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Scraping event details using Python and Playwright
Scraping event details, such as names, dates, and locations, is useful for building event aggregators or calendars. Many event websites use JavaScript to dynamically load their content, making Python and Playwright an excellent combination for rendering and extracting data. The first step is to use Playwright to navigate to the webpage and wait for all elements to load. Once the content is rendered, you can use Playwright’s built-in selectors to scrape the required details. This approach works well for infinite scrolling or dynamically updated event listings.
Here’s an example using Playwright to scrape event details:from playwright.sync_api import sync_playwright def scrape_events(): with sync_playwright() as p: browser = p.chromium.launch(headless=True) page = browser.new_page() page.goto("https://example.com/events") events = page.query_selector_all(".event-item") for event in events: title = event.query_selector(".event-title").inner_text() date = event.query_selector(".event-date").inner_text() location = event.query_selector(".event-location").inner_text() print(f"Title: {title}, Date: {date}, Location: {location}") browser.close() scrape_events()Handling anti-scraping mechanisms, such as CAPTCHAs or rate limiting, is crucial for long-term scraping. How do you optimize performance when scraping large-scale event listings?
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2 Replies
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For large-scale scraping, I use Playwright’s headless mode to reduce resource consumption while maintaining the ability to render JavaScript content.
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Adding caching for previously scraped pages saves time and bandwidth, especially for event pages that don’t update frequently.
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