtd-theme—indirect
PyPItensorflow—indirect
PyPItensorflow-macos—indirect
PyPItensorflow-metal—indirect
PyPItorch—indirect
PyPItorch2.5.1indirect
PyPItorchaudio2.5.1indirect
PyPItorcheval0.0.7indirect
PyPItorchvision—indirect
Dependency advisories 0

Installing pypi:scaleoututil@1.0.5 pulls in 20 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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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.