python-scipyHow can I use Python and SciPy to implement multithreading?
Python and SciPy can be used to implement multithreading. The threading module can be used to create threads, and the multiprocessing module can be used to manage the threads.
Example code
import threading
def thread_function():
print("Thread function")
if __name__ == "__main__":
thread = threading.Thread(target=thread_function)
thread.start()
thread.join()
print("Thread finished")
Output example
Thread function
Thread finished
The code above creates a thread, starts it, and waits for the thread to finish. The thread_function will be executed in the thread, and when it is done, the main thread will print "Thread finished".
Code explanation
- import threading - imports the threading module
- def thread_function(): - defines the thread function that will be executed in the thread
- thread = threading.Thread(target=thread_function) - creates a thread, with the thread_function as the target
- thread.start() - starts the thread
- thread.join() - waits for the thread to finish
- print("Thread finished") - prints "Thread finished" when the thread is done
Helpful links
More of Python Scipy
- How do I create a 2D array of zeros using Python and NumPy?
- How do I use Python XlsxWriter to write a NumPy array to an Excel file?
- How can I use Python Scipy to perform a wavelet transform?
- How can I check if a certain version of Python is compatible with SciPy?
- How can I use Python and SciPy to generate a uniform distribution?
- How do I use the NumPy transpose function in Python?
- How do I use the scipy ttest_ind function in Python?
- How do I use Python and SciPy to create a tutorial PDF?
- How can I use Python and SciPy to visualize data?
- How do I use the trapz function in Python SciPy?
See more codes...