The Reddit Project (Data engineering project with Airflow, Slack, Snowflake and OpenAI)
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!
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👨💻 The Code: https://robust-dinosaur-2ef.notion.si...
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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