This is not something I normally do and to be quite honest in a work environment I wouldn't do this, but I've decided to re-create Moodster using FastAPI.

FastAPI is a small API focused web framework built on top of a few rather large projects:

• Starlette - An ASGI Web Framework
• Pydantic - Data validation using Type hints

There are a few reasons I've done this:

First of all Flask-Restplus was already giving me issues with data validation as mentioned in this post. They didn't seem to have a proper answer for the correct way to do this yet. On top of that I saw how clean it looked with pydantic to use type hints for data validation.

I have also been hearing about many different web frameworks that are now built with asyncio out of the box and thought it would be a good idea to future proof a little by choosing a framework that was capable of this. Realistically I'm not even going to use the async capabilities straight away as I don't think it's necessary for the scope of the project. It is certainly a plus knowing that it is there if I need to boost performance in that way.

Finally back in this blog post I said one of the reasons I didn't opt for a web framework that was ASGI was due to the lack of the ORM libraries not being async capable. Well the project that the starlette web framework is under also has libraries for async capable ORM's. This final piece put me at ease enough to make the switch.

There is a lot of work ahead essentially re-inventing functionality that already exists but it's also going to give me a chance to do things in a slightly better way as I've learnt quite a bit since starting out the Moodster API project.

A while ago I posted a blog post about a hackathon project I did for work. In this project it required me to run multiple SSH sessions to many machines at once to query the state of the system.

Recently I've been listening to a lot of the Talk Python To Me Podcast, and hearing all about the new async features of Python 3. This got me thinking about this project and how this would be the perfect candidate for some async functionality. Why is this?

So we had a fairly large number of machines that we were wanting to run these SSH Commands on and many of those machines were simply not turned on or currently unavailable for SSH connections. This caused an issue as we simply had to wait for the timeout to occur which was down to about 1 second to ensure we gave enough variance for slow network.

During this 1 second window each of the worked threads were simply waiting there counting down the milliseconds. This was extremely inefficient!

So Python introduced the async and await keywords but unfortunately it is likely going to be a while before there are many ORM's that are async capable. This is really handy as I had decided that the API was going to be fairly stateless other than the in memory cache, which means implementing this new approach should be fairly simple.

So I used Flask for the web framework for the API and there is now a drop in replacement being developed called Quart. This enables the async and await functionality into that same Flask development style that everyone loves with Flask.

​Along with Quart is another python package called asyncSSH which allows the use of async and await for SSH Connections.

So the actual changes required to test out this new approach hopefully shouldn't be too much effort.

The big question is will this actually improve performance?

I've just started the API portion of the Moodster project and I wanted to talk a little about my decisions for the tech stack.

I've decided I'm going to stick with Python as my language of choice as I have become fairly proficient with it and it does allow you to get things up and running pretty quickly.

I was tempted to try out  Golang for this as I have heard that it is well suited to api's/services. I decided against that in the end opting for something that I already know. This comes back round to the whole idea of trying to actually get something completed.

So I've been listening to the Talk Python To Me lately and heard a hell of a lot about the new async capabilities of python 3. I've been looking around and found Quart, which is a async capable version of the Flask API. 

I've been really tempted to start off with this but I have now decided against it. At the moment of writing there are only some of the Flask Plugins which are guaranteed to work with Quart and I think picking a framework that is still in its infancy could also end up tripping me back in the long run for the benefit of potentially getting some speed increases.

This seems to scream out the old adage "premature optimisation is the root of all evil".

Secondly from what I can see at the moment there doesn't seem to be a great story on using the SQLAlchemy ORM with async which would be the main usecase/potential speed increase for asycn and await.

I've ended up settling on Flask and the Flask-Restplus plugin as my starting point for this project. Flask Restplus gives you some added functionality for pretty much free when concerned with REST API's.

Some of these are:

• Built in OpenAPI Spec Documentation generation.
• Response Marshalling.
• Request Parsing.

That's my overall starting point with this project, who knows what additional plugins/tools I will venture towards later on.