MLA-pilot-group4

MLA Fitness App

A simple and interactive fitness tracking application built with multiple microservices and programming languages. This application allows users to track their exercises and monitor their progress over time.

The Activity Tracking functionality uses the MERN stack (MongoDB, Express.js, React, Node.js), the Analytics service uses Python/Flask and the Authentication Microservice using Java.

Current Features

• User registration for personalized tracking
• Log various types of exercises with descriptions, duration, distance, date and get real time pace and speed
• See overall statistics like with new chart
• weekly statistics with weekly target
• User profile with information like height, weight and BMI
• Real-time data persistence with MongoDB

Prerequisites

• Node.js
• MongoDB
• npm or yarn
• Python Flask
• Java 8 (all already installed in the devcontainer)

Development in Github Codespaces

Starting a new Devcontainer

1. Click on “Code”
2. Switch to the “Codespaces” tab

3. Create new Codespace from main

4. Open Codespace in VS code for best experience:

Walktrough:

https://docs.github.com/en/codespaces/developing-in-a-codespace/using-github-codespaces-in-visual-studio-code

Check needed packages are installed:

sh .devcontainer/check-installation.sh 

expected output:

Checking installations...
node is /usr/local/bin/node
node is installed with version: v18.16.0
npm is /usr/local/bin/npm
npm is installed with version: 9.5.1
python3 is /usr/bin/python3
python3 is installed with version: Python 3.9.2
pip3 is /usr/bin/pip3
pip3 is installed with version: pip 20.3.4 from /usr/lib/python3/dist-packages/pip (python 3.9)
gradle is /usr/bin/gradle
gradle is installed with version: 
------------------------------------------------------------
Gradle 4.4.1
------------------------------------------------------------
......
Done checking installations.

if you’re missing any version, please contact your course administrator.

Building entire project with Docker (+ starting containers up)

docker-compose up --build

Start existing containers (no rebuild of images)

docker-compose up

Spinning up a single service

docker-compose up [servicename]

Shutting down a service

docker-compose down [servicename]

Development without using Docker-Compose

Running Node.js Activity Tracker

cd activity-tracking
npm install
nodemon server

Running Flask application

cd analytics
flask run -h localhost -p 5050

Running Java application

cd authservice
./gradlew clean build
./gradlew bootRun

Start the Frontend

cd frontend
npm install
npm start

spin up MongoDB without docker-compose:

docker run --name mongodb -d -p 27017:27017 -v mongodbdata:/data/db mongo:latest

Connect to MongoDB

mongosh -u root -p cfgmla23 --authenticationDatabase admin --host localhost --port 27017

show registered activities:

db.exercises.find()

show registered users:

db.users.find()

Deployment

The application is containerized using Docker and can be deployed on any platform that supports Docker containers. For AWS deployment, a GitHub Actions pipeline is configured for CI/CD.