Multithreading and multiprocessing are two techniques used in Python to achieve concurrency and parallelism, which can help improve the performance of certain types of applications.
## Multithreading
Multithreading is the technique of running multiple threads of execution within the same process. Each thread runs independently and can perform its own set of operations. Python provides a built-in `threading` module that you can use to create and manage threads.
Here’s an example of how to create a thread in Python:
python
import threading
def my_function():
print("Hello from thread")
# Create a thread and start it
thread = threading.Thread(target=my_function)
thread.start()
# Wait for the thread to finish
thread.join()
In this example, we define a function called `my_function` that prints a message. We then create a thread using the `Thread` class from the `threading` module, passing in the `target` argument as the function to run in the thread. We start the thread using the `start()` method, and then wait for it to finish using the `join()` method.
## Multiprocessing
Multiprocessing is the technique of using multiple processes to achieve parallelism. Each process runs independently and can perform its own set of operations. Python provides a built-in `multiprocessing` module that you can use to create and manage processes.
Here’s an example of how to create a process in Python:
python
import multiprocessing
def my_function():
print("Hello from process")
# Create a process and start it
process = multiprocessing.Process(target=my_function)
process.start()
# Wait for the process to finish
process.join()
In this example, we define a function called `my_function` that prints a message. We then create a process using the `Process` class from the `multiprocessing` module, passing in the `target` argument as the function to run in the process. We start the process using the `start()` method, and then wait for it to finish using the `join()` method.
## Differences between Multithreading and Multiprocessing
The main difference between multithreading and multiprocessing is that multithreading uses multiple threads within a single process, while multiprocessing uses multiple processes. This means that multiprocessing can take advantage of multiple CPU cores, while multithreading is limited to a single CPU core.
In general, multiprocessing is more scalable and can achieve higher levels of parallelism, but it can also be more complex to use and may have higher overhead due to the creation of multiple processes. Multithreading is simpler to use and may have lower overhead, but it may not scale as well and can be more prone to issues such as deadlocks and race conditions.
Overall, the choice between multithreading and multiprocessing depends on the specific requirements of your application and the resources available on your system.