Public record
Software health reportschema 0.26.0 · metrics 2.10.0 · 2026-07-22 18:42 UTC

glotzerlab / freud

Powerful, efficient particle trajectory analysis in scientific Python.

C++ · PythonBSD-3-Clause★ 324 stars⑂ 53 forkssince Jan 2019View on GitHub ↗

glotzerlab/freud holds a health index of 93 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (90/100) and lowest on AI Readiness (59/100). It was last updated 1 day ago. 3 contributors account for most of its recent work.

93
overall / 100
Exceptional

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.

93
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 79 is calibrated to 93 on the published index scale (record calibration 2026-08-02).

Ownership

Glotzer GroupOrganization
121 followers70 public repossince Feb 2017

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIfreud-analysis3.5.08,44236287 days agosimulationanalysismolecular-dynamicssoft-matterparticlesystemcomputationalphysics

Metrics by category

Vitality

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

81Excellent · 21% of overall
How it's scored
36/36Push recencylast push 1 days ago
29.1/36Commit cadence42/52 weeks with commits
18/18Commit volume363 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year363
human_commit_share0.64
days_since_last_push1
active_weeks_last_year42
How it's scored
27/27Ships releases24 releases published
16.2/36Release recencylatest release 287 days ago
19.8/27Release cadencea release every ~98.1 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count24
latest_release_tagv3.5.0
releases_from_tagsno
days_since_latest_release287
mean_days_between_releases98.1

Community & Adoption

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

68Good · 17% of overall
How it's scored
40.7/60Stars324 stars
14.3/25Forks53 forks
6/15Watchers13 watchers
Inputs used
forks53
stars324
watchers13
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (BSD-3-Clause)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateyes
How it's scored
52.4/80Monthly downloads8,442 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesfreud-analysis
dependents
ecosystemspypi
total_downloads
monthly_downloads8,442
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?

85Excellent · 23% of overall
How it's scored
36/54Bus factor3 contributor(s) cover half of all commits
17.1/22.5Commit distributiontop contributor authored 24% of commits
13.5/13.5Contributor breadth52 contributors
10/10OpenSSF Scorecard: Contributorsproject has 16 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled52
top_contributor_share0.242
How it's scored
41/42Issue resolution98% of issues closed
28.2/30PR acceptance902/961 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
7.5/15OpenSSF Scorecard: Code-ReviewFound 1/2 approved changesets -- score normalized to 5
Inputs used
merged_prs902
open_issues11
closed_issues458
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.977
closed_unmerged_prs59
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
15/25Owner reach121 followers of glotzerlab
25/25Track record70 public repos, account ~9 yr old
Inputs used
followers121
owner_typeOrganization
is_verified
owner_loginglotzerlab
public_repos70
account_age_days3,442
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 287 days ago
20/20Version history36 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesfreud-analysis
ecosystemspypi
any_deprecatedno
min_days_since_publish287

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall
How it's scored
24/24CI workflows4 workflow(s)
24/24Tests present
16/16Linter config.ruff.toml
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests21 out of 21 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://freud.readthedocs.io
10/10Repository description
10/10Topics11 topics
10/10Wiki
Inputs used
topicsmolecular-dynamics, analysis, scientific-computing, python, monte-carlo-simulation, data-analysis, spatial-analysis, particle-system, computational-chemistry, computational-physics, science
has_wikiyes
homepagehttps://freud.readthedocs.io
docs_sitehttps://freud.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

69Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
3/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests21 out of 21 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3.8/7.5Code-ReviewFound 1/2 approved changesets -- score normalized to 5
2.5/2.5Contributorsproject has 16 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
4.5/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate6.1

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages5
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:freud-analysis@3.5.0 runtime dependency closure — what installing the published package pulls in — 5 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.

59Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
10.8/40Legible commit history13 of 64 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.203
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapdoc/Makefile
22/22Automated tests
11/11Lint / format config.ruff.toml
11/11Static type checkingC++ (statically typed)
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance36 of the last 100 commits are automated dependency updates
9/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageyes
bootstrap_filesdoc/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.36
How it's scored
45/45Type-checkable codeC++ (statically typed)
54.8/55Manageable file sizes1/228 source files over 60KB
Inputs used
primary_languageC++
largest_source_bytes295,471
source_files_sampled228
oversized_source_files1

Key facts

324GitHub stars
52contributors
363commits, last 12 months
1days since last push
24releases
3bus factor
11open 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 ★ / 53 ⇿
0Stars
53Forks
24Releases

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.

01020304050605322019-072023-012026-07
Major 1Minor 16Patch 7

Each point covers 7 days.

OpenSSF Scorecard 6.1 / 10
6.1aggregate

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 · 2026-07-22 18:41 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests21 out of 21 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 1/2 approved changesets -- score normalized to 5
10Contributorsproject has 16 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
9Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
0SASTSAST tool is not run on all commits -- score normalized to 0
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
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPInumpy>=1.19pyproject.toml
PyPIrowan>=1.2.1pyproject.toml
PyPIscipy>=1.1pyproject.toml
PyPIparsnip-cif>=0.2.0pyproject.toml
All dependencies 4

Full resolved dependency set from the GitHub dependency graph: 4 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpydirect
PyPIparsnip-cifdirect
PyPIrowandirect
PyPIscipydirect
Dependency advisories 0

Installing pypi:freud-analysis@3.5.0 pulls in 5 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 v0.26.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.