{"id":31782093,"url":"https://github.com/keshav1516/amazon_web_scraping","last_synced_at":"2026-05-15T08:38:18.656Z","repository":{"id":314268223,"uuid":"1054837095","full_name":"Keshav1516/amazon_web_scraping","owner":"Keshav1516","description":"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. 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It uses Requests and BeautifulSoup to parse product \ninformation and saves it in a structured format (CSV/Excel).\n\n# 🚀 Features\n-------------------------\n- Extracts:\n  - Product Title\n  - Product Price\n  - Product Rating\n  - Number of Reviews\n  - Product Availability\n  - Stores results in CSV or Excel format.\n- Modular functions for each product attribute.\n- Can be extended to scrape multiple product URLs.\n\n# 🛠️ Requirements\n---------------------------------\nInstall dependencies before running:\n\npip install requests beautifulsoup4 pandas numpy\n\n# ⚡ Usage\n-----------------------------\n1. Open the notebook:\n\njupyter notebook Amazon_Web_Scrapping.ipynb\n\n2. Run the cells in order.\n3. Provide the Amazon product URL(s) inside the code. Example:\n\nURL = \"https://www.amazon.in/dp/B09G9BL5CP\"\nheaders = {\"User-Agent\": \"...\"}  # Use your browser's User-Agent\n\n4. The scraper will extract:\n- Title\n- Price\n- Rating\n- Reviews\n- Availability\nand save them into a structured DataFrame.\n\n# 📊 Output\n---------------------------------------\nThe output is saved as:\n- CSV file (amazon_products.csv)\n- or Excel file (amazon_products.xlsx)\ndepending on the code you enable in the notebook.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkeshav1516%2Famazon_web_scraping","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkeshav1516%2Famazon_web_scraping","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkeshav1516%2Famazon_web_scraping/lists"}