All Types of the Python Queue Explained

How to use a queue in Python

To start building Python queues, you need to import the queue Python module first:

import queue

Python 1.4 and all the newer versions have this module available for use. It allows you to implement Python multithreading queues:

• To add an element to the queue, use put(). This is called an enqueue operation.
• To remove an element from the queue, use get(). This is called a dequeue operation.
• The FIFO (First In, First Out) principle means the first element you insert will also be the first to be removed.

By using the maxsize argument, you can choose to restrict the number of elements in a queue. To leave the size unlimited, define it as 0 or a negative number.

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Python queue examples: four types

To create a basic Python queue, use queue.Queue():

BitDegree = queue.Queue(maxsize=0) 
  
BitDegree.put("B")
BitDegree.put("i")
BitDegree.put("t")

print (BitDegree.get())

You can also create a queue in Python that follows the LIFO principle (Last In, First Out). In such a case, the first element to remove will be the one that got added last. To do that, use queue.LifoQueue():

import queue

BitDegree = queue.LifoQueue(maxsize=0) 
  
BitDegree.put("B")
BitDegree.put("i")
BitDegree.put("t")

print (BitDegree.get())

If you need to sort your elements in a specific way, you can also create a priority queue. For that, you would use queue.PriorityQueue(). In such a case, the first element to remove will be the one that has the lowest value:

BitDegree = queue.PriorityQueue(maxsize=0) 
  
BitDegree.put((3, "B"))
BitDegree.put((1, "i"))
BitDegree.put((2, "t"))

print (BitDegree.get())

If you're using Python 3.7 or a newer version, you can also use queue.SimpleQueue() to create simple Python queues with less functionalities – e.g, they will not allow task tracking:

BitDegree = queue.SimpleQueue(maxsize=0) 
  
BitDegree.put("B")
BitDegree.put("i")
BitDegree.put("t")

Python queue: useful tips

• To simplify working with priority queues, follow the number, element pattern and use the number to define priority.
• To create Python multiprocessing queues (as opposed to multithreading), use multiprocessing.Queue() function for the multiprocessing module.