How Can I Run Python Functions Concurrently Using Multiprocessing?

How to Execute Functions Concurrently in Python

Introduction

In Python, it can be desirable to execute multiple functions simultaneously to optimize performance, especially when the functions are independent and do not interfere with each other. This article explores techniques for running functions in parallel.

Using Threads and Multiprocessing

Due to limitations of the CPython interpreter, threading may not provide true parallelism. Multiprocessing, however, generally offers better performance.

Example Implementation

Consider the following example where we wish to run two functions, func1 and func2, in parallel:

def func1():
    # Some code

def func2():
    # Some code

To run these functions concurrently using multiprocessing, we can use the following steps:

1. Create Process objects for each function:

   p1 = Process(target=func1)
   p2 = Process(target=func2)

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2. Start the processes:

   p1.start()
   p2.start()

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3. Wait for the processes to complete:

   p1.join()
   p2.join()

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Encapsulation

To simplify the process of running functions in parallel, we can define a utility function:

def runInParallel(*fns):
    # Start the processes
    for fn in fns:
        p = Process(target=fn)
        p.start()

    # Wait for the processes to finish
    for p in fns:
        p.join()

Using this function, we can now run the two functions concurrently with ease:

runInParallel(func1, func2)

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