Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-14 23:45 UTC

iree-org / iree-turbine

IREE's PyTorch Frontend, based on Torch Dynamo.

PythonApache-2.0★ 110 stars⑂ 83 forkssince Apr 2024View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

iree-org/iree-turbine holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (91/100) and lowest on Security (40/100). It was last updated 56 days ago. 4 contributors account for most of its recent work.

83
overall / 100
Excellent

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.

83
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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

IREEOrganization
205 followers33 public repossince Jun 2022

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIiree-turbine3.9.024,57517293 days ago

Metrics by category

Vitality

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

72Good · 21% of overall
How it's scored
18/36Push recency — last push 56 days ago
24.9/36Commit cadence — 36/52 weeks with commits
18/18Commit volume — 164 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year164
human_commit_share0.44
days_since_last_push56
active_weeks_last_year36
How it's scored
27/27Ships releases — 14 releases published
16.2/36Release recency — latest release 293 days ago
27/27Release cadence — a release every ~39.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count14
latest_release_tagv3.9.0
releases_from_tagsno
days_since_latest_release293
mean_days_between_releases39.5

Community & Adoption

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

65Good · 17% of overall
How it's scored
33/60Stars — 110 stars
16/25Forks — 83 forks
7.1/15Watchers — 20 watchers
Inputs used
forks83
stars110
watchers20
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized 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_servicesbadge.fury.io, readthedocs.org
has_pull_request_templateno
How it's scored
58.5/80Monthly downloads — 24,575 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesiree-turbine
dependents—
ecosystemspypi
total_downloads—
monthly_downloads24,575
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?

76Good · 23% of overall
How it's scored
43.2/54Bus factor — 4 contributor(s) cover half of all commits
18.7/22.5Commit distribution — top contributor authored 17% of commits
13.5/13.5Contributor breadth — 63 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor4
contributors_sampled63
top_contributor_share0.167
How it's scored
21/42Issue resolution — 50% of issues closed
25.4/30PR acceptance — 954/1,128 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs954
open_issues95
closed_issues95
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.5
closed_unmerged_prs174
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 backing — organization-owned
0/20Verified domain
16.6/25Owner reach — 205 followers of iree-org
19.6/25Track record — 33 public repos, account ~4 yr old
Inputs used
followers205
owner_typeOrganization
is_verifiedno
owner_loginiree-org
public_repos33
account_age_days1,546
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
26/35Publish recency — latest publish 293 days ago
20/20Version history — 17 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesiree-turbine
ecosystemspypi
any_deprecatedno
min_days_since_publish293

Engineering Quality

Are baseline engineering and documentation practices in place?

91Excellent · 19% of overall
How it's scored
24/24CI workflows — 6 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-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_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://iree.dev/guides/ml-frameworks/pytorch/
10/10Repository description
10/10Topics — 5 topics
0/10Wiki
Inputs used
topicscompiler, machine-learning, mlir, pytorch, runtime
has_wikino
homepagehttps://iree.dev/guides/ml-frameworks/pytorch/
docs_sitehttps://iree.dev/guides/ml-frameworks/pytorch/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

40Weak · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfiles
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestsbuild_tools/requirements-packaging.txt, docs/requirements.txt, pyproject.toml, requirements-iree-pinned.txt, requirements-iree-unpinned.txt, requirements-wave-runtime.txt, requirements.txt, setup.cfg, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configyes

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_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:iree-turbine@3.9.0 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.

67Good · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 44 of 44 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
11/11Static type checking — iree/turbine/py.typed, mypy.ini
0/10Reproducible environment
10/10Demonstrated agent practice — 14 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 8 of the last 100 commits are automated dependency updates
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_configsiree/turbine/py.typed, mypy.ini
agent_commit_share0.14
toolchain_manifests—
dependency_bot_commit_share0.08
How it's scored
27/45Type-checkable code — Python with type-check config (iree/turbine/py.typed, mypy.ini)
55/55Manageable file sizes — 0/219 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes40,633
source_files_sampled219
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
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

110GitHub stars
63contributors
164commits, last 12 months
56days since last push
14releases
4bus factor
95open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'iree-turbine' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • pypi download figures for iree-turbine carried forward from the previous scan (stats endpoint unavailable this scan)
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit; 2026/09/14 23:44:08 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 83 ⇿
0Stars
83Forks
14Releases

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.

0204060801008332024-042025-052026-07
Major 1Minor 12Patch 0

Each point covers 3 days.

All dependencies 38

Full resolved dependency set from the GitHub dependency graph: 0 direct and 38 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIchange-wheel-version—indirect
PyPIcmake3.31.6indirect
PyPIdecorator5.2.1indirect
PyPIfilecheck1.0.0indirect
PyPIiree-base-compiler—indirect
PyPIiree-base-compiler3.12.0rc20260629indirect
PyPIiree-base-runtime—indirect
PyPIiree-base-runtime3.12.0rc20260629indirect
PyPIiree-turbine—indirect
PyPIjinja23.1.4indirect
PyPIlit18.1.7indirect
PyPImaturin1.8.6indirect
PyPIml-dtypes0.5.0indirect
PyPImypy1.8.0indirect
PyPImyst-parser4.0.0indirect
PyPInanobind2.5.0indirect
PyPInumpy—indirect
PyPIpackaging—indirect
PyPIparameterized0.9.0indirect
PyPIpkginfo—indirect
PyPIpre-commit—indirect
PyPIpytest8.0.0indirect
PyPIpytest-timeout2.4.0indirect
PyPIpytest-xdist3.5.0indirect
PyPIsetuptools—indirect
PyPIshibuya—indirect
PyPIsphinx8.1.3indirect
PyPIsphinx-autobuild2024.10.3indirect
PyPIsphinx-rtd-theme3.0.2indirect
PyPIsphinxcontrib-mermaid1.0.0indirect
PyPItorch—indirect
PyPItorchaudio—indirect
PyPItorchvision—indirect
PyPItransformers—indirect
PyPItwine—indirect
PyPItypes-decorator5.2.0.20251101indirect
PyPItyping-extensions—indirect
PyPIwheel—indirect
Dependency advisories 0

Installing pypi:iree-turbine@3.9.0 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 v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.