- \n
- Develop a tool for comparing product prices across multiple e-commerce websites.<\/li>\n
- Implement a user-friendly interface for entering product names and displaying the scraping process.<\/li>\n
- Automate the web scraping process to gather product information from Amazon, Flipkart, and eBay.<\/li>\n
- Save the gathered data into a CSV file for further analysis.<\/li>\n<\/ul>\n
Project Setup<\/h3>\n
Required Libraries<\/h4>\n
- \n
- Selenium<\/strong>: For web scraping and browser automation.<\/li>\n
- Pandas<\/strong>: For data manipulation and analysis.<\/li>\n
- webdriver-manager<\/strong>: For managing browser drivers.<\/li>\n
- Tkinter<\/strong>: For building the graphical user interface.<\/li>\n<\/ul>\n
Prerequisites for Python Price Comparison Extension<\/h4>\n
- \n
- Basic understanding of Python programming.<\/li>\n
- Familiarity with web scraping concepts using Selenium.<\/li>\n
- Understanding of Tkinter for GUI development.<\/li>\n<\/ul>\n
Download the Python Price Comparison Extension Project<\/h3>\n
Please download the source code of the Python Price Comparison Extension Project: Python Price Comparison Extension Project Code.<\/strong><\/a><\/p>\n
Step-by-Step Code Implementation of Python Price Comparison Extension<\/h3>\n
1. Importing Libraries<\/h4>\n
- \n
- time<\/strong>: It introduces delays in the web scraping process to allow pages to load.<\/li>\n
- Pandas<\/strong>: It is used for data manipulation and saving scraped data.<\/li>\n
- Selenium and related imports<\/strong>: Used for automating web browser interactions.<\/li>\n
- Tkinter and messagebox:<\/strong> Used for creating a graphical user interface.<\/li>\n<\/ul>\n
import time\r\nimport pandas as pd\r\nfrom selenium import webdriver\r\nfrom selenium.webdriver.common.by import By\r\nfrom selenium.webdriver.chrome.service import Service as ChromeService\r\nfrom webdriver_manager.chrome import ChromeDriverManager\r\nimport tkinter as tk\r\nfrom tkinter import messagebox\r\n<\/pre>\n
2. Scraping Function<\/h4>\n
- \n
- This function initiates the scraping process, taking product_name<\/strong> as an argument.<\/li>\n
- The webdriver.Chrome( )<\/strong> sets up the Chrome WebDriver using webdriver_manager<\/strong> to manage driver installations.<\/li>\n
- urls<\/strong> is a dictionary containing search URLs for Amazon, Flipkart, and eBay.<\/li>\n
- Scrape_amazon<\/strong>: This function scrapes data from the search results page of the specified product on Amazon.<\/li>\n
- scrape_flipkart:<\/strong> This function scrapes data from the Flipkart site’s search result page for the specified product.<\/li>\n
- scrape_ebay:<\/strong> This function scrapes data from the eBay site’s search result page for the specified product.<\/span><\/li>\n
- The above functions call each scraping function to gather data.<\/li>\n
- driver.quit():<\/strong> Closes the web browser.<\/li>\n
- df = pd.DataFrame(results):<\/strong> This converts the results list into a Pandas DataFrame.<\/li>\n
- Finally, it is saved to a CSV file using\u00a0df.to_csv().<\/strong><\/span><\/li>\n<\/ul>\n
def start_scraping(product_name):\r\n driver = webdriver.Chrome(service=ChromeService(ChromeDriverManager().install()))\r\n\r\n\r\n urls = {\r\n \"Amazon\": f\"https:\/\/www.amazon.in\/s?k={product_name}\",\r\n \"Flipkart\": f\"https:\/\/www.flipkart.com\/search?q={product_name}\",\r\n \"eBay\": f\"https:\/\/www.ebay.com\/sch\/i.html?_nkw={product_name}\"\r\n }\r\n\r\n\r\n results = []\r\n\r\n\r\n def scrape_amazon():\r\n driver.get(urls[\"Amazon\"])\r\n time.sleep(3)\r\n products = driver.find_elements(By.XPATH, \"\/\/div[@data-component-type='s-search-result']\")\r\n for product in products[:5]:\r\n title = product.find_element(By.TAG_NAME, \"h2\").text\r\n try:\r\n price = product.find_element(By.CLASS_NAME, \"a-price-whole\").text\r\n except:\r\n price = \"N\/A\"\r\n results.append({\"Website\": \"Amazon\", \"Title\": title, \"Price\": price})\r\n\r\n\r\n def scrape_flipkart():\r\n driver.get(urls[\"Flipkart\"])\r\n time.sleep(3)\r\n products = driver.find_elements(By.CLASS_NAME, \"_1AtVbE\")\r\n for product in products[:5]: \r\n try:\r\n title = product.find_element(By.CLASS_NAME, \"IRpwTa\").text\r\n price = product.find_element(By.CLASS_NAME, \"_30jeq3\").text\r\n results.append({\"Website\": \"Flipkart\", \"Title\": title, \"Price\": price})\r\n except:\r\n continue\r\n\r\n\r\n def scrape_ebay():\r\n driver.get(urls[\"eBay\"])\r\n time.sleep(3)\r\n products = driver.find_elements(By.CLASS_NAME, \"s-item\")\r\n for product in products[:5]:\r\n try:\r\n title = product.find_element(By.CLASS_NAME, \"s-item__title\").text\r\n price = product.find_element(By.CLASS_NAME, \"s-item__price\").text\r\n results.append({\"Website\": \"eBay\", \"Title\": title, \"Price\": price})\r\n except:\r\n continue\r\n\r\n\r\n scrape_amazon()\r\n scrape_flipkart()\r\n scrape_ebay()\r\n\r\n\r\n driver.quit()\r\n\r\n\r\n df = pd.DataFrame(results)\r\n df.to_csv(\"price_comparison_results.csv\", index=False)\r\n\r\n\r\n messagebox.showinfo(\"Info\", \"Comparison completed and results saved to price_comparison_results.csv\")\r\n<\/pre>\n3. Tkinter Interface<\/h4>\n
- \n
- get_product_name()<\/strong> function gets the product name from the user input.<\/li>\n
- Then retrieves the product name from the input entry, and if the product name is not empty, then it calls the start_scraping function<\/li>\n
- root = tk.Tk():<\/strong> It initializes the main Tkinter window.<\/li>\n
- tk.Button( ):<\/strong> It creates a button that, when clicked, calls the get_product_name function to start the scraping process.<\/li>\n<\/ul>\n
def get_product_name():\r\n product_name = entry.get()\r\n if product_name:\r\n start_scraping(product_name)\r\n else:\r\n messagebox.showerror(\"Input Error\", \"Please enter a product name\")\r\n\r\n\r\nroot = tk.Tk()\r\nroot.title(\"TechVidvan@Price Comparison Extension\")\r\n\r\n\r\ntk.Label(root, text=\"Enter Product Name:\").pack(pady=10)\r\nentry = tk.Entry(root)\r\nentry.pack(pady=5)\r\n\r\n\r\ntk.Button(root, text=\"Start Scraping\", command=get_product_name).pack(pady=20)\r\n\r\n\r\nroot.mainloop()\r\n<\/pre>\n
Python Price Comparison Extension Output<\/h3>\n
1. Application Interface<\/strong><\/p>\n
![\"price](\"https:\/\/techvidvan.com\/tutorials\/wp-content\/uploads\/2025\/10\/price-comparison-interface.webp\")
<\/a><\/p>\n2. Scraping Site 1<\/strong><\/p>\n
![\"scraping](\"https:\/\/techvidvan.com\/tutorials\/wp-content\/uploads\/2025\/10\/scraping-site1.webp\")
<\/a><\/p>\n3. Scraping Site 2<\/strong><\/p>\n
![\"scraping](\"https:\/\/techvidvan.com\/tutorials\/wp-content\/uploads\/2025\/10\/scraping-site2.webp\")
<\/a><\/p>\n4. Scraping Site 3<\/strong><\/p>\n
![\"scraping](\"https:\/\/techvidvan.com\/tutorials\/wp-content\/uploads\/2025\/10\/scraping-site3.webp\")
<\/a><\/p>\n5. Comparison Completed<\/strong><\/p>\n
- The webdriver.Chrome( )<\/strong> sets up the Chrome WebDriver using webdriver_manager<\/strong> to manage driver installations.<\/li>\n
- Pandas<\/strong>: It is used for data manipulation and saving scraped data.<\/li>\n
- time<\/strong>: It introduces delays in the web scraping process to allow pages to load.<\/li>\n
- Pandas<\/strong>: For data manipulation and analysis.<\/li>\n
- Selenium<\/strong>: For web scraping and browser automation.<\/li>\n
![\"comparison](\"https:\/\/techvidvan.com\/tutorials\/wp-content\/uploads\/2025\/10\/comparison-completed.webp\")
<\/a><\/p>\n![\"price](\"https:\/\/techvidvan.com\/tutorials\/wp-content\/uploads\/2025\/10\/price-comparison-results.webp\")
<\/a><\/p>\n