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dag-factory

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Declare Airflow DAGs from YAML, fast.

Software Engineering#yaml#configuration management#apache airflow#dynamic task mapping#dataset scheduling#declarative automation#dag generation
Authorminyeamer
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Builds and maintains Apache Airflow DAGs without hand-coding repetitive Python by letting you define workflows declaratively in YAML.

Core Features & Use Cases

  • Declarative YAML → Airflow DAGs: Generate DAGs from YAML configuration with a consistent, low-code structure.
  • Reusable defaults & configuration layering: Share common DAG settings via a top-level default block or merged defaults.yml files.
  • Production-ready configuration patterns: Support dynamic task mapping, dataset-based scheduling, custom typed objects using type, callbacks, and DAG topology wiring via dependencies.

Quick Start

Use the dag-factory skill to generate an Airflow DAG from your YAML by installing dag-factory, adding load_yaml_dags in your Airflow loader file, and then creating a DAG YAML under your configured dags folder.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: dag-factory
Download link: https://github.com/minyeamer/linkmerce/archive/main.zip#dag-factory

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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