Create Python script to check product status on website and match the SKU number
Budget: $100 – $101 NZD
I have an Excel file that lists many of product URLs alongside their expected SKU numbers. I need a clean, well-commented Python script that can automate two distinct passes over that data:
Part A – Public page check
• For every URL in the spreadsheet, request the page without logging in and report whether the product still shows as available or if it has been removed / out of stock. The status should flow back into a new column in the same sheet.
Part B – Logged-in detail match
• After authenticating with a standard email-and-password form on the e-commerce site, navigate to each product page again, parse the variant block, and compare every displayed SKU with the one supplied in the sheet.
• If a mismatch appears, or if the page meets several criteria I will share (e.g., no match found, duplicate names found), flag that row.
Deliverables
1. Python source with clear function boundaries for Part A and Part B
2. A short README: setup, required libraries, how to run, and how to adjust the flagging rules
3. One-time installation or run-through on my machine via screenshare so we confirm everything works end-to-end
If this sounds straightforward to you and you can turn it around quickly, let’s get started.
Part A – Public page check
• For every URL in the spreadsheet, request the page without logging in and report whether the product still shows as available or if it has been removed / out of stock. The status should flow back into a new column in the same sheet.
Part B – Logged-in detail match
• After authenticating with a standard email-and-password form on the e-commerce site, navigate to each product page again, parse the variant block, and compare every displayed SKU with the one supplied in the sheet.
• If a mismatch appears, or if the page meets several criteria I will share (e.g., no match found, duplicate names found), flag that row.
Deliverables
1. Python source with clear function boundaries for Part A and Part B
2. A short README: setup, required libraries, how to run, and how to adjust the flagging rules
3. One-time installation or run-through on my machine via screenshare so we confirm everything works end-to-end
If this sounds straightforward to you and you can turn it around quickly, let’s get started.
Related categories:
PHP
Python
Data Processing
Excel
Web Scraping
Software Architecture
BeautifulSoup
Selenium
Automation
Pandas