Build a Bluesky Analytics Dashboard with Python (Step-by-Step)

Bluesky just crossed 30 million users, and the best part? Its AT Protocol makes all public data freely accessible — no API keys, no rate limit headaches, no $42K/month Twitter API bills. In this tutorial, you'll build a Python dashboard that scrapes Bluesky posts, analyzes engagement patterns, and outputs actionable insights. Whether you're doing brand monitoring, competitor research, or tracking trending topics — this gets you from zero to working analytics in about 30 minutes. What We're Building A Python script that: Scrapes Bluesky posts matching your search terms Processes the data into a structured format Generates engagement analytics (top posts, posting times, hashtag frequency) Outputs a clean CSV report you can open in any spreadsheet tool Prerequisites Python 3.8+ An Apify free account (no credit card needed) 10 minutes of patience pip install apify-client pandas matplotlib Step 1: Set Up the Bluesky Scraper We'll use the Bluesky Posts Scraper on Apify, which handles all the