Web Scraping Script for E-commerce Data Extraction and Price Monitoring
Budget: €250 – €750 EUR
I'm looking for an experienced developer to create a custom web scraping solution for extracting product data from one or more e-commerce websites. The project includes two main phases:
Phase 1 – Initial Data Extraction:
Create a script that scrapes and exports product information into an Excel file, including:
Product name/title
Product image URL (or download image locally, if possible)
Product description
Technical features/specifications
Product code/SKU
Price
Category
Product URL
The output should be a well-structured Excel (.xlsx) file with clean and organized data.
Phase 2 – Price Monitoring:
Implement a periodic check (daily or custom interval) to monitor price variations for the same products. This phase should include:
Automatic scraping on schedule (cron or other scheduler)
Comparison with previous price data
Logging of price changes (e.g., timestamp, old price, new price)
Optional: Alert system (email or notification) for significant price changes
Output of the monitoring process in an updated Excel file or database
Technical Requirements:
Python preferred (Selenium, BeautifulSoup, Scrapy, or similar)
Ability to handle dynamic content (JavaScript-rendered pages)
Include robust error handling and logs for failed requests or structure changes
Avoid detection (headers, user agents, optional proxy rotation)
Support for future scalability or additional websites
Deliverables:
Fully documented script(s)
Setup and usage instructions
Sample Excel file from test scraping
Optional: lightweight UI or dashboard (not required, but nice to have)
Please include examples of similar projects you’ve worked on. Experience with scraping large or dynamic e-commerce websites is highly appreciated.
Phase 1 – Initial Data Extraction:
Create a script that scrapes and exports product information into an Excel file, including:
Product name/title
Product image URL (or download image locally, if possible)
Product description
Technical features/specifications
Product code/SKU
Price
Category
Product URL
The output should be a well-structured Excel (.xlsx) file with clean and organized data.
Phase 2 – Price Monitoring:
Implement a periodic check (daily or custom interval) to monitor price variations for the same products. This phase should include:
Automatic scraping on schedule (cron or other scheduler)
Comparison with previous price data
Logging of price changes (e.g., timestamp, old price, new price)
Optional: Alert system (email or notification) for significant price changes
Output of the monitoring process in an updated Excel file or database
Technical Requirements:
Python preferred (Selenium, BeautifulSoup, Scrapy, or similar)
Ability to handle dynamic content (JavaScript-rendered pages)
Include robust error handling and logs for failed requests or structure changes
Avoid detection (headers, user agents, optional proxy rotation)
Support for future scalability or additional websites
Deliverables:
Fully documented script(s)
Setup and usage instructions
Sample Excel file from test scraping
Optional: lightweight UI or dashboard (not required, but nice to have)
Please include examples of similar projects you’ve worked on. Experience with scraping large or dynamic e-commerce websites is highly appreciated.