Updated app.py to include logs to debug errors

app.py

@@ -8,8 +8,19 @@ from rapidfuzz import process, fuzz
 import spotipy
 from spotipy.oauth2 import SpotifyClientCredentials
 import os
+import logging
+import psutil
 
 
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logging.info("Application started")
+
+def log_memory_usage():
+    process = psutil.Process()
+    memory_info = process.memory_info()
+    logging.info(f"Memory Usage: {memory_info.rss / 1024 ** 2:.2f} MB")
+
 # Spotify API setup
 sp = spotipy.Spotify(client_credentials_manager=SpotifyClientCredentials(
     client_id=os.environ['sp_client_id'],
@@ -21,16 +32,22 @@ features = ['popularity', 'danceability', 'energy', 'loudness', 'speechiness',
 default_weights = [1/len(features)] * len(features)
 
 # Read and preprocess the data
-tracks_data = pd.read_csv('filtered_songs.csv')
+logging.info("Reading and preprocessing track data")
+tracks_data = pd.read_csv('iltered_songs.csv')
 tracks_data = tracks_data[(tracks_data['popularity'] > 40) & (tracks_data['instrumentalness'] <= 0.85)]
+logging.info("Track data loaded and processed")
+log_memory_usage()
+
 
 # Function to fetch a song from Spotify
 def get_song_from_spotify(song_name, artist_name=None):
     try:
         search_query = song_name if not artist_name else f"{song_name} artist:{artist_name}"
+        logging.info(f"Searching Spotify for: {search_query}")
         results = sp.search(q=search_query, limit=1, type='track')
         if results['tracks']['items']:
             track = results['tracks']['items'][0]
+            logging.info(f"Found track on Spotify: {track['name']} by {', '.join(artist['name'] for artist in track['artists'])}")
             audio_features = sp.audio_features(track['id'])[0]
             song_details = {
                 'id': track['id'],
@@ -54,13 +71,16 @@ def get_song_from_spotify(song_name, artist_name=None):
             }
             return song_details
         else:
+            logging.warning(f"No results found on Spotify for: {search_query}")
             return None
     except Exception as e:
-        print(f"Error fetching song from Spotify: {e}")
+        logging.error(f"Error fetching song from Spotify: {e}")
         return None
 
 # Enhanced Fuzzy Matching Function
 def enhanced_fuzzy_matching(song_name, artist_name, df):
+    logging.info(f"Performing fuzzy matching for: {song_name}, {artist_name}")
+    # Existing code
     combined_query = f"{song_name} {artist_name}".strip()
     df['combined'] = df['name'] + ' ' + df['artists']
     matches = process.extractOne(combined_query, df['combined'], scorer=fuzz.token_sort_ratio)
@@ -68,6 +88,7 @@ def enhanced_fuzzy_matching(song_name, artist_name, df):
 
 # Function to apply the selected scaler and calculate weighted cosine similarity
 def calculate_weighted_cosine_similarity(input_song_index, weights, num_songs_to_output, tracks_data, scaler_choice):
+    logging.info("Calculating weighted cosine similarity")
     # Apply the selected scaler
     if scaler_choice == 'Standard Scaler':
         scaler = StandardScaler()
@@ -97,7 +118,8 @@ def recommend_songs_interface(song_name, artist_name, num_songs_to_output, scale
         return pd.DataFrame(columns=['name', 'artists'])
 
 # Gradio interface setup
-description = "Enter a song name and artist name to get song recommendations. Adjust the feature weights using the sliders. The system will automatically normalize the weights. Please note that this database can only recommend songs that have been released up until the year 2020. You can adjust the scaler and tweak the sliders to get the right song for you based on the metrics of your choice"
+logging.info("Setting up Gradio interface")
+description = "Enter a song name and artist name (optional) to get song recommendations. Adjust the feature weights using the sliders. The system will automatically normalize the weights."
 
 inputs = [
     gr.components.Textbox(label="Song Name", placeholder="Enter a song name..."),
@@ -121,4 +143,7 @@ iface = gr.Interface(
 
 # Run the Gradio app
 if __name__ == "__main__":
+    logging.info("Setting up Gradio interface")
+    logging.info("Launching Gradio interface")
     iface.launch()
+    logging.info("Application finished")