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We will be making use of Spotify API (Spotipy) accompanied by Python to get data from Spotify Web API. Based on the data extracted from each music we planned to analyse various audio features and patterns of the music.

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Spotanalyst

For other Detailed Information visit our Wiki Page: Click Here

Initial Setup

Installation:

  1. Git clone: Github Link

  2. In Terminal, pip install -r requirements.txt to install the pre-requisites

Setup ENV & Spotify Developer Account:

  • Setup Config.py file @ prediction/config.py:

    1. Login with Kaggle Account Click Here
    2. Once logged in, generate new API Key from Accounts Tab
    3. Save those details in required empty fields in prediction/config.py file
  • Setup Config.py file @ webapp/server/config.py:

    1. Login with Spotify Developer Click Here

    2. Create a new App on Spotify Developer Console

      • Create a New App #1
      • Collect Spotify Client ID, Secret and also set Redirect URI in "Edit Settings" #2
    3. Edit the file at webapp/server/config.py

    4. Setup Chart Studio:

    5. Edit the details on webapp/server/config.py with respective data


Create Prediction Model

  1. Run generate_ml_model.py
  2. Make sure a .pkl file is made finally

Front End

Run App:

  1. Setup correct location of training model and make sure every field is changed as per instructions.

  2. Run app.py to start the app

  3. If everything goes well, your app will be posted at http://localhost:9090

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We will be making use of Spotify API (Spotipy) accompanied by Python to get data from Spotify Web API. Based on the data extracted from each music we planned to analyse various audio features and patterns of the music.

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