I need a complete snapshot of every product listed on industrykitchens.com.au. The task is a one-time scrape and delivery of clean, well-structured data. Deliverables • A single CSV file containing, for each product information as much as possible min required: SKU, category, product name, full description, current price, primary image URL and any additional image URLs. • A folder (or compressed archive) of the referenced images, organised by SKU or another logical structure. • The scraping script (Python with Scrapy/BeautifulSoup/Selenium, or a comparable stack) plus a brief “how-to-run” note so I can reproduce the extraction later. Acceptance criteria • Every product that can be reached through site navigation, search filters or pagination is present in the CSV. • Text fields are free of HTML artefacts; prices are numeric; images open without error. • No duplicate rows. Handle polite behaviour toward the site (rate limiting, retries, user-agent spoofing) so the crawl completes without triggering blocks. I’m ready to review as soon as you provide a small sample CSV for confirmation, then we can move on to the full run.