🎵 Music Playlist Recommendation App

📌 Project Overview

This Flask-based music playlist recommendation application was developed as part of a Software Construction course.

It features:

• 🧾 MongoDB-based user authentication
• 🎧 Spotify API for track metadata
• 🔍 Multiple personalized music recommendation techniques

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👥 Project Team

Developed by a team of 5 members:

• KARTHICK S
• JEGADEESWARAN D
• KARTHIKEYAN S
• KEERTHNA S
• MALLU KARTHICK BALAJI REDDY

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🚀 Features

✅ User Authentication

• User registration and login using MongoDB

🎧 Music Recommendations

Generate playlists based on:

• 🔥 Popularity
• 🎤 Artist
• 🎲 Random
• 📝 Lyrics similarity
• 😄 Mood
• 🎼 Genre

🎵 Spotify API Integration

• Retrieves:
  • 🎨 Album cover
  • ▶️ Track preview URL
  • 🔗 Spotify link

🗃️ MongoDB Integration

• Stores and manages user data

💻 Responsive Frontend

• Built with HTML, CSS, and JavaScript

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🔄 DevOps Pipeline

Integrated with Azure DevOps for CI/CD:

• ✅ Build stage
• 🧪 Test stage
• 🚀 Deployment stage

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🧪 Testing & Load Testing

📋 Test Case Documentation

• Covers all core features

📈 Load Testing

• Simulates multiple users
• Includes load testing scripts

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🌀 Agile Methodology

• Agile development principles
• Tools used:
  • 📁 GitHub: Epics, features, user stories
  • 🃏 Poker Estimation: Effort prediction
  • 📈 Progress Reports: Development tracking

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📊 Diagrams

• 🗺️ ER Diagram: User & music database schema
• 🧱 Class Diagram: System classes & relationships
• 🔄 Sequence Diagram: User interaction and backend flow

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🛠️ Installation & Setup

✅ Prerequisites

• Python 3.x
• Flask
• MongoDB
• Spotipy (Spotify API library)
• Pip packages:
  • pandas, numpy, werkzeug, pymongo, etc.

📦 Installation Steps

# Clone the repository
git clone https://github.com/yourusername/music-recommendation-app.git
cd music-recommendation-app

# Install dependencies
pip install -r requirements.txt