Selenium Table Data Scraper

I need a Python 3 script that uses Selenium (ChromeDriver) to visit one or more dynamic web pages, wait for their tables to finish rendering, and export the complete content to a clean CSV (JSON as a secondary option). The pages rely on JavaScript pagination and lazy loading, so simple HTTP libraries won’t work—reliable browser automation is essential.

Key points of the job
• Employ explicit waits to ensure every row, even those revealed by “Next” buttons or infinite scroll, is captured.
• Keep column headers intact and map each cell accurately.
• Handle common hurdles such as cookie pop-ups, login prompts (if I supply credentials), and unexpected client-side alerts.
• Write clear, modular code with comments so I can tweak selectors or extend the scraper later.

Deliverables
• scrape.py (well-documented, PEP-8 compliant)
• requirements.txt with exact package versions
• Sample output file demonstrating successful extraction from a target URL
• Brief README explaining setup, command-line arguments, and how to add new sites

Acceptance criteria
Running `python scrape.py --url ` on my machine should create a CSV whose row count and values match what I see in the browser. No hard-coded paths; everything configurable through flags or a small JSON/YAML file.

Timeframe
I’m aiming for a first working draft ASAP, ideally within the next day or two, and a polished final hand-off immediately after testing.