Optimizing Puppeteer for large-scale web scraping

Help with Puppeteer performance for big scraping jobs

I’m working on a project that needs to scrape about 500,000 web pages each day. The tricky part is these scrape jobs happen randomly throughout the day not all at once.

I’m not sure what’s the best way to handle this for good performance. Should I:

  1. Open a new browser for each page then close it right after? This might be slower but better for memory.

  2. Keep one browser open all the time and just open new tabs as needed? This could be faster but might use more memory over time.

Has anyone dealt with Puppeteer at this scale before? What worked well for you? Any tips on managing memory or keeping things running smoothly would be super helpful.

I’m pretty new to using Puppeteer especially for big projects like this. Thanks for any advice!

hey, u might try a small browser pool (5-10 insts) and reuse pages. error handling is key to manage memory leaks. hope it helps!

I’ve been in your shoes, and here’s what worked for me:

Hybrid approach is the way to go. Keep a small pool of browser instances (around 5-7) running constantly, but implement a smart rotation system. This balances performance and resource usage nicely.

Key thing: implement a robust session management system. I found that resetting browser contexts after every 100-200 requests helps prevent memory bloat without sacrificing too much speed.

Also, don’t underestimate the power of good data caching. I reduced my scraping load by about 30% just by implementing a smart caching layer that avoided re-scraping unchanged content.

Lastly, consider using a headless browser like Playwright instead of Puppeteer. In my experience, it handled memory much better at scale.

Remember, it’s a marathon, not a sprint. Regular monitoring and tweaking will be your best friends in keeping this beast running smoothly.

I’ve worked on a similar scale project with Puppeteer, and here’s what I found effective:

Keep a pool of browser instances running (say, 10-20) and reuse them for multiple requests. This balances speed and memory usage. Implement a queue system to manage incoming scrape requests and distribute them across your browser pool.

Use browser.pages() to reuse existing pages instead of creating new ones constantly. Set a limit on concurrent pages per browser to prevent memory issues.

Implement intelligent error handling and retries. Network issues are common at this scale.

Consider running your scraper on multiple machines or cloud instances to distribute the load.

Regularly monitor and restart browsers to prevent memory leaks. A simple cron job can handle this.

Optimize your scraping code. Use page.evaluate() for DOM manipulation instead of Puppeteer’s API when possible.

This approach has worked well for me, maintaining stability and performance over extended periods.