Improve Go Concurrency Performance With This Pattern 

Thank you! I really appreciate your support and I’m glad that the videos are helpful 😊❤️

Hi! Thank you for your support. New concurrency video coming soon 😊

Happy to help 😊 and thank you!

Much appreciated! I’m glad you enjoy it 😊

I’m glad it was helpful! 😊

Happy to help brother!

Thank you! It’s always reassuring to see people actually appreciate the amount of effort I put in. Sometimes I feel like people only want to see overly simplified gimmicky content 🫠

Thank you! I’m glad it was interesting for you as well 🙂

My pleasure 😊

No problem brother! Good luck with your interview 🚀

hey how did it go?

how did it go?

did it go?

Unfortunately He's fail his interview

Commenting really helps so thank you!! ❤️

Thank you! ❤️

I’m happy to help brother ❤️

Thank you! I’m glad it helps 😊

Yes! I hope it helped! 😊

Hmm, I don’t really know what the video would consist of. I mean of course, the more you contribute to open source, the better you will become.. but I don’t really have anything specific to say other than, just keep contributing to open source. Also, literally any open source project is fine imo. Thank you for the suggestion! 😊 If you have additional details please let me know!

🤔

Hey! Thanks for watching. I’d say you are limited by the host system at the very least. The degree of such a limit would likely depend on the system or machine that it’s running on. Regarding other resources, if you are focused specifically on concurrency, this video is part of a playlist of 3 videos. I’d start with the concurrency patterns video 👍

Thanks@@kantancoding​I watched part2 just now lol and I left one question, I'll look for part 3 for sure 😄Godo stuff

@@webcodeuniversity You watches part 2/2. There is a part 1/2 in the playlist.

So slices are a bit confusing but let me try to explain. In Go, slices are passed by value but a slice value is a header describing a section of a backing array. So if we just pass result in instead of a pointer to result, processData will basically just receive it’s own copy of a header to the same backing array. And when we append to that slice in processData, it will only modify the slice or header in the scope of processData. Since the slice in main() is a different slice.. it won’t get modified. Therefore, in each go routine, it will have its own slice… and append the processed data to it… then once that go routine finishes.. the processed data in the slice within the scope of that go routines processData call will be removed from the stack. So the end result is that the result slice in main() will be empty since each go routine was appending to its own slice. You can actually test this behavior quite easily. Just try it the way you mentioned and print the result both inside of processData and in main and you’ll see what I mean 👍

@@kantancoding Indeed, under the hoods things can get overly complicated, but you managed to summarize the whole concept. I’ve just re-watched your video on mastering concurrency patterns and I few this time I had a deeper understanding about your explanations. It’s a shame we can’t give more than one thumbs up to your videos.

You’ve actually inspired me to make a video explaining arrays & slices in Go so thank you! ❤️ Also, I’m happy that you were able to understand things more deeply. Thank you for your support. It really means a lot to me 😊

@@kantancoding Can’t wait to watch it!

Hey sorry, haven’t watched this video in a while. Would what work?

Think of this series as a set of tools. I’m not saying that any one tool solves ALL problems. I’m presenting an array of tools (no pun intended) but in the real world, the specific project will determine which tools are viable in a given scenario.

I’m pretty sure the GIL is a mutex but you should confirm. As for Thread.lock, I’ve actually never used it so I don’t know. Thanks for watching! 😊

Happy to help! Thanks for watching 🥹