Python Threading Tutorial: Run Code Concurrently Using the Threading Module

Hey everybody! I hope you find this video helpful. I'll be releasing the multiprocessing video next week. I am currently packing up my temporary recording station and will be moving into my new place tomorrow, so I should be able to get it recorded, edited, and released next week for sure. We'll be covering how to use multiprocessing to process the high-resolution images we downloaded in this video. Hope you all get some good use out of these topics!

This dude is like the bible for programming tutorials.

But when I tried it out, it looked like threads are switching between each other even if there is no "dead time" in the threads. Are they switching switching between each other or are they actually happening in parallel (are they actually multiprocessing)?


import threading

def cpu_bound_task(game_id):
i = 0
while i < 10**7:
i += 1
print(f"Game {game_id} CPU-bound task - iteration {i}")

def main():
threads = []

for game_id in range(3):
thread = threading.Thread(target=cpu_bound_task, args=(game_id,))
threads.append(thread)
thread.start()

for thread in threads:
thread.join()

if _name_ == "__main__":
main()

Thank you so much, Corey, for this fantastic tutorial on introducing threading in Python to beginners! Your clear explanations and step-by-step demonstrations have really helped me grasp this concept much better. Your tutorials are always a go-to resource for me, and I appreciate how you make even complex topics so accessible. Your contribution to the Python community is invaluable, catering to both newcomers like me and experienced developers. Keep up the fantastic work, Corey!

nice video!

omg.
I was using some of it, but not all of it's potential.
Amazing.

still valid even after 3 yrs
Awesome tutorial

I think you meant asynchronously a couple of times

Can we use thread in APIs(created in fastapi), does it cause database deadlock?

why do I get None between my thread and finished in thread pool executor?

thanks alot ,
and for those who the method didn't work for after using with concurrent.futures.ThreadPoolExecutor() as executor :
add max_workers=(to more than or equal to the number in the range function)
like this
with concurrent.futures.ThreadPoolExecutor(max_workers=20) as executor :

So threads in python only uses one core of CPU of underlying server?

Amazing video, thank you!!

Thank you

I'd be so screwed without your videos. The BEST explanations anywhere on the internet for learning python.

Your a great teacher i keep comming back to your lessons!

Thanks

when I See Someone is appreciate your video. I don't know why i'm just feel so fine💝💝

Amazing! Tried something similar with multiprocess, but will test this one out. Thanks!

Corey I love you

your'e awesome

I am blown away

For five years I was looking for some simple explanation that I could use in my code, to pull my dna, from snpedia...OMG. So simple but very good. Thanks man.

In the minute 24 I subscribe and like it !!!OMG

Thanks for the wonderful video

Thanks man.

I don't know if this comment will be seen but I'm having trouble running the concurrent.futures method with a for loop

Thank youu so much Highlyy recommended , you just express it in a simple way

Beautiful !

can I perform multithreading from dictionary? i cant seem to find out the syntax :(

Completely agree about the basic example tutorials, I often find them useless. Great video, thanks!

What would be candidate for doing something with json, like extracting and storing, multi threading?

I am curious about a best practice for dividing up a list of REST API calls so that chunks can be sent to different processes via multi-processing first, then each process can use multi-threading to request data and subsequently process the payloads individually. Basically a good way of using both techniques in such a way that you leverage the strengths of multi-threading within a multi-process operation which I know can be done.

There's just a bit of magic that thread/process pools are doing where they determine how to allocate workers for you and I don't know how to use that magic to divide the list of REST calls optimally per process. I guess I could count the number of CPUs available on the machine but then I kind of like how process pools does that for you and helps make your operations safe without potentially maxing out all processors.

Thank you for this powerful tutorial.

This video is a life-saver! I have a project due in 3 days that needs me to do a lot of fancy stuff in a multithreaded program, and I had no clue what multithreaded programs are! I'm in a much better position after watching this video. Thank you, Corey!

what a godsend tutorial

Thanks Corey. Why do you pass in the args as a list [1.5]?

Thank you for this. The Thread Pool Executor is really simple to use.

Thank for the detailed step by step explanation. How do we control the number of threads using a ThreadPoolExecutor when processing a list of say 40k urls? For example if I want to process 10urls at a time. Is creating a smaller sublist with 10 items from the main 40k list an ideal solution?

this is kinda interesting that you can run a code in parallel withing for loop THANKS COREY

Tried Skillshare to take on learning Python. There is a bunch of milquetoast videos with no real substance. These videos by Corey are outstanding. Much appreciation. I'm glad it was a free subscription.

Hey Corey, thanks for this. You are an awesome teacher. I will be watching your other videos too as needed and Subscribed! :D

You're great. Your video on multithreading helped me to undertand the differncce between multithread & multiprocess. Great explaination!!❤❤