Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 22:17 UTC

astronomer / dag-factory

Construct Apache Airflow DAGs Declaratively via YAML configuration files

PythonApache-2.0★ 1,458 stars⑂ 237 forkssince Nov 2018View on GitHub ↗
KindCommand-line toolPluginLibraryhow this is determined
#airflow#apache-airflow#python#dags

astronomer/dag-factory holds a health index of 98 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (96/100) and lowest on Community & Adoption (72/100). It was last updated today. 2 contributors account for most of its recent work.

98
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.

98
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 86 is calibrated to 98 on the published index scale (record calibration 2026-08-02).

Ownership

AstronomerOrganization · verified domain
817 followers358 public repossince May 2015

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdag-factory1.1.0442,89566133 days agoairflowapache-airflowastronomerdagprovider

Metrics by category

Vitality

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

91Excellent · 21% of overall

Development activity

91Excellent
How it's scored
36/36Push recency — last push 0 days ago
27/36Commit cadence — 39/52 weeks with commits
18/18Commit volume — 208 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year208
human_commit_share0.22
days_since_last_push0
active_weeks_last_year39

Release discipline

90Excellent
How it's scored
27/27Ships releases — 28 releases published
27/36Release recency — latest release 133 days ago
27/27Release cadence — a release every ~33 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count28
latest_release_tagv1.1.0
releases_from_tagsno
days_since_latest_release133
mean_days_between_releases33
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?

72Good · 17% of overall

Popularity & adoption

78Good
How it's scored
51.3/60Stars — 1,458 stars
19.8/25Forks — 237 forks
7/15Watchers — 19 watchers
Inputs used
forks237
stars1,458
watchers19
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

94Exceptional
How it's scored
75.3/80Monthly downloads — 442,895 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdag-factory
dependents—
ecosystemspypi
total_downloads—
monthly_downloads442,895
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?

84Excellent · 23% of overall

Maintainer resilience (bus factor)

65Good
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
16.2/22.5Commit distribution — top contributor authored 28% of commits
13.5/13.5Contributor breadth — 51 contributors
10/10OpenSSF Scorecard: Contributors — project has 7 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled51
top_contributor_share0.282

Issue & PR responsiveness

84Excellent
How it's scored
32.1/42Issue resolution — 76% of issues closed
25.6/30PR acceptance — 511/598 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs511
open_issues68
closed_issues220
prs_merged_7d2
prs_decided_7d2
prs_merged_30d2
prs_decided_30d2
issue_closed_ratio0.764
closed_unmerged_prs87
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.

Ownership & stewardship

96Exceptional
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
20.9/25Owner reach — 817 followers of astronomer
25/25Track record — 358 public repos, account ~11 yr old
Inputs used
followers817
owner_typeOrganization
is_verifiedyes
owner_loginastronomer
public_repos358
account_age_days4,144

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 133 days ago
20/20Version history — 66 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdag-factory
ecosystemspypi
any_deprecatedno
min_days_since_publish133

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff], [tool.black])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://astronomer.github.io/dag-factory/latest/
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicsairflow, apache-airflow, python, dags
has_wikiyes
homepagehttps://astronomer.github.io/dag-factory/latest/
docs_sitehttps://astronomer.github.io/dag-factory/latest/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

86Excellent · 16% of overall

Security posture

83Excellent
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 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
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 7 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
4/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 8
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
6.8/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate8.3
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages127
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:dag-factory@1.1.0 runtime dependency closure — what installing the published package pulls in — 127 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.

83Excellent · 4% of overall

Agent context & guidance

85Excellent
How it's scored
45/45Agent instructions — AGENTS.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 22 of 22 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_filesAGENTS.md
agent_instruction_max_bytes11,534

Verify loop (build / test / typecheck)

87Excellent
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff], [tool.black])
0/11Static type checking
10/10Reproducible environment — Dockerfile
10/10Demonstrated agent practice — 20 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 78 of the last 100 commits are automated dependency updates
8/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 8
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.2
toolchain_manifests—
dependency_bot_commit_share0.78

Code legibility for models

54Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
54.1/55Manageable file sizes — 1/60 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes71,234
source_files_sampled60
oversized_source_files1

Machine-readable interfaces

100Exceptional
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

1,458GitHub stars
51contributors
208commits, last 12 months
0days since last push
28releases
2bus factor
68open 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 ★ / 237 ⇿
0Stars
237Forks
28Releases

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.

0408012016020024023242018-112022-092026-07
Major 1Minor 5Patch 1

Each point covers 8 days.

OpenSSF Scorecard 8.3 / 10
8.3aggregate

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 · 2026-09-17 22:16 UTC

10Binary-Artifactsno binaries found in the repo
1Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 7 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
n/aPackagingpackaging workflow not detected
8Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 8
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIapache-airflow>=2.9pyproject.toml
PyPIpathspec—pyproject.toml
PyPIpyyaml—pyproject.toml
PyPIpackaging—pyproject.toml
PyPItyper—pyproject.toml
All dependencies 201

Full resolved dependency set from the GitHub dependency graph: 10 direct and 191 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPIapache-airflow3.2.2direct
PyPIpackaging—direct
PyPIpackaging26.2direct
PyPIpathspec—direct
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PyPIpyyaml—direct
PyPIpyyaml6.0.3direct
PyPItyper—direct
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PyPIaiofiles24.1.0indirect
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PyPIvirtualenv20.36.1indirect
PyPIwatchfiles1.1.1indirect
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Dependency advisories 0

Installing pypi:dag-factory@1.1.0 pulls in 127 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

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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.