You've built, tested, and automated your Python code. The final step is making it fast and getting it online. Many real programs spend most of their time waiting on networks, databases, and files, and asynchronous programming lets them do other work during that wait.
You'll start with asyncio: coroutines, the event loop, and the
async/await syntax for writing concurrent code. Then you'll learn
Docker, which packages your app and everything it needs into a container that
runs the same way on any machine, and see how to containerize a Python web API.
Finally, you'll deploy a container to production.
Once you finish this module, you're ready to put everything together in the Projects section.
How asynchronous Python works: async and await, running tasks concurrently, making API calls without blocking, and turning slow synchronous code into concurrent code.
What Docker is and why it matters: images and containers, essential commands, Docker Compose, volumes, and building your own image.
How to build a small FastAPI app and package it into a Docker container, step by step.
How to take your container from your machine to a production server and run it there.