I’m working on a big web scraping project using Puppeteer. The goal is to scrape about 500k pages daily but not all at once. It’s more like random scraping jobs throughout the day.
I’m not sure what’s the best way to handle this for good performance and memory use. Should I:
Open and close the browser for each scraping job? Might be slower but better for memory?
Keep one browser open all the time and just open/close pages? Faster but might use more memory?
I’m new to using Puppeteer for big projects like this. Any tips on what to watch out for or best practices?
I’ve been in a similar situation with large-scale scraping using Puppeteer, and in my experience, keeping one browser open while managing pages carefully is more efficient. I found that using separate browser contexts for each job helps isolate memory usage and prevents resources from leaking over time. It’s important to close pages and contexts properly after each task to avoid memory buildup. I also implemented a periodic health check by restarting the browser regularly to mitigate any lingering issues. Monitoring system resources and running jobs concurrently but within system limits allowed me to scale up to 750k pages daily without major problems.
hey, i’ve used puppeteer on large projects. keeping one browser open works fine if u use contexts for each task and ensure to close pages. restarting periodically also helps. just monitor resources and adjust parallel jobs accordingly. best luck with the scraping!
From my experience with large-scale scraping projects, I’d recommend keeping one browser instance open and managing pages efficiently. This approach tends to be faster and more resource-efficient in the long run. However, it’s crucial to implement proper memory management techniques.
Consider using browser contexts to isolate each scraping job, which helps prevent memory leaks. Always close pages and contexts after each task is completed. Implement a system to monitor memory usage and restart the browser periodically if needed.
For performance, run jobs concurrently but be mindful of your system’s limits. Use headless mode and request interception to optimize resource usage. Lastly, keep an eye on your scraping frequency to avoid overloading target servers or getting blocked. With careful implementation, you should be able to handle your 500k daily page target efficiently.