Building a Costco Price Tracker with Python, Playwright, and Streamlit

In e-commerce, prices are rarely static. Retail giants like Costco adjust prices based on inventory levels, seasonal promotions, and regional demand. If you are a developer hunting for deals or an analyst monitoring competitive intelligence, a single snapshot of a price isn't enough. You need historical data to identify trends and predict future drops. This guide walks through building a production-ready Costco price tracker. Using the open-source Costco.com-Scrapers repository, we will extract product data with Playwright, store it with timestamps, and visualize the history in a Streamlit dashboard. Prerequisites Before starting, ensure you have: Python 3.8+ ScrapeOps API Key : Costco employs aggressive anti-bot measures. We’ll use ScrapeOps to handle proxy rotation and browser headers. You can get a free API key here . Terminal access : Comfort working within a virtual environment. Setup and Installation Clone the repository and install the dependencies: # Clone the repository git cl