Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-15 12:19 UTC

reacon-io / reacon-python

Reacon SDK for Python.

PythonApache-2.0★ 0 stars⑂ 0 forkssince Sep 2026View on GitHub ↗
KindLibraryhow this is determined

reacon-io/reacon-python holds a health index of 50 out of 100, placing it in the Moderate band. It scores highest on Vitality (76/100) and lowest on Security (1/100). It was last updated today. A single contributor accounts for most of its recent work.

50
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.

50
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 50 is calibrated to 50 on the published index scale (record calibration 2026-08-02).

Ownership

reacon-ioOrganization
0 followers9 public repossince Sep 2026

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIreacon_sdk6.0.0b12,396270 days agoopenapiopenapi-generatorreacon-api

Metrics by category

Vitality

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

76Good · 21% of overall

Development activity

60Moderate
How it's scored
36/36Push recency — last push 0 days ago
1.4/36Commit cadence — 2/52 weeks with commits
16.6/18Commit volume — 70 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year70
human_commit_share0.465
days_since_last_push0
active_weeks_last_year2

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 22 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~1.3 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count22
latest_release_tagsdk-ci-input-0e8bb82c47151812caba65ac3bfa409dcb1361992c0500372cbc4ecde72dfd46
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases1.3

Community & Adoption

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

32At Risk · 17% of overall

Popularity & adoption

1Critical
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

Community health

50Moderate
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_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

56Moderate
How it's scored
45.1/80Monthly downloads — 2,396 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesreacon_sdk
dependents—
ecosystemspypi
total_downloads—
monthly_downloads2,396
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?

58Moderate · 23% of overall

Maintainer resilience (bus factor)

12Critical
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

Issue & PR responsiveness

100Exceptional
How it's scored
0/42Issue resolution — no issues or no data
30/30PR acceptance — 48/48 decided PRs merged
13/13Newcomer PR acceptance — 11/11 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs48
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d11
prs_decided_30d11
issue_closed_ratio—
closed_unmerged_prs0
first_time_authors_30d1
first_time_prs_merged_30d11
first_time_prs_decided_30d11
Excluded from scoring (no data or not applicable): Issue resolution. Remaining weights renormalized.

Ownership & stewardship

37Weak
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
0/25Owner reach — 0 followers of reacon-io
7.4/25Track record — 9 public repos, account ~0 yr old
Inputs used
followers0
owner_typeOrganization
is_verifiedno
owner_loginreacon-io
public_repos9
account_age_days18

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 27 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesreacon_sdk
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

68Good · 19% of overall

Engineering practices

80Excellent
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

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

1Critical · 16% of overall

Security posture

1Critical
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
lockfilespackage-lock.json
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.

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.

59Moderate · 4% of overall

Agent context & guidance

28At Risk
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
27.5/40Legible commit history — 17 of 33 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.515
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

74Good
How it's scored
12.6/18One-command bootstrap — .github/sdk-ci/recordings/csharp/Consumer.csproj, .github/sdk-ci/recordings/kotlin/build.gradle (toolchain convention, no task runner)
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.pylint]), setup.cfg ([flake8]), tox.ini
11/11Static type checking — reacon_sdk/py.typed
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 71
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfilespackage-lock.json
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configsreacon_sdk/py.typed
agent_commit_share0
toolchain_manifests.github/sdk-ci/recordings/csharp/Consumer.csproj, .github/sdk-ci/recordings/kotlin/build.gradle
dependency_bot_commit_share0

Code legibility for models

81Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (reacon_sdk/py.typed)
54.3/55Manageable file sizes — 9/723 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes1,559,844
source_files_sampled723
oversized_source_files9

Key facts

0GitHub stars
1contributors
70commits, last 12 months
0days since last push
22releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index pypi:reacon_sdk@6.0.0b1; advisories assessed against the repository dependency graph instead
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIhttpx-sse== 0.4.3pyproject.toml
PyPIpython-dateutil(>=2.8.2)pyproject.toml
PyPIhttpx(>=0.28.1)pyproject.toml
PyPIpydantic(>=2.11)pyproject.toml
PyPItyping-extensions(>=4.7.1)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

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.