Challenge

This project began out of genuine frustration. I was eagerly anticipating a New York Jets vs. Denver Broncos game that had been hyped as one of the most exciting matchups of the day, only to sit through a rain-soaked mess that ended with zero touchdowns and what felt like one of the most boring games ever televised. That experience made me realize just how much weather can affect not only the outcome of a game, but also the viewing experience. So, I built a weather bot.

The bot automatically pulls weather forecasts for every upcoming NFL game each week, focusing on metrics like temperature, wind, and precipitation. I designed a Python-based pipeline that scrapes matchup schedules, maps them to game times and locations, and queries a weather API to get forecast data, which is then posted via a Twitter bot using AWS Lambda. I had to learn how to handle deployment in the cloud using cron expressions and Dockerized dependencies for the Python 3.12 ARM runtime, accounting for compatibility issues with packages like pandas and numpy. While it started as a fun way to avoid another disappointing Sunday, the project became a valuable lesson in automation, cloud architecture, and integrating multiple APIs in a clean, hands-off system.