Welcome to Part 3, where you will move to the next crucial step—setting up a Django application. Just like following a simple recipe, you will walk through the foundational steps to create the Django project and app that will host your data engine.
You will begin by setting up a virtual environment, installing Django, and starting a new project named backend. This will serve as the core of your web application. Once Django is installed, you use the command django-admin startproject backend to create the initial project folder, and inside it, you create a new app named base.
With our project structure set, you will move your previously developed data engine (which generates football match data) into the newly created app. You then ensure that the necessary configurations, like paths, are correctly aligned so that the app can run within Django’s structure.
Next, you will adjust the settings in the settings.py file to include the base app. You will also introduce static and media URL configurations, ensuring Django can handle those assets down the road. After configuring your app, you will run migrations to set up the database (though empty for now) and create a superuser for admin control. At this point, the basic admin and API URLs are functional, including the ability to run the Django development server and test the application locally.
For the API, you begin by creating basic views in views.py. Initially, you will set up a simple "Hello World" response for the /api endpoint and for /api/dashboard, and create a placeholder for future dashboard data. This lays the foundation for integrating the actual match data from our engine.
Finally, you will introduce the Django REST Framework to your project. This framework will enable you to serve data through an API. You install and configure it within Django, preparing your app to handle future GET requests for dashboard data and making it available to users via a RESTful interface.
By the end of this post, you should have a fully functioning Django app that serves as the foundation for future steps—embedding live data forecasts from our engine and delivering them via the Django REST API.