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Since Python 3.4, there has been inbuilt support for asynchronous programming in Python. Unfortunately, the Asyncio library has received a lot of criticism, with much of this criticism being rather unjust. These days many of the asynchronous web frameworks and database tools out there require little interaction with the underlying Asyncio library and simply require an understanding of the async await syntax. In this post, we are going to go into how you can use the Asyncio library in a more general sense. As pointed out by Yury Selivanov except ClientError: return url, 'Unable to reach URL' else: return url, resp             resp = await resp.text()         except ClientError:             return url, 'Unable to reach URL'         else: We are going to use the same simple function throughout the following examples. The function simply creates a client and makes a http request. This simple function will help us demonstrate the different ways we can use the underlying Asyncio library. The helper function pulls in a dependency, namely Aiohttp and will be used throughout the following examples. Note that we aren’t properly handling errors here and simply pas*ing back a string stating the request returned an exception. Any production code would need to do a better job with If we need to collect a group of results before proceeding with our script or program, using as completed can be a good option. This allows us to asynchronously run a number of coroutines at once, with the results being returned when they are ready. An example can be However, this is not always appropriate as we may have to wait a long time to receive all of the returned results particularly if the list of URLs we wanted to retrieve was particularly large. If we want to run a group of coroutines and gather the results, as completed gives Asyncio also has the concept of futures this means that you can register code to run after an asynchronous function has completed.