Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-24 11:58 UTC

Matt52 / bayesian-testing

Bayesian A/B testing

PythonMIT★ 83 stars⑂ 11 forkssince Dec 2021View on GitHub ↗

Matt52/bayesian-testing holds a health index of 59 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (70/100) and lowest on Security (43/100). It was last updated today. A single contributor accounts for most of its recent work.

59
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.

59
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 56 is calibrated to 59 on the published index scale (record calibration 2026-08-02).

Ownership

MatusPersonal account
3 followers1 public reposince Oct 2014

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
PyPIbayesian-testing0.10.06,426300 days agoab-testingbayesbayesian-statistics

Metrics by category

Vitality

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

63Moderate · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
2.1/36Commit cadence — 3/52 weeks with commits
5.4/18Commit volume — 3 commits in the last year
1/10OpenSSF Scorecard: Maintained — 2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
Inputs used
commits_last_year3
human_commit_share1
days_since_last_push0
active_weeks_last_year3
How it's scored
27/27Ships releases — 30 releases published
36/36Release recency — latest release 0 days ago
19.8/27Release cadence — a release every ~98.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count30
latest_release_tagv0.10.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases98.8
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?

50Moderate · 17% of overall
How it's scored
31/60Stars — 83 stars
8.3/25Forks — 11 forks
1.7/15Watchers — 3 watchers
Inputs used
forks11
stars83
watchers3
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_badges3
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateno
How it's scored
50.8/80Monthly downloads — 6,426 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesbayesian-testing
dependents—
ecosystemspypi
total_downloads—
monthly_downloads6,426
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?

53Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.2/22.5Commit distribution — top contributor authored 99% of commits
2.7/13.5Contributor breadth — 2 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.989
How it's scored
42/42Issue resolution — 100% of issues closed
28/30PR acceptance — 41/44 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 1/30 approved changesets -- score normalized to 0
Inputs used
merged_prs41
open_issues0
closed_issues7
prs_merged_7d2
prs_decided_7d2
prs_merged_30d2
prs_decided_30d2
issue_closed_ratio1
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
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
4.3/25Owner reach — 3 followers of Matt52
14.2/25Track record — 1 public repos, account ~12 yr old
Inputs used
followers3
owner_typeUser
is_verified—
owner_loginMatt52
public_repos1
account_age_days4,390
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 0 days ago
20/20Version history — 30 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesbayesian-testing
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

70Good · 19% of overall
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
2/20OpenSSF Scorecard: CI-Tests — 5 out of 30 merged PRs checked by a CI test -- score normalized to 1
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 5 topics
10/10Wiki
Inputs used
topicspython, bayesian-statistics, bayes, probability, ab-testing
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?

43Weak · 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
0.2/2.5CI-Tests — 5 out of 30 merged PRs checked by a CI test -- score normalized to 1
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 1/30 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
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
0.8/7.5Maintained — 2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
0/5Packaging — no data
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
6/7.5Vulnerabilities — 2 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate2.9
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. 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
advisories3
affected_packages1
assessed_packages122
unassessed_packages0
affected_by_severitymoderate 1
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 122 resolved dependencies against OSV. 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.

47Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
23.3/40Legible commit history — 41 of 94 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.436
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 94
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
lockfilespoetry.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/26 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes22,187
source_files_sampled26
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, notebooks
Inputs used
example_dirsexamples, notebooks
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

83GitHub stars
2contributors
3commits, last 12 months
0days since last push
30releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:bayesian-testing@0.10.0; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 11 ⇿
0Stars
11Forks
20Releases

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.

0246810121112022-062024-082026-09
Major 0Minor 7Patch 13

Each point covers 4 days.

OpenSSF Scorecard 2.9 / 10
2.9aggregate

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 · 2026-10-24 11:57 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
1CI-Tests5 out of 30 merged PRs checked by a CI test -- score normalized to 1
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 1/30 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
1Maintained2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
n/aPackagingpackaging workflow not 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
8Vulnerabilities2 existing vulnerabilities detected
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPInumpy>=1.19pyproject.toml
All dependencies 122

Full resolved dependency set from the GitHub dependency graph: 1 direct and 121 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpy2.4.6direct
PyPIanyio4.15.1indirect
PyPIappnope1.0.0indirect
PyPIargon2-cffi25.1.0indirect
PyPIargon2-cffi-bindings26.1.0indirect
PyPIarrow1.4.0indirect
PyPIasttokens3.0.2indirect
PyPIasync-lru2.4.0indirect
PyPIattrs26.1.0indirect
PyPIbabel2.18.0indirect
PyPIbeautifulsoup44.15.0indirect
PyPIblack26.10.1indirect
PyPIbleach6.4.0indirect
PyPIcertifi2026.10.23indirect
PyPIcffi2.1.1indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.5.2indirect
PyPIclick8.5.0indirect
PyPIcolorama0.4.6indirect
PyPIcomm0.2.3indirect
PyPIcoverage7.17.0indirect
PyPIdebugpy1.8.22indirect
PyPIdefusedxml0.7.1indirect
PyPIdistlib0.4.4indirect
PyPIexecuting2.3.0indirect
PyPIfastjsonschema2.22.2indirect
PyPIfilelock4.2.4indirect
PyPIfqdn1.4.0indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIidentify2.6.20indirect
PyPIidna3.20indirect
PyPIiniconfig2.3.1indirect
PyPIipykernel7.4.0indirect
PyPIipython9.17.1indirect
PyPIipython-pygments-lexers1.1.1indirect
PyPIipywidgets8.1.9indirect
PyPIisoduration20.11.0indirect
PyPIisort9.0.2indirect
PyPIjedi0.20.1indirect
PyPIjinja23.1.6indirect
PyPIjson50.17.3indirect
PyPIjsonpointer3.4indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPIjupyter1.1.1indirect
PyPIjupyter-builder1.2.3indirect
PyPIjupyter-client8.10.0indirect
PyPIjupyter-console6.6.3indirect
PyPIjupyter-core5.9.1indirect
PyPIjupyter-events0.12.1indirect
PyPIjupyter-lsp2.3.1indirect
PyPIjupyter-server2.21.1indirect
PyPIjupyter-server-terminals0.5.4indirect
PyPIjupyterlab4.6.4indirect
PyPIjupyterlab-pygments0.3.0indirect
PyPIjupyterlab-server2.28.1indirect
PyPIjupyterlab-widgets3.0.17indirect
PyPIlark1.3.1indirect
PyPImarkupsafe3.0.4indirect
PyPImatplotlib-inline0.2.2indirect
PyPImistune3.4.0indirect
PyPImypy-extensions1.1.0indirect
PyPInbclient0.11.0indirect
PyPInbconvert7.17.2indirect
PyPInbformat5.11.1indirect
PyPInest-asyncio21.7.4indirect
PyPInodeenv1.11.0indirect
PyPInotebook7.6.3indirect
PyPInotebook-shim0.2.4indirect
PyPIoverrides7.7.0indirect
PyPIpackaging26.3indirect
PyPIpandas3.1.0indirect
PyPIpandocfilters1.5.1indirect
PyPIparso0.8.7indirect
PyPIpathspec1.1.1indirect
PyPIpexpect4.9.0indirect
PyPIplatformdirs4.13.5indirect
PyPIpluggy1.7.0indirect
PyPIpre-commit4.7.0indirect
PyPIprometheus-client0.26.0indirect
PyPIprompt-toolkit3.0.53indirect
PyPIpsutil7.2.2indirect
PyPIptyprocess0.7.0indirect
PyPIpure-eval0.2.4indirect
PyPIpycparser3.12indirect
PyPIpygments2.21.0indirect
PyPIpytest9.1.1indirect
PyPIpython-dateutil3.0.0indirect
PyPIpython-discovery1.6.4indirect
PyPIpython-json-logger4.2.0indirect
PyPIpytokens0.4.1indirect
PyPIpywinpty3.1.0indirect
PyPIpyyaml6.0.3indirect
PyPIpyzmq27.2.0indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIrfc3339-validator0.1.4indirect
PyPIrfc3986-validator0.1.1indirect
PyPIrfc3987-syntax1.1.0indirect
PyPIrpds-py2026.9.1indirect
PyPIsend2trash2.1.0indirect
PyPIsetuptools78.1.1indirect
PyPIsix1.17.0indirect
PyPIsoupsieve2.10indirect
PyPIstack-data0.6.3indirect
PyPItabulate0.10.0indirect
PyPIterminado0.18.1indirect
PyPItinycss21.5.1indirect
PyPItornado6.6indirect
PyPItraitlets5.16.1indirect
PyPItyping-extensions4.16.0indirect
PyPItzdata2026.5indirect
PyPIuri-template1.3.0indirect
PyPIurllib32.8.0indirect
PyPIvirtualenv21.14.13indirect
PyPIwcwidth0.9.3indirect
PyPIwebcolors25.10.0indirect
PyPIwebencodings0.6.1indirect
PyPIwebsocket-client1.9.2indirect
PyPIwidgetsnbextension4.0.16indirect
Dependency advisories 1

This repository publishes no package the index resolves, so its own dependency graph was assessed — 122 packages, which also include development and test pins that never ship: 1 carry known advisories, of which 0 are direct.

PackageVersionRelationSeverityAdvisoriesFixed in
setuptools78.1.1indirectmoderate384.1.0

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.