Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-19 12:42 UTC

DC-analysis / dclab

Python library for the post-measurement analysis of deformability cytometry (DC) data sets

PythonCustom license★ 12 stars⑂ 14 forkssince Jun 2015View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

DC-analysis/dclab holds a health index of 75 out of 100, placing it in the Good band. It scores highest on Engineering Quality (86/100) and lowest on Community & Adoption (44/100). It was last updated today. A single contributor accounts for most of its recent work.

75
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.

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

Ownership

5 followers10 public repossince Jan 2022

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdclab0.73.416,3183310 days agort-dcdeformabilitycytometry

Metrics by category

Vitality

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

83Excellent · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
15.9/36Commit cadence — 23/52 weeks with commits
18/18Commit volume — 144 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year144
human_commit_share1
days_since_last_push0
active_weeks_last_year23
How it's scored
16.2/27Ships releases — 100 version tags (no GitHub releases)
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~21.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tag0.73.4
releases_from_tagsyes
days_since_latest_release0
mean_days_between_releases21.4
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?

44Weak · 17% of overall
How it's scored
16.9/60Stars — 12 stars
9.3/25Forks — 14 forks
2.7/15Watchers — 4 watchers
Inputs used
forks14
stars12
watchers4
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
56.2/80Monthly downloads — 16,318 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdclab
dependents—
ecosystemspypi
total_downloads—
monthly_downloads16,318
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?

62Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.8/22.5Commit distribution — top contributor authored 96% of commits
13.5/13.5Contributor breadth — 12 contributors
10/10OpenSSF Scorecard: Contributors — project has 14 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled12
top_contributor_share0.964
How it's scored
35.7/42Issue resolution — 85% of issues closed
26/30PR acceptance — 58/67 decided PRs merged
11.1/13Newcomer PR acceptance — 6/7 first-time contributors' PRs merged in 30d
3/15OpenSSF Scorecard: Code-Review — Found 6/29 approved changesets -- score normalized to 2
Inputs used
merged_prs58
open_issues34
closed_issues191
prs_merged_7d0
prs_decided_7d0
prs_merged_30d6
prs_decided_30d7
issue_closed_ratio0.849
closed_unmerged_prs9
first_time_authors_30d1
first_time_prs_merged_30d6
first_time_prs_decided_30d7
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
5.6/25Owner reach — 5 followers of DC-analysis
17/25Track record — 10 public repos, account ~4 yr old
Inputs used
followers5
owner_typeOrganization
is_verifiedno
owner_loginDC-analysis
public_repos10
account_age_days1,725

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 331 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdclab
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 6 out of 6 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

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://dclab.readthedocs.io
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepagehttps://dclab.readthedocs.io
docs_sitehttps://dclab.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

47Weak · 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 — 6 out of 6 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
1.5/7.5Code-Review — Found 6/29 approved changesets -- score normalized to 2
2.5/2.5Contributors — project has 14 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
7.5/7.5Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
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
6/7.5Vulnerabilities — 2 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4.7
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. 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.

52Moderate · 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 — 94 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.94
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
0/10Reproducible environment
10/10Demonstrated agent practice — 6 of the last 100 commits agent-authored or agent-credited
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_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.06
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/234 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes48,994
source_files_sampled234
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

12GitHub stars
12contributors
144commits, last 12 months
0days since last push
100releases
1bus factor
34open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:dclab@0.73.4; advisories assessed against the repository dependency graph instead
  • No resolved dependencies carried a version and a supported ecosystem

More detail

Star and fork history 0 ★ / 14 ⇿
0Stars
14Forks
96Releases

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.

03581013151422021-022023-112026-09
Major 0Minor 18Patch 78

Each point covers 6 days.

OpenSSF Scorecard 4.7 / 10
4.7aggregate

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 · 2026-10-19 12:41 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-Tests6 out of 6 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 6/29 approved changesets -- score normalized to 2
10Contributorsproject has 14 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
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
8Vulnerabilities2 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPIh5py>=3.0.0, <4pyproject.toml
PyPIhdf5plugin>=3.3.1, <5pyproject.toml
PyPInumpy>=1.21, <3pyproject.toml
PyPIscipy>=1.10.0, !=1.18.0pyproject.toml
All dependencies 23

Full resolved dependency set from the GitHub dependency graph: 4 direct and 19 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIh5py—direct
PyPIhdf5plugin—direct
PyPInumpy—direct
PyPIscipy—direct
PyPIboto3—indirect
PyPIclick—indirect
PyPIdclab—indirect
PyPIfcswrite—indirect
PyPIimageio—indirect
PyPIipython—indirect
PyPIlmfit—indirect
PyPImatplotlib—indirect
PyPInptdms—indirect
PyPIopencv-contrib-python—indirect
PyPIpytest—indirect
PyPIrequests—indirect
PyPIscikit-image—indirect
PyPIseaborn—indirect
PyPIsetuptools—indirect
PyPIsetuptools-scm—indirect
PyPIsphinx—indirect
PyPIsphinx-rtd-theme—indirect
PyPIsphinxcontrib-bibtex—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 — PyPI.