Airflow: Automate Workflows
Airflow: Automate Workflows lets you create a schedule for tasks and jobs with code.
"A solo developer uses Airflow to automate a daily report on website traffic. She sets up a DAG, creates a schedule for the task to run every morning, and configures a connection to Google Analytics. Once done, the report will be sent to her email every morning at 8 am."
- •When you need to manage complex data workflows across multiple systems and teams
- •To automate and schedule recurring data tasks, such as data ingestion and processing
- •For building and managing machine learning pipelines that require data preparation, training, and deployment
Run a sample DAG with `airflow trigger_dag example_bash_operator` to see how Airflow can execute a series of bash commands
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/airflow && curl -fsSL https://workflowstacks.com/api/skills/airflow/claude-skill -o ~/.claude/skills/airflow/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Airflow: Automate Workflows is a very large Python project (~945k lines across 5104 code files, plus 4034 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit this month, Apache-2.0 license, has a test suite.
- 1README.mdStart here — what it does and how to install it
- 2AGENTS.mdThe instructions the AI actually follows
- 3pyproject.tomlDependencies and the commands it exposes
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/airflow && curl -fsSL https://workflowstacks.com/api/skills/airflow/claude-skill -o ~/.claude/skills/airflow/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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