Music-to-scrape

We’re music-to-scrape, a fictitious music streaming service with a real website and API. Built for educational purposes, you can use us to learn web scraping!

Getting started

We'll post a link to the website and API here eventually.

Running this project

Using Docker

The easiest way to run our project is using Docker.

• Install Docker and clone this repository.
• Open the terminal at the root of the repository and run the following command: docker compose up.
• Wait a few moments for the website and API to be launched.
• Once these are launched, you can access them at these addresses:
  • API: http://localhost:8080
  • Front end: http://localhost:8000
• Press Ctrl + C in the terminal to quit.

Manual setup (i.e., not using Docker)

Install packages and simulate data

• Clone this repository
• Ensure you have R installed, and run simulate.R in src/simulate to generate the ficitious data.
• Install required Python packages

pip install fastapi
pip install fastapi_utils
pip install sqlalchemy
pip install pydantic
pip install uvicorn
pip install gunicorn
pip install flask
pip install flask_sqlalchemy

Start the API

• Open terminal
• Go to the sql_app folder inside the repository
• Run the following command: uvicorn main:app --port 8080
  • If you want to the FastAPI connection, press Ctrl + C in the terminal to quit.
  • If you want to check the documentation, you can go to following address when uvicorn is started:
    • http://127.0.0.1:8080/docs
    • uvicorn will show you which link is used when running the application.

Start the front end

• Open terminal
• Go to the flask_app folder inside the repository
• Run the following command: gunicorn app:app --bind 127.0.0.1:8000
• If you want to the Flask connection, press Ctrl + c in the terminal to quit.

Changing the data

• Open the simulate.R file within the src/simulate folder
• Make your adjustments
• Run the complete file top-down, and the databases will be updated.

Acknowledgements

• Raw data with song names used in simulating the data: https://github.com/mahkaila/songnames
• Photos
  • Landing page
    • Featured artist: A trumpet player from Caracas, Venezuela. Credits to Ana Maria Arevalo Gosen for providing the photo.
    • Recently played & featured artists
      • https://picsum.photos/id/100/100/100
      • The images are released under the Unsplash license, which allows for free and unrestricted use, including commercial use, without requiring attribution (although attribution is appreciated).
    • Top 15
      • https://picsum.photos/id/237/50/50
      • License is same as above
    • Recent users:
      • Self-made icon
  • Song Page: No Pictures
  • Artist Page:
    • https://images.unsplash.com/photo-1605722243979-fe0be8158232
    • "Unsplash photos are made to be used freely. All photos can be downloaded and used for free for commercial and non-commercial purposes. Attribution isn’t required"
  • User Page:
    • Self-made icon