https://github.com/keshav1516/amazon_web_scraping
This project extracts product details from Amazon using Python, Requests, and BeautifulSoup. It scrapes titles, prices, ratings, reviews, and availability, then organizes the data into CSV or Excel files. Designed for learning web scraping, it demonstrates structured data collection and analysis from e-commerce sites.
https://github.com/keshav1516/amazon_web_scraping
beautifulsoup bs4 requests requests-library-python selenium webscraping webscraping-beautifulsoup webscrapping-python
Last synced: 24 days ago
JSON representation
This project extracts product details from Amazon using Python, Requests, and BeautifulSoup. It scrapes titles, prices, ratings, reviews, and availability, then organizes the data into CSV or Excel files. Designed for learning web scraping, it demonstrates structured data collection and analysis from e-commerce sites.
- Host: GitHub
- URL: https://github.com/keshav1516/amazon_web_scraping
- Owner: Keshav1516
- Created: 2025-09-11T11:56:26.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2025-09-11T12:05:26.000Z (about 2 months ago)
- Last Synced: 2025-09-11T14:28:56.106Z (about 2 months ago)
- Topics: beautifulsoup, bs4, requests, requests-library-python, selenium, webscraping, webscraping-beautifulsoup, webscrapping-python
- Language: Jupyter Notebook
- Homepage:
- Size: 8.79 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Amazon Web Scraping 🛒
-------------------------
This project is a Python-based web scraping tool that extracts product details from Amazon product pages. It uses Requests and BeautifulSoup to parse product
information and saves it in a structured format (CSV/Excel).
# 🚀 Features
-------------------------
- Extracts:
- Product Title
- Product Price
- Product Rating
- Number of Reviews
- Product Availability
- Stores results in CSV or Excel format.
- Modular functions for each product attribute.
- Can be extended to scrape multiple product URLs.
# 🛠️ Requirements
---------------------------------
Install dependencies before running:
pip install requests beautifulsoup4 pandas numpy
# ⚡ Usage
-----------------------------
1. Open the notebook:
jupyter notebook Amazon_Web_Scrapping.ipynb
2. Run the cells in order.
3. Provide the Amazon product URL(s) inside the code. Example:
URL = "https://www.amazon.in/dp/B09G9BL5CP"
headers = {"User-Agent": "..."} # Use your browser's User-Agent
4. The scraper will extract:
- Title
- Price
- Rating
- Reviews
- Availability
and save them into a structured DataFrame.
# 📊 Output
---------------------------------------
The output is saved as:
- CSV file (amazon_products.csv)
- or Excel file (amazon_products.xlsx)
depending on the code you enable in the notebook.