Python E-commerce Data Scraper
Budget: ₹1,500 – ₹12,500 INR
I need a Python script that reliably harvests product information from a set of e-commerce websites I’ll provide once we start. The goal is to pull every item’s name, price, full description, key specifications, plus customer ratings and reviews, then place everything into a clean, well-structured CSV.
The sites mix static and dynamic content, so the solution may involve requests/BeautifulSoup for straightforward pages and Selenium or another headless approach where JavaScript rendering is required. Rotating proxies or polite rate-limiting will likely be needed to stay under the radar and avoid CAPTCHAs.
Scraping product information from
1. https://www.zeptonow.com/
2. https://www.swiggy.com/instamart
3. https://blinkit.com/
4. Amazon fresh
Information to logged in to csv file . The data to be collected are
1. Product name
2. Product description ( if applicable )
3. Product price
4. Quantity or package
5. Rating ( if any )
Code should auto scroll vertically or horizontally to get full list of information
Note that product changes from location-to-location Eg if the tomato is 30Rs in Bangalore, I might be 60 in Delhi. Code must take in location information and scrape corresponding data only. I should be able to change the location and get information for that specific location
Code has to be done in Python
Deliverables
• A fully commented .py file ready to run from the command line
• A sample CSV containing the scraped data with separate columns for each required field
• A brief README outlining setup (pip installs, environment variables if any) and usage
Acceptance criteria
• All requested fields (name, price, description, specs, ratings, reviews) captured with no stray HTML
• Script runs end-to-end without manual intervention and can be rerun to append or overwrite data
• Clean, deduplicated output formatted consistently across all target sites
Feel free to lean on standard libraries like pandas, Scrapy, or Playwright , https://docs.crawl4ai.com/core/quickstart/ if they shorten the build. Let me know your timeline and any clarifications you need.
The sites mix static and dynamic content, so the solution may involve requests/BeautifulSoup for straightforward pages and Selenium or another headless approach where JavaScript rendering is required. Rotating proxies or polite rate-limiting will likely be needed to stay under the radar and avoid CAPTCHAs.
Scraping product information from
1. https://www.zeptonow.com/
2. https://www.swiggy.com/instamart
3. https://blinkit.com/
4. Amazon fresh
Information to logged in to csv file . The data to be collected are
1. Product name
2. Product description ( if applicable )
3. Product price
4. Quantity or package
5. Rating ( if any )
Code should auto scroll vertically or horizontally to get full list of information
Note that product changes from location-to-location Eg if the tomato is 30Rs in Bangalore, I might be 60 in Delhi. Code must take in location information and scrape corresponding data only. I should be able to change the location and get information for that specific location
Code has to be done in Python
Deliverables
• A fully commented .py file ready to run from the command line
• A sample CSV containing the scraped data with separate columns for each required field
• A brief README outlining setup (pip installs, environment variables if any) and usage
Acceptance criteria
• All requested fields (name, price, description, specs, ratings, reviews) captured with no stray HTML
• Script runs end-to-end without manual intervention and can be rerun to append or overwrite data
• Clean, deduplicated output formatted consistently across all target sites
Feel free to lean on standard libraries like pandas, Scrapy, or Playwright , https://docs.crawl4ai.com/core/quickstart/ if they shorten the build. Let me know your timeline and any clarifications you need.
Related categories:
PHP
JavaScript
Python
Data Processing
Web Scraping
Data Scraping
BeautifulSoup
Data Analysis
Selenium
Pandas