What is the best way to run functions in parallel in Python?

Python
#1

I have a scenario where I need to execute multiple functions simultaneously to improve the performance of my program. I am familiar with the concept of parallel processing, but I am not sure how to implement it in Python.

Here is an example of what I have tried so far:


import multiprocessing

def function1():
    # Code for function1

def function2():
    # Code for function2

def function3():
    # Code for function3

# Create Process objects for each function
process1 = multiprocessing.Process(target=function1)
process2 = multiprocessing.Process(target=function2)
process3 = multiprocessing.Process(target=function3)

# Start the processes
process1.start()
process2.start()
process3.start()

# Wait for all processes to finish
process1.join()
process2.join()
process3.join()

Although this code runs the functions in parallel, I am encountering some challenges. For instance, I am unsure how to handle the return values from each function or properly synchronize access to shared resources.

I would greatly appreciate it if someone could provide guidance on the most effective way to run functions in parallel. Specifically, I would like to know:

  1. How can I handle the return values from parallel functions?
  2. What is the best approach for managing shared resources and avoiding conflicts?
  3. Are there any performance considerations or best practices I should be aware of when working with parallel processing in Python?

If anyone could offer assistance or provide relevant code examples, I would be grateful. Thank you!