This is the final article in our comprehensive series on asynchronous programming. We've learned how to create and run concurrent tasks, but with this power comes new challenges. One of the most notorious problems in any concurrent system is the deadlock.
Welcome to the final chapter of our advanced Python section. We are about to tackle asynchronous programming, a powerful paradigm for writing concurrent code that can significantly boost the performance of certain types of applications.
We've seen how to create individual tasks with asyncio.create_task() and then await them. This is a great way to start multiple background jobs. However, it can be a bit verbose if you just want to run a list of coroutines concurrently and wait for all of them to finish.