I am using multiprocessing.pool to parallelize my code. The code is running fine if I do small analysis on my data (like manipulating/creating few numpy arrays). However, when I do heavy analysis, the code just stucks/freezes forever. It never returns any output or error ,and the top commands also shows that nothing is happening. The ..
I have a system with two processes, where: a ‘reader’ process, getting frames from a remote camera through RTSP; frames read from ‘reader’ are sent to ‘consumer’, to run some computer vision algorithms on them. Now, the problem is that frames are read from the camera in ‘reader’ at 25 FPS, but they are clearly ..
How can I transfer a huge df to a hive table from python? I want to transfer df in the memory of python to directly hive table. I generate connections with sqlalchemy create engine. I can write df to table. Below is how I applied this method. from sqlalchemy import create_engine from multiprocessing import Lock, ..
I would like to create a button ipywidget that allows to stop an execution when clicking on a cancel button in Jupyter. I have seen several examples (including this) but they all require to be able to modify the function being ran by the process itself. This sounds rather simple, but I am beginning to ..
I’m parsing website and using ProcessPoolExecutor for multiprocessing. Each time I need to check page for new info, if it appeared return it to main() and then do rest of the code with this info in main(). It works with ThreadPoolExecutor fine but how to make it work with ProcessPoolExecutor ? Source: Python..
I want to perform a parallel get_item dynamodb operation to save processing time. def get_carrier(segments, slice_id): segments = get_slice_segments(segments, slice_id) with Pool(processes=len(segments)) as pool: distances = pool.map(getDistanceDynamodb, segments) return distances My problem is that i want to cache the dynamoDB item because I am expecting a lot of requests so it would also help to ..
I want to execute the log files that hold the data of two different sensors in a single file in parallel and as sub process. I’ve searched the asyncio and multiprocessing libraries but don’t know where to start. Can you give an idea for a start? Source: Python..
I’m developing a telegram bot in python. I’m using python-telegram-bot and my objetive is make an option that allows me to make the bot consult the price of X currency every X seconds/minutes/hours and return it to me in a message, at the same time the bot must be able to execute other types of ..
I’m trying to parallelize a piece of code given below using the mupltiprocessing module. Everything I try leads to each child process being run one after the other even though they all have different PIDs. I have tried: CentOS and MacOS Context as spawn and as fork Using Queues and using pools Using Apply and ..
In Linux, the multiprocesing module uses fork as the default starting method for a new process. Why is then necessary to pickle the function passed to map? As far as I understand all the state of the process is cloned, including the functions. I can imagine why that’s necessary if spawn is used but not ..