Only once everything is cooked, prepared, and layered can you place the last piece of toast onto your sandwich, slice it (optional), and eat it.īecause it requires you to perform multiple tasks at the same time, making a BLT is inherently a concurrent process, even if you are not giving your full attention to each of those tasks all at once. Once your bread is done toasting, you apply to it your sandwich spread of choice, and then you can start layering on your tomatoes, lettuce, and then, once it's done cooking, your bacon. As pieces get finished, you pull them out and place them on a plate. While it's toasting, you continue checking on your bacon. All the while, you continue checking on and occasionally flipping over your bacon.Īt this point, you've started a task, and then started and completed two more in the meantime, all while you're still waiting on the first.Įventually you put your bread in a toaster. While the bacon's cooking, you can get out your tomatoes and lettuce and start preparing (washing and cutting) them. First, you'll want to throw the bacon in a pan on medium-low heat. If that was confusing to you, let's instead think of an analogy: Say you want to make a BLT. Tasks start asynchronously, get performed asynchronously, and then finish asynchronously. Once one task is finished, it switches again to an unfinished task until they have all been performed. Instead, a process might start, then once it's waiting on a specific instruction to finish, switch to a new task, only to come back once it's no longer waiting. This is a bit misleading though, as the tasks may or may not actually be performed at exactly the same time. What's the difference between multiprocessing, asyncio, and concurrency.futures?Īn effective definition for concurrency is "being able to perform multiple tasks at once".When should you use multiprocessing vs asyncio or threading?.Is it possible to combine asyncio with multiprocessing?.What's the difference between concurrency and parallelism?.When should you use threading, and when should you use asyncio?.Why is the asyncio method always a bit faster than the threading method?.What does it mean when something is non-blocking?.Recap: When to use multiprocessing vs asyncio or threadingīy the end of this article, you should be able to answer the following questions:.To work through the examples in this article, you should already know how to work with HTTP requests. You can find all the code examples from this article in the concurrency-parallelism-and-asyncio repo on GitHub. The last portion of this article will compare Python's implementation of async/ await with how other languages have implemented them. Whether you're dealing with external web resources, reading from and writing to multiple files, or need to use a calculation-intensive function multiple times with different parameters, this article should help you maximize the efficiency and speed of your code.įirst, we'll delve into what concurrency and parallelism are and how they fit into the realm of Python using standard libraries such as threading, multiprocessing, and asyncio. They allow your programs to do multiple things at once, either at the same time or by wasting the least possible time waiting on busy tasks. That's where concurrency and parallelism fit in. Sometimes, however, it's due to forces outside of our control, such as hardware constraints or the quirks of networking. Sometimes this is due to poor algorithmic design or the wrong choice of data structure. There are many reasons your applications can be slow. What are concurrency and parallelism, and how do they apply to Python?
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