We will be running the system on the Lubuntu 20.4.1 LTS virtual machine image.
First, update the packages and install pip for Python3 on the Lubuntu VM.
sudo apt update && sudo apt upgrade -y
sudo apt install python3-pip
To install Node.js,
sudo apt install npm
To download the latest source code from GitHub,
git clone https://github.com/COMP3900-9900-Capstone-Project/capstoneproject-comp9900-w16a-fifa.git
Make sure that config.js is in capstoneproject-comp9900-w16a-fifa/server and config.ini is in capstoneproject-comp9900-w16a-fifa/server/recommender. These two files contain the login credentials required to connect to the PostgreSQL database.
To install the required Python libraries needed by the recommender system,
cd capstoneproject-comp9900-w16a-fifa/server/recommender
pip install -r requirements.txt
The nltk Python library needs to download a set of corpus in order to perform word stemming. This will only need to be run once.
cd capstoneproject-comp9900-w16a-fifa/server
python3 run.py
In separate terminals:
To start the back-end code,
cd capstoneproject-comp9900-w16a-fifa/server
npm install
npm run start
To start the front-end code,
cd capstoneproject-comp9900-w16a-fifa/client
npm install
npm run start
If for some reason, npm install gives an error, run npm install --force