import json
import requests
import pandas as pd
from pandas import DataFrame
import csv
from pprint import pprint
import datetime


auth = "Bearer " + "BQAM9rwnXsoUzkguWjiKRn8ffxSeZV0ixaU249PpooTtI5ltX3siaO3USH4TjsbN7mhXxCLZjO9iiCbsv0ZPGBVO6Kdngc9EAqNs2xFOO12Fs1Uj5NP2-Vm-Hv1jN5au9qxgv-ciWVN1ig"
user_id = 'spotify'

response = requests.get('https://api.spotify.com/v1/users/' + user_id + '/playlists?offset=0&limit=50', headers={"Authorization": auth})

data = response.json()

#print data

ids = []




total_playlists = data.get("total")
print total_playlists , "total playlists from user " + user_id

for offset in range (0, total_playlists, 50):
	#print offset 
	response = requests.get('https://api.spotify.com/v1/users/' + user_id + '/playlists?offset={}&limit=50'.format(offset), headers={"Authorization": auth})
	data = response.json()
	
	for item in data:
		ls = data.get("items")
		for n in range(len(ls)):
			id = [ls[n].get("name"), ls[n].get("id")]
			if id not in ids: ids.append(id)

pprint(ids)

new_tracks = []

# for each playlist in list of playlists get the tracks
for playlist in ids:
	uri = playlist[1]
	p_name = playlist[0].encode('utf-8')
	response = requests.get('https://api.spotify.com/v1/users/' + user_id + '/playlists/{}/tracks?fields=items(added_at,track(id,name,artists(name)))'.format(uri), headers={"Authorization": auth})
	# tracks json stored in t_data:
	t_data = response.json()
	#print t_data
	ls = t_data.get("items")
	try:
		for n in range(len(ls)):
			track = []
			id = ls[n].get("track").get("id").encode('utf-8')
			track.append(id)
			added = ls[n].get("added_at").encode('utf-8')
			track.append(added)
			title = ls[n].get("track").get("name").encode('utf-8')
			track.append(title)
			track.append(p_name)
			print track
			new_tracks.append(track)
	except: pass


new_tracks_df = DataFrame.from_records(new_tracks, columns=['ID','ADDED','TITLE','PLAYLIST_NAME'])
#print new_tracks_df[:50]
#

orchard_tracks_df = pd.read_csv('spotify_uri_list.csv')
orchard_tracks_df.columns = ['ID']

merge_df = new_tracks_df.merge(orchard_tracks_df,on=['ID'])

merge_df = merge_df.sort_values(by=['ADDED'], ascending = False)

merge_df['ADDED'] =  pd.to_datetime(merge_df['ADDED']).dt.date
now = datetime.datetime.now().date()
merge_df['DAYS_AGO'] = (now - merge_df['ADDED']).dt.days

merge_df = merge_df.drop(merge_df[merge_df.DAYS_AGO>2].index)

print(merge_df.to_string())

merge_df.to_csv('playlist_adds_june14.csv')



### export new tracks to csv ###
# import csv
# 	
# with open('spotify_owned_playlists_new_tracks.csv', 'wb') as myfile:
#     wr = csv.writer(myfile, quoting=csv.QUOTE_ALL)
#     wr.writerow(new_tracks)

### export playlists and IDs to csv ###
# import csv
# 
# for x in ids:
# 	for y in x:
# 		y=y.encode('utf-8')
# 	
# with open('spotify_owned_playlists.csv', 'wb') as myfile:
#     wr = csv.writer(myfile, quoting=csv.QUOTE_ALL)
#     wr.writerow(ids)