Public record
Software health reportschema 0.15.0 · metrics 2.10.0 · 2026-07-19 18:31 UTC

davidusb-geek / emhass

emhass: Energy Management for Home Assistant, is a Python module designed to optimize your home energy interfacing with Home Assistant.

PythonMIT★ 638 stars⑂ 157 forkssince Sep 2021View on GitHub ↗
KindLibraryhow this is determined
#energy#home-automation#linear-programming#management#model-predictive-control#optimization

davidusb-geek/emhass holds a health index of 92 out of 100, placing it in the Excellent band. It scores highest on Vitality (98/100) and lowest on Sustainability & Governance (68/100). It was last updated today. A single contributor accounts for most of its recent work.

92
overall / 100
Excellent

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.

92
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 78 is calibrated to 92 on the published index scale (record calibration 2026-08-02).

Ownership

DavidPersonal account
44 followers13 public repossince Oct 2017

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 publishTags
PyPIemhass0.17.91,3251467 days agoenergyhassmanagementoptimization

Metrics by category

Vitality

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

98Exceptional · 21% of overall

Development activity

96Exceptional
How it's scored
36/36Push recency — last push 0 days ago
32.5/36Commit cadence — 47/52 weeks with commits
18/18Commit volume — 1,028 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 16 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year1,028
human_commit_share—
days_since_last_push0
active_weeks_last_year47

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 7 days ago
27/27Release cadence — a release every ~14.9 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tagv0.17.9
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases14.9
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?

71Good · 17% of overall

Popularity & adoption

71Good
How it's scored
45.5/60Stars — 638 stars
18.3/25Forks — 157 forks
7.2/15Watchers — 21 watchers
Inputs used
forks157
stars638
watchers21
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 (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

52Moderate
How it's scored
41.6/80Monthly downloads — 1,325 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesemhass
dependents—
ecosystemspypi
total_downloads—
monthly_downloads1,325
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?

68Good · 23% of overall

Maintainer resilience (bus factor)

43Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
10.8/22.5Commit distribution — top contributor authored 52% of commits
13.5/13.5Contributor breadth — 57 contributors
10/10OpenSSF Scorecard: Contributors — project has 14 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled57
top_contributor_share0.52

Issue & PR responsiveness

89Excellent
How it's scored
39/42Issue resolution — 93% of issues closed
26.8/30PR acceptance — 454/509 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
12/15OpenSSF Scorecard: Code-Review — Found 9/11 approved changesets -- score normalized to 8
Inputs used
merged_prs454
open_issues31
closed_issues408
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.929
closed_unmerged_prs55
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

53Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
11.9/25Owner reach — 44 followers of davidusb-geek
20.3/25Track record — 13 public repos, account ~8 yr old
Inputs used
followers44
owner_typeUser
is_verified—
owner_logindavidusb-geek
public_repos13
account_age_days3,195
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 7 days ago
20/20Version history — 146 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesemhass
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Engineering Quality

Are baseline engineering and documentation practices in place?

81Excellent · 19% of overall

Engineering practices

68Good
How it's scored
24/24CI workflows — 10 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 11 out of 11 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

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://emhass.readthedocs.io
10/10Repository description
10/10Topics — 6 topics
10/10Wiki
Inputs used
topicsenergy, home-automation, linear-programming, management, model-predictive-control, optimization
has_wikiyes
homepagehttps://emhass.readthedocs.io
docs_sitehttps://emhass.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

71Good · 16% of overall

Security posture

71Good
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 — 11 out of 11 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
6/7.5Code-Review — Found 9/11 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 14 contributing companies or organizations
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 16 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
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
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate7.1
Excluded from scoring (no data or not applicable): Branch-Protection, 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.

69Good · 4% of overall

Agent context & guidance

75Good
How it's scored
45/45Agent instructions — AGENTS.md
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_filesAGENTS.md
agent_instruction_max_bytes8,340
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

61Moderate
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — devcontainer, Dockerfile
0/10Demonstrated agent practice — no data
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
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_devcontaineryes
has_linter_configno
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.

Code legibility for models

45Weak
How it's scored
0/45Type-checkable code — Python without a type-check config
44.6/55Manageable file sizes — 11/58 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes393,714
source_files_sampled58
oversized_source_files11

Machine-readable interfaces

100Exceptional
How it's scored
40/40API schema (OpenAPI/GraphQL/proto) — src/emhass/static/openapi.json
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — cookbook
Inputs used
example_dirscookbook
has_mcp_signalno
api_schema_filessrc/emhass/static/openapi.json
interfaces_expected_of—
Excluded from scoring (no data or not applicable): MCP server. Remaining weights renormalized.

Key facts

638GitHub stars
57contributors
1,028commits, last 12 months
0days since last push
100releases
1bus factor
31open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 7.1 / 10
7.1aggregate

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 · 2026-07-19 18:30 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-Tests11 out of 11 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 9/11 approved changesets -- score normalized to 8
10Contributorsproject has 14 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 16 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
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
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 24
RegistryPackageVersion constraintManifest
PyPInumpy>=2.0.0, <2.3.0pyproject.toml
PyPIscipy>=1.15.0pyproject.toml
PyPIpandas>=2.2.0pyproject.toml
PyPIpvlib>=0.11.0pyproject.toml
PyPIprotobuf>=5.29.3pyproject.toml
PyPIpytz>=2024.2pyproject.toml
PyPIh5py>=3.12.1pyproject.toml
PyPIhighspy>=1.10.0pyproject.toml
PyPIcvxpy>=1.6.0, <1.8.0pyproject.toml
PyPIpyyaml>=6.0.2pyproject.toml
PyPItables>=3.10.0pyproject.toml
PyPIskforecast>=0.19.1,<0.23.0pyproject.toml
PyPIwaitress>=3.0.2pyproject.toml
PyPIplotly>=6.0.0pyproject.toml
PyPIgunicorn>=23.0.0pyproject.toml
PyPIquart—pyproject.toml
PyPIaiofiles—pyproject.toml
PyPIjinja2—pyproject.toml
PyPIasyncio—pyproject.toml
PyPIaiohttp—pyproject.toml
PyPIorjson—pyproject.toml
PyPIwebsockets—pyproject.toml
PyPIuvicorn==0.30.6pyproject.toml
PyPIinfluxdb>=5.3.1pyproject.toml
All dependencies 24

Full resolved dependency set from the GitHub dependency graph: 18 direct and 6 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaiohttp—direct
PyPIcvxpy—direct
PyPIgunicorn—direct
PyPIh5py—direct
PyPIhighspy—direct
PyPIinfluxdb—direct
PyPInumpy—direct
PyPIpandas—direct
PyPIplotly—direct
PyPIprotobuf—direct
PyPIpvlib—direct
PyPIpytz—direct
PyPIpyyaml—direct
PyPIscipy—direct
PyPIskforecast—direct
PyPItables—direct
PyPIuvicorn0.30.6direct
PyPIwaitress—direct
PyPIflask—indirect
PyPIkaleido—indirect
PyPIpulp—indirect
PyPIrequests—indirect
PyPItabulate—indirect
PyPItslearn—indirect
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 v0.15.0 — full methodology · metrics wiki.

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