I try to asign a float to the multiprocessing.Value shared ctype as follows: However, the float stored in multiprocessing.Value is != the input float: Whats the problem here? EDIT: Found the solution (see answers) However, I do not understand, why a “double” is the correct type here and not a “float”. If someone can elaborate on that and include the
Tag: multiprocessing
Multiprocessing managers and custom classes
I do not know why, but I get this strange error whenever I try to pass to the method of a shared object shared custom class object. Python version: 3.6.3 Code: Error: What’s the problem here? Answer Found temporary solution here. I’ve managed to fix it by adding needed keyword to initializer of AutoProxy in multiprocessingmanagers.py Though, I don’t know
Python check isinstance multiprocessing.Manager().Queue()
I am using python 2.7 multiprocessing on windows 7: Output: My question is: I would like to check if a variable is an instance of a multiprocessing queue, how should i go about checking? I have referred to: Check for instance of Python multiprocessing.Connection? Accessing an attribute of a multiprocessing Proxy of a class but they dont seem to address
Multiprocessing : use tqdm to display a progress bar
To make my code more “pythonic” and faster, I use multiprocessing and a map function to send it a) the function and b) the range of iterations. The implanted solution (i.e., calling tqdm directly on the range tqdm.tqdm(range(0, 30))) does not work with multiprocessing (as formulated in the code below). The progress bar is displayed from 0 to 100% (when
Launch program with python on a specific core
there is any way to launch program by its API using python and run it on a specified core? i need to launch a cpu-expensive application about 5 times and run it on different core in order to save time. i’m using windows Answer The process can set its own affinity, here is what I do (you can change the
Accessing an attribute of a multiprocessing Proxy of a class
I have a class that I want to share in a read-only fashion with children processes in a pool, so I prepared a proxy of a class but it didn’t work. The following is a simplified example of my problem. When I run this code I get: It seems that I cannot access the attribute of a shared object directly
What kind of problems (if any) would there be combining asyncio with multiprocessing?
As almost everyone is aware when they first look at threading in Python, there is the GIL that makes life miserable for people who actually want to do processing in parallel – or at least give it a chance. I am currently looking at implementing something like the Reactor pattern. Effectively I want to listen for incoming socket connections on
how do I use key word arguments with python multiprocessing pool apply_async
I’m trying to get to grips with pythons multiprocessing module, specifically the apply_async method of Pool. I’m trying to call a function with arguments and keyword arguments. If I call the function without kwargs it’s fine but when I try to add in a keyword argument I get: TypeError: apply_async() got an unexpected keyword argument ‘arg2’ Below is the test
Shared memory in multiprocessing
I have three large lists. First contains bitarrays (module bitarray 0.8.0) and the other two contain arrays of integers. These data structures take quite a bit of RAM (~16GB total). If i start 12 sub-processes using: Does this mean that l1, l2 and l3 will be copied for each sub-process or will the sub-processes share these lists? Or to be
How to use multiprocessing queue in Python?
I’m having much trouble trying to understand just how the multiprocessing queue works on python and how to implement it. Lets say I have two python modules that access data from a shared file, let’s call these two modules a writer and a reader. My plan is to have both the reader and writer put requests into two separate multiprocessing