The Reddit Project (Data engineering project with Airflow, Slack, Snowflake and OpenAI)

Description

The Reddit Project (with Airflow, Slack, Snowflake, and OpenAI) Learn how we build and run a real-world data pipeline at Astronomer! In this deep-dive tutorial, we'll walk through creating a complete Airflow DAG that scrapes data from Reddit, processes it using a Large Language Model (LLM) for categorization, loads it into Snowflake, and sends notifications via Slack. This is more than just a theoretical example. Here's what you'll learn: ✅ Designing a complex data pipeline with multiple branches and tasks. ✅ Setting up Snowflake connections and creating tables using Airflow. ✅ Fetching data from the Reddit API. ✅ Using an LLM (like OpenAI or similar) directly within tasks. ✅ Implementing branching logic to skip tasks when no data is found. ✅ Filtering and transforming data. ✅ Sending automated Slack notifications upon pipeline completion. And more! Get ready to level up your Airflow skills with a practical project you can adapt for your own use cases! 🤖 Try the Astro IDE: http://astronomer.io/ide/marc 🏆 BECOME A PRO: https://www.udemy.com/course/the-ultimate-hands-on-course-to-master-apache-airflow/?referralCode=1A510C39C666078F07F4 👍 Smash the like button to become an Airflow Super Hero! ❤️ Subscribe to my channel to become a master of Airflow 00:00:00 Introduction & Project Goal 00:00:28 Airflow Data Pipeline Overview 00:01:34 Slack Notification Example 00:02:44 Starting the Project: Local vs. Astro IDE 00:03:26 Step 1: Create Airflow Project 00:05:09 Step 2: Install Python Dependencies 00:06:02 Step 3: Create Reddit API Connection 00:07:52 Step 4: Create the Airflow DAG 00:09:07 Task 1: Create Snowflake Table 00:13:00 Testing the First Task 00:14:31 Task 2: Fetch Reddit Posts 00:17:39 Task 3: Check for Posts (Branching) 00:18:47 Task 4: Categorize Posts with LLM 00:22:24 Define Task Dependencies 00:26:45 Task 5: Filter DevRel Posts 00:28:13 Task 6: Send Slack Notifications 00:30:27 Conclusion