Spotify_Recommend_Playlist

• Team discusisson doc
  • google sheet

Intro

• Build an UI grab user's song taste via Tinder like process, then train a ML model from user taste data, then predict the potentail users liked songs via the classification from ML model, finally call the Spotify recommendation API then get the playlist of the songs that fit such user classification

Architecture

• Architecture Idea

  • dev

• Workflow

User rate the songs ---> detector ---> Model_training  ---> Spotify_ML_API ---> recommended_playlist ---> Web_UI 

FILE STRUCTURE

├── [1.8k]  README.md
├── [3.1k]  collect_data.py  : Script collect data (/data)
├── [ 160]  data             : Scraped data for model training 
├── [ 613]  install.sh       : Bash help install needed environment 
├── [3.3k]  server.py        : Script hold server-side services (Python flask)
├── [ 192]  templates	     
│   ├── [9.4k]  client.js    : Script hold client-side services (playlist..) (JS)
│   ├── [4.0k]  index.html   : Main html file 
│   └── [3.6k]  style.css    : Main CSS file 
├── [4.6k]  utility.js       : Backup JS help script 
└── [2.8k]  utility.py       : Python script query spotify API 

QUICK START

Prerequisites

Prerequisites

• Step 1

  • Get the spotify SPOTIPY_CLIENT_ID and SPOTIPY_CLIENT_SECRET
  • https://developer.spotify.com/dashboard/applications

• Step 2

  • Create an APP at developer page with created SPOTIPY_CLIENT_ID
  • https://developer.spotify.com

• Step 3

  • Rename .creds.yml.dev to .creds.yml and update the Spotify credential (SPOTIPY_CLIENT_ID, SPOTIPY_CLIENT_SECRET)

• Step 4

  • Execute the following commands (Method 1)then run the web APP locally
  • The APP UI should be available at : http://127.0.0.1:7777/

Method 1) Run (manually)

• quick start

Method 2) Run (docker)

• quick start docker

TECH

• Backend : Python3 flask, spotipy, sklearn
• Frontend : Javascript, Ajax, HTML, CSS, Bootstrap

REF

REF

• ref.md
• Inspired by
  • https://nelson.glitch.me/#

TODO

TODO

• Fix JS Ajax call API part
• Fix frontend layout
• Dockerize the project