The task is to extract the complete product catalogue from a website and deliver it as a clean, well-formatted Excel workbook. The site exposes most of its data through JSON responses, although a few sections sit behind a simple login; I’ll provide credentials for those pages. Key points you should know ahead of time: • Source: public website (not an API). • Data format on site: JSON payloads embedded in the page. • Access: some sections require authentication—credentials will be supplied once the project starts. I’m expecting an automated, repeatable approach—Python with requests/BeautifulSoup, Node with Axios/Cheerio, or any comparable tool you’re comfortable with is fine as long as the final spreadsheet updates cleanly when rerun. Deliverables • Executable script (with clear setup instructions) that logs in where needed, collects every product record, and writes the data to Excel. • An .xlsx file containing all captured fields—product name, SKU, price, description, images, and any other attributes present in the JSON. • Brief read-me outlining how to rerun the scrape and update the sheet. The script should gracefully handle pagination or lazy-loaded content, respect polite scraping intervals, and flag any items it cannot fetch.