Update app.py

app.py

@@ -24,8 +24,7 @@ import spotipy
 from spotipy.oauth2 import SpotifyClientCredentials
 
 client_id = "85e49fdb7eb54d84a8da5609196538e7"
-client_credentials_manager = SpotifyClientCredentials(client_id=client_id)
-sp = spotipy.Spotify(client_credentials_manager=client_credentials_manager)
+
 
 
 
@@ -42,6 +41,8 @@ df_num = df.select_dtypes(include = ['float64', 'int64'])
 
 numeric_cols = ['acousticness', 'danceability', 'energy', 'instrumentalness', 'liveness', 'loudness', 'speechiness', 'tempo', 'valence']
 categorical_cols = ['key', 'mode']
+client_secret="16d293ae0c5a4c6ea3e8e301c75bcd43"
+
 
 # Create the preprocessing pipeline
 preprocessing_pipeline = ColumnTransformer(
@@ -52,11 +53,12 @@ preprocessing_pipeline = ColumnTransformer(
 
 # Apply the preprocessing pipeline to your DataFrame
 df_processed = preprocessing_pipeline.fit_transform(df_num)
-
+client_credentials_manager = SpotifyClientCredentials(client_id=client_id)
 num_cols_transformed = numeric_cols
 cat_cols_transformed = preprocessing_pipeline.named_transformers_['cat'].get_feature_names_out(categorical_cols)
 
 # Combine the transformed column names
+sp = spotipy.Spotify(client_credentials_manager=client_credentials_manager)
 all_cols_transformed = num_cols_transformed + cat_cols_transformed.tolist()
 
 # Convert the processed NumPy array back to a DataFrame