I wrote a little program to check a bunch of hashes, and I was wondering if this is a correct application of starmap and if it should be making other processes. My current understanding is that starmap is supposed to divide the task amongst the workers, but it doesn’t seem to do it. Python apparently has 9 processes open, but
Tag: python-multiprocessing
python multiprocessing.Array typing
When creating an array, I want to put it inside a dataclass, but I cannot find the type of the returned object. arr = multiprocessing.RawArray(“i”, 2) If I do: but multiprocessing.sharedctypes.c_long_Array_2 does not exists. How can I use type hints, e.g arr: the_type with multiprocessing Array? UPDATE Pycharm example when using typing ctypes.c_long * 2, there’s still a value attribute
`SolverResults Error` When Parallelising Pyomo Optimisations
I’m trying to optimise multiple linear programming problems in parallel using Pyomo and the standard Python multiprocessing library. When switching to using multi-processing I keep running into the error: ValueError: Cannot load a SolverResults object with bad status: error. A similar issue was reported in this question, where their problem seemed to be that the solver (n.b. they used cbc
Quit Python QR Scanner when no code is detected but keep running while processing the code
I’m creating a python script that scans QR codes, and then processes the info in the code. The python-script will launch every few seconds via a timer in systemd on RBPI, but while scanning for a code – if no code has been detected in 5 seconds, the script should terminate. However, if a code is detected, the processing should
Trying to optimize a Python for loop for large data set (4 million rows)
I’m new to Python and getting used to these really handy implicit array/list actions, so please bear with me. I’ve completed a proof-of-concept code (120 combinations), but as expected it is experiencing a significant slowdown when working against the full dataset (4 million combinations). The current slowdown is in the following for loop: I’m trying not to make this a
Issue when importing kivy.core.window and using the multiprocessing library
First of all, I’d like to clarify that I have absolutely 0 background as a software engineer and this is the first time I’m using python for something besides API’s and creating excel/plots. My issue is that I was trying to create an app using kivy and then I imported the kivy.core.window library a blank screen appears. I’ve seen that
what is the underlying process of python multiprocess queue?
Does anyone explain the python multiprocessing queue communication in detail? What’s happening when the parameter been put into the queue? I have a snippet of code, which is confusing me. and the output is: why do I have this inconsistency? I see the doc saying ” When an object is put on a queue, the object is pickled and a
Create a new list of dictionary from the index in dataframe Python with the fastest way
I have a ~200mil data in dictionary index_data: Key is a value in CustId and Value is an index of CustID in df_data: I have a DataFrame df_data: NOTE: If CustID is duplicate, only column Score have different data in each row I want to create a new list of dict(Total_Score is an avg Score of each CustID, Number is
Python thread.join(timeout) not timing out
I am using threading python module. I want to execute a function which runs an expression entered by a user. I want to wait for it to finish execution or until a timeout period is reached. The following code should timeout after 5 second, but it never times out. Why is this and how can I fix this behaviour? Should
Process a function on different arguments in parallel in Python
This is my simple code where I want to run printRange() in parallel: My question is different from this SO question as here, the each process is hardcoded, started and finally joined. I want to run printRange() in parallel with say 100 other printRange() worker functions. Hardcoding each time is not feasible. How could this be done? Answer Using multiprocessing