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Building Large Flask Apps In The Real World

Scaling a Flask application is no immediately obvious matter. At we had ~22,000 line Flask application. At my previous employer our Flask application was significantly larger. Ultimately scaling a code-base is less about the framework used and more about the software design experience of the developers working on it. Scaling in terms concurrent users also has little to do with the web framework and more to do with your understanding of load-balancing, caching, databases, etc. That being said, what have I learned about how to organize a Flask application to comfortably grow?

Firstly, fbone and flask-bones are great first approximations. If you're struggling to figure out how to structure your flask application have a look at those and consider using either one as a template that you can evolve to your needs. Also, I have to mention cookiecutter as a tool for templating the structure of python applications in general. In terms of the web application itself you might also consider using Flask-Classy to build out your views.

Beyond that I hestitate to dictate anything else. There's never a one-size-fits-all solutions for complex real-world problems like this. There will never be a substitute for thinking up-front, and deeply at that, about the organization of your application. The first few organizational decisions will have ripple effects throughout the lifetime of the code base. Bad decisions can trap you into a corner. Good decisions can make previously difficult problems much easier. So instead here are a few heuristics that I've used to kickstart this process:

  1. Think about deployment. How is it getting to the server? egg, wheel, rpm? Will there be continuous integration? Are you using salt or puppet? How you deploy your application will determine what kind of structure you need and what kind of supporting utilites you may or may not have to write.
  2. Think about app initialization. Where is the entry point? How are components initialized and shared? If my user module needs a database connection how do I ensure that it always gets an initialized database connection? Do I use singletons? lazy loading? dependency injection? It depends, and you should always be willing to revisit this decision. Also think about how you'd do a deploy to a completely uninitailized environment. How do you initialize the database(s)? Is the app configured by environment variables or cfg files? How are those being shared and deployed?
  3. Think about resource lifetimes. Make sure you understand how your database connections and other resources should be managed within a Flask application. Typically you should initialize a resource when a request comes in and tear it down before the response goes out. SQLAlchemy explicitly covers integration with web frameworks in its documentation.
  4. Organize by principle of least suprise. Ask yourself, "How would I organize this so that someone using Notepad with a good grasp on the programming language would be able to find and edit any arbitrary component?" This is ultimately how your codebase will seem to every new person who encounters it. For example, if you are asked to modify the function that geocodes a location and you have no experience with a code base it's reasonable that you'd look in app.geolocation.utils as a first approximation. You'd be suprised if instead it were somewhere like app.auth.models. The first example follows the principle of least surprise. Reduce the mental strain on yourself and others by sensibly organizing components into well named modules.
  5. Think about testing. A focus on testing can help you avoid sticky designs because they simply become untestable. Organize your tests along the same lines as your modules so that the corresponding tests for any chunk of code can easily be found.
  6. Think about logging. Bugs are going to happen and you're going to need to gather the information to solve them. Come up with a logging strategy that covers your whole application and stick to it. You should be able to log data from anywhere in any module and the logs should indicate exactly where the data came from. In Python the best way to do this is to initialize a logger at the top of each .py file, that way you always have access to a logger from every module.
  7. Think about infrastructure changes. One of the best design heuristics you can use is to imagine how you would build your application so that arbitrary third-party dependencies (databases, web frameworks, etc.) could be swapped out with minimal impact. As your application grows your infrastructure will change. You should be able to switch databases, web frameworks, or deploy code to mobile devices with minimal code changes. A good place to start in figuring out how to do this is the Architecture The Lost Years talk by Bob Martin.

Each of these topics could easily fill a blog post on its own. With Flask in particular (2), (3), and (6) are crucial. Flask isn't like Ruby on Rails for a reason. Flask is designed to be easy to get up and running. It also puts you closer to WSGI. This, however, is a double-edged sword. It can make development easier in areas where you know what you're doing while also making it easy to shoot yourself in the foot in the areas where you don't.

In the end you should be aiming to design your application to depend on Flask as little as possible. The framework shouldn't dictate your application design, and microframeworks in particular try to avoid doing this as much as possible. Recently even Flask has felt bulky. Falcon seems like a good step in the direction of something smaller.