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Python
docs.python.org › 3 › library › queue.html
queue — A synchronized queue class
February 23, 2026 - Source code: Lib/queue.py The queue module implements multi-producer, multi-consumer queues. It is especially useful in threaded programming when information must be exchanged safely between multip...
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Real Python
realpython.com › ref › stdlib › queue
queue | Python Standard Library – Real Python
import logging import queue import threading import time logging.basicConfig(level=logging.INFO, format="%(threadName)s %(message)s") def worker(tasks): while True: task = tasks.get() if task is None: tasks.task_done() break logging.info(f"processing {task}") time.sleep(1) tasks.task_done() tasks = queue.Queue() for task in ["task1", "task2", "task3", "task4", "task5"]: tasks.put(task) num_workers = 2 for _ in range(num_workers): tasks.put(None) threads = [ threading.Thread(target=worker, args=(tasks,)) for _ in range(num_workers) ] for thread in threads: thread.start() tasks.join() for thread in threads: thread.join() # Output: # Thread-1 (worker) processing task1 # Thread-2 (worker) processing task2 # Thread-1 (worker) processing task3 # Thread-2 (worker) processing task4 # Thread-1 (worker) processing task5
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Python
docs.python.org › 3 › library › asyncio-queue.html
Queues — Python 3.14.4 documentation
February 22, 2026 - Source code: Lib/asyncio/queues.py asyncio queues are designed to be similar to classes of the queue module. Although asyncio queues are not thread-safe, they are designed to be used specifically i...
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GeeksforGeeks
geeksforgeeks.org › python › queue-in-python
Queue in Python - GeeksforGeeks
December 11, 2025 - Explanation: popleft() efficiently removes the first element without shifting, making deque ideal for queues. Python’s queue module provides a thread-safe FIFO queue. You can specify a maxsize.
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W3Schools
w3schools.com › python › ref_module_queue.asp
Python queue Module
Python Examples Python Compiler Python Exercises Python Quiz Python Challenges Python Practice Problems Python Server Python Syllabus Python Study Plan Python Interview Q&A Python Bootcamp Python Certificate Python Training · ❮ Standard Library Modules · Create a FIFO queue, put an item, then get it back: import queue q = queue.Queue() q.put('task1') print(q.get()) Try it Yourself » ·
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W3Schools
w3schools.com › python › python_dsa_queues.asp
Queues with Python
Queues are often mentioned together with Stacks, which is a similar data structure described on the previous page. For Python lists (and arrays), a Queue can look and behave like this:
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Medium
basillica.medium.com › working-with-queues-in-python-a-complete-guide-aa112d310542
Working with Queues in Python — A Complete Guide | by Basillica | Medium
March 27, 2024 - Python provides a queue module in the standard library that has different queue implementations for programmers to use in their applications.
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Real Python
realpython.com › queue-in-python
Python Stacks, Queues, and Priority Queues in Practice – Real Python
December 1, 2023 - To get the most out of this tutorial, you should be familiar with Python’s sequence types, such as lists and tuples, and the higher-level collections in the standard library. You can download the complete source code for this tutorial with the associated sample data by clicking the link in the box below: Get Source Code: Click here to get access to the source code and sample data that you’ll use to explore queues in Python.
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O'Reilly
oreilly.com › library › view › python-standard-library › 0596000960 › ch03s03.html
The Queue Module - Python Standard Library [Book]
May 10, 2001 - File: queue-example-1.py import threading import Queue import time, random WORKERS = 2 class Worker(threading.Thread): def _ _init_ _(self, queue): self._ _queue = queue threading.Thread._ _init_ _(self) def run(self): while 1: item = self._ _queue.get() if item is None: break # reached end of queue # pretend we're doing something that takes 10—100 ms time.sleep(random.randint(10, 100) / 1000.0) print "task", item, "finished" # # try it queue = Queue.Queue(0) for i in range(WORKERS): Worker(queue).start() # start a worker for i in range(10): queue.put(i) for i in range(WORKERS): queue.put(None) # add end-of-queue markers task 1 finished task 0 finished task 3 finished task 2 finished task 4 finished task 5 finished task 7 finished task 6 finished task 9 finished task 8 finished
Author   Fredrik Lundh
Published   2001
Pages   304
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Runestone Academy
runestone.academy › ns › books › published › pythonds › BasicDS › ImplementingaQueueinPython.html
4.12. Implementing a Queue in Python — Problem Solving with Algorithms and Data Structures
CodeLens 1 shows the Queue class in action as we perform the sequence of operations from Table 1. Activity: CodeLens Example Queue Operations (ququeuetest)
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RQ
python-rq.org
RQ: Simple job queues for Python
from rq.repeat import Repeat # Repeat job 3 times after successful completion, with 60 second intervals job = queue.enqueue(say_hello, repeat=Repeat(times=3, interval=60)) # Use different intervals between repetitions job = queue.enqueue(say_hello, repeat=Repeat(times=3, interval=[10, 30, 60]))
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Simplilearn
simplilearn.com › home › resources › software development › queue in python: working with queue data structure in python
Queue in Python: Working With Queue Data Structure in Python
March 5, 2026 - A queue is a built-in module of python used in threaded programming. It stores items sequentially in a FIFO manner. Learn all about the queue in python now!
Address   5851 Legacy Circle, 6th Floor, Plano, TX 75024 United States
Top answer
1 of 2
23

The for loop is launching a number of worker threads to perform the function defined by "worker". Here is working code that should run on your system in python 2.7.

import Queue
import threading

# input queue to be processed by many threads
q_in = Queue.Queue(maxsize=0)

# output queue to be processed by one thread
q_out = Queue.Queue(maxsize=0)

# number of worker threads to complete the processing
num_worker_threads = 10

# process that each worker thread will execute until the Queue is empty
def worker():
    while True:
        # get item from queue, do work on it, let queue know processing is done for one item
        item = q_in.get()
        q_out.put(do_work(item))
        q_in.task_done()

# squares a number and returns the number and its square
def do_work(item):
    return (item,item*item)

# another queued thread we will use to print output
def printer():
    while True:
        # get an item processed by worker threads and print the result. Let queue know item has been processed
        item = q_out.get()
        print "%d squared is : %d" % item
        q_out.task_done()

# launch all of our queued processes
def main():
    # Launches a number of worker threads to perform operations using the queue of inputs
    for i in range(num_worker_threads):
         t = threading.Thread(target=worker)
         t.daemon = True
         t.start()

    # launches a single "printer" thread to output the result (makes things neater)
    t = threading.Thread(target=printer)
    t.daemon = True
    t.start()

    # put items on the input queue (numbers to be squared)
    for item in range(10):
        q_in.put(item)

    # wait for two queues to be emptied (and workers to close)   
    q_in.join()       # block until all tasks are done
    q_out.join()

    print "Processing Complete"

main()

Python 3 version per @handle

import queue 
import threading

# input queue to be processed by many threads
q_in = queue.Queue(maxsize=0) 

# output queue to be processed by one thread
q_out = queue.Queue(maxsize=0) 

# number of worker threads to complete the processing
num_worker_threads = 10

# process that each worker thread will execute until the Queue is empty
def worker():
    while True:
        # get item from queue, do work on it, let queue know processing is done for one item
        item = q_in.get()
        q_out.put(do_work(item))
        q_in.task_done()

# squares a number and returns the number and its square
def do_work(item):
    return (item,item*item)

# another queued thread we will use to print output
def printer():
    while True:
        # get an item processed by worker threads and print the result. Let queue know item has been processed
        item = q_out.get()
        print("{0[0]} squared is : {0[1]}".format(item) )
        q_out.task_done()

# launch all of our queued processes
def main():
    # Launches a number of worker threads to perform operations using the queue of inputs
    for i in range(num_worker_threads):
         t = threading.Thread(target=worker)
         t.daemon = True
         t.start()

    # launches a single "printer" thread to output the result (makes things neater)
    t = threading.Thread(target=printer)
    t.daemon = True
    t.start()

    # put items on the input queue (numbers to be squared)
    for item in range(10):
        q_in.put(item)

    # wait for two queues to be emptied (and workers to close)   
    q_in.join()       # block until all tasks are done
    q_out.join()

    print( "Processing Complete" )

main()
2 of 2
3

You can think of the number of worker threads as the number of bank tellers at a bank. So people (your items) stand in line (your queue) to be processed by a bank teller (your worker thread). Queues are actually an easy and well understood mechanism to manage complexities in threads.

I have adjusted your code a bit to show how it works.

import queue
import time
from threading import Thread

def do_work(item):
    print("processing", item)

def source():
    item = 1
    while True:
        print("starting", item)
        yield item
        time.sleep(0.2)
        item += 1

def worker():
    while True:
        item = q.get()
        do_work(item)
        q.task_done()

q = queue.Queue(maxsize=0)
def main():
    for i in range(2):
        t = Thread(target=worker)
        t.daemon = True
        t.start()

    for item in source():
        q.put(item)

    q.join()       # block until all tasks are done

main()
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AskPython
askpython.com › home › python queue module
Python Queue Module - AskPython
February 26, 2020 - In Python, we can use the queue module to create a queue of objects. This is a part of the standard Python library, so there’s no need to use pip.
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GitHub
github.com › scrapy › queuelib
GitHub - scrapy/queuelib: Collection of persistent (disk-based) and non-persistent (memory-based) queues for Python
Collection of persistent (disk-based) and non-persistent (memory-based) queues for Python - scrapy/queuelib
Starred by 289 users
Forked by 55 users
Languages   Python 100.0% | Python 100.0%
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Built In
builtin.com › data-science › priority-queues-in-python
Introduction to Priority Queues in Python | Built In
A queue in Python is a data structure that follows a first-in-first-out (FIFO) order, in which items are taken out or accessed on a first-come-first-served basis. An example of a queue would be a line at a movie ticket stand.
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GitHub
github.com › rq › rq
GitHub - rq/rq: Simple job queues for Python · GitHub
from rq import cron from myapp import send_newsletter, backup_database # Database backup every day at 3:00 AM cron.register( backup_database, queue_name='maintenance', cron_string='0 3 * * *' ) # Monthly report on the first day of each month at 8:00 AM cron.register( generate_monthly_report, queue_name='reports', cron_string='0 8 1 * *' ) ```python More details on functionality can be found in the [docs](https://python-rq.org/docs/cron/).
Starred by 10.6K users
Forked by 1.5K users
Languages   Python
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Microsoft Learn
learn.microsoft.com › en-us › azure › storage › queues › storage-quickstart-queues-python
Quickstart: Azure Queue Storage client library for Python - Azure Storage | Microsoft Learn
June 29, 2023 - In your console window, navigate ... Storage client library - Python quickstart sample Creating queue: quickstartqueues-<UUID> Adding messages to the queue......
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Intellipaat
intellipaat.com › home › blog › queue in python – implementation explained
Queue in Python: How to Implement Queue in Python
October 14, 2025 - There are Four types of queues in Python. They are: ... In the first-in-first-out queue, the first tasks added are the first retrieved. It is just like putting the element inside an open cylinder. Before we move ahead, we need to import one library called a queue.