This project contains a very simple web based application for controlling a Fan. This was my first time creating a web app and as such is not the best app ever built. However it was done as an educational project to explore different aspects of web development. The project consists of both a backend and frontend component. The backend is written in Python and uses the Flask framework. The frontend is written in HTML and CSS and uses Bootstrap for styling. The backend and frontend are packaged together in a Docker compose file, the system is designed to run on a raspberry pi. However the frontend docker container can be moved to a seperate server if desired.
The architecture of the system is as follows:
Firstly, navigate to the PythonWebApp/BackEnd/src directory and open the app.py file. In this file you will need to update the constructor of FanController to the pins you have connected the fan to. The pin number should be the BCM pin number.
Once this is completed, save the file and close it.
Next, navigate to the PythonWebApp directory and run the following command:
docker-compose up -d --buildIf you want to build the mock version of the backend, run the following command instead:
docker-compose up -d --build -e MOCK="mock"After this the docker image will be built and the containers will be started. The web app should now be accessible at http://server-ip:5001.
Alternatively, you can build the docker images manually. To do this, navigate to the PythonWebApp/BackEnd directory and run the following command:
sh run.shThe same can be done for the frontend by navigating to the PythonWebApp/FrontEnd directory and running the following command:
sh run.shThe project uses GitHub actions to perform continuous integration. The workflow is defined in the `.github/workflows folder
As part of the pipelines associated with this project is a build stage, Which builds the docker images for the backend and frontend. The build stage is defined in the Build.yml file. It also performs static analysis on the code using the following tools:
- shellcheck
- hadolint
This allows both dockerfiles to be validated and tested. This stage also tests the run scripts for both backend and frontend.
The static analysis stage is defined in the Static Analysis.yml file. It performs static analysis on the code using the following tools:
- pylint
- cslint
- eslint
- htmllint
This allows all the code associated with this project to be properly verified and kept up to certain standards.