Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 02:12 UTC

pyro-ppl / numpyro

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

PythonApache-2.0★ 2,735 stars⑂ 301 forkssince Feb 2019View on GitHub ↗

pyro-ppl/numpyro holds a health index of 93 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (95/100) and lowest on Security (58/100). It was last updated today. A single contributor accounts for most of its recent work.

93
overall / 100
Exceptional

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.

93
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 79 is calibrated to 93 on the published index scale (record calibration 2026-08-02).

Ownership

pyro-pplOrganization
207 followers13 public repossince Jan 2019

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPInumpyro0.21.0-39102 days agoprobabilisticmachine-learningbayesianstatistics

Metrics by category

Vitality

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

87Excellent · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
25.6/36Commit cadence37/52 weeks with commits
18/18Commit volume120 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 6 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year120
human_commit_share1
days_since_last_push0
active_weeks_last_year37
How it's scored
27/27Ships releases39 releases published
27/36Release recencylatest release 102 days ago
19.8/27Release cadencea release every ~71.2 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count39
latest_release_tag0.21.0
releases_from_tagsno
days_since_latest_release102
mean_days_between_releases71.2
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?

79Good · 17% of overall
How it's scored
55.7/60Stars2,735 stars
20.6/25Forks301 forks
9.2/15Watchers47 watchers
Inputs used
forks301
stars2,735
watchers47
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, coveralls.io, github.com, readthedocs.org, www.bestpractices.dev
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

78Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
9.8/22.5Commit distributiontop contributor authored 56% of commits
13.5/13.5Contributor breadth100 contributors
10/10OpenSSF Scorecard: Contributorsproject has 31 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled100
top_contributor_share0.565
How it's scored
39.6/42Issue resolution94% of issues closed
27.9/30PR acceptance1,246/1,340 decided PRs merged
13/13Newcomer PR acceptance4/4 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs1,246
open_issues51
closed_issues826
prs_merged_7d4
prs_decided_7d4
prs_merged_30d14
prs_decided_30d15
issue_closed_ratio0.942
closed_unmerged_prs94
first_time_authors_30d4
first_time_prs_merged_30d4
first_time_prs_decided_30d4
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
16.7/25Owner reach207 followers of pyro-ppl
20.3/25Track record13 public repos, account ~7 yr old
Inputs used
followers207
owner_typeOrganization
is_verified
owner_loginpyro-ppl
public_repos13
account_age_days2,764
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 102 days ago
20/20Version history39 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesnumpyro
ecosystemspypi
any_deprecatedno
min_days_since_publish102

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall
How it's scored
24/24CI workflows6 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests29 out of 30 merged PRs checked by a CI test -- score normalized to 9
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://num.pyro.ai
10/10Repository description
10/10Topics8 topics
10/10Wiki
Inputs used
topicspyro, jax, hmc, inference-algorithms, numpy, bayesian-inference, probabilistic-programming, mcmc
has_wikiyes
homepagehttps://num.pyro.ai
docs_sitehttps://num.pyro.ai
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

58Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
2.2/2.5CI-Tests29 out of 30 merged PRs checked by a CI test -- score normalized to 9
1.2/2.5CII-Best-Practicesbadge detected: Passing
7.5/7.5Code-Reviewall changesets reviewed
2.5/2.5Contributorsproject has 31 contributing companies or organizations
0/10Dangerous-Workflowdangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 6 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4.8
Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages8
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:numpyro@0.21.0 runtime dependency closure — what installing the published package pulls in — 8 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.

63Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history97 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.97
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile, docs/Makefile, notebooks/Makefile
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environmentDockerfile
10/10Demonstrated agent practice12 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile, docs/Makefile, notebooks/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0.12
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
53.4/55Manageable file sizes6/201 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes186,671
source_files_sampled201
oversized_source_files6
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples, 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

2,735GitHub stars
100contributors
120commits, last 12 months
0days since last push
39releases
1bus factor
51open 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 ★ / 301 ⇿
0Stars
301Forks
39Releases

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.

05010015020025030029362019-032022-112026-08
Major 0Minor 21Patch 18

Each point covers 7 days.

OpenSSF Scorecard 4.8 / 10
4.8aggregate

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 · 2026-08-13 02:12 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
9CI-Tests29 out of 30 merged PRs checked by a CI test -- score normalized to 9
5CII-Best-Practicesbadge detected: Passing
10Code-Reviewall changesets reviewed
10Contributorsproject has 31 contributing companies or organizations
0Dangerous-Workflowdangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 6 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
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
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIjax>=0.7.0pyproject.toml
PyPIjaxlib>=0.7.0pyproject.toml
PyPImultipledispatchpyproject.toml
PyPInumpypyproject.toml
PyPItqdmpyproject.toml
All dependencies 22

Full resolved dependency set from the GitHub dependency graph: 2 direct and 20 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIjaxdirect
PyPIjaxlibdirect
PyPIcoverageindirect
PyPIcoverallsindirect
PyPIfunsorindirect
PyPIgpjaxindirect
PyPIimportlib-metadataindirect
PyPIjaxnsindirect
PyPInbsphinxindirect
PyPIoptaxindirect
PyPIpandasindirect
PyPIpyro-apiindirect
PyPIpytestindirect
PyPIreadthedocs-sphinx-searchindirect
PyPIruffindirect
PyPIscikit-learnindirect
PyPIscipyindirect
PyPIseabornindirect
PyPIsetuptoolsindirect
PyPIsphinxindirect
PyPIty0.0.57indirect
PyPIwordcloudindirect
Dependency advisories 0

Installing pypi:numpyro@0.21.0 pulls in 8 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 v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.