import spotify_query as spq
import numpy as np
import matplotlib.pyplot as plt
def generateHistDistGraph(features_data, key, bins=25):
plt.hist(features_data[key], bins=bins)
plt.title('Distribution of ' + key + ' feature for given playlist')
plt.show()
playlistID = '1t4NkaqXYRl8g5FTNBUVgG'
requester = spq.requester()
playlist_features_data = requester.get_playlist_features_data(playlistID)
for key in playlist_features_data:
print(key + ": ")
print("\taverage:\t" + str(np.mean(playlist_features_data[key])))
print("\tstandard dev:\t" + str(np.std(playlist_features_data[key])))
print("\tmedian:\t" + str(np.median(playlist_features_data[key])))
plt.style.use('ggplot')
for key in playlist_features_data:
generateHistDistGraph(playlist_features_data, key)
plt.figtext(0, 1, "Yeehaw")
OTHERSTREAM = auto()
DISCOUNT = auto()
PLAYLIST = auto()
CONVENIENCE = auto()
SELECTION = auto()
SHOWS = auto()
DOWNLOAD = auto()
DISCOVERY = auto()
END = auto()
TERMINAL = auto()
ERR = auto()
ARTIST_ERROR = auto()
NOUNRES = auto()
PLACERES = auto()
sp_requester = requester()
class ARTIST_GENRE(Macro):
def run(self, ngrams: Ngrams, vars: Dict[str, Any], args: List[Any]):
if 'fav_artist' in vars:
fav_artist_name = vars['fav_artist']
vars['artist_genre'] = sp_requester.get_artist_genres(fav_artist_name)[0]
# returns the first genre in the artists' genre list
return vars['artist_genre']
class ARTIST_QUALITIES(Macro):
def run(self, ngrams: Ngrams, vars: Dict[str, Any], args: List[Any]):
if 'fav_artist' in vars:
fav_artist_name = vars['fav_artist']