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How to scrape movie titles and genres from WatchSoMuch using JavaScript?
Scraping movie titles and genres from WatchSoMuch requires a thoughtful approach, especially since the site might use JavaScript to render content dynamically. JavaScript frameworks like Puppeteer are well-suited for this task as they allow you to control a headless browser, rendering the page fully before extracting content. The first step is to inspect the page structure using developer tools to identify the tags and classes containing movie titles and genres. If pagination or infinite scrolling is involved, Puppeteer can simulate these actions as well.Here’s an example using Puppeteer to scrape movie titles and genres:
const puppeteer = require('puppeteer'); (async () => { const browser = await puppeteer.launch({ headless: true }); const page = await browser.newPage(); await page.goto('https://example.com/movies', { waitUntil: 'networkidle2' }); const movies = await page.evaluate(() => { return Array.from(document.querySelectorAll('.movie-item')).map(movie => ({ title: movie.querySelector('.movie-title')?.innerText.trim(), genre: movie.querySelector('.movie-genre')?.innerText.trim(), })); }); console.log(movies); await browser.close(); })();Managing anti-scraping measures, such as CAPTCHAs or rate-limiting, is important for long-term projects. You can also store the scraped data in a database for further processing or analysis. How do you ensure that your scraper handles unexpected changes in the website layout?
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3 Replies
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Storing the IPs in a database like MongoDB allows for easy deduplication and querying, especially for generating subsets of random IPs later.
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When dealing with infinite scrolling, I use Selenium to simulate user scrolling until all content is loaded. This approach works well for sites like TamilMV.
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Storing scraped data in a structured database like MongoDB allows for easy querying and analysis, especially for tracking new movie releases over time.
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