Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-18 19:23 UTC

diffpy / diffpy.structure

Crystal structure container and parsers for structure formats.

PythonCustom license★ 40 stars⑂ 34 forkssince Aug 2013View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

diffpy/diffpy.structure holds a health index of 73 out of 100, placing it in the Good band. It scores highest on Engineering Quality (86/100) and lowest on AI Readiness (47/100). It was last updated 55 days ago. A single contributor accounts for most of its recent work.

73
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.

73
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 64 is calibrated to 73 on the published index scale (record calibration 2026-08-02).

Ownership

diffpyOrganization
47 followers47 public repossince Oct 2013

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdiffpy.structure3.5.018,2953255 days agodiffpycrystal-structure-data-storagecifpdb

Metrics by category

Vitality

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

64Moderate · 21% of overall
How it's scored
18/36Push recency — last push 55 days ago
8.3/36Commit cadence — 12/52 weeks with commits
18/18Commit volume — 139 commits in the last year
1/10OpenSSF Scorecard: Maintained — 2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
Inputs used
commits_last_year139
human_commit_share0.99
days_since_last_push55
active_weeks_last_year12
How it's scored
27/27Ships releases — 31 releases published
36/36Release recency — latest release 55 days ago
19.8/27Release cadence — a release every ~74 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count31
latest_release_tag3.5.0
releases_from_tagsno
days_since_latest_release55
mean_days_between_releases74
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?

50Moderate · 17% of overall
How it's scored
25.8/60Stars — 40 stars
12.7/25Forks — 34 forks
4.3/15Watchers — 7 watchers
Inputs used
forks34
stars40
watchers7
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno
How it's scored
56.8/80Monthly downloads — 18,295 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdiffpy.structure
dependents—
ecosystemspypi
total_downloads—
monthly_downloads18,295
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?

68Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
7.7/22.5Commit distribution — top contributor authored 66% of commits
13.5/13.5Contributor breadth — 25 contributors
10/10OpenSSF Scorecard: Contributors — project has 10 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled25
top_contributor_share0.656
How it's scored
36.6/42Issue resolution — 87% of issues closed
23.4/30PR acceptance — 103/132 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
7.5/15OpenSSF Scorecard: Code-Review — Found 7/12 approved changesets -- score normalized to 5
Inputs used
merged_prs103
open_issues9
closed_issues61
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.871
closed_unmerged_prs29
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
12.1/25Owner reach — 47 followers of diffpy
24.2/25Track record — 47 public repos, account ~13 yr old
Inputs used
followers47
owner_typeOrganization
is_verifiedno
owner_logindiffpy
public_repos47
account_age_days4,762

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 55 days ago
20/20Version history — 32 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdiffpy.structure
ecosystemspypi
any_deprecatedno
min_days_since_publish55

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall
How it's scored
24/24CI workflows — 5 workflow(s)
24/24Tests present
16/16Linter config — .flake8, pyproject.toml ([tool.black])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 10 out of 10 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
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

54Moderate · 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 — 10 out of 10 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
3.8/7.5Code-Review — Found 7/12 approved changesets -- score normalized to 5
2.5/2.5Contributors — project has 10 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
0.8/7.5Maintained — 2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
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 — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4.3
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. 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_packages11
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:diffpy.structure@3.5.0 runtime dependency closure — what installing the published package pulls in — 11 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.

47Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
37.7/40Legible commit history — 70 of 99 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.707
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — docs/Makefile, docs/manual/Makefile
22/22Automated tests
11/11Lint / format config — .flake8, pyproject.toml ([tool.black])
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 — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile, docs/manual/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
52.9/55Manageable file sizes — 2/53 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes245,731
source_files_sampled53
oversized_source_files2

Key facts

40GitHub stars
25contributors
139commits, last 12 months
55days since last push
31releases
1bus factor
9open 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 ★ / 34 ⇿
0Stars
34Forks
29Releases

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.

01325383222013-112020-032026-07
Major 1Minor 4Patch 11

Each point covers 12 days.

OpenSSF Scorecard 4.3 / 10
4.3aggregate

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 · 2026-10-18 19:22 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-Tests10 out of 10 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
5Code-ReviewFound 7/12 approved changesets -- score normalized to 5
10Contributorsproject has 10 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
1Maintained2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
n/aPackagingpackaging workflow not 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
All dependencies 16

Full resolved dependency set from the GitHub dependency graph: 0 direct and 16 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcodecov—indirect
PyPIcoverage—indirect
PyPIdiffpy-utils—indirect
PyPIdoctr—indirect
PyPIflake8—indirect
PyPIm2r—indirect
PyPIm2r2—indirect
PyPInumpy—indirect
PyPIpycifrw—indirect
PyPIpytest—indirect
PyPIpytest-cov—indirect
PyPIpytest-env—indirect
PyPIsphinx—indirect
PyPIsphinx-copybutton—indirect
PyPIsphinx-py3doc-enhanced-theme—indirect
PyPIsphinx-rtd-theme—indirect
Dependency advisories 0

Installing pypi:diffpy.structure@3.5.0 pulls in 11 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.