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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.
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()Run this code and you will see the message "Hello, world!" being printed continuously.
multi-Progress
Using multiple processes in Python
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()Run this code and you will see the message "Hello, world!" being printed continuously.
Comparison of multi-threading and multi-process
Multithreading | multi-Progress | |
---|---|---|
yes | no | |
possible | impossible | |
I/O intensive tasks | CPU intensive tasks | |
threading
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multiprocessing
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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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