Python Tutorial - 28. Sharing Data Between Processes Using Array and Value

Today’s tutorial is based on sharing data between processes using Array and Value. The topics that we are including in this python tutorial are how to solve issue sharing data between the process, what is shared memory, how to use shared memory in the process using an array, what is shared memory methods enumerate() and how to use shared memory in a process using value.

Topics that are covered in this Python Video:
0:00 Overview
2:15 How to solve issue sharing data between the process
2:21 What is shared memory
2:41 Use shared memory in a process using an array
3:37 Shared memory methods enumerate()
5:15 Use shared memory in the process using the value

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[ivarvaw]

Was stuck on this for 2 days, finally got it to work thanks to you. Thanks!

[venkatjoopalli]

Hi Sir, very good explanation, I am able to understand now, could you please help to eloborate in which of the scenarios do we prefer multi processing, multi threading. And one more request is could you please share few exercises to pracy same, Thanks a lot for your excellent teaching.

[mahajanravish]

so far the best python tutorial
clear and very well explained . thank you sir☺☺

[thyagtubes]

Fantastic tutorial. I wish more tutors explain concepts with lighter/universal examples such as squares, cubes and to-do lists rather than noisy ones like monte-carlo simulations or mandelbrot sets or tic-tac-toe games.

[dewzzjr]

What a clear and simple tutorial. Very good, thank you.
is this method applicable to Threading too?

[minnyanlin]

it really help me to touch threading topic

[namkang]

can multiprocesing.Array be an 2-dimension array ? If yes, how ?

[justinstar]

Hi, thx for the tutorial. Very good way to introduce these concepts in a series and make a lot more sense with the graphics and demo.
Two thoughts, if I may,
1. Sometimes your murmured for a bit in the end of the sentences.
2. Passing Objects could be explained in advance in the beginning.

[mpty]

thanks for the code. made life easier :D

[Revention]

Very nice tutorial like all of your videos!

[samcrane]

Fantastic tutorial! such a great help :)

[sabarishamaravadi]

Awesome. I have a question.It would be great if you could answer. I have two child processes and one parent process. Is it possible to use the variables and its values in a third process or in a parent process?.

[allanerissat]

If I want the data type in Array / Value parenthesis to be a string, what do I pass?

[arlenalem]

Thanks for your videos, How could i create a matrix, which can be access from more than 2 process, let-s say two of them can write data in the matrix and the a third one can read the data?

[lessmore]

Is this for sharing large data, like GB-sized numpu arrays?

[testtesto]

I have added this line (print 'from inside of CUBE PID %d:' % os.getpid()) to get process ID in the codes of your both Multi Threading and MutiProcessing videos. The PID always come different while printing from inside and outside. For multithreading the PID should be same, right? is this the right way to track the PID of process?

[haifa]

i have a question kindly, this sharing is only done in initial state, of calling these process. how about passing variable or argument during the running state of the processes. how can two process during running state, pass sharing variable. please. thank you. i hope there is reply for my question. thanks again

[marshallcocop]

Thank you for this very explanatory video :) However, I can not create a shared memory with strings, not floats..
Could you give me an example with strings so that I could better understand how it works (If you can of course!) ? :)
I would be very grateful, I have a lot of trouble with this librairy..
Thank you very much

[보기나만]

Hello. sir. I tried to use this, but in my case, when I printed it at the end, it just showed 0.0 for v. May I ask what is wrong?

[jabeddh]

I have tried to create 2D array by result = Array(ctypes.c_double, np.shape(result)) and in a function I am trying to pass a numpy array (B) to result array by result[:, n] = B
But I am getting an error "result = Array(c.c_double, np.shape(result))", I tried result[:, int(n)], nothing did work. Would have any suggestions?