Prerequisites

The backend of this project is run based on docker and docker-compose.

Please install docker at https://docs.docker.com/install/ and docker-compose at https://docs.docker.com/compose/install/.

Running the Project

Backend

1. Copy the .env.example file available and create an .env file at the same directory. Update the fields accordingly for secret data.

2. docker-compose --env-file .env config

   • This command will configure the docker-compose.yml by taking in the environment variables stated in .env
   • Note: please ensure to install docker-compose version 1.8+ for the config to work properly

3. docker-compose up --force-recreate

   1. This will start the process of building the backend image from the source Python 3.6 base image, and installing pip packages stated inside the requirements.txt file.

      • Please refer to Dockerfile for more details.
      • All codes will be mounted as a volume inside the /code directory.

   2. A PostgreSQL base image will also be pulled from the docker registry.

   3. After building the image, the processes will be started as stated in the docker-compose.yml file.

      • Upon starting up, a data migration will be carried out based on the migrations stated inside the migrations folder.
      • Upon starting up, a loaddata will also be done using the following command: python ./manage.py loaddata booking/fixtures/data.json. If you do not wish to have this be done, please comment out this line.
      • A --force-recreate flag is set when calling docker-compose up to prevent data from being uploaded multiple times. You can remove this as well.

4. Visit APIs documentation at localhost:8000/swagger/

5. To list running docker containers, you can run docker ps, note the container id stated in the output.

6. To execute commands inside the image, you can run docker exec -it <container_id> bash then run whatever commands you need.

   If you would like to run the test cases, run python manage.py test after getting into the backend image.

Frontend

Run the codes as stated in the frontend README.md.

The Tech Stack

1. This project uses Django-Rest-Framework to deploy REST API.
2. The database used is Postgresql. The ORM comes with Django is being used.
3. drf-yasg is used to run Swagger for API documentation.