Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 03:54 UTC

astronomer / dag-factory

Construct Apache Airflow DAGs Declaratively via YAML configuration files

PythonApache-2.0★ 1,451 stars⑂ 238 forkssince Nov 2018View on GitHub ↗
KindCommand-line toolPluginLibraryhow this is determined

astronomer/dag-factory holds a health index of 97 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (96/100) and lowest on Community & Adoption (65/100). It was last updated today. 2 contributors account for most of its recent work.

97
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.

97
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 85 is calibrated to 97 on the published index scale (record calibration 2026-08-02).

Ownership

AstronomerOrganization
805 followers352 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-factory1.1.0-6697 days agoairflowapache-airflowastronomerdagprovider

Metrics by category

Vitality

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

91Excellent · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
27/36Commit cadence39/52 weeks with commits
18/18Commit volume216 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 13 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year216
human_commit_share0.25
days_since_last_push0
active_weeks_last_year39
How it's scored
27/27Ships releases28 releases published
27/36Release recencylatest release 97 days ago
27/27Release cadencea release every ~33 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count28
latest_release_tagv1.1.0
releases_from_tagsno
days_since_latest_release97
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?

65Good · 17% of overall
How it's scored
51.3/60Stars1,451 stars
19.8/25Forks238 forks
7/15Watchers19 watchers
Inputs used
forks238
stars1,451
watchers19
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized 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

Sustainability & Governance

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

85Excellent · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
16.1/22.5Commit distributiontop contributor authored 28% of commits
13.5/13.5Contributor breadth51 contributors
10/10OpenSSF Scorecard: Contributorsproject has 7 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled51
top_contributor_share0.284
How it's scored
33.3/42Issue resolution79% of issues closed
25.6/30PR acceptance498/584 decided PRs merged
13/13Newcomer PR acceptance1/1 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs498
open_issues57
closed_issues219
prs_merged_7d0
prs_decided_7d0
prs_merged_30d4
prs_decided_30d4
issue_closed_ratio0.793
closed_unmerged_prs86
first_time_authors_30d1
first_time_prs_merged_30d1
first_time_prs_decided_30d1
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
20.9/25Owner reach805 followers of astronomer
25/25Track record352 public repos, account ~11 yr old
Inputs used
followers805
owner_typeOrganization
is_verified
owner_loginastronomer
public_repos352
account_age_days4,108
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 97 days ago
20/20Version history66 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesdag-factory
ecosystemspypi
any_deprecatedno
min_days_since_publish97

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall
How it's scored
24/24CI workflows4 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests30 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 sitehttps://astronomer.github.io/dag-factory/latest/
10/10Repository description
10/10Topics4 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-Artifactsno binaries found in the repo
0.8/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests30 out of 30 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
7.5/7.5Code-Reviewall changesets reviewed
2.5/2.5Contributorsproject has 7 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 13 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
4/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 8
5/5SASTSAST tool is run on all commits
5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
6.8/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 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 advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages128
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 — 128 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
How it's scored
45/45Agent instructionsAGENTS.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history25 of 25 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
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environmentDockerfile
10/10Demonstrated agent practice25 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance75 of the last 100 commits are automated dependency updates
8/10OpenSSF Scorecard: Pinned-Dependenciesdependency 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_share0.25
toolchain_manifests
dependency_bot_commit_share0.75
How it's scored
0/45Type-checkable codePython without a type-check config
54.1/55Manageable file sizes1/59 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes71,234
source_files_sampled59
oversized_source_files1
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples
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

1,451GitHub stars
51contributors
216commits, last 12 months
0days since last push
28releases
2bus factor
57open 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 ★ / 238 ⇿
0Stars
238Forks
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.

0408012016020024023342018-112022-092026-07
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 · 2026-08-13 03:54 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 13 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
PyPIpathspecpyproject.toml
PyPIpyyamlpyproject.toml
PyPIpackagingpyproject.toml
PyPItyperpyproject.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
PyPIapache-airflowdirect
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PyPIpackagingdirect
PyPIpackaging26.2direct
PyPIpathspecdirect
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PyPIpyyamldirect
PyPIpyyaml6.0.3direct
PyPItyperdirect
PyPItyper0.26.7direct
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PyPIaiofiles24.1.0indirect
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Dependency advisories 0

Installing pypi:dag-factory@1.1.0 pulls in 128 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.

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.