I’m Alex, and I need a Python solution that pulls data from a social-media platform and then runs a full analytical pass on it. The aim is to move from raw posts, likes, comments, and timestamps to clear insights I can act on. Here is exactly what the script must cover: • User engagement • Sentiment analysis • Trend analysis The flow I picture is straightforward: a scraper (or API connector, if available) gathers the latest content, saves it locally in a clean format, and hands it straight to the analysis module. Using familiar libraries—think requests/BeautifulSoup or Selenium for collection, then pandas, scikit-learn, TextBlob (or similar) plus matplotlib/Seaborn for reporting—you will deliver reproducible code that I can run from the command line. Deliverables • Well-commented Python scripts for data collection and analysis • A concise README explaining setup, any required credentials, and the commands to generate results • Sample output files (CSV or JSON) and visual summaries so I can verify the three analytics above quickly I value clean structure and plain English comments over clever one-liners, and I’m happy to review incremental milestones so you’re never coding in the dark. Let’s turn social chatter into actionable numbers.