Книга: Learning Concurrency in Python
Назад: Context manager
Дальше: Output


This time, we'll define a different task that takes in a variable n as input just to give you a simple demonstration of how we can do this. The task function just prints out that it's processing ‘n', and nothing more.

Within our main function, we utilize our ThreadPoolExecutor as a context manager, and then call future = executor.submit(task, (n)) three times in order to give our thread pool something to do:

from concurrent.futures import ThreadPoolExecutor

def task(n):
print("Processing {}".format(n))

def main():
print("Starting ThreadPoolExecutor")
with ThreadPoolExecutor(max_workers=3) as executor:
future = executor.submit(task, (2))
future = executor.submit(task, (3))
future = executor.submit(task, (4))
print("All tasks complete")

if __name__ == '__main__':
Назад: Context manager
Дальше: Output

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