Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-14 21:08 UTC

google-deepmind / distrax

PythonApache-2.0★ 651 stars⑂ 48 forkssince Apr 2021View on GitHub ↗
KindLibraryCommand-line toolhow this is determined

google-deepmind/distrax holds a health index of 75 out of 100, placing it in the Good band. It scores highest on Sustainability & Governance (75/100) and lowest on AI Readiness (42/100). It was last updated 3 days ago. 3 contributors account for most of its recent work.

75
overall / 100
Good

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.

75
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 65 is calibrated to 75 on the published index scale (record calibration 2026-08-02).

Ownership

Google DeepMindOrganization
26,771 followers404 public repossince Aug 2014

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdistrax0.1.9175,1131393 days agojaxprobabilitydistributionpythonmachine-learning

Metrics by category

Vitality

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

66Good · 21% of overall
How it's scored
36/36Push recencylast push 3 days ago
7.6/36Commit cadence11/52 weeks with commits
11.1/18Commit volume16 commits in the last year
5/10OpenSSF Scorecard: Maintained6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
Inputs used
commits_last_year16
human_commit_share1
days_since_last_push3
active_weeks_last_year11
How it's scored
27/27Ships releases16 releases published
27/36Release recencylatest release 93 days ago
12.6/27Release cadencea release every ~134.9 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count16
latest_release_tagv0.1.9
releases_from_tagsno
days_since_latest_release93
mean_days_between_releases134.9
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?

73Good · 17% of overall
How it's scored
45.6/60Stars651 stars
13.9/25Forks48 forks
6.4/15Watchers15 watchers
Inputs used
forks48
stars651
watchers15
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_badges2
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno
How it's scored
69.9/80Monthly downloads175,113 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesdistrax
dependents
ecosystemspypi
total_downloads
monthly_downloads175,113
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?

75Good · 23% of overall
How it's scored
36/54Bus factor3 contributor(s) cover half of all commits
16.4/22.5Commit distributiontop contributor authored 27% of commits
13.5/13.5Contributor breadth26 contributors
10/10OpenSSF Scorecard: Contributorsproject has 4 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled26
top_contributor_share0.27
How it's scored
21/42Issue resolution50% of issues closed
18/30PR acceptance151/251 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-ReviewFound 5/30 approved changesets -- score normalized to 1
Inputs used
merged_prs151
open_issues28
closed_issues28
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.5
closed_unmerged_prs100
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
30/30Ownership backingorganization-owned
0/20Verified domain
25/25Owner reach26,771 followers of google-deepmind
25/25Track record404 public repos, account ~12 yr old
Inputs used
followers26,771
owner_typeOrganization
is_verifiedno
owner_logingoogle-deepmind
public_repos404
account_age_days4,398

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 93 days ago
20/20Version history13 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesdistrax
ecosystemspypi
any_deprecatedno
min_days_since_publish93

Engineering Quality

Are baseline engineering and documentation practices in place?

63Moderate · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff], [tool.pylint])
0/9.6Pre-commit hooks
0/6.4.editorconfig
14/20OpenSSF Scorecard: CI-Tests19 out of 25 merged PRs checked by a CI test -- score normalized to 7
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
0/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionno

Security

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

46Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
1.8/2.5CI-Tests19 out of 25 merged PRs checked by a CI test -- score normalized to 7
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-ReviewFound 5/30 approved changesets -- score normalized to 1
2.5/2.5Contributorsproject has 4 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
3.8/7.5Maintained6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
5/5Packagingpackaging workflow detected
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
3.5/5SASTSAST tool is not run on all commits -- score normalized to 7
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_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4.6
Excluded from scoring (no data or not applicable): 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.

42Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
19.7/40Legible commit history37 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.37
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff], [tool.pylint])
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
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_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 codePython without a type-check config
55/55Manageable file sizes0/141 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes23,076
source_files_sampled141
oversized_source_files0
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
Inputs used
example_dirsexamples
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

651GitHub stars
26contributors
16commits, last 12 months
3days since last push
16releases
3bus factor
28open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'distrax' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • pypi download figures for distrax carried forward from the previous scan (stats endpoint unavailable this scan)
  • No resolved dependencies carried a version and a supported ecosystem

More detail

Star and fork history 0 ★ / 48 ⇿
0Stars
48Forks
15Releases

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.

010203040504822021-042023-122026-09
Major 0Minor 1Patch 14

Each point covers 5 days.

OpenSSF Scorecard 4.6 / 10
4.6aggregate

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 · 2026-09-14 21:08 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
7CI-Tests19 out of 25 merged PRs checked by a CI test -- score normalized to 7
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 5/30 approved changesets -- score normalized to 1
10Contributorsproject has 4 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
5Maintained6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
7SASTSAST tool is not run on all commits -- score normalized to 7
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 6
RegistryPackageVersion constraintManifest
PyPIabsl-py>=2.3.1pyproject.toml
PyPIchex>=0.1.90pyproject.toml
PyPIjax>=0.7.0pyproject.toml
PyPIjaxlib>=0.7.0pyproject.toml
PyPInumpy>=1.24.1pyproject.toml
PyPItfp-nightlypyproject.toml
All dependencies 6

Full resolved dependency set from the GitHub dependency graph: 6 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIabsl-pydirect
PyPIchexdirect
PyPIjaxdirect
PyPIjaxlibdirect
PyPInumpydirect
PyPItfp-nightlydirect
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies carried a version and a supported ecosystem

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 statisticsPyPI.