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How to build a shopping bot to scrape product prices using Python?
Building a shopping bot to scrape product prices can help automate price comparisons across multiple e-commerce websites. Python, combined with libraries like requests and BeautifulSoup, is an excellent choice for scraping static content. For dynamic websites, Selenium or Playwright can be used to handle JavaScript-rendered pages. The bot should navigate through product categories, extract prices and titles, and store them in a structured format, such as a database or a CSV file. You’ll also need to implement rate-limiting and proxy rotation to avoid detection and blocking.Here’s an example of a basic shopping bot using BeautifulSoup:
import requests from bs4 import BeautifulSoup def scrape_prices(url): headers = {"User-Agent": "Mozilla/5.0"} response = requests.get(url, headers=headers) if response.status_code == 200: soup = BeautifulSoup(response.content, "html.parser") products = soup.find_all("div", class_="product-item") for product in products: title = product.find("h2", class_="product-title").text.strip() price = product.find("span", class_="product-price").text.strip() print(f"Product: {title}, Price: {price}") else: print("Failed to access the website.") url = "https://example.com/products" scrape_prices(url)For a more advanced bot, you can integrate APIs (if available) to fetch product data directly, as it’s more efficient and reliable than scraping HTML. How do you ensure the shopping bot adapts to frequent changes in website structures?
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2 Replies
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For JavaScript-heavy sites, I prefer Selenium to ensure all dynamic elements are fully rendered before scraping. It’s slower but reliable for complex layouts.
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For pagination, I use a loop to navigate through “Next Page” buttons until all extensions are scraped. This ensures comprehensive data collection.
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