Python multi-threading and multi-process: Reveal the secrets of concurrent programming and improve code performance

Multi-threading and multi-process are the two main ways of Concurrent programming. They both allow the program to perform multiple tasks at the same time, thus Improve program performance. However, there are some differences between them that are important to understand in order to choose the right approach.

Multithreading

Python Using multi-threading

Python, you can use the threading module to create and manage threads. To create a thread, you can use the threading.Thread() function, which requires a callable object as a parameter. For example, the following code creates a simple thread that prints a message in an infinite loop:

import threading

def print_message():
while True:
print("Hello, world!")

thread = threading.Thread(target=print_message)
thread.start()

multiprocessing module to create and manage processes. To create a process, you can use the multiprocessing.Process() function, which requires a callable object as a parameter. For example, the following code creates a simple process that prints a message in an infinite loop:

import multiprocessing

def print_message():
while True:
print("Hello, world!")

process = multiprocessing.Process(target=print_message)
process.start()

concurrencyprogramming in Python, both of which can greatly improve code performance. However, there are some differences between them that are important to understand in order to choose the right approach. For I/O-intensive tasks, you can use multithreading, and for CPU-intensive tasks, you can use multiple processes.

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