Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-15 20:37 UTC

pyroll-project / pyroll-core

PyRoll rolling simulation framework - core library.

PythonBSD-3-Clause★ 18 stars⑂ 8 forkssince Mar 2022View on GitHub ↗

pyroll-project/pyroll-core holds a health index of 53 out of 100, placing it in the Moderate band. It scores highest on Sustainability & Governance (63/100) and lowest on AI Readiness (38/100). It was last updated 245 days ago. A single contributor accounts for most of its recent work.

53
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.

53
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 52 is calibrated to 53 on the published index scale (record calibration 2026-08-02).

Ownership

The PyRoll ProjectOrganization
35 followers52 public repossince Mar 2022

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIpyroll-core3.1.152,0927025 days ago

Metrics by category

Vitality

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

42Weak · 21% of overall
How it's scored
3.6/36Push recency — last push 245 days ago
3.5/36Commit cadence — 5/52 weeks with commits
11.5/18Commit volume — 18 commits in the last year
5/10OpenSSF Scorecard: Maintained — 0 commit(s) and 7 issue activity found in the last 90 days -- score normalized to 5
Inputs used
commits_last_year18
human_commit_share1
days_since_last_push245
active_weeks_last_year5
How it's scored
27/27Ships releases — 22 releases published
16.2/36Release recency — latest release 342 days ago
19.8/27Release cadence — a release every ~48.9 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count22
latest_release_tagv.3.1.0
releases_from_tagsno
days_since_latest_release342
mean_days_between_releases48.9
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?

49Weak · 17% of overall
How it's scored
20/60Stars — 18 stars
7/25Forks — 8 forks
4.7/15Watchers — 8 watchers
Inputs used
forks8
stars18
watchers8
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (BSD-3-Clause)
0/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingno
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io, www.bestpractices.dev
has_pull_request_templateno
How it's scored
44.3/80Monthly downloads — 2,092 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespyroll-core
dependents—
ecosystemspypi
total_downloads—
monthly_downloads2,092
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?

63Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
7.9/22.5Commit distribution — top contributor authored 65% of commits
6.8/13.5Contributor breadth — 5 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled5
top_contributor_share0.651
How it's scored
35.6/42Issue resolution — 85% of issues closed
27.4/30PR acceptance — 160/175 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-Review — Found 4/30 approved changesets -- score normalized to 1
Inputs used
merged_prs160
open_issues20
closed_issues112
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.848
closed_unmerged_prs15
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
11.2/25Owner reach — 35 followers of pyroll-project
21.6/25Track record — 52 public repos, account ~4 yr old
Inputs used
followers35
owner_typeOrganization
is_verifiedno
owner_loginpyroll-project
public_repos52
account_age_days1,656

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 25 days ago
20/20Version history — 70 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespyroll-core
ecosystemspypi
any_deprecatedno
min_days_since_publish25

Engineering Quality

Are baseline engineering and documentation practices in place?

56Moderate · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config — ruff.toml
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 17 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://pyroll.readthedocs.io
10/10Repository description
10/10Topics — 7 topics
0/10Wiki
Inputs used
topicsgroove-rolling, materials, metal-forming, pyroll, python, rolling, simulation
has_wikino
homepagehttps://pyroll.readthedocs.io
docs_sitehttps://pyroll.readthedocs.io
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

52Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
0/2.5CI-Tests — 0 out of 17 merged PRs checked by a CI test -- score normalized to 0
1.2/2.5CII-Best-Practices — badge detected: Passing
0.8/7.5Code-Review — Found 4/30 approved changesets -- score normalized to 1
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
0/10Dangerous-Workflow — no data
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
3.8/7.5Maintained — 0 commit(s) and 7 issue activity found in the last 90 days -- score normalized to 5
0/5Packaging — no data
0/5Pinned-Dependencies — no data
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 — no data
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated12
scorecard_versionv5.5.0
checks_inconclusive6
scorecard_aggregate4
Excluded from scoring (no data or not applicable): Branch-Protection, Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. Remaining weights renormalized.

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_packages3
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:pyroll-core@3.1.15 runtime dependency closure — what installing the published package pulls in — 3 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.

38Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
32/40Legible commit history — 60 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.6
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — ruff.toml
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
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_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/147 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes27,992
source_files_sampled147
oversized_source_files0

Key facts

18GitHub stars
5contributors
18commits, last 12 months
245days since last push
22releases
1bus factor
20open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'pyroll-core' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • pypi download figures for pyroll-core carried forward from the previous scan (stats endpoint unavailable this scan)

More detail

Star and fork history 0 ★ / 8 ⇿
0Stars
8Forks
22Releases

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.

02468812022-112024-102026-09
Major 1Minor 1Patch 14

Each point covers 4 days.

OpenSSF Scorecard 4.0 / 10
4.0aggregate

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 · 2026-09-15 20:36 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
0CI-Tests0 out of 17 merged PRs checked by a CI test -- score normalized to 0
5CII-Best-Practicesbadge detected: Passing
1Code-ReviewFound 4/30 approved changesets -- score normalized to 1
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
5Maintained0 commit(s) and 7 issue activity found in the last 90 days -- score normalized to 5
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPInumpy~= 2.0pyproject.toml
PyPIscipy~= 1.13pyproject.toml
PyPIshapely>= 2.0.6, <3.0pyproject.toml
All dependencies 3

Full resolved dependency set from the GitHub dependency graph: 3 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpy—direct
PyPIscipy—direct
PyPIshapely—direct
Dependency advisories 0

Installing pypi:pyroll-core@3.1.15 pulls in 3 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.