Spotify.py

import spotipy
import spotipy.util as util
from spotipy.oauth2 import SpotifyClientCredentials
import spotipy.oauth2 as oauth2
import json
import pandas as pd
import lyricsgenius as genius
import sys
import pprint
import os

os.chdir('<Set Up your working Directory')

##Set up your client ID and Client Secret
CLIENT_ID = <YOUR CLIENT ID>
CLIENT_SECRET = <YOUR CLIENT SECRET>
credentials = oauth2.SpotifyClientCredentials(
    client_id=CLIENT_ID,
    client_secret=CLIENT_SECRET)

token = credentials.get_access_token()
sp = spotipy.Spotify(auth=token)

uri = 'spotify:user:spotifycharts:playlist:37i9dQZEVXbMDoHDwVN2tF?si=0MkpydG_SWC5Y7loG59M9Q'
username = uri.split(':')[2]
playlist_id = uri.split(':')[4]

# This is a selection of 25 popular Spotify playlists, to get the id of different playlists just use the Spotify web app
# the last part of the url has the playlist ID.

list_of_playslists = ["37i9dQZF1DX0XUsuxWHRQd?si=BO56978gQqSiLl4g73P4jA","37i9dQZEVXbMDoHDwVN2tF?si=0MkpydG_SWC5Y7loG59M9Q",
"37i9dQZF1DX0MLFaUdXnjA","37i9dQZF1DWXJyjYpHunCf","37i9dQZF1DWWOrEmtp56BZ","37i9dQZF1DWSkMjlBZAZ07",
"37i9dQZF1DWUH2AzNQzWua","37i9dQZF1DX3rxVfibe1L0?si=HUmvaZpJTGGUbEJiUFr-Rw","37i9dQZF1DWSqmBTGDYngZ",
"37i9dQZF1DXdPec7aLTmlC","37i9dQZF1DX7KNKjOK0o75","37i9dQZF1DX2SK4ytI2KAZ","37i9dQZF1DX2FsCLsHeMrM",
"37i9dQZF1DWSlw12ofHcMM?si=vvuafurOTHq9aFGmx1pogw","37i9dQZF1DX9Z3vMB2b8im","37i9dQZF1DWY7IeIP1cdjF",
"37i9dQZF1DWYmmr74INQlb","37i9dQZF1DX8Kgdykz6OKj","37i9dQZF1DX1lVhptIYRda","37i9dQZF1DWWnMZKMl7SWB",
"37i9dQZF1DWY4xHQp97fN6","37i9dQZF1DX76Wlfdnj7AP","37i9dQZF1DX70RN3TfWWJh","37i9dQZF1DWUVpAXiEPK8P?si=RCJzumEeRgy9fXeoxfKx2A"
]


#Function to pull from several playlists
def df_creation(playlist_id):
    results = sp.user_playlist(username, playlist_id)
    golbal_top_50 = results['tracks']['items']
    df_t50 = pd.DataFrame(columns =['artists','name','duration_ms','popularity','playlist'])
    for i in range(len(golbal_top_50)):
        try:
            df_t50.loc[i,'artists'] = golbal_top_50[i]['track']['artists'][0]['name']
            df_t50.loc[i,'name'] = golbal_top_50[i]['track']['name']
            df_t50.loc[i,'duration_ms'] = golbal_top_50[i]['track']['duration_ms']
            df_t50.loc[i,'popularity'] = golbal_top_50[i]['track']['popularity']
            df_t50.loc[i,'playlist'] = results['name']
        except TypeError:
            df_t50.loc[i, 'artists'] = None
            df_t50.loc[i, 'name'] = None
            df_t50.loc[i, 'duration_ms'] = None
            df_t50.loc[i, 'popularity'] = None
            df_t50.loc[i, 'playlist'] = None
    return df_t50

#Creating a dictionary of datasets for each playlist
Songs_Df = {} 
for playll in list_of_playslists:
    Songs_Df[playll] = df_creation(playll)

#Merging the Dictionary into one big dataset    
df = pd.concat(Songs_Df).reset_index(drop=True)
df = df.mask(df.astype(object).eq('None')).dropna().reset_index(drop=True)

df2 = df.drop(columns=["playlist"]).drop_duplicates().reset_index()

df3 = pd.merge(df2,df['playlist'],how='left',left_on=df2['index'],right_index=True).drop(columns=['index'])

#Pulling Lyrics
api = genius.Genius('<GENIUS API CODE>')

lyrics = []
for a in range(len(df3)):
    ss = api.search_song(df3.loc[a,'name'],df3.loc[a,'artists'])
    try:
        lyrics.append(ss.lyrics)
    except AttributeError:
        lyrics.append(" ")

#Merging Lyrics to Dataset
df3.insert(loc=5,column = 'lyrics',value = lyrics)
df4 = df3.mask(df3.astype(object).eq('None')).dropna().reset_index(drop=True)

#Create CSV to use later on
df4.to_csv('pre-clean-dataset.csv')