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How to scrape restaurant menus and prices from online food delivery platforms?
Scraping restaurant menus and prices from online food delivery platforms requires handling structured but often dynamically loaded data. Menus are typically displayed in a hierarchical format, with categories like appetizers, mains, and desserts. Using BeautifulSoup, you can extract this data for static pages, while Puppeteer or Selenium is needed for JavaScript-rendered content. Monitoring network traffic might also reveal APIs that return menu data in JSON format, simplifying the scraping process.
Here’s an example using BeautifulSoup for static menu scraping:import requests from bs4 import BeautifulSoup url = "https://example.com/restaurant-menu" headers = {"User-Agent": "Mozilla/5.0"} response = requests.get(url, headers=headers) if response.status_code == 200: soup = BeautifulSoup(response.content, "html.parser") items = soup.find_all("div", class_="menu-item") for item in items: name = item.find("span", class_="item-name").text.strip() price = item.find("span", class_="item-price").text.strip() print(f"Dish: {name}, Price: {price}") else: print("Failed to fetch the menu.")Dynamic pages often require scrolling or interaction to load additional items, which can be automated with Puppeteer. Handling anti-scraping measures like CAPTCHAs is crucial when dealing with large-scale scraping. How do you ensure the scraper adapts to frequent platform updates?
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3 Replies
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For dynamic updates, I use modular code that isolates the scraping logic for each section of the menu. This makes it easy to update when the platform changes its layout.
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Using Puppeteer to interact with dropdowns and filters ensures I capture all menu items, even those hidden behind dynamic elements.
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To avoid detection, I randomize headers and request intervals. Mimicking real user behavior helps bypass anti-scraping measures.
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