Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-13 11:19 UTC

NIRALUser / DTIPlayground

An integrated framework for DWI Image QC and processing

PythonMIT★ 13 stars⑂ 2 forkssince Aug 2021View on GitHub ↗

NIRALUser/DTIPlayground holds a health index of 59 out of 100, placing it in the Moderate band. It scores highest on Vitality (74/100) and lowest on Security (21/100). It was last updated today. A single contributor accounts for most of its recent work.

59
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.

59
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 56 is calibrated to 59 on the published index scale (record calibration 2026-08-02).

Ownership

niralUserOrganization
22 followers78 public repossince Sep 2012

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdtiplayground0.8.42,7961540 days agodtiplaygrounddmriprepdmriatlasdmriautotractdmrifiberprofilenrrdniftidwidtiqcquality-control

Metrics by category

Vitality

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

74Good · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
4.2/36Commit cadence — 6/52 weeks with commits
18/18Commit volume — 104 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year104
human_commit_share1
days_since_last_push0
active_weeks_last_year6
How it's scored
16.2/27Ships releases — 56 version tags (no GitHub releases)
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~2.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count56
latest_release_tagv0.8.4
releases_from_tagsyes
days_since_latest_release0
mean_days_between_releases2.2

Community & Adoption

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

40Weak · 17% of overall
How it's scored
17.5/60Stars — 13 stars
0/25Forks — 2 forks
2.7/15Watchers — 4 watchers
Inputs used
forks2
stars13
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
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
46/80Monthly downloads — 2,796 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdtiplayground
dependents—
ecosystemspypi
total_downloads—
monthly_downloads2,796
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
10.3/22.5Commit distribution — top contributor authored 54% of commits
8.1/13.5Contributor breadth — 6 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled6
top_contributor_share0.544
How it's scored
38.9/42Issue resolution — 93% of issues closed
25.3/30PR acceptance — 38/45 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs38
open_issues2
closed_issues25
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.926
closed_unmerged_prs7
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
9.8/25Owner reach — 22 followers of NIRALUser
25/25Track record — 78 public repos, account ~14 yr old
Inputs used
followers22
owner_typeOrganization
is_verifiedno
owner_loginNIRALUser
public_repos78
account_age_days5,137

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 — 154 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdtiplayground
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

66Good · 19% of overall
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno
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?

21At Risk · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestsdocs/requirements.txt, requirements-headless.txt, requirements.txt, setup.cfg, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages7
unassessed_packages31
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 7 resolved dependencies against OSV. 31 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

62Moderate · 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 — 98 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.98
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — Dockerfile
10/10Demonstrated agent practice — 98 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0.98
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
53/55Manageable file sizes — 5/136 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes97,554
source_files_sampled136
oversized_source_files5
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

13GitHub stars
6contributors
104commits, last 12 months
0days since last push
56releases
1bus factor
2open 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:dtiplayground@0.8.4; advisories assessed against the repository dependency graph instead
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit; 2026/10/13 11:16:51 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 2 ⇿
0Stars
2Forks
3Releases

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.

111222212022-092023-042023-11
Major 0Minor 1Patch 2

Each point covers 2 days.

All dependencies 38

Full resolved dependency set from the GitHub dependency graph: 0 direct and 38 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIantspynet—indirect
PyPIantspyx—indirect
PyPIcmake—indirect
PyPIdipy—indirect
PyPIdipy1.9.0indirect
PyPIdmri-amico—indirect
PyPIflask—indirect
PyPIflask-cors—indirect
PyPIflask-jwt-extended—indirect
PyPIfury—indirect
PyPIfury0.10.0indirect
PyPImarkdown—indirect
PyPImatplotlib—indirect
PyPInibabel—indirect
PyPInibabel5.2.1indirect
PyPInumpy—indirect
PyPInumpy1.26.4indirect
PyPIopencv-python—indirect
PyPIopencv-python-headless—indirect
PyPIpandas—indirect
PyPIpandas2.2.2indirect
PyPIpynrrd—indirect
PyPIpynrrd1.0.0indirect
PyPIpypdf2—indirect
PyPIpyyaml—indirect
PyPIreportlab—indirect
PyPIscikit-image—indirect
PyPIscikit-learn—indirect
PyPIscipy—indirect
PyPIsimpleitk—indirect
PyPIsphinx—indirect
PyPIsphinx-rtd-theme—indirect
PyPIsphinx-rtd-theme2.0.0indirect
PyPItensorflow—indirect
PyPItorch—indirect
PyPIvtk—indirect
PyPIwheel—indirect
PyPIxhtml2pdf—indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 7 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 31 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

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.