Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-27 04:34 UTC

QuantumBPM / quantum-python-sdk

Official Python SDK for QuantumBPM: async BPMN 2.0 workflow orchestration, DMN 1.5 decision evaluation with FEEL, and external job workers.

PythonMIT★ 0 stars⑂ 0 forkssince May 2026View on GitHub ↗

QuantumBPM/quantum-python-sdk holds a health index of 45 out of 100, placing it in the Weak band. It scores highest on Engineering Quality (74/100) and lowest on Security (21/100). It was last updated 32 days ago. A single contributor accounts for most of its recent work.

45
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.

45
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 47 is calibrated to 45 on the published index scale (record calibration 2026-08-02).

Ownership

QuantumBPMOrganization
3 followers4 public repossince Apr 2026

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIquantumbpm-sdk1.1.071332 days agoquantumbpmdmnbpmnworkflowfeelsdk

Metrics by category

Vitality

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

66Good · 21% of overall
How it's scored
18/36Push recency — last push 32 days ago
7.6/36Commit cadence — 11/52 weeks with commits
12.7/18Commit volume — 25 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year25
human_commit_share1
days_since_last_push32
active_weeks_last_year11

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 5 releases published
36/36Release recency — latest release 32 days ago
27/27Release cadence — a release every ~28.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count5
latest_release_tagv1.1.0
releases_from_tagsno
days_since_latest_release32
mean_days_between_releases28.2

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

26At Risk · 17% of overall
How it's scored
0/60Stars — 0 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars0
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
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_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno
How it's scored
24.8/80Monthly downloads — 71 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesquantumbpm-sdk
dependents—
ecosystemspypi
total_downloads—
monthly_downloads71
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?

43Weak · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0/22.5Commit distribution — top contributor authored 100% of commits
1.4/13.5Contributor breadth — 1 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
4.3/25Owner reach — 3 followers of QuantumBPM
5.9/25Track record — 4 public repos, account ~0 yr old
Inputs used
followers3
owner_typeOrganization
is_verifiedno
owner_loginQuantumBPM
public_repos4
account_age_days153
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 32 days ago
12/20Version history — 3 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesquantumbpm-sdk
ecosystemspypi
any_deprecatedno
min_days_since_publish32

Engineering Quality

Are baseline engineering and documentation practices in place?

74Good · 19% of overall
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.pylint]), setup.cfg ([flake8]), tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://quantumbpm.com/docs/sdks/python
10/10Repository description
10/10Topics — 7 topics
0/10Wiki
Inputs used
topicsbpm, bpmn, bpmn-engine, bpmn2, dmn, dmn-engine, dmn-feel
has_wikino
homepagehttps://quantumbpm.com/docs/sdks/python
docs_sitehttps://quantumbpm.com/docs/sdks/python
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

21At Risk · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestspyproject.toml, requirements.txt, setup.cfg, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. 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_packages17
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:quantumbpm-sdk@1.1.0 runtime dependency closure — what installing the published package pulls in — 17 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
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
12.8/40Legible commit history — 6 of 25 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.24
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.pylint]), setup.cfg ([flake8]), tox.ini
11/11Static type checking — quantumbpm/py.typed
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 25
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configsquantumbpm/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
27/45Type-checkable code — Python with type-check config (quantumbpm/py.typed)
53.9/55Manageable file sizes — 2/103 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes482,849
source_files_sampled103
oversized_source_files2
How it's scored
40/40API schema (OpenAPI/GraphQL/proto) — openapi.yaml
0/20MCP server — not applicable to this kind of software
0/40Runnable examples
Inputs used
example_dirs—
has_mcp_signalno
api_schema_filesopenapi.yaml
interfaces_expected_of—
Excluded from scoring (no data or not applicable): MCP server. Remaining weights renormalized.

Key facts

0GitHub stars
1contributors
25commits, last 12 months
32days since last push
5releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Direct dependencies 7
RegistryPackageVersion constraintManifest
PyPIurllib3(>=2.1.0,<3.0.0)pyproject.toml
PyPIpython-dateutil(>=2.8.2)pyproject.toml
PyPIpydantic(>=2)pyproject.toml
PyPItyping-extensions(>=4.7.1)pyproject.toml
PyPIPyJWT(>=2.8.0)pyproject.toml
PyPIsimplejson(>=3.19)pyproject.toml
PyPIrequests(>=2.31.0)pyproject.toml
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

Dependency advisories 0

Installing pypi:quantumbpm-sdk@1.1.0 pulls in 17 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.

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.