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Queue

As explained in Python Concurrency with asyncio

A queue is a data structure that holds items for processing in an ordered sequence, typically first in first out.

A queue holds work items in first-in, first-out order: the item added first is the first one removed. Like a checkout line, items join at the end and leave from the front. section 12.1

An asynchronous queue lets multiple workers take available items concurrently. A bounded queue also limits how many items can wait or how much work proceeds at once. section 12.1 section 12.1.1

Queues solve two practical coordination problems:

  • They distribute work among workers, such as cashiers processing customers from one checkout line. section 12.1
  • They move slow operations into background tasks, allowing a web endpoint to respond before order processing finishes. section 12.1.1
  • They can apply backpressure: putting into a full bounded queue waits or raises an exception, depending on the method used. section 12.1.1

Background order processing

An aiohttp endpoint places an order on an asyncio.Queue and immediately acknowledges it. Worker tasks retrieve orders, simulate slow processing, and call task_done(); limiting the queue and worker count controls load on the order system. section 12.1.1

How Python Concurrency with asyncio covers it

How deep it goes
Defines FIFO behavior and demonstrates asyncio workers, bounded queues, coroutine methods, and web integration.
Examples
Uses supermarket checkout, variable product times, bounded queues, and aiohttp order processing as concrete examples.
What it assumes
Assumes asynchronous programming basics while teaching FIFO behavior through a grocery checkout analogy.
What you can do after
Build it with asyncio.Queue, worker tasks, coroutine methods, and aiohttp background processing.
How it connects
Connects queues with asynchronous programming, concurrency, worker tasks, background processing, web applications, and data persistence.

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This explainer was generated by Manning's knowledge graph from the text of Python Concurrency with asyncio. The section links point to the parts of the book it draws on.