Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-22 17:54 UTC

dials / dials

Diffraction Integration for Advanced Light Sources

Python · C++BSD-3-Clause★ 106 stars⑂ 61 forkssince Jul 2015View on GitHub ↗

dials/dials holds a health index of 89 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on Security (46/100). It was last updated today. 3 contributors account for most of its recent work.

89
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.

89
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 75 is calibrated to 89 on the published index scale (record calibration 2026-08-02).

Ownership

DIALSOrganization
17 followers36 public repossince Jul 2015

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

Metrics by category

Vitality

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

90Excellent · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
30.5/36Commit cadence — 44/52 weeks with commits
18/18Commit volume — 177 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 14 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year177
human_commit_share0.98
days_since_last_push0
active_weeks_last_year44
How it's scored
27/27Ships releases — 88 releases published
36/36Release recency — latest release 35 days ago
19.8/27Release cadence — a release every ~53 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count88
latest_release_tagv3.30.1
releases_from_tagsno
days_since_latest_release35
mean_days_between_releases53

Community & Adoption

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

62Moderate · 17% of overall
How it's scored
32.8/60Stars — 106 stars
14.8/25Forks — 61 forks
7.6/15Watchers — 24 watchers
Inputs used
forks61
stars106
watchers24
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)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, shields.io
has_pull_request_templateno

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 factor — 3 contributor(s) cover half of all commits
15.9/22.5Commit distribution — top contributor authored 30% of commits
13.5/13.5Contributor breadth — 50 contributors
10/10OpenSSF Scorecard: Contributors — project has 36 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled50
top_contributor_share0.295
How it's scored
36.9/42Issue resolution — 88% of issues closed
27.9/30PR acceptance — 1,546/1,665 decided PRs merged
13/13Newcomer PR acceptance — 2/2 first-time contributors' PRs merged in 30d
9/15OpenSSF Scorecard: Code-Review — Found 20/29 approved changesets -- score normalized to 6
Inputs used
merged_prs1,546
open_issues191
closed_issues1,387
prs_merged_7d10
prs_decided_7d10
prs_merged_30d21
prs_decided_30d21
issue_closed_ratio0.879
closed_unmerged_prs119
first_time_authors_30d1
first_time_prs_merged_30d2
first_time_prs_decided_30d2
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
9/25Owner reach — 17 followers of dials
23.4/25Track record — 36 public repos, account ~11 yr old
Inputs used
followers17
owner_typeOrganization
is_verifiedno
owner_logindials
public_repos36
account_age_days4,109

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 27 out of 27 merged PRs checked by a CI test -- score normalized to 10
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 site — https://dials.github.io
10/10Repository description
10/10Topics — 3 topics
10/10Wiki
Inputs used
topicscrystallography, python, cpp
has_wikiyes
homepagehttps://dials.github.io
docs_sitehttps://dials.github.io
has_readmeyes
has_docs_diryes
has_descriptionyes

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-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 27 out of 27 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
4.5/7.5Code-Review — Found 20/29 approved changesets -- score normalized to 6
2.5/2.5Contributors — project has 36 contributing companies or organizations
0/10Dangerous-Workflow — 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
7.5/7.5Maintained — 30 commit(s) and 14 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
2/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
3.5/5SAST — SAST tool is not run on all commits -- score normalized to 7
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 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): Branch-Protection. 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.

61Moderate · 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 — 89 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.908
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — doc/sphinx/Makefile, installer/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — Dockerfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
4/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesdoc/sphinx/Makefile, installer/Makefile
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
54.2/55Manageable file sizes — 15/1,070 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes1,153,009
source_files_sampled1,070
oversized_source_files15
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

106GitHub stars
50contributors
177commits, last 12 months
0days since last push
88releases
3bus factor
191open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • No resolved dependencies carried a version and a supported ecosystem

More detail

Star and fork history 0 ★ / 61 ⇿
0Stars
61Forks
84Releases

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.

01020304050605722016-122021-102026-08
Major 2Minor 41Patch 41

Each point covers 9 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 · 2026-10-22 17:54 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
10CI-Tests27 out of 27 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 20/29 approved changesets -- score normalized to 6
10Contributorsproject has 36 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 14 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
4Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
7SASTSAST tool is not run on all commits -- score normalized to 7
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 3

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

RegistryPackageVersionRelation
PyPIdials-data—indirect
PyPIpytest—indirect
PyPIpytest-randomly—indirect
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 statistics.