Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-21 11:32 UTC

energyquantified / eq-python-client

Python library for Montel EQ's Time Series API.

PythonApache-2.0★ 35 stars⑂ 5 forkssince Jul 2020View on GitHub ↗
KindLibraryCommand-line toolhow this is determined

energyquantified/eq-python-client holds a health index of 48 out of 100, placing it in the Weak band. It scores highest on Vitality (68/100) and lowest on Engineering Quality (37/100). It was last updated today. A single contributor accounts for most of its recent work.

48
overall / 100
Weak

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.

48
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 49 is calibrated to 48 on the published index scale (record calibration 2026-08-02).

Ownership

Montel EQOrganization
3 followers1 public reposince Jul 2020

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

Metrics by category

Vitality

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

68Good · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
2.1/36Commit cadence — 3/52 weeks with commits
8.6/18Commit volume — 8 commits in the last year
5/10OpenSSF Scorecard: Maintained — 6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
Inputs used
commits_last_year8
human_commit_share1
days_since_last_push0
active_weeks_last_year3
How it's scored
27/27Ships releases — 48 releases published
36/36Release recency — latest release 0 days ago
19.8/27Release cadence — a release every ~62.3 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count48
latest_release_tagv0.18
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases62.3
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?

41Weak · 17% of overall
How it's scored
24.8/60Stars — 35 stars
5/25Forks — 5 forks
3.9/15Watchers — 6 watchers
Inputs used
forks5
stars35
watchers6
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
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?

52Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
10.9/22.5Commit distribution — top contributor authored 52% of commits
6.8/13.5Contributor breadth — 5 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled5
top_contributor_share0.516
How it's scored
40.5/42Issue resolution — 96% of issues closed
28.8/30PR acceptance — 75/78 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-Review — Found 6/30 approved changesets -- score normalized to 2
Inputs used
merged_prs75
open_issues3
closed_issues83
prs_merged_7d1
prs_decided_7d1
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio0.965
closed_unmerged_prs3
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
4.3/25Owner reach — 3 followers of energyquantified
14.2/25Track record — 1 public repos, account ~6 yr old
Inputs used
followers3
owner_typeOrganization
is_verifiedno
owner_loginenergyquantified
public_repos1
account_age_days2,288

Engineering Quality

Are baseline engineering and documentation practices in place?

37Weak · 19% of overall
How it's scored
0/24CI workflows
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 15 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://energyquantified-python.readthedocs.io/
10/10Repository description
10/10Topics — 9 topics
0/10Wiki
Inputs used
topicsapi-client, integration, data-analysis, power-market, energy-market, time-series, pandas, python, energy-data
has_wikino
homepagehttps://energyquantified-python.readthedocs.io/
docs_sitehttps://energyquantified-python.readthedocs.io/
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 — branch protection not enabled on development/release branches
0/2.5CI-Tests — 0 out of 15 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 6/30 approved changesets -- score normalized to 2
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
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
3.8/7.5Maintained — 6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
0/5Packaging — no data
0/5Pinned-Dependencies — no data
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 — no data
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate3.4
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
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages2
unassessed_packages7
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 2 resolved dependencies against OSV. 7 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

39Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
25.1/40Legible commit history — 47 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.47
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — docs/Makefile
0/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
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 — no data
Inputs used
has_nixno
has_testsno
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/95 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes40,246
source_files_sampled95
oversized_source_files0
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

35GitHub stars
5contributors
8commits, last 12 months
0days since last push
48releases
1bus factor
3open 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 ★ / 5 ⇿
0Stars
5Forks
37Releases

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.

12345512021-032023-082026-01
Major 0Minor 0Patch 27

Each point covers 5 days.

OpenSSF Scorecard 3.4 / 10
3.4aggregate

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 · 2026-10-21 11:32 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 15 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 6/30 approved changesets -- score normalized to 2
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
5Maintained6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 9

Full resolved dependency set from the GitHub dependency graph: 0 direct and 9 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPImyst-parser4.0.1indirect
PyPIpython-dateutil—indirect
PyPIpytz—indirect
PyPIrequests—indirect
PyPIsphinx8.1.3indirect
PyPItwine—indirect
PyPItzlocal—indirect
PyPIwebsocket-client—indirect
PyPIwheel—indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 2 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 7 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

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.