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26 lines
815 B
Plaintext
26 lines
815 B
Plaintext
import threading
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import time
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import random
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# Create a function to do our computationally expensive work.
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# We'll just simulate a long calculation with time.sleep
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def do_work(number):
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time.sleep(random.random() * 3)
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print(number, 'is done')
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# Using a list comprehension, we create a list of 4 threads that each run the
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# do_work function and pass in a value for its 'number' parameter.
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threads = [threading.Thread(target=do_work, args=(i,)) for i in range(1, 5)]
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# Start execution of all the threads in parallel. They'll likely finish out
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# of order.
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[t.start() for t in threads]
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# 1 is done
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# 3 is done
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# 4 is done
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# 2 is done
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# The main thread is not blocked while the other threads are running. If you
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# want to block the main thread until another thread completes, call join()
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# on the other thread.
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