Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-08 19:06 UTC

rnag / dataclass-wizard

Simple, elegant, wizarding tools for interacting with Python's dataclasses.

PythonCustom license★ 247 stars⑂ 35 forkssince Aug 2021View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

rnag/dataclass-wizard holds a health index of 80 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (100/100) and lowest on AI Readiness (50/100). It was last updated 7 days ago. A single contributor accounts for most of its recent work.

80
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.

80
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 68 is calibrated to 80 on the published index scale (record calibration 2026-08-02).

Ownership

Ritvik NagPersonal account
30 followers68 public repossince Sep 2015

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

Metrics by category

Vitality

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

69Good · 21% of overall
How it's scored
36/36Push recencylast push 7 days ago
4.2/36Commit cadence6/52 weeks with commits
16/18Commit volume59 commits in the last year
1/10OpenSSF Scorecard: Maintained2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
Inputs used
commits_last_year59
human_commit_share1
days_since_last_push7
active_weeks_last_year6
How it's scored
16.2/27Ships releases85 version tags (no GitHub releases)
36/36Release recencylatest release 36 days ago
27/27Release cadencea release every ~21.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count85
latest_release_tagv1.0.0
releases_from_tagsyes
days_since_latest_release36
mean_days_between_releases21.8
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?

61Moderate · 17% of overall
How it's scored
38.8/60Stars247 stars
12.8/25Forks35 forks
0/15Watchers1 watchers
Inputs used
forks35
stars247
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
18/18CONTRIBUTING guide
0/13.5Code of conduct
7.2/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingyes
has_issue_templateyes
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

58Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
7.2/22.5Commit distributiontop contributor authored 68% of commits
13.5/13.5Contributor breadth17 contributors
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled17
top_contributor_share0.68
How it's scored
26.1/42Issue resolution62% of issues closed
19.1/30PR acceptance95/149 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 2/30 approved changesets -- score normalized to 0
Inputs used
merged_prs95
open_issues34
closed_issues56
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d1
issue_closed_ratio0.622
closed_unmerged_prs54
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
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
10.7/25Owner reach30 followers of rnag
25/25Track record68 public repos, account ~10 yr old
Inputs used
followers30
owner_typeUser
is_verified
owner_loginrnag
public_repos68
account_age_days3,987
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 36 days ago
20/20Version history85 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesdataclass-wizard
ecosystemspypi
any_deprecatedno
min_days_since_publish36

Engineering Quality

Are baseline engineering and documentation practices in place?

100Exceptional · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://dcw.ritviknag.com
10/10Repository description
10/10Topics11 topics
10/10Wiki
Inputs used
topicsdataclasses-json, dataclass, dataclasses, deserialization, python3, json-api, for-humans, python, json, serialization, python-dataclasses
has_wikiyes
homepagehttps://dcw.ritviknag.com
docs_sitehttps://dcw.ritviknag.com
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

52Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
2.2/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests12 out of 12 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
0/7.5Code-ReviewFound 2/30 approved changesets -- score normalized to 0
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.2/2.5Licenselicense file detected
0.8/7.5Maintained2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
5/5Packagingpackaging workflow detected
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories4
affected_packages2
assessed_packages19
unassessed_packages12
affected_by_severityhigh 1, moderate 1
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 19 resolved dependencies against OSV. 12 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.

50Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
19.2/40Legible commit history36 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.36
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile, docs/Makefile
22/22Automated tests
11/11Lint / format config
11/11Static type checkingdataclass_wizard/py.typed, dataclass_wizard/v0/py.typed
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configsdataclass_wizard/py.typed, dataclass_wizard/v0/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
How it's scored
27/45Type-checkable codePython with type-check config (dataclass_wizard/py.typed, dataclass_wizard/v0/py.typed)
53.5/55Manageable file sizes4/148 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes97,691
source_files_sampled148
oversized_source_files4

Key facts

247GitHub stars
17contributors
59commits, last 12 months
7days since last push
85releases
1bus factor
34open 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 ★ / 35 ⇿
0Stars
35Forks
40Releases

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.

01325383422022-072024-072026-07
Major 1Minor 17Patch 22

Each point covers 4 days.

OpenSSF Scorecard 4.0 / 10
4.0aggregate

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 · 2026-08-08 19:06 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 2/30 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
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
10Packagingpackaging workflow 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
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPItyping-extensions>=4.13.0pyproject.toml
All dependencies 31

Full resolved dependency set from the GitHub dependency graph: 1 direct and 30 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPItyping-extensionsdirect
PyPIattrs25.4.0indirect
PyPIbump-my-version1.2.5indirect
PyPIcoverageindirect
PyPIdacite1.9.2indirect
PyPIdataclass-factory2.16indirect
PyPIdataclasses-json0.6.7indirect
PyPIflake8indirect
PyPIjsons1.6.3indirect
PyPImashumaro3.17indirect
PyPImypyindirect
PyPIpipindirect
PyPIpydantic2.12.5indirect
PyPIpytest8.3.4indirect
PyPIpytest-cov6.0.0indirect
PyPIpytest-mockindirect
PyPIpython-dotenvindirect
PyPIpytimeparse1.1.8indirect
PyPIpyyamlindirect
PyPIsetuptoolsindirect
PyPIsphinx7.4.7indirect
PyPIsphinx-autodoc-typehints2.5.0indirect
PyPIsphinx-copybutton0.5.2indirect
PyPIsphinx-issues5.0.0indirect
PyPItomliindirect
PyPItomli-windirect
PyPItox4.23.2indirect
PyPItwine6.0.1indirect
PyPItzdataindirect
PyPIwatchdog6.0.0indirect
PyPIwheel0.45.1indirect
Dependency advisories 2

This repository publishes no package the index resolves, so its own dependency graph was assessed — 19 packages, which also include development and test pins that never ship: 2 carry known advisories, of which 0 are direct. 12 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
wheel0.45.1indirecthigh20.46.2
pytest8.3.4indirectmoderate29.0.3

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 v0.31.0 — full methodology · metrics wiki.

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