Airflow DAG Generator

Generate Airflow DAG Python files directly from VS Code using an intuitive GUI. Supports multiple operators, inline code, and file-based inputs.

Features

Add tasks dynamically and configure multiple operators:
- BigQueryOperator: Inline SQL or external SQL file.
- BashOperator: Inline command or script file.
- GCSToGCSOperator: Transfer objects between GCS buckets.
- GCSToBigQueryOperator: Load GCS data to BigQuery.
- PythonOperator: Run Python functions.
- BranchPythonOperator: Conditional branching tasks.
- DagRunOperator: Trigger another DAG.
- EmailOperator: Send emails from the DAG.
- DataflowPythonOperator: Run Google Cloud Dataflow Python pipelines.
Supports downstream dependencies automatically for tasks in order.
Generates well-formatted DAG Python files with dag=dag included in all operators.

For example if there is an image subfolder under your extension project workspace:

![feature X](images/feature-x.png)

If you have any requirements or dependencies, add a section describing those and how to install and configure them.

Include if your extension adds any VS Code settings through the contributes.configuration extension point.

For example:

This extension contributes the following settings:

Calling out known issues can help limit users opening duplicate issues against your extension.

Users appreciate release notes as you update your extension.

Initial release of ...

Fixed issue #.

Added features X, Y, and Z.

You can author your README using Visual Studio Code. Here are some useful editor keyboard shortcuts:

Enjoy!