Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-09 04:38 UTC

Beuth-Erdelt / Benchmark-Experiment-Host-Manager

This python tool helps managing DBMS benchmarking experiments in a Kubernetes-based HPC cluster environment. It enables users to configure hardware / software setups for easily repeating tests over varying configurations.

Jupyter NotebookAGPL-3.0★ 5 stars⑂ 0 forkssince Sep 2019View on GitHub ↗
KindCommand-line toolLibraryNetwork servicehow this is determined

Beuth-Erdelt/Benchmark-Experiment-Host-Manager holds a health index of 69 out of 100, placing it in the Good band. It scores highest on Vitality (87/100) and lowest on Community & Adoption (40/100). It was last updated 3 days ago. A single contributor accounts for most of its recent work.

69
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.

69
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 62 is calibrated to 69 on the published index scale (record calibration 2026-08-02).

Ownership

1 follower6 public repossince Feb 2016

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIbexhoma0.10.125397812 days ago

Metrics by category

Vitality

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

87Excellent · 21% of overall
How it's scored
36/36Push recency — last push 3 days ago
17.3/36Commit cadence — 25/52 weeks with commits
15.3/18Commit volume — 49 commits in the last year
10/10OpenSSF Scorecard: Maintained — 23 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year49
human_commit_share1
days_since_last_push3
active_weeks_last_year25

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 98 releases published
36/36Release recency — latest release 12 days ago
27/27Release cadence — a release every ~5.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count98
latest_release_tagv0.10.12
releases_from_tagsno
days_since_latest_release12
mean_days_between_releases5.8
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?

40Weak · 17% of overall
How it's scored
9.8/60Stars — 5 stars
0/25Forks — 0 forks
0/15Watchers — 2 watchers
Inputs used
forks0
stars5
watchers2
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (AGPL-3.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges13
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, readthedocs.org, shields.io
has_pull_request_templateno
How it's scored
36.4/80Monthly downloads — 539 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesbexhoma
dependents—
ecosystemspypi
total_downloads—
monthly_downloads539
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?

55Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.3/22.5Commit distribution — top contributor authored 98% of commits
2.7/13.5Contributor breadth — 2 contributors
10/10OpenSSF Scorecard: Contributors — project has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.985
How it's scored
38.2/42Issue resolution — 91% of issues closed
18.6/30PR acceptance — 167/269 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs167
open_issues48
closed_issues478
prs_merged_7d0
prs_decided_7d0
prs_merged_30d3
prs_decided_30d3
issue_closed_ratio0.909
closed_unmerged_prs102
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.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
2.2/25Owner reach — 1 followers of Beuth-Erdelt
18.2/25Track record — 6 public repos, account ~10 yr old
Inputs used
followers1
owner_typeOrganization
is_verifiedno
owner_loginBeuth-Erdelt
public_repos6
account_age_days3,861

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 — 78 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesbexhoma
ecosystemspypi
any_deprecatedno
min_days_since_publish12

Engineering Quality

Are baseline engineering and documentation practices in place?

75Good · 19% of overall
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 29 out of 29 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

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 17 topics
10/10Wiki
Inputs used
topicspython, dbms, k8s, kubernetes, cluster, database, tpc-c, tpc-h, ycsb, benchmarking, cloud-native, orchestration, postgresql, tpc-ds, containers, docker, reproducibility
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

47Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 29 out of 29 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 0/30 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
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 — 23 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
0/7.5Vulnerabilities — 37 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4.2
Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.
How it's scored
12.3/35Direct dependencies free of known advisories — 2 affected: urllib3 2.2.3 (high 7.5), requests 2.32.3 (moderate 5.5)
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
30.2/40No advisories left outstanding — 2 advisory-carrying package(s) unaddressed past 90 days; oldest published 456 days ago
Inputs used
sourceosv
advisories16
affected_packages2
assessed_packages95
unassessed_packages0
affected_by_severityhigh 1, moderate 1
direct_affected_packages2
Matched the pypi:bexhoma@0.10.12 runtime dependency closure — what installing the published package pulls in — 95 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.

58Moderate · 4% of overall
How it's scored
45/45Agent instructions — docs/Agent.md
0/15Machine-readable docs (llms.txt)
34.7/40Legible commit history — 65 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.65
agent_instruction_filesdocs/Agent.md
agent_instruction_max_bytes330
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — Dockerfile
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
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Jupyter Notebook without a type-check config
52.6/55Manageable file sizes — 5/117 source files over 60KB
Inputs used
primary_languageJupyter Notebook
largest_source_bytes168,158
source_files_sampled117
oversized_source_files5
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
0/20MCP server
40/40Runnable examples — example, notebooks
Inputs used
example_dirsexample, notebooks
has_mcp_signalno
api_schema_files—
interfaces_expected_ofnetwork-service

Key facts

5GitHub stars
2contributors
49commits, last 12 months
3days since last push
98releases
1bus factor
48open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

OpenSSF Scorecard 4.2 / 10
4.2aggregate

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 · 2026-09-09 04:37 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests29 out of 29 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 0/30 approved changesets -- score normalized to 0
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained23 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
0Vulnerabilities37 existing vulnerabilities detected
All dependencies 26

Full resolved dependency set from the GitHub dependency graph: 0 direct and 26 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIdash—indirect
PyPIdbmsbenchmarker—indirect
PyPIfonttools—indirect
PyPIhiyapyco0.5.1indirect
PyPIidna—indirect
PyPIkubernetes22.6.0indirect
PyPImistune—indirect
PyPImyst-parser—indirect
PyPInumpy—indirect
PyPIpillow—indirect
PyPIprettytable—indirect
PyPIpsutil—indirect
PyPIpyarrow—indirect
PyPIpyasn1—indirect
PyPIpygments—indirect
PyPIrequests2.32.3indirect
PyPIrequests2.33.0indirect
PyPIseaborn—indirect
PyPIsetuptools—indirect
PyPIsphinx—indirect
PyPIsphinx-mdinclude—indirect
PyPIsphinx-rtd-theme—indirect
PyPIurllib32.2.3indirect
PyPIurllib32.7.0indirect
PyPIwerkzeug—indirect
PyPIzipp—indirect
Dependency advisories 2

Installing pypi:bexhoma@0.10.12 pulls in 95 packages, direct and transitive: 2 carry known advisories, of which 2 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
urllib32.2.3directhigh122.7.0
requests2.32.3directmoderate42.33.0

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.