Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-05 14:28 UTC

yu-iskw / dbt-artifacts-parser

A dbt artifacts parser in python

PythonApache-2.0★ 116 stars⑂ 26 forkssince Mar 2022View on GitHub ↗

#dbt #python #dbt-artifacts #parser #python-package #pypi-package

yu-iskw/dbt-artifacts-parser holds a health index of 86 out of 100, placing it in the Excellent band. It scores highest on AI Readiness (88/100) and lowest on Sustainability & Governance (60/100). It was last updated 2 days ago. A single contributor accounts for most of its recent work.

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.

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)

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 72 is calibrated to 86 on the published index scale (record calibration 2026-08-02).

Ownership

Yu IshikawaPersonal account

298 followers331 public repossince Mar 2012

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

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish
PyPI	dbt-artifacts-parser	0.15.0	265,422	32	26 days ago

Metrics by category

Vitality

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

85Excellent · 21% of overall

Development activity

80Excellent

How it's scored

36/36	Push recency — last push 2 days ago
17.3/36	Commit cadence — 25/52 weeks with commits
16.6/18	Commit volume — 69 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 11 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	69
human_commit_share	0.56
days_since_last_push	2
active_weeks_last_year	25

Release discipline

92Excellent

How it's scored

27/27	Ships releases — 31 releases published
36/36	Release recency — latest release 26 days ago
19.8/27	Release cadence — a release every ~48.1 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	31
latest_release_tag	v0.15.0
releases_from_tags	no
days_since_latest_release	26
mean_days_between_releases	48.1

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?

65Good · 17% of overall

Popularity & adoption

45Weak

How it's scored

33.4/60	Stars — 116 stars
11.7/25	Forks — 26 forks
0/15	Watchers — 1 watchers

Inputs used

forks	26
stars	116
watchers	1
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

70Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (Apache-2.0)
18/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
0/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	3
has_contributing	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	github.com, shields.io
has_pull_request_template	no

Ecosystem adoption (downloads)

90Excellent

How it's scored

72.3/80	Monthly downloads — 265,422 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	dbt-artifacts-parser
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	265,422
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?

60Moderate · 23% of overall

Maintainer resilience (bus factor)

25At Risk

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
2.6/22.5	Commit distribution — top contributor authored 88% of commits
13.5/13.5	Contributor breadth — 14 contributors
0/10	OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0

Inputs used

bus_factor	1
contributors_sampled	14
top_contributor_share	0.885

Issue & PR responsiveness

62Moderate

How it's scored

32/42	Issue resolution — 76% of issues closed
22/30	PR acceptance — 183/249 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15	OpenSSF Scorecard: Code-Review — Found 1/20 approved changesets -- score normalized to 0

Inputs used

merged_prs	183
open_issues	5
closed_issues	16
prs_merged_7d	2
prs_decided_7d	2
prs_merged_30d	4
prs_decided_30d	5
issue_closed_ratio	0.762
closed_unmerged_prs	66
first_time_authors_30d	0
first_time_prs_merged_30d	0
first_time_prs_decided_30d	0

Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

66Good

How it's scored

10/30	Ownership backing — personal (user) account
0/20	Verified domain — not applicable to user accounts
17.8/25	Owner reach — 298 followers of yu-iskw
25/25	Track record — 331 public repos, account ~14 yr old

Inputs used

followers	298
owner_type	User
is_verified	—
owner_login	yu-iskw
public_repos	331
account_age_days	5,291

Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 26 days ago
20/20	Version history — 32 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	dbt-artifacts-parser
ecosystems	pypi
any_deprecated	no
min_days_since_publish	26

Engineering Quality

Are baseline engineering and documentation practices in place?

85Excellent · 19% of overall

Engineering practices

92Excellent

How it's scored

24/24	CI workflows — 5 workflow(s)
24/24	Tests present
16/16	Linter config — .pylintrc, pyproject.toml ([tool.ruff])
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
18/20	OpenSSF Scorecard: CI-Tests — 29 out of 30 merged PRs checked by a CI test -- score normalized to 9

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

75Good

How it's scored

30/30	README
0/25	Documentation directory
15/15	Documentation / homepage site — https://pypi.org/project/dbt-artifacts-parser/
10/10	Repository description
10/10	Topics — 6 topics
10/10	Wiki

Inputs used

topics	dbt, python, dbt-artifacts, parser, python-package, pypi-package
has_wiki	yes
homepage	https://pypi.org/project/dbt-artifacts-parser/
docs_site	https://pypi.org/project/dbt-artifacts-parser/
has_readme	yes
has_docs_dir	no
has_description	yes

Security

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

63Moderate · 16% of overall

Security posture

54Moderate

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — no data
2.2/2.5	CI-Tests — 29 out of 30 merged PRs checked by a CI test -- score normalized to 9
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5	Code-Review — Found 1/20 approved changesets -- score normalized to 0
0/2.5	Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5	Dependency-Update-Tool — update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 11 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
0/5	Packaging — no data
1/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5	Vulnerabilities — 0 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	15
scorecard_version	v5.5.0
checks_inconclusive	3
scorecard_aggregate	5.4

Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	5
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:dbt-artifacts-parser@0.15.0 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.

88Excellent · 4% of overall

Agent context & guidance

85Excellent

How it's scored

45/45	Agent instructions — AGENTS.md, CLAUDE.md
0/15	Machine-readable docs (llms.txt)
40/40	Legible commit history — 55 of 56 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.982
agent_instruction_files	AGENTS.md, CLAUDE.md
agent_instruction_max_bytes	2,620

Verify loop (build / test / typecheck)

92Excellent

How it's scored

18/18	One-command bootstrap — Makefile
22/22	Automated tests
11/11	Lint / format config — .pylintrc, pyproject.toml ([tool.ruff])
11/11	Static type checking — dbt_artifacts_parser/py.typed
10/10	Reproducible environment — lockfile
10/10	Demonstrated agent practice — 7 of the last 100 commits agent-authored or agent-credited
8/8	Automated maintenance — 37 of the last 100 commits are automated dependency updates
2/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2

Inputs used

has_nix	no
has_tests	yes
lockfiles	uv.lock
has_dockerfile	no
typed_language	no
bootstrap_files	Makefile
has_devcontainer	no
has_linter_config	yes
typecheck_configs	dbt_artifacts_parser/py.typed
agent_commit_share	0.07
toolchain_manifests	—
dependency_bot_commit_share	0.37

Code legibility for models

81Excellent

How it's scored

27/45	Type-checkable code — Python with type-check config (dbt_artifacts_parser/py.typed)
53.6/55	Manageable file sizes — 1/39 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	195,127
source_files_sampled	39
oversized_source_files	1

Key facts

116GitHub stars

14contributors

69commits, last 12 months

2days since last push

31releases

1bus factor

5open 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 ★ / 26 ⇿

0Stars

26Forks

26Releases

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.

Major 0Minor 11Patch 13

Each point covers 4 days.

OpenSSF Scorecard 5.4 / 10

5.4aggregate

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 · 2026-09-05 14:27 UTC

10	Binary-Artifacts	no binaries found in the repo
n/a	Branch-Protection	internal 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
9	CI-Tests	29 out of 30 merged PRs checked by a CI test -- score normalized to 9
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
0	Code-Review	Found 1/20 approved changesets -- score normalized to 0
0	Contributors	project has 0 contributing companies or organizations -- score normalized to 0
10	Dangerous-Workflow	no dangerous workflow patterns detected
10	Dependency-Update-Tool	update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	11 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
n/a	Packaging	packaging workflow not detected
2	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 2
0	SAST	SAST tool is not run on all commits -- score normalized to 0
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
10	Vulnerabilities	0 existing vulnerabilities detected

Direct dependencies 1

Registry	Package	Version constraint	Manifest
PyPI	pydantic	`>=2.12,<3.0`	pyproject.toml

All dependencies 54

Full resolved dependency set from the GitHub dependency graph: 1 direct and 53 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	pydantic	`2.13.4`	direct
PyPI	annotated-types	`0.7.0`	indirect
PyPI	argcomplete	`3.6.3`	indirect
PyPI	ast-serialize	`0.8.0`	indirect
PyPI	astroid	`4.0.4`	indirect
PyPI	black	`26.3.1`	indirect
PyPI	build	`1.5.0`	indirect
PyPI	cfgv	`3.5.0`	indirect
PyPI	click	`8.3.3`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	datamodel-code-generator	`0.72.2`	indirect
PyPI	dill	`0.4.1`	indirect
PyPI	distlib	`0.4.0`	indirect
PyPI	exceptiongroup	`1.3.1`	indirect
PyPI	filelock	`3.29.0`	indirect
PyPI	genson	`1.3.0`	indirect
PyPI	identify	`2.6.19`	indirect
PyPI	importlib-metadata	`9.0.0`	indirect
PyPI	inflect	`7.5.0`	indirect
PyPI	iniconfig	`2.3.0`	indirect
PyPI	isort	`8.0.1`	indirect
PyPI	jinja2	`3.1.6`	indirect
PyPI	librt	`0.15.0`	indirect
PyPI	mako	`1.3.12`	indirect
PyPI	markdown	`3.10.2`	indirect
PyPI	markupsafe	`3.0.3`	indirect
PyPI	mccabe	`0.7.0`	indirect
PyPI	more-itertools	`11.0.2`	indirect
PyPI	mypy	`2.3.1`	indirect
PyPI	mypy-extensions	`1.1.0`	indirect
PyPI	nodeenv	`1.10.0`	indirect
PyPI	packaging	`26.2`	indirect
PyPI	pathspec	`1.1.1`	indirect
PyPI	pdoc3	`0.11.6`	indirect
PyPI	platformdirs	`4.9.6`	indirect
PyPI	pluggy	`1.6.0`	indirect
PyPI	pre-commit	`4.6.0`	indirect
PyPI	pydantic-core	`2.46.4`	indirect
PyPI	pygments	`2.20.0`	indirect
PyPI	pylint	`4.0.5`	indirect
PyPI	pyproject-hooks	`1.2.0`	indirect
PyPI	pytest	`9.0.3`	indirect
PyPI	python-discovery	`1.3.0`	indirect
PyPI	pytokens	`0.4.1`	indirect
PyPI	pyyaml	`6.0.3`	indirect
PyPI	ruff	`0.16.4`	indirect
PyPI	tomli	`2.4.1`	indirect
PyPI	tomlkit	`0.14.0`	indirect
PyPI	typeguard	`4.5.1`	indirect
PyPI	typing-extensions	`4.15.0`	indirect
PyPI	typing-inspection	`0.4.2`	indirect
PyPI	uv	`—`	indirect
PyPI	virtualenv	`21.3.1`	indirect
PyPI	zipp	`3.23.1`	indirect

Dependency advisories 0

Installing pypi:dbt-artifacts-parser@0.15.0 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.

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.

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

More detail

Feedback

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