Monthly E-Commerce Product Data Scrape

I need a reliable solution that pulls fresh product information from a specific website and drops it into a neat, well-structured Excel workbook each month. The data points are the standard e-commerce essentials—name, price, SKU, description, availability and any variants that appear on the page. If the site nests details behind dynamic elements, please factor that in; I still expect a complete dataset.

Your script can run in Python (BeautifulSoup, Scrapy or Selenium are all fine) or any language you prefer, as long as the final output is a tidy .xlsx file ready for analysis. I’ll trigger the run once a month, so the process should be repeatable with minimal manual tweaking—ideally a single command or scheduled task.

Acceptance criteria
• A working scraper that navigates pagination and captures every live product listing.
• Clean Excel file with separate columns for each attribute, no duplicates or missing rows.
• Clear instructions so I can rerun the job monthly on my own machine (or a lightweight hosting option you recommend).
• Basic error handling and logging so I can see what was scraped and flag pages that change or break.

Share a brief outline of your approach, mention any libraries you plan to use, and let me know if you need sample URLs before you begin.