Music Library System – OOP Lab

Overview

This project implements a Song class using Object-Oriented Programming concepts in Python.

The system models individual songs while also maintaining global statistics about all created songs. These insights simulate features used in music streaming platforms such as:

Total number of songs Unique artists Unique genres Song count per genre Song count per artist

This lab demonstrates proper use of class attributes, class methods, and automatic state updates when new objects are created.

Concepts Demonstrated

Class attributes Class methods Instance attributes Automatic state updates on object creation Data aggregation using dictionaries Test-driven development with pytest

Project Structure

PYTHON-MUSIC-LIBRARY-SYSTEM-LAB/
│
├── song.py
├── song_test.py
├── conftest.py
└── README.md

Song Class Design

Instance Attributes

Each Song object has: name artist genre

Class Attributes

The class tracks global data: count → total number of songs created genres → list of unique genres artists → list of unique artists genre_count → dictionary tracking songs per genre Example:

{"Rap": 2, "Pop": 3}

artist_count → dictionary tracking songs per artist Example:

{"Beyonce": 5, "Jay Z": 2}

Class Methods

Each method is automatically triggered when a new Song is created: add_song_to_count add_to_genres add_to_artists add_to_genre_count add_to_artist_count

Running Tests

Install pytest:

python -m pip install pytest

Run tests:

pytest

All tests should pass successfully.

Features Implemented

✔ Create Song objects ✔ Track total song count ✔ Store unique artists ✔ Store unique genres ✔ Count songs by genre ✔ Count songs by artist ✔ Fully tested with pytest

Requirements

Python 3.12+ pytest Check Python version: python --version