Example based on queue documentation:
#!python3
import threading
from queue import Queue
import time
# lock to serialize console output
lock = threading.Lock()
def do_work(item):
time.sleep(.1) # pretend to do some lengthy work.
# Make sure the whole print completes or threads can mix up output in one line.
with lock:
print(threading.current_thread().name,item)
# The worker thread pulls an item from the queue and processes it
def worker():
while True:
item = q.get()
do_work(item)
q.task_done()
# Create the queue and thread pool.
q = Queue()
for i in range(4):
t = threading.Thread(target=worker)
t.daemon = True # thread dies when main thread (only non-daemon thread) exits.
t.start()
# stuff work items on the queue (in this case, just a number).
start = time.perf_counter()
for item in range(20):
q.put(item)
q.join() # block until all tasks are done
# "Work" took .1 seconds per task.
# 20 tasks serially would be 2 seconds.
# With 4 threads should be about .5 seconds (contrived because non-CPU intensive "work")
print('time:',time.perf_counter() - start)
Output:
Thread-3 2
Thread-1 0
Thread-2 1
Thread-4 3
Thread-3 4
Thread-1 5
Thread-2 6
Thread-4 7
Thread-3 8
Thread-1 9
Thread-2 10
Thread-4 11
Thread-3 12
Thread-1 13
Thread-2 14
Thread-4 15
Thread-1 17
Thread-3 16
Thread-2 18
Thread-4 19
time: 0.5017914706686906
