10x Airflow DAGs development with Cursor AI
In this video, you will learn:
✅ What is Cursor AI and why it is important for you
✅ Configuring Cursor AI for developing Airflow DAGs and Tasks
✅ Creating Project Rules for your LLM to follow Airflow best practices
✅ Fetching online documentation to get up to date information with Airflow
✅ Creating a data pipeline from scratch with Cursor Composer (AI Agent)
✅ Generating unit tests for your tasks
✅ Indexing your codebase to ask questions about your DAGs and Tasks with the chat
and more!
📖 Chapters
00: 00 Introduction & Welcome
01: 15 What is Cursor – AI Code Editor Overview
02: 59 Setting Up a Python Project with uv
04: 37 Configuring Cursor for Airflow
05: 31 Define AI Rules
07: 05 The three files to have for every Cursor project
08: 21 Project rules for Cursor and Apache Airflow
12: 51 Set up you Airflow local environment with the Astro CLI
14: 37 Code Base Indexing
14: 51 Using Chat & Documentation Features
16: 00 Adding online documentation to Cursor
18: 05 Creating Data Pipeline with AI Agent
24: 14 Adding Tasks & Unit Tests
27: 20 Conclusion & Wrap-up
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