Python Scraper Efficiency Consultation

I already have a working Python script that scrapes text-based research data through a Chrome-based browser, running on schedules that range from monthly to near-real-time.

The program works currently but requires analysis. This would be the first part of the project.

Thereafter I’d like to sit down with an experienced scraper for a focused one-hour screen-share (Zoom or TeamViewer—whichever you prefer) and dissect the code line by line.

During the session I want to:
• spot bottlenecks that slow the crawl or chew up memory,
• discuss smarter ways to handle dynamic pages and pagination,
• tighten error handling and rate-limit management so it survives longer runs, and
• come away with a short action list I can implement immediately, or
• provide time estimates for a combination of your and my future enhancements

The deliverables are simple: the live walkthrough itself and a brief written recap of the key optimizations we identify. My goal is to make the scraper faster, lighter, and more reliable without changing its core purpose—collecting text data for research at varying intervals. If this sounds straightforward to you and you can speak clearly to performance profiling, headless Chrome tuning, and Python best practices, let’s schedule the hour.