Python Thread Priority: Managing Queues with PriorityQueue and Queue Module
Discover how to manage thread priority in Python using the PriorityQueue class from the queue module. Learn how to safely exchange information between threads and control task priority with methods like get(), put(), qsize(), empty(), and full().
Python - Thread Priority
The queue
module in Python's standard library is useful in threaded programming when information must be exchanged safely between multiple threads. The PriorityQueue
class in this module implements all the required locking semantics.
With a priority queue, the entries are kept sorted (using the heapq
module) and the lowest valued entry is retrieved first.
The Queue objects have the following methods to control the queue:
get()
- Removes and returns an item from the queue.put()
- Adds an item to the queue.qsize()
- Returns the number of items that are currently in the queue.empty()
- ReturnsTrue
if the queue is empty; otherwise,False
.full()
- ReturnsTrue
if the queue is full; otherwise,False
.
Priority Queue Constructor
queue.PriorityQueue(maxsize=0)
This is the constructor for a priority queue. maxsize
is an integer that sets the upper limit on the number of items that can be placed in the queue. If maxsize
is less than or equal to zero, the queue size is infinite.
The lowest valued entries are retrieved first (the lowest valued entry is the one that would be returned by min(entries)
). A typical pattern for entries is a tuple in the form:
(priority_number, data)
Example
This example demonstrates the usage of a priority queue:
Code
from time import sleep
from random import random, randint
from threading import Thread
from queue import PriorityQueue
queue = PriorityQueue()
def producer(queue):
print('Producer: Running')
for i in range(5):
value = random()
priority = randint(0, 5)
item = (priority, value)
queue.put(item)
queue.join()
queue.put(None)
print('Producer: Done')
def consumer(queue):
print('Consumer: Running')
while True:
item = queue.get()
if item is None:
break
sleep(item[1])
print(item)
queue.task_done()
print('Consumer: Done')
producer = Thread(target=producer, args=(queue,))
producer.start()
consumer = Thread(target=consumer, args=(queue,))
consumer.start()
producer.join()
consumer.join()
Output
Producer: Running
Consumer: Running
(0, 0.15332707626852804)
(2, 0.4730737391435892)
(2, 0.8679231358257962)
(3, 0.051924220435665025)
(4, 0.23945882716108446)
Producer: Done
Consumer: Done