Python Multiprocessing Tutorial: Run Code in Parallel Using the Multiprocessing Module
In this video, we will be learning how to use multiprocessing in Python.
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In this Python Programming video, we will be learning how to run code in parallel using the multiprocessing module. We will also look at how to process multiple high-resolution images at the same time using a ProcessPoolExecutor from the concurrent.futures module. Let's get started...
The code from this video can be found at:
bit.ly/multiprocess-code
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Hey everybody! I hope you find this video helpful. I'm finally moved into my new home, so I should be back on a schedule of regular releases very soon. Hope everyone has a great weekend!
Please make a video on asyncio too..
@@deadfool6105 yes yes
Congrats on the move
Corey, can you make jupyter notebooks on these tutorials also. By the way congratulations!
Bless you man!
Why do people give thumbs down to someone who teaches for free? And a small detail ... the man is a grandmaster! Thank you sir for doing this. Greetings from the Netherlands
There are jealous because they're programming in Cobol.
I think it's the Australians. You see, they have everything upside down there, when they thumbs up, it's thumbs down for us. Corey is the best.
I think it's some kind of obsessive compulsive disorder.
~0.78% of people who voted, thumbed down down.
.. because its not working for them.. so they wasted their time getting 'taught' something that didn't work. .hence thumbs down.
There are courses that take thousands of dollars for teaching what you're teaching. you're teaching very well and you give it free. Respect.
@Corey Schafer, Thank you very much for taking the time to make this video. I have written my first-ever parallelized code and the speedup is invaluable. For years I was apprehensive about learning parallelization methods because they seemed very complicated. You, my friend, have opened the flood gates. This work puts me one step closer to completing my Master's.
It's one of those tutorials that has you reaching for the like button several times during the video, and once more after it's ended.
Well, then let's hope this urge posesses you an uneven number of times or it would be unfair to the author.
Another wonderful video. Thanks to your videos I've gained an understanding of how to build and deploy a Django web application, using matplotlib for data visualisations, python multi-threading, python-multiprocessing, exception handling, python unit test cases and more. Your content is consistently excellent because of how practical and well thought out your videos are. Extremely useful! Please keep making these videos! Thanks a lot! You're helping a lot of people with this high quality content!
31:12 Mr. Schafer finishes with the theory and goes into the real-world example with processing images 35:37 implementing multi-processing to single thread/process operation 40:04 easy switch from Processes to Threads Love Your videos Mr. Schafer. Especially Your communication skills. No BS, just clear communication. I also love that You don't edit out mistakes, and summarize after several steps. Thank You for putting the effort and sharing.
We need at least a dozen of Corey Schafer in our programming learning life. I wish everyone would follow your method. You are simply the best! God bless.
Great video! If you are running this in Windows and a later version of Python (I'm running 3.7), you need to run all multiprocessing under main(), then run if __name__ == '__main__': main() Make sure the do_something() function is declared outside main().
current
Thank you! Just the fix I was looking for. This is apparently true of macs as well
You fixed my Programm🤝
Only the code that spawns the subprocess needs to be guarded.
thank you so mutch
I just started an internship in Germany and you have no idea how helpful these classes series are to young people like me that want to succeed in the professional world of today :)
This has been incredibly helpful for me and my team. I'm a network engineer working on multiprocessing SSH connections and this made everything make sense. Definitely subscribed after seeing this.
when i watch your vidieos i belive that if you can't explain something easy to understand, absolutely nobody on this world can do that. thanks you alot Corey, you make my life easier.
This video is gold, every second of it. You are very talented at teaching complex concepts, you can't even begin to fathom how much I appreciate your work. Thanks!
Corey, thank you so much for such an amazing explanation. Even lingering questions that were happening in my head during the video, you managed to answer them right away.
This video came on time. I work with AI with python and, at university, I'm seeing operating system. Now I can join OS and python for do faster algorithms. Thanks Corey. I really like your videos!
the longest deja vu in my life so far
same, lmao
Same LOL
I swear
I needed to check github repo first to confirm that I was not watching the same tutorial yesterday ;))
Hahaha! Same
Of all the resources out there that I have looked to get a start and grasp on this subject (some cost money), this video is on point!
Corey's channel has done more for me in 2 weeks than any other resource I have tried over the last 10 years.
I have been looking for videos like this for like over 1 year, and today I randomly saw your video. Very helpful, easy to understand, thanks a lot Corey!
Seriously learning more from your vids on Python than the Python 'class' I took one time. Clear and helpful. Everytime I watch I learn something new.
Thank you, Corey, for such a wonderful explanation. The best part of this video is you have used the real-time problem, which helps to understand the concept in more depth.
Thanks for the smooth and didactic intro to multiprocessing, I've done this a year ago during a fast and furious degree and needed a refresher. I have a case in which this will come in handy although it's hundreds of lines of code, but I bet I can wrap them all into a function to be the executor's target.
A function with hundreds of lines might not be such a good idea lol. Try learning Classes and Methods and I’m sure you can incorporate multiprocessing in a much more encapsulated way
@@drygordspellweaver8761 right you are, god knows what insanity I was up to 2 years ago.
@@bigbangdata haha must have been a blast
Outstanding video! Never learned so much about multiprocessing in python - in just 45 Minutes. Thank you, Corey!
incredible video! you've covered more information than all articles all together that i've read so far - thank you for that!
I am not in a position right now to donate through patreon. All I can do is watch your videos without skipping ads and give it a like.
That helps a ton too! Thanks!
Just a reminder, on Windows you need to add "if __name__ == '__main__'"
Thanks! I usually run my videos through my Windows laptop before posting just to make sure it's the same for both operating systems, but I didn't do that this time. I appreciate the comment!
@@coreyms Somehow, me too facing errors without using main function. Even after using the if __name__ == '__main__', i got my output in different way . done sleeping 5 second(s)..... done sleeping 4 second(s)..... done sleeping 3 second(s)..... done sleeping 2 second(s)..... done sleeping 1 second(s)..... sleeping 3 second(s).... sleeping 2 second(s).... sleeping 1 second(s).... sleeping 4 second(s).... sleeping 5 second(s).... Finished in 5.5 second(s)
Just curious (python beginner), where would that go in the script?
@@whoa_that_ruled import multiprocessing import time start = time.perf_counter() def do_something(): print('Sleeping for 1 second') time.sleep(1) print('Done sleeping...') if ___name___ == '__main__': p1 = multiprocessing.Process(target=do_something) p2 = multiprocessing.Process(target=do_something) p1.start() p2.start() p1.join() p2.join() finish = time.perf_counter() print(f'Finished in {round(finish-start,4)} seconds')
Add a shebang directive and you wouldn’t need one.
Best Python Multiprocessing Tutorial ever on KZhead. I love it, you explain so well! Keep it up!
You're a grandmaster. I really appreciate you put all stuff in ONE video. So easy to navigate. Thank you!
oh man, you don't even know how long I was looking for a video on multiprocessing.
Thnx sir I got placed in a MNC all bcz of you learned python a lot and still learning a lot whenever I have any doubts stack overflow and you r my mentor thnx again preparing for higher studies now..
i pursuing a college degree and I'm learning python in different resources and i learned the basics , will you please recommend me a good resource for mastering python language and to go to next level??
Excellent tutorials, he teaches practical concepts with zero assumptions on the background and makes sure he gives real life examples and practical code to get you through! Brilliant 🙏🏻
I joined the C# start to finish course last year and am so glad that you did this video. Hope you are keeping well. Thanks for this well explained tutorial
Hi Corey, great video covered a lot, one thing I was hoping to see here which I did not was using Pool from Multiprocessing to pass multiple parameters to a class or function. I ended up finding it after some digging using starmap with zip instead of map. To pass constants with this method import itertools and use the repeat inside the zip. Hope this helps anyone looking for this.
Thank you so much for this quality of videos on Python!... Cant tell you how much i`ve learned with them. Keep it coming! :D PS. Any GUI tutorials coming? PS2. Greetings from Chile!
best explanation ever, I was really stuck when studying multiprocessing on coursera, could not get my head around, now is all crystal clear, thanks Corey
This is the best explanation of that topic I have watched so far! Many thanks, Corey!
thx so much, already implemented that into my webscraping scripts and the speed gain is tremendous. you’re explaining this so well an clear. thx a lot.
Hear trying to achieve the same
Thanks Corey! Next please do async!!
Yes, this is concept I haven't used but would really like to learn about.
Yes please, async and when to use async/asyncio/threading/multiprocessing.
Yes would strongly appreciate this
Yes, async will a perfect next. Thanks Corey for the handwork.
Yes please and then about locks,race conditions and queues as well. Thanks a lot.Loved your explanation.
Still. After 3 years - it's still helpful. Even counting that I need to test this out - nothing that much has changed in Python for MP. Thanks for such an excellent explanation!
I do have to thank you @Corey Schafer your work in these videos. I learn a lot from them and in the end I use them on my work to automate some tasks. Some love from Portugal
This is the second video I've watched from your channel and was blown away at the quality of the content and the clarity of the concepts explained. Once I get into a data analyst role, I will support you on Patreon. Until then, I will watch every other video! 😁Thanks a million!
Thanks! That helps more than you know. I really appreciate it!
Corey is great. When you help people, and I mean really HELP people, he is just a saint. I am on Python 3.9.12 and my code does not execute properly, even though I am copying verbatim and I a stuck at the 10:20 mark. After I put in the p1/p2.start() statements, the script runs without printing the "sleep" statements. The final print statement does execute. But after I put in the p1/p2.join() statements, I get a runtime error: An attempt has been made to start a new process before the current process has finished its bootstrapping phase. This probably means that you are not using fork to start your child processes and you have forgotten to use the proper idiom in the main module: if __name__ == '__main__': freeze_support() ...
same here
another one with same error
thanks a lot Mr Schafer!! your videos helps me a lot, plus the tips u give to keep the code clean are making my projects look awesome
Excellent hands-on walkthrough of Python with lots of examples. Thank you, appreciate your video!
Brah i was stuck at work tryna do this. Searched your name and braaaah! Your videos are so helpful.
same
Dude you are amazing! Excellent excellent stuff! Truly great educator and we own you a lot. I have a question. What if my function takes more than one argument. Will the ProcessPoolExecutor instance (executor) be able to map the function to however number of arguments for every process?
It’s the map method that would handle that. The function then would naturally need to accept multiple arguments
Thank You Very Much!!! I now understood how this works. Your way of teaching and explaining are very understandable unlike the other videos that I have watched.
That last piece showing how to switch from processes to threads for testing was super cool. Thanks for this great video.
In newer versions of Python instead of using a list in args you should use tuple. So instead of writing this args=[1.5] write this args=(1.5,). It's okay to use the list version, but you will get a warning. Good tutorial btw.
Not anymore ... self = reduction.pickle.load(from_parent) AttributeError: Can't get attribute ...
Any computer vision tutorial coming ? Would be awesome !
Awesome tutorial! Thanks showing both methods of handling multiprocessing.
Excelent tutorial!, just for completeness, i'd love to see some tutorial on python coroutines, thanks a lot.
What is that
Me too
Hi Sir, As you mentioned, I am interested to learn advanced threading concepts like race condition, mocks, etc. Please make videos on that too. I will be waiting... Between really nice video. Thanks for the effort.
You are one of the awesome, rocking teachers out there in KZhead, if you have time please make some tutorial videos for R language and TensorFlow
thx Corey for this great video! I'm a biomedicine master student from Sweden. This tutorial enabled me to use multiprocessing in a program I write for dna analysis during my master thesis!:)
When faced with a python challenge, I ask myself "What would Corey Schafer do?" I then, somewhat ironically, ask myself "Why am I wasting my time asking myself rhetorical questions, when I could be watching one of his outstanding videos."
That's the module I used to parallelize and optimize Mosaik smart grid co-simulations in my bachelor's thesis, which I finished this week! :D
You are my favorite channel for python I always learn something new! Will you also try to do other languages as well? Wondering about your road map.
This is A GREAT VIDEO!!!Thanks for explaining each step of the code
You could have put the image processing and the reading and writing from disk in separate functions you could have used threads for the IO and procesess for the processing
31 people didn't find a piece of code they could copy and paste for their work.
#indians sorry
your sopposed to follow along
NΛVΛZ don’t be jealous
57 now
My python classes knowledge came from you and now multiprocessing/threading. Thanks a lot for AMAZING content!
Thanks, Corey. One of your best tutorials IMO.
The reason it finished the 1s future in the Multiprocessing part after the 2 and (just after) the 3s future is that the PoolExecutor limited the threads to 4 (you said yourself that it chooses the number of concurrent threads based i.e. your hardware). And your list of times to wait is reversed in duration. So it only started the future for the 1s duration AFTER the first future finished, the one with a duration of 2s. So the 1s future finished after 2+1= 3s plus overhead, so slightly after the 3s future. Edit: Aaand you realized that just shortly after. Was wondering why noone else wrote this before.
No one mentioned it because it’s literally spelled out in the video 🤦♂️
@@drygordspellweaver8761 I did wait some time to write that comment. You meanwhile were too lazy to read my whole comment.
@@9SMTM6 Literally everyone who watched the video understood what was going on. Only you saw fit to go out of your way to write a comment to "explain" what was literally explained in the video like 5 seconds after it happened. You are insufferably arrogant and dense.
I had to add if __name__ == '__main__': for it to work in Python 3.7.6 I did not get the print output, but the images were processed
The same for me! def main(): if __name__ == "__main__": main() and it worked, anyone can help to explain why?
thanks man , you are a savior , after watching your videos on multiprocessing and threading i could finally make a project i wanted to make for a long time - python which counts the number of times i press each key and store them in an excel file for each day
I was pretty scared of touching this topic, but you made it so easily to understand!
What's the difference between time.perf_counter() and time.time()? Why should I use one over the other?
The resolution of perf_counter() is higher than that of time().
But he is eventually rounding off😅
Bro, can you tell me why this error pops up?? I'm trying to print the return value of the function. concurrent.futures.process.BrokenProcessPool: A process in the process pool was terminated abruptly while the future was running or pending.
Very good video, though yes, this is really frustrating me too!
@@concert_music You have to encase your code in that > if ___name___ == "__main__": thing. This is done to avoid unwanted side effects, and multiprocessing and concurrent.futures libraries both force programmers (at least on Windows; Corey is on Mac) to do that. Hope that helps! :D
Took me a while to find the issue: stackoverflow.com/questions/61860800/running-a-processpoolexecutor-in-ipython Basically I added those lines on top when I'm using MacOS on jupyter-lab: import multiprocessing as mp mp.set_start_method('fork')
One of the best video of Multiprocessing I have ever seen. Thanks for all your effort and teaching us.
Very well explained! With right level of complexity for someone looking to explore simple multi processing in python
for i inrange(1,1000000): print ("Thank you")
print("Thank you "*1000000) # :)
@@jimmy2643 wow. I didn't know this was possible... thank you!
It's great video. However, I receive the following error when run your code to print results in my windows. But the code works when I run it in aws environment. BrokenProcessPool Traceback (most recent call last) in 3 results = executor.map(do_something, secs) 4 ----> 5 for result in results: 6 print(result) 7 ~\AppData\Local\Continuum\anaconda3\lib\concurrent\futures\process.py in _chain_from_iterable_of_lists(iterable) 474 careful not to keep references to yielded objects. 475 """ --> 476 for element in iterable: 477 element.reverse() 478 while element: ~\AppData\Local\Continuum\anaconda3\lib\concurrent\futures\_base.py in result_iterator() 584 # Careful not to keep a reference to the popped future 585 if timeout is None: --> 586 yield fs.pop().result() 587 else: 588 yield fs.pop().result(end_time - time.monotonic()) ~\AppData\Local\Continuum\anaconda3\lib\concurrent\futures\_base.py in result(self, timeout) 430 raise CancelledError() 431 elif self._state == FINISHED: --> 432 return self.__get_result() 433 else: 434 raise TimeoutError() ~\AppData\Local\Continuum\anaconda3\lib\concurrent\futures\_base.py in __get_result(self) 382 def __get_result(self): 383 if self._exception: --> 384 raise self._exception 385 else: 386 return self._result BrokenProcessPool: A process in the process pool was terminated abruptly while the future was running or pending.
@Hongbing , even I am getting the same error in windows. Did you manage to get around it - if so then how ?
@@surajitchakraborty1903 I'm getting similar errors in pycharm - not exactly the same, but similar (also on windows)
I watch both of threading and multiprocessing video together without skipping a moment. I enjoy your video more than movie.
Thank you Corey, it is brilliant to start from the basics. Really helpful approach and advice !
At 40:40 you're omitting one important thing: GaussianBlur() is an extension using a library written in C. So it can processing the image in a separately managed thread in C and relinquish execution to the python interpreter to process python bytecode on other python threads. So it's essentially a bad example, because at the low-level it behaves like multiprocessing in the sense that it can run things outside the python interpreter (multiprocessing does that in a separate process, PIL does that in a private thread, in C). So your assessment that the workload is I/O bound is incorrect. It is mostly CPU bound, but the processing you chose released the GIL, that's an unfortunate choice.
I have no words to appreciate your efforts for the method of explanation and content of your videos you even took the trouble of repeating yourself even though you have covered the similar concept in threading video(others would just tell to go watch the threading video) thank you so much for sharing your knowledge.
Even these years, this video is really informative about that topic
This is awesome! cleared so many concepts on parallel processing :) Subscribed!
Great video as always! Would you mind talking a little but about the problems of using processes vs using threads? What you have to consider when converting a project to be running in parallel and also what is pickable and what isn't.
Have never understood multithreading and multiprocessing this clearly ever before in my life. Would greatly appreciate if you can post a video on locks. Deadlock and livelock and how to resolve them. Thanks for the service you are doing to so many people.
Thank you very much. I had written a script to download all the rpms from remote server. It used to take approximately three minutes. With ThreadPoolExecutor, Now it is taking only 20secs. Very happy to implement the concepts on real day to day work scenarios. You are doing a great Job. Please do create videos on advance topics which you mentioned at the last section of the video. (race condition etc). Happy New Year :)
i cannot thank you enough for all the videos you've put out
by far the best out there ! waiting for locks and raise conditions !!!
Wow! The use of map() is brilliant way to automatically batch the jobs for each process. Thanks for showing this!!
Wow!! I kind of understood multi processing, but this polished up everything I know into a very sparkly vision.... Thank you!!!
You are an amazing professor! Really easy to follow your speech. Thank you so much!
Excellent as always, Corey! You are truly a national treasure.
Man... You have explained so good.... Fall in love with your teaching style.
Another perfect video :) I like the feeling when you started explaining something, I'm thinking 'Wow intresting, I'd like to test it out' and finally you're doing testing - like in the last part with thread instead of process.
Great Video!!! As always, the best, most logical explanation on KZhead.
I am about to get into using Pandas to gather data from multiple spreadsheets and output cleaned up versions of those sheets as well as generate some simple reporting from the data, and I am so glad that I came across your multiprocessing video! While my use case would not take more than maybe a minute or two to run, I'm big on efficiency and if it can be run in under 15 seconds instead that is a win for me.
Your teaching method is amazing , it helped me lot in implementing multiprocessing in python code for data processing.
This Video is great! especially that you've shown dynamic processes and the rl example THANKS!
WOW! What a great KZhead channel! Congratulations and THANK YOU! I am recommending it to all my students!
Hey Corey, thanks again for a really great tutorial! First time i did understand multithreading ;-)
I came to this video with a working knowledge of python threads, processes and asynchronous coroutines. I must say, this video was very well-executed. It helped me arrange my own thoughts on the matter, and I think anyone new to the concept of multiprocessing would find Corey's explanation easy to understand. I also commend his insistence on showing a practical example, as it helps a lot of people bring new concepts into perspective. Congratulations on a job well done!
Yeah sure you are a thread expert that’s why you watched a tutorial video. People and their cringey little egos... lmao 🤦♂️
Thank you for your time and effort.Keep spreading the knowledge. Only video we need for this topic.
Absolutely amazing video. Well if anybody is getting any error for the same code as in the video then use the main function in your code. I had encountered it (don't know why)...
Very informative, useful, and well-delivered.
Thanks for your great videos with awesome explanations & examples! I learn from your videos a lot ! - from the beginning when I started learning python and now this wonderful videos which is "just in time" for me (threading & multiprocessing ). I'll definitely continue watch your videos ( Django Tutorial is next :) ) & recommend it!