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import streamlit as st
import spotipy
from spotipy.oauth2 import SpotifyClientCredentials
import pandas as pd
import matplotlib.pyplot as plt
import os
from dotenv import load_dotenv
# Carica le credenziali di Spotify
load_dotenv()
SPOTIPY_CLIENT_ID = os.getenv("SPOTIPY_CLIENT_ID")
SPOTIPY_CLIENT_SECRET = os.getenv("SPOTIPY_CLIENT_SECRET")
auth_manager = SpotifyClientCredentials(client_id=SPOTIPY_CLIENT_ID, client_secret=SPOTIPY_CLIENT_SECRET)
sp = spotipy.Spotify(auth_manager=auth_manager)
def get_artist_info(artist_name):
artist = sp.search(q=artist_name, type='artist')['artists']['items'][0]
return {
'name': artist['name'],
'id': artist['id'],
'followers': artist['followers']['total'],
'popularity': artist['popularity'],
'genres': artist['genres'],
'image': artist['images'][0]['url'] if artist['images'] else None
}
def get_top_tracks(artist_id):
results = sp.artist_top_tracks(artist_id)
tracks = results['tracks'][:10] # Limit to top 10 tracks
return [{
'name': track['name'],
'album': track['album']['name'],
'artist': track['artists'][0]['name'],
'release_date': track['album']['release_date'],
'popularity': track['popularity'],
'album_cover': track['album']['images'][0]['url'] if track['album']['images'] else None,
'danceability': sp.audio_features(track['id'])[0]['danceability'] if sp.audio_features(track['id']) else 0,
'loudness': sp.audio_features(track['id'])[0]['loudness'] if sp.audio_features(track['id']) else 0,
'energy': sp.audio_features(track['id'])[0]['energy'] if sp.audio_features(track['id']) else 0,
'valence': sp.audio_features(track['id'])[0]['valence'] if sp.audio_features(track['id']) else 0,
'tempo': sp.audio_features(track['id'])[0]['tempo'] if sp.audio_features(track['id']) else 0,
'artist_id': artist_id
} for track in tracks]
def plot_features_comparison(data_tracks, artist1_info, artist2_info):
df = pd.DataFrame(data_tracks)
fig, ax = plt.subplots()
colors = {artist1_info['id']: 'blue', artist2_info['id']: 'red'}
for artist_id, group in df.groupby('artist_id'):
ax.scatter(group['danceability'], group['loudness'], alpha=0.7, label=group['artist'].iloc[0], c=colors[artist_id])
plt.title('Confronto Danceability vs. Loudness')
plt.xlabel('Danceability')
plt.ylabel('Loudness (dB)')
plt.legend(title='Artist')
st.pyplot(fig)
def plot_audio_features_boxplot(data_tracks, artist1_name, artist2_name):
df = pd.DataFrame(data_tracks)
fig, axs = plt.subplots(1, 4, figsize=(20, 5)) # 1 riga, 4 colonne per 4 features
features = ['danceability', 'energy', 'valence', 'tempo']
for i, feature in enumerate(features):
ax = axs[i]
artist1_data = df[df['artist'] == artist1_name][feature]
artist2_data = df[df['artist'] == artist2_name][feature]
ax.boxplot([artist1_data, artist2_data], labels=[artist1_name, artist2_name])
ax.set_title(f'Distribution of {feature}')
ax.set_ylabel(feature)
plt.tight_layout()
st.pyplot(fig)
def plot_audio_features_violinplot(data_tracks, artist1_name, artist2_name):
df = pd.DataFrame(data_tracks)
fig, axs = plt.subplots(1, 4, figsize=(20, 5)) # 1 riga, 4 colonne per 4 features
features = ['danceability', 'energy', 'valence', 'tempo']
for i, feature in enumerate(features):
ax = axs[i]
data_to_plot = [df[df['artist'] == artist1_name][feature], df[df['artist'] == artist2_name][feature]]
ax.violinplot(data_to_plot)
ax.set_xticks([1, 2])
ax.set_xticklabels([artist1_name, artist2_name])
ax.set_title(f'Distribution of {feature}')
ax.set_ylabel(feature)
plt.tight_layout()
st.pyplot(fig)
def show_average_features(data_tracks):
df = pd.DataFrame(data_tracks)
numeric_columns = ['loudness', 'danceability', 'energy', 'valence', 'tempo', 'artist']
df = df[numeric_columns]
average_features = df.groupby('artist').mean()[['loudness', 'danceability', 'energy', 'valence', 'tempo']]
st.write("Media delle Caratteristiche Audio per Artista:")
st.dataframe(average_features)
def main():
st.title("Confronto Artisti su Spotify")
artist1_name = st.text_input("Inserisci il nome del primo artista")
artist2_name = st.text_input("Inserisci il nome del secondo artista")
if st.button("Confronta"):
if artist1_name and artist2_name:
artist1_info = get_artist_info(artist1_name)
artist2_info = get_artist_info(artist2_name)
artist1_tracks = get_top_tracks(artist1_info['id'])
artist2_tracks = get_top_tracks(artist2_info['id'])
data_tracks = artist1_tracks + artist2_tracks
col1, col2 = st.columns(2)
with col1:
st.image(artist1_info['image'], caption=artist1_info['name'])
st.markdown(f"**Nome:** {artist1_info['name']}")
st.markdown(f"**Follower:** {artist1_info['followers']:,}")
st.markdown(f"**Popolarità:** {artist1_info['popularity']}")
st.markdown(f"**Generi:** {', '.join(artist1_info['genres'])}")
with col2:
st.image(artist2_info['image'], caption=artist2_info['name'])
st.markdown(f"**Nome:** {artist2_info['name']}")
st.markdown(f"**Follower:** {artist2_info['followers']:,}")
st.markdown(f"**Popolarità:** {artist2_info['popularity']}")
st.markdown(f"**Generi:** {', '.join(artist2_info['genres'])}")
show_average_features(data_tracks)
plot_features_comparison(data_tracks, artist1_info, artist2_info)
plot_audio_features_boxplot(data_tracks, artist1_name, artist2_name)
plot_audio_features_violinplot(data_tracks, artist1_name, artist2_name)
else:
st.error("Per favore inserisci i nomi di entrambi gli artisti.")
if __name__ == "__main__":
main()
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