song_recommender.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# SONG RECOMMENDER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Retrieving notices: ...working... done\n",
      "Collecting package metadata (current_repodata.json): \\ WARNING conda.models.version:get_matcher(556): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.7.1.*, but conda is ignoring the .* and treating it as 1.7.1\n",
      "done\n",
      "Solving environment: done\n",
      "\n",
      "\n",
      "==> WARNING: A newer version of conda exists. <==\n",
      "  current version: 23.7.4\n",
      "  latest version: 23.11.0\n",
      "\n",
      "Please update conda by running\n",
      "\n",
      "    $ conda update -n base -c defaults conda\n",
      "\n",
      "Or to minimize the number of packages updated during conda update use\n",
      "\n",
      "     conda install conda=23.11.0\n",
      "\n",
      "\n",
      "\n",
      "## Package Plan ##\n",
      "\n",
      "  environment location: /Users/minhnguyen/anaconda3\n",
      "\n",
      "  added / updated specs:\n",
      "    - streamlit\n",
      "\n",
      "\n",
      "The following packages will be downloaded:\n",
      "\n",
      "    package                    |            build\n",
      "    ---------------------------|-----------------\n",
      "    altair-5.2.0               |     pyhd8ed1ab_0         447 KB  conda-forge\n",
      "    blinker-1.7.0              |     pyhd8ed1ab_0          17 KB  conda-forge\n",
      "    cachetools-5.3.2           |     pyhd8ed1ab_0          14 KB  conda-forge\n",
      "    gitdb-4.0.11               |     pyhd8ed1ab_0          52 KB  conda-forge\n",
      "    gitpython-3.1.41           |     pyhd8ed1ab_0         147 KB  conda-forge\n",
      "    protobuf-3.20.3            |  py311h814d153_1         344 KB  conda-forge\n",
      "    pydeck-0.8.0               |     pyhd8ed1ab_0         3.9 MB  conda-forge\n",
      "    rich-13.7.0                |     pyhd8ed1ab_0         180 KB  conda-forge\n",
      "    smmap-5.0.0                |     pyhd8ed1ab_0          22 KB  conda-forge\n",
      "    streamlit-1.30.0           |     pyhd8ed1ab_1         6.5 MB  conda-forge\n",
      "    tzlocal-5.2                |  py311h6eed73b_0          41 KB  conda-forge\n",
      "    validators-0.22.0          |     pyhd8ed1ab_0          25 KB  conda-forge\n",
      "    ------------------------------------------------------------\n",
      "                                           Total:        11.6 MB\n",
      "\n",
      "The following NEW packages will be INSTALLED:\n",
      "\n",
      "  altair             conda-forge/noarch::altair-5.2.0-pyhd8ed1ab_0 \n",
      "  blinker            conda-forge/noarch::blinker-1.7.0-pyhd8ed1ab_0 \n",
      "  cachetools         conda-forge/noarch::cachetools-5.3.2-pyhd8ed1ab_0 \n",
      "  gitdb              conda-forge/noarch::gitdb-4.0.11-pyhd8ed1ab_0 \n",
      "  gitpython          conda-forge/noarch::gitpython-3.1.41-pyhd8ed1ab_0 \n",
      "  protobuf           conda-forge/osx-64::protobuf-3.20.3-py311h814d153_1 \n",
      "  pydeck             conda-forge/noarch::pydeck-0.8.0-pyhd8ed1ab_0 \n",
      "  rich               conda-forge/noarch::rich-13.7.0-pyhd8ed1ab_0 \n",
      "  smmap              conda-forge/noarch::smmap-5.0.0-pyhd8ed1ab_0 \n",
      "  streamlit          conda-forge/noarch::streamlit-1.30.0-pyhd8ed1ab_1 \n",
      "  tzlocal            conda-forge/osx-64::tzlocal-5.2-py311h6eed73b_0 \n",
      "  validators         conda-forge/noarch::validators-0.22.0-pyhd8ed1ab_0 \n",
      "\n",
      "The following packages will be UPDATED:\n",
      "\n",
      "  openssl              pkgs/main::openssl-3.0.12-hca72f7f_0 --> conda-forge::openssl-3.2.0-hd75f5a5_1 \n",
      "\n",
      "The following packages will be SUPERSEDED by a higher-priority channel:\n",
      "\n",
      "  ca-certificates    pkgs/main::ca-certificates-2023.12.12~ --> conda-forge::ca-certificates-2023.11.17-h8857fd0_0 \n",
      "  certifi            pkgs/main/osx-64::certifi-2023.11.17-~ --> conda-forge/noarch::certifi-2023.11.17-pyhd8ed1ab_0 \n",
      "\n",
      "\n",
      "\n",
      "Downloading and Extracting Packages\n",
      "cachetools-5.3.2     | 14 KB     |                                       |   0% \n",
      "pydeck-0.8.0         | 3.9 MB    |                                       |   0% \u001b[A\n",
      "\u001b[A\n",
      "\n",
      "\n",
      "gitpython-3.1.41     | 147 KB    |                                       |   0% \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "rich-13.7.0          | 180 KB    |                                       |   0% \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "altair-5.2.0         | 447 KB    |                                       |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "gitdb-4.0.11         | 52 KB     |                                       |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "smmap-5.0.0          | 22 KB     |                                       |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "validators-0.22.0    | 25 KB     |                                       |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "streamlit-1.30.0     | 6.5 MB    |                                       |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "blinker-1.7.0        | 17 KB     |                                       |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "protobuf-3.20.3      | 344 KB    |                                       |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "pydeck-0.8.0         | 3.9 MB    | 1                                     |   0% \u001b[A\n",
      "\n",
      "\n",
      "cachetools-5.3.2     | 14 KB     | ##################################### | 100% \u001b[A\u001b[A\u001b[A\n",
      "pydeck-0.8.0         | 3.9 MB    | #############                         |  35% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "rich-13.7.0          | 180 KB    | ###2                                  |   9% \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "altair-5.2.0         | 447 KB    | #3                                    |   4% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "gitdb-4.0.11         | 52 KB     | ###########4                          |  31% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "tzlocal-5.2          | 41 KB     | ##############5                       |  39% \u001b[A\u001b[A\n",
      "pydeck-0.8.0         | 3.9 MB    | ########################1             |  65% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "blinker-1.7.0        | 17 KB     | #################################8    |  92% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "pydeck-0.8.0         | 3.9 MB    | ####################################1 |  98% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "validators-0.22.0    | 25 KB     | ########################              |  65% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "smmap-5.0.0          | 22 KB     | ##########################9           |  73% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "streamlit-1.30.0     | 6.5 MB    |                                       |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "streamlit-1.30.0     | 6.5 MB    | #######9                              |  22% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "protobuf-3.20.3      | 344 KB    | #7                                    |   5% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "streamlit-1.30.0     | 6.5 MB    | ############9                         |  35% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "streamlit-1.30.0     | 6.5 MB    | #################6                    |  48% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "streamlit-1.30.0     | 6.5 MB    | ########################7             |  67% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "cachetools-5.3.2     | 14 KB     | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "gitdb-4.0.11         | 52 KB     | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "gitdb-4.0.11         | 52 KB     | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "gitpython-3.1.41     | 147 KB    | ##################################### | 100% \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "gitpython-3.1.41     | 147 KB    | ##################################### | 100% \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "tzlocal-5.2          | 41 KB     | ##################################### | 100% \u001b[A\u001b[A\n",
      "\n",
      "tzlocal-5.2          | 41 KB     | ##################################### | 100% \u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "rich-13.7.0          | 180 KB    | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "rich-13.7.0          | 180 KB    | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "blinker-1.7.0        | 17 KB     | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "smmap-5.0.0          | 22 KB     | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "smmap-5.0.0          | 22 KB     | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "altair-5.2.0         | 447 KB    | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "altair-5.2.0         | 447 KB    | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "validators-0.22.0    | 25 KB     | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "validators-0.22.0    | 25 KB     | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "pydeck-0.8.0         | 3.9 MB    | ##################################### | 100% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "protobuf-3.20.3      | 344 KB    | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "protobuf-3.20.3      | 344 KB    | ##################################### | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "                                                                                \u001b[A\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\n",
      "\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                                                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "Preparing transaction: done\n",
      "Verifying transaction: done\n",
      "Executing transaction: done\n",
      "\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%conda install streamlit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting song_recommender.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile song_recommender.py\n",
    "#import libraries\n",
    "import requests\n",
    "import pandas as pd\n",
    "import numpy as np \n",
    "import pickle\n",
    "\n",
    "import sys\n",
    "sys.path.append('/Users/minhnguyen/IronHack2023-2024/Bootcamp/')\n",
    "from config_2 import *\n",
    "\n",
    "import spotipy\n",
    "import json\n",
    "from spotipy.oauth2 import SpotifyClientCredentials\n",
    "from time import sleep\n",
    "import streamlit as st\n",
    "#Initialize SpotiPy with user credentias #\n",
    "sp = spotipy.Spotify(auth_manager=SpotifyClientCredentials(client_id=Client_ID, client_secret=Client_Secret))\n",
    "# import libraries\n",
    "#from recommend_function_2 import *\n",
    "\n",
    "# load song_db\n",
    "song_db = pd.read_csv('song_db_cluster.csv')\n",
    "\n",
    "# split list of song ids:\n",
    "def chunks (song_ids, n:int =50)-> list:\n",
    "    \"\"\"\n",
    "    Divides a sequence of song IDs into chunks of a specified size.\n",
    "\n",
    "    Parameters:\n",
    "    - song_ids (list or pandas.DataFrame): The sequence of song IDs to be divided into chunks.\n",
    "      It can be either a list or a pandas DataFrame.\n",
    "    - n (int, optional): The desired size of each chunk. Default is 50.\n",
    "\n",
    "    Returns:\n",
    "    - list: A list containing chunks of song IDs, where each chunk has a maximum size of 'n'.\n",
    "\n",
    "    Note:\n",
    "    - If 'song_ids' is a list, the chunks are created using list slicing.\n",
    "    - If 'song_ids' is a pandas DataFrame, the chunks are created using DataFrame row slicing.\n",
    "    - If 'song_ids' is smaller than 'n', a single chunk containing all elements is returned.\n",
    "    \"\"\"\n",
    "    if len(song_ids) > n:\n",
    "        if type(song_ids) == list:\n",
    "            chunks = [song_ids[x:x+n] for x in range(0, len(song_ids), n)]\n",
    "            return chunks\n",
    "        elif type(song_ids) == pd.DataFrame:\n",
    "            chunks = [song_ids.iloc[x:x+n,] for x in range(0, len(song_ids), n)]\n",
    "            return chunks\n",
    "        else:\n",
    "            pass\n",
    "        \n",
    "    else:\n",
    "        chunks = [song_ids]\n",
    "        return chunks\n",
    "\n",
    "\n",
    "def song_info_spotify(title:str, artist:str ='', limit:int = 1):\n",
    "\n",
    "    track_id_list = []\n",
    "    track_name_list = []\n",
    "    artist_name_list = []\n",
    "    href_list = []\n",
    "    popularity_list = []\n",
    "\n",
    "    if artist == '':\n",
    "        try:\n",
    "            result = sp.search(q=f\"track:{title}\", limit=limit)\n",
    "            for i in range(0,limit):\n",
    "                track_id = result['tracks']['items'][i]['id']\n",
    "                track_id_list.append(track_id)\n",
    "                track_name = result['tracks']['items'][i]['name']\n",
    "                track_name_list.append(track_name)\n",
    "                href = result['tracks']['items'][i]['href']\n",
    "                href_list.append(href)\n",
    "                artist_name = result['tracks']['items'][i]['artists'][0]['name']\n",
    "                artist_name_list.append(artist_name)\n",
    "                popularity = result['tracks']['items'][i]['popularity']\n",
    "                popularity_list.append(popularity)\n",
    "\n",
    "        except:\n",
    "            print('Song not found')\n",
    "            track_id_list.append('None')\n",
    "            track_name_list.append('None')\n",
    "            href_list.append('None')\n",
    "            artist_name_list.append(\"None\")\n",
    "            popularity_list.append('None')\n",
    "\n",
    "    else:\n",
    "        try:\n",
    "            result = sp.search(q=f\"track:{title} artist:{artist}\", limit=limit)\n",
    "            for i in range(0,limit):\n",
    "                track_id = result['tracks']['items'][i]['id']\n",
    "                track_id_list.append(track_id)\n",
    "                track_name = result['tracks']['items'][i]['name']\n",
    "                track_name_list.append(track_name)\n",
    "                href = result['tracks']['items'][i]['href']\n",
    "                href_list.append(href)\n",
    "                artist_name = result['tracks']['items'][i]['artists'][0]['name']\n",
    "                artist_name_list.append(artist_name)\n",
    "                popularity = result['tracks']['items'][i]['popularity']\n",
    "                popularity_list.append(popularity)\n",
    "\n",
    "        except:\n",
    "            print('Song not found')\n",
    "            track_id_list.append('None')\n",
    "            track_name_list.append('None')\n",
    "            href_list.append('None')\n",
    "            artist_name_list.append(\"None\")\n",
    "            popularity_list.append('None')\n",
    "\n",
    "    track_info = pd.DataFrame({'song_id':track_id_list, 'track_name': track_name_list, 'artist_name': artist_name_list, 'track_href': href_list, 'popularity': popularity_list})\n",
    "\n",
    "    return track_info\n",
    "\n",
    "# function for getting audio features\n",
    "def get_audio_features (list:list):\n",
    "    \n",
    "    sublists = chunks(list,100)\n",
    "    audio_features_dict ={'danceability':[], 'energy':[], 'key':[], 'loudness':[], 'mode':[], 'speechiness':[], 'acousticness':[],'instrumentalness':[], 'liveness':[], 'valence':[], 'tempo':[], 'type':[], 'id':[], 'uri':[], 'track_href':[], 'analysis_url':[], 'duration_ms':[], 'time_signature':[]}\n",
    "    for index,list in enumerate(sublists):\n",
    "        #print(f\"Retrieving audio_features from chunk {index}\")\n",
    "        # get audio_features\n",
    "        try:\n",
    "            audio_features = sp.audio_features(list)\n",
    "            for feature in audio_features:\n",
    "                for key in audio_features_dict:\n",
    "                    audio_features_dict[key].append(feature[key])\n",
    "            #audio_features['song_id'] = song_id # add dict item with key 'song_id' and value song_id            \n",
    "            #audio_features_list.append(audio_features)\n",
    "        except requests.exceptions.HTTPError as e:\n",
    "            if e.response.status_code == 429:\n",
    "                retry_after = int(e.response.headers.get('Retry-After', 1))\n",
    "                print(f\"Rate limited. Retrying after {retry_after} seconds.\")\n",
    "                sleep(retry_after + 1)\n",
    "                continue\n",
    "            else:\n",
    "                raise\n",
    "        except Exception as e:\n",
    "            print(f\"Failed to get audio features for some track IDs: {e}\")\n",
    "\n",
    "        #print(\"sleep a bit before getting the next chunk\")\n",
    "        print('Processing...')  \n",
    "        sleep(10)\n",
    "\n",
    "    audio_features_df = pd.DataFrame(audio_features_dict)\n",
    "    return audio_features_df\n",
    "\n",
    "# function to add audio features to the track info dataframe\n",
    "def add_audio_features (df1, df2, left_col, right_col, how = 'inner' ):\n",
    "   \n",
    "    extended_df = pd.merge(df1, df2, left_on=left_col, right_on=right_col, how = how)\n",
    "    return extended_df\n",
    "\n",
    "# function to get recommendation from the song_db\n",
    "def recommendation(song_db, user_song_cluster, hot_value:str = None, num_recommendations=5):\n",
    "    if hot_value != None:\n",
    "        recommendation = song_db[(song_db['cluster'] == int(user_song_cluster)) & (song_db['hotness'] == hot_value)].sample(num_recommendations)\n",
    "    else: \n",
    "        recommendation = song_db[(song_db['cluster'] == int(user_song_cluster))].sample(num_recommendations)\n",
    "\n",
    "    recommendation = recommendation[['track_name', 'artist_name', 'track_href']]\n",
    "    sleep(20)\n",
    "    print(\"\\n Here are recommended songs and the link to spotify for you to try out: \\n\")\n",
    "    print()\n",
    "    print(recommendation)\n",
    "    \n",
    "# get Scaler and model\n",
    "with open( \"song_cluster_scaled.pkl\",\"rb\") as file:\n",
    "    scaler= pickle.load(file)\n",
    "    \n",
    "with open( \"KMeans_cluster.pkl\",\"rb\") as file:\n",
    "    model= pickle.load(file)\n",
    "\n",
    "choice = 'yes'\n",
    "while choice == 'yes':\n",
    "\n",
    "# ask for user inputs:\n",
    "    track_name = str(input(\"Please enter your favourite's song: \"))\n",
    "    artist_name = str(input(\"Please enter the artist name (press enter to skip): \"))\n",
    "\n",
    "#from get_feature_update import *\n",
    "    song_info = song_info_spotify(track_name, artist_name, 5)\n",
    "# output the spotify search result of 5 songs with track_name with or without an artist_name\n",
    "    print('Processing ... \\n')\n",
    "    print()\n",
    "    print('we retrieved the below songs from Spotify: \\n')\n",
    "    print()\n",
    "    print(song_info[['track_name', 'artist_name', 'popularity']])\n",
    "    sleep(5)\n",
    "    print()\n",
    "    print('\\n Please choose which song you would like to search: ')\n",
    "\n",
    "# get choice from user\n",
    "    choice = int(input(\"Please enter the number of the song you would like to search:\"))\n",
    "    print()\n",
    "    print('\\n Processing ... \\n')\n",
    "# set selected track from user input\n",
    "    selected_track_id = [song_info.iloc[choice, 0]]\n",
    "\n",
    "# get audio features for the selected track\n",
    "    song_audio = get_audio_features(selected_track_id)\n",
    "\n",
    "# calling function to add audio features to the selected track info dataframe\n",
    "    user_song_final = add_audio_features(song_info, song_audio, 'song_id', 'id')\n",
    "# get the df with selected audio features for cluster prediction\n",
    "    user_song_cluster_df = user_song_final[['danceability', 'energy', 'acousticness', 'key', 'valence']]\n",
    "\n",
    "\n",
    "# perform scale data and cluster prediction for selected track\n",
    "    user_song_cluster_scaled = scaler.transform(user_song_cluster_df)\n",
    "    user_song_cluster_scaled_df = pd.DataFrame(user_song_cluster_scaled, columns = user_song_cluster_df.columns)\n",
    "    user_song_cluster = model.predict(user_song_cluster_scaled_df)\n",
    "\n",
    "# check in which group of 'hotness' the selected track is, and get recommendation from song_db with the same cluster and the same hotness\n",
    "# output recommendation to user, and promtp for new input\n",
    "    if song_info.iloc[choice, 0] in song_db[song_db['hotness'] == 'yes']['song_id'].tolist():\n",
    "        recommendation = recommendation(song_db, user_song_cluster, 'yes')\n",
    "        print('\\n What do you think?')\n",
    "        print()\n",
    "        sleep(10)\n",
    "        print('\\n You enjoyed and would like to have another recommendation from us?\\n ')\n",
    "        sleep(10)\n",
    "        print()\n",
    "        choice = str(input(\"If yes, please enter 'yes' to provide a song name! \\n If not, please enter 'no' to escape\"))\n",
    "        if choice == 'yes':\n",
    "            continue\n",
    "        else:\n",
    "            break\n",
    "    elif song_info.iloc[choice, 0] in song_db[song_db['hotness'] == 'no']['song_id'].tolist():\n",
    "        recommendation = recommendation(song_db, user_song_cluster, 'no')\n",
    "        print('\\n What do you think?')\n",
    "        print()\n",
    "        sleep(10)\n",
    "        print('\\n You enjoyed and would like to have another recommendation from us?\\n ')\n",
    "        sleep(10)\n",
    "        print()\n",
    "        choice = str(input(\"If yes, please enter 'yes' to provide a song name! \\n If not, please enter 'no' to escape\"))\n",
    "        if choice == 'yes':\n",
    "            continue\n",
    "        else:\n",
    "            break\n",
    "    else:\n",
    "        print('\\n We could not process the \"hotness\" of this song at this moment yet.\\n' )\n",
    "        print('\\n But we think you might enjoy these songs still! \\n' )\n",
    "        recommendation = recommendation(song_db, user_song_cluster)\n",
    "        print('\\n What do you think?')\n",
    "        print()\n",
    "        sleep(10)\n",
    "        print('\\n You enjoyed and would like to have another recommendation from us?\\n ')\n",
    "        sleep(10)\n",
    "        print()\n",
    "        choice = str(input(\"If yes, please enter 'yes' to provide a song name! \\n If not, please enter 'no' to escape\"))\n",
    "        if choice == 'yes':\n",
    "            continue\n",
    "        else:\n",
    "            break\n",
    "\n",
    "\n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "#selected_track_id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "#song_audio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "#user_song_final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>danceability</th>\n",
       "      <th>energy</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>key</th>\n",
       "      <th>valence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.735</td>\n",
       "      <td>0.478</td>\n",
       "      <td>0.189</td>\n",
       "      <td>2</td>\n",
       "      <td>0.947</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   danceability  energy  acousticness  key  valence\n",
       "0         0.735   0.478         0.189    2    0.947"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#user_song_cluster_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "#song_db[['track_name', 'artist_name']].sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we retrieved the below songs from Spotify: \" please choose which song you would like to search: \n",
      "                        track_name artist_name  popularity\n",
      "0                   Last Christmas       Wham!          93\n",
      "1  Last Christmas - Single Version       Wham!          88\n",
      "2      Last Christmas - Remastered       Wham!          85\n",
      "3                   Last Christmas       Wham!          70\n",
      "4                   Last Christmas       Wham!          71\n",
      "Please choose which song you would like to search: \n",
      "Retrieving audio_features from chunk 0\n",
      "sleep a bit before getting the next chunk\n",
      "Here are recommended songs and the link to spotify for you to try out:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>track_name</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>track_href</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1882</th>\n",
       "      <td>not fade away</td>\n",
       "      <td>mick fleetwood</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/1G1OgcGURIWs...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2049</th>\n",
       "      <td>cucurucucú paloma</td>\n",
       "      <td>willie colón</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/1BUHjtsfyGTX...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>805</th>\n",
       "      <td>it's the same old song</td>\n",
       "      <td>four tops</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/7d1ustAIlXG7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2396</th>\n",
       "      <td>it feels alright</td>\n",
       "      <td>black lips</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/31hueWsGBgEE...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1102</th>\n",
       "      <td>this is how we do it</td>\n",
       "      <td>montell jordan</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/6uQKuonTU8VK...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  track_name     artist_name  \\\n",
       "1882           not fade away  mick fleetwood   \n",
       "2049       cucurucucú paloma    willie colón   \n",
       "805   it's the same old song       four tops   \n",
       "2396        it feels alright      black lips   \n",
       "1102    this is how we do it  montell jordan   \n",
       "\n",
       "                                             track_href  \n",
       "1882  https://api.spotify.com/v1/tracks/1G1OgcGURIWs...  \n",
       "2049  https://api.spotify.com/v1/tracks/1BUHjtsfyGTX...  \n",
       "805   https://api.spotify.com/v1/tracks/7d1ustAIlXG7...  \n",
       "2396  https://api.spotify.com/v1/tracks/31hueWsGBgEE...  \n",
       "1102  https://api.spotify.com/v1/tracks/6uQKuonTU8VK...  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n",
      "\n",
      " What do you think?\n",
      "\n",
      " If you enjoy and would like to have another recommendation from us?\n"
     ]
    }
   ],
   "source": [
    "%run song_recommender.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>track_name</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>song_id</th>\n",
       "      <th>danceability</th>\n",
       "      <th>energy</th>\n",
       "      <th>key</th>\n",
       "      <th>loudness</th>\n",
       "      <th>mode</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>...</th>\n",
       "      <th>tempo</th>\n",
       "      <th>type</th>\n",
       "      <th>id</th>\n",
       "      <th>uri</th>\n",
       "      <th>track_href</th>\n",
       "      <th>analysis_url</th>\n",
       "      <th>duration_ms</th>\n",
       "      <th>time_signature</th>\n",
       "      <th>hotness</th>\n",
       "      <th>cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Rockin' Around The Christmas Tree</td>\n",
       "      <td>Brenda Lee</td>\n",
       "      <td>2EjXfH91m7f8HiJN1yQg97</td>\n",
       "      <td>0.589</td>\n",
       "      <td>0.472</td>\n",
       "      <td>8</td>\n",
       "      <td>-8.749</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0502</td>\n",
       "      <td>0.614000</td>\n",
       "      <td>...</td>\n",
       "      <td>67.196</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>2EjXfH91m7f8HiJN1yQg97</td>\n",
       "      <td>spotify:track:2EjXfH91m7f8HiJN1yQg97</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/2EjXfH91m7f8...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/2EjX...</td>\n",
       "      <td>126267</td>\n",
       "      <td>4</td>\n",
       "      <td>yes</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>All I Want For Christmas Is You</td>\n",
       "      <td>Mariah Carey</td>\n",
       "      <td>0bYg9bo50gSsH3LtXe2SQn</td>\n",
       "      <td>0.336</td>\n",
       "      <td>0.627</td>\n",
       "      <td>7</td>\n",
       "      <td>-7.463</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0384</td>\n",
       "      <td>0.164000</td>\n",
       "      <td>...</td>\n",
       "      <td>150.273</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>0bYg9bo50gSsH3LtXe2SQn</td>\n",
       "      <td>spotify:track:0bYg9bo50gSsH3LtXe2SQn</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/0bYg9bo50gSs...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/0bYg...</td>\n",
       "      <td>241107</td>\n",
       "      <td>4</td>\n",
       "      <td>yes</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jingle Bell Rock</td>\n",
       "      <td>Bobby Helms</td>\n",
       "      <td>7vQbuQcyTflfCIOu3Uzzya</td>\n",
       "      <td>0.754</td>\n",
       "      <td>0.424</td>\n",
       "      <td>2</td>\n",
       "      <td>-8.463</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0363</td>\n",
       "      <td>0.643000</td>\n",
       "      <td>...</td>\n",
       "      <td>119.705</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>7vQbuQcyTflfCIOu3Uzzya</td>\n",
       "      <td>spotify:track:7vQbuQcyTflfCIOu3Uzzya</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/7vQbuQcyTflf...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/7vQb...</td>\n",
       "      <td>130973</td>\n",
       "      <td>4</td>\n",
       "      <td>yes</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Last Christmas</td>\n",
       "      <td>Wham!</td>\n",
       "      <td>2FRnf9qhLbvw8fu4IBXx78</td>\n",
       "      <td>0.735</td>\n",
       "      <td>0.478</td>\n",
       "      <td>2</td>\n",
       "      <td>-12.472</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0293</td>\n",
       "      <td>0.189000</td>\n",
       "      <td>...</td>\n",
       "      <td>107.682</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>2FRnf9qhLbvw8fu4IBXx78</td>\n",
       "      <td>spotify:track:2FRnf9qhLbvw8fu4IBXx78</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/2FRnf9qhLbvw...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/2FRn...</td>\n",
       "      <td>262960</td>\n",
       "      <td>4</td>\n",
       "      <td>yes</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A Holly Jolly Christmas</td>\n",
       "      <td>Burl Ives</td>\n",
       "      <td>77khP2fIVhSW23NwxrRluh</td>\n",
       "      <td>0.683</td>\n",
       "      <td>0.375</td>\n",
       "      <td>0</td>\n",
       "      <td>-13.056</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0303</td>\n",
       "      <td>0.579000</td>\n",
       "      <td>...</td>\n",
       "      <td>140.467</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>77khP2fIVhSW23NwxrRluh</td>\n",
       "      <td>spotify:track:77khP2fIVhSW23NwxrRluh</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/77khP2fIVhSW...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/77kh...</td>\n",
       "      <td>135533</td>\n",
       "      <td>4</td>\n",
       "      <td>yes</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2802</th>\n",
       "      <td>reckless life</td>\n",
       "      <td>guns n' roses</td>\n",
       "      <td>7I2Q7AQqVInZYwOoDHZGOf</td>\n",
       "      <td>0.442</td>\n",
       "      <td>0.888</td>\n",
       "      <td>10</td>\n",
       "      <td>-8.820</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0663</td>\n",
       "      <td>0.000054</td>\n",
       "      <td>...</td>\n",
       "      <td>108.024</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>7I2Q7AQqVInZYwOoDHZGOf</td>\n",
       "      <td>spotify:track:7I2Q7AQqVInZYwOoDHZGOf</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/7I2Q7AQqVInZ...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/7I2Q...</td>\n",
       "      <td>200600</td>\n",
       "      <td>4</td>\n",
       "      <td>no</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2803</th>\n",
       "      <td>pain and love</td>\n",
       "      <td>t. rex</td>\n",
       "      <td>5Qe7x9x8mfl2YcbYTP5yRM</td>\n",
       "      <td>0.588</td>\n",
       "      <td>0.629</td>\n",
       "      <td>0</td>\n",
       "      <td>-10.226</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0318</td>\n",
       "      <td>0.055500</td>\n",
       "      <td>...</td>\n",
       "      <td>136.091</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>5Qe7x9x8mfl2YcbYTP5yRM</td>\n",
       "      <td>spotify:track:5Qe7x9x8mfl2YcbYTP5yRM</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/5Qe7x9x8mfl2...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/5Qe7...</td>\n",
       "      <td>221440</td>\n",
       "      <td>4</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2804</th>\n",
       "      <td>brave new world</td>\n",
       "      <td>greta van fleet</td>\n",
       "      <td>0HwdiT4MVRzY0OALcjq0Oh</td>\n",
       "      <td>0.341</td>\n",
       "      <td>0.848</td>\n",
       "      <td>7</td>\n",
       "      <td>-4.475</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0371</td>\n",
       "      <td>0.058300</td>\n",
       "      <td>...</td>\n",
       "      <td>136.568</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>0HwdiT4MVRzY0OALcjq0Oh</td>\n",
       "      <td>spotify:track:0HwdiT4MVRzY0OALcjq0Oh</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/0HwdiT4MVRzY...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/0Hwd...</td>\n",
       "      <td>300880</td>\n",
       "      <td>4</td>\n",
       "      <td>no</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2805</th>\n",
       "      <td>i-76</td>\n",
       "      <td>g. love &amp; special sauce</td>\n",
       "      <td>40c4Zo0r2HH9aKDgEsbsVA</td>\n",
       "      <td>0.643</td>\n",
       "      <td>0.713</td>\n",
       "      <td>11</td>\n",
       "      <td>-6.716</td>\n",
       "      <td>0</td>\n",
       "      <td>0.2150</td>\n",
       "      <td>0.138000</td>\n",
       "      <td>...</td>\n",
       "      <td>103.942</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>40c4Zo0r2HH9aKDgEsbsVA</td>\n",
       "      <td>spotify:track:40c4Zo0r2HH9aKDgEsbsVA</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/40c4Zo0r2HH9...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/40c4...</td>\n",
       "      <td>225640</td>\n",
       "      <td>4</td>\n",
       "      <td>no</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2806</th>\n",
       "      <td>just out of reach (of my two open arms)</td>\n",
       "      <td>patsy cline</td>\n",
       "      <td>2VmffxY9mAdESaSElIHL4u</td>\n",
       "      <td>0.553</td>\n",
       "      <td>0.123</td>\n",
       "      <td>10</td>\n",
       "      <td>-17.765</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0323</td>\n",
       "      <td>0.753000</td>\n",
       "      <td>...</td>\n",
       "      <td>87.847</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>2VmffxY9mAdESaSElIHL4u</td>\n",
       "      <td>spotify:track:2VmffxY9mAdESaSElIHL4u</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/2VmffxY9mAdE...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/2Vmf...</td>\n",
       "      <td>149667</td>\n",
       "      <td>4</td>\n",
       "      <td>no</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2807 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   track_name              artist_name  \\\n",
       "0           Rockin' Around The Christmas Tree               Brenda Lee   \n",
       "1             All I Want For Christmas Is You             Mariah Carey   \n",
       "2                            Jingle Bell Rock              Bobby Helms   \n",
       "3                              Last Christmas                    Wham!   \n",
       "4                     A Holly Jolly Christmas                Burl Ives   \n",
       "...                                       ...                      ...   \n",
       "2802                            reckless life            guns n' roses   \n",
       "2803                            pain and love                   t. rex   \n",
       "2804                          brave new world          greta van fleet   \n",
       "2805                                     i-76  g. love & special sauce   \n",
       "2806  just out of reach (of my two open arms)              patsy cline   \n",
       "\n",
       "                     song_id  danceability  energy  key  loudness  mode  \\\n",
       "0     2EjXfH91m7f8HiJN1yQg97         0.589   0.472    8    -8.749     1   \n",
       "1     0bYg9bo50gSsH3LtXe2SQn         0.336   0.627    7    -7.463     1   \n",
       "2     7vQbuQcyTflfCIOu3Uzzya         0.754   0.424    2    -8.463     1   \n",
       "3     2FRnf9qhLbvw8fu4IBXx78         0.735   0.478    2   -12.472     1   \n",
       "4     77khP2fIVhSW23NwxrRluh         0.683   0.375    0   -13.056     1   \n",
       "...                      ...           ...     ...  ...       ...   ...   \n",
       "2802  7I2Q7AQqVInZYwOoDHZGOf         0.442   0.888   10    -8.820     0   \n",
       "2803  5Qe7x9x8mfl2YcbYTP5yRM         0.588   0.629    0   -10.226     0   \n",
       "2804  0HwdiT4MVRzY0OALcjq0Oh         0.341   0.848    7    -4.475     1   \n",
       "2805  40c4Zo0r2HH9aKDgEsbsVA         0.643   0.713   11    -6.716     0   \n",
       "2806  2VmffxY9mAdESaSElIHL4u         0.553   0.123   10   -17.765     1   \n",
       "\n",
       "      speechiness  acousticness  ...    tempo            type  \\\n",
       "0          0.0502      0.614000  ...   67.196  audio_features   \n",
       "1          0.0384      0.164000  ...  150.273  audio_features   \n",
       "2          0.0363      0.643000  ...  119.705  audio_features   \n",
       "3          0.0293      0.189000  ...  107.682  audio_features   \n",
       "4          0.0303      0.579000  ...  140.467  audio_features   \n",
       "...           ...           ...  ...      ...             ...   \n",
       "2802       0.0663      0.000054  ...  108.024  audio_features   \n",
       "2803       0.0318      0.055500  ...  136.091  audio_features   \n",
       "2804       0.0371      0.058300  ...  136.568  audio_features   \n",
       "2805       0.2150      0.138000  ...  103.942  audio_features   \n",
       "2806       0.0323      0.753000  ...   87.847  audio_features   \n",
       "\n",
       "                          id                                   uri  \\\n",
       "0     2EjXfH91m7f8HiJN1yQg97  spotify:track:2EjXfH91m7f8HiJN1yQg97   \n",
       "1     0bYg9bo50gSsH3LtXe2SQn  spotify:track:0bYg9bo50gSsH3LtXe2SQn   \n",
       "2     7vQbuQcyTflfCIOu3Uzzya  spotify:track:7vQbuQcyTflfCIOu3Uzzya   \n",
       "3     2FRnf9qhLbvw8fu4IBXx78  spotify:track:2FRnf9qhLbvw8fu4IBXx78   \n",
       "4     77khP2fIVhSW23NwxrRluh  spotify:track:77khP2fIVhSW23NwxrRluh   \n",
       "...                      ...                                   ...   \n",
       "2802  7I2Q7AQqVInZYwOoDHZGOf  spotify:track:7I2Q7AQqVInZYwOoDHZGOf   \n",
       "2803  5Qe7x9x8mfl2YcbYTP5yRM  spotify:track:5Qe7x9x8mfl2YcbYTP5yRM   \n",
       "2804  0HwdiT4MVRzY0OALcjq0Oh  spotify:track:0HwdiT4MVRzY0OALcjq0Oh   \n",
       "2805  40c4Zo0r2HH9aKDgEsbsVA  spotify:track:40c4Zo0r2HH9aKDgEsbsVA   \n",
       "2806  2VmffxY9mAdESaSElIHL4u  spotify:track:2VmffxY9mAdESaSElIHL4u   \n",
       "\n",
       "                                             track_href  \\\n",
       "0     https://api.spotify.com/v1/tracks/2EjXfH91m7f8...   \n",
       "1     https://api.spotify.com/v1/tracks/0bYg9bo50gSs...   \n",
       "2     https://api.spotify.com/v1/tracks/7vQbuQcyTflf...   \n",
       "3     https://api.spotify.com/v1/tracks/2FRnf9qhLbvw...   \n",
       "4     https://api.spotify.com/v1/tracks/77khP2fIVhSW...   \n",
       "...                                                 ...   \n",
       "2802  https://api.spotify.com/v1/tracks/7I2Q7AQqVInZ...   \n",
       "2803  https://api.spotify.com/v1/tracks/5Qe7x9x8mfl2...   \n",
       "2804  https://api.spotify.com/v1/tracks/0HwdiT4MVRzY...   \n",
       "2805  https://api.spotify.com/v1/tracks/40c4Zo0r2HH9...   \n",
       "2806  https://api.spotify.com/v1/tracks/2VmffxY9mAdE...   \n",
       "\n",
       "                                           analysis_url duration_ms  \\\n",
       "0     https://api.spotify.com/v1/audio-analysis/2EjX...      126267   \n",
       "1     https://api.spotify.com/v1/audio-analysis/0bYg...      241107   \n",
       "2     https://api.spotify.com/v1/audio-analysis/7vQb...      130973   \n",
       "3     https://api.spotify.com/v1/audio-analysis/2FRn...      262960   \n",
       "4     https://api.spotify.com/v1/audio-analysis/77kh...      135533   \n",
       "...                                                 ...         ...   \n",
       "2802  https://api.spotify.com/v1/audio-analysis/7I2Q...      200600   \n",
       "2803  https://api.spotify.com/v1/audio-analysis/5Qe7...      221440   \n",
       "2804  https://api.spotify.com/v1/audio-analysis/0Hwd...      300880   \n",
       "2805  https://api.spotify.com/v1/audio-analysis/40c4...      225640   \n",
       "2806  https://api.spotify.com/v1/audio-analysis/2Vmf...      149667   \n",
       "\n",
       "     time_signature hotness  cluster  \n",
       "0                 4     yes        3  \n",
       "1                 4     yes        5  \n",
       "2                 4     yes        3  \n",
       "3                 4     yes        0  \n",
       "4                 4     yes        3  \n",
       "...             ...     ...      ...  \n",
       "2802              4      no        5  \n",
       "2803              4      no        0  \n",
       "2804              4      no        5  \n",
       "2805              4      no        1  \n",
       "2806              4      no        2  \n",
       "\n",
       "[2807 rows x 23 columns]"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "song_db"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}