Update utils.py

utils.py

@@ -10,6 +10,15 @@ from joblib import dump, load
 from sklearn.preprocessing import normalize
 import re
 
+def check_write_permissions(folder='RecommendationFiles/'):
+    """Check if the folder has write permissions."""
+    if os.access(folder, os.W_OK):
+        st.write(f"DEBUG: Tienes permisos de escritura en '{folder}'.")
+        return True
+    else:
+        st.write(f"DEBUG: No tienes permisos de escritura en '{folder}'.")
+        return False
+
 def get_next_version(file_prefix, folder='RecommendationFiles/'):
     """Find the latest version of a file and return the next version's filename."""
     if not os.path.exists(folder):
@@ -46,7 +55,6 @@ def get_latest_version(file_prefix, folder='RecommendationFiles/'):
     else:
         raise FileNotFoundError(f"No versions found for {file_prefix} in folder '{folder}'")
 
-
 def recomienda_tf(new_basket, cestas, productos): 
 
     # Get the latest versions of the matrix and vectorizer from the folder
@@ -117,34 +125,38 @@ def retroalimentacion(cestas, cesta_nueva):
     # Debugging message
     st.write(f"DEBUG: La nueva cesta es {cesta_unida}")
     
-    # Add the new basket to the historical baskets if it doesn't already exist
-    if not cestas['Cestas'].isin([cesta_unida]).any():
-        cestas.loc[len(cestas)] = cesta_unida
-        st.success("✓ Cesta añadida al DataFrame.")
+    # Check if we have write permissions in the folder
+    if check_write_permissions('RecommendationFiles/'):
+        # Add the new basket to the historical baskets if it doesn't already exist
+        if not cestas['Cestas'].isin([cesta_unida]).any():
+            cestas.loc[len(cestas)] = cesta_unida
+            st.success("✓ Cesta añadida al DataFrame.")
+            
+            # Re-save the updated baskets DataFrame
+            file_path = 'RecommendationFiles/cestas_final.csv'
+            cestas.to_csv(file_path, index=False)
+            
+            st.write(f"DEBUG: Se ha guardado la nueva cesta en {file_path}")
+        else:
+            st.warning("⚠️ La cesta ya existe en el DataFrame.")
+        
+        # Re-vectorize the basket DataFrame
+        count_vectorizer = CountVectorizer()
+        count_vectorizer.fit(cestas['Cestas'])
+        count_matrix = count_vectorizer.transform(cestas['Cestas'])
+        tf_matrix = normalize(count_matrix, norm='l1')
+
+        # Save new versions of the vectorizer and matrix
+        count_vectorizer_file = get_next_version('count_vectorizer')
+        tf_matrix_file = get_next_version('count_matrix')
         
-        # Re-save the updated baskets DataFrame
-        file_path = 'RecommendationFiles/cestas_final.csv'
-        cestas.to_csv(file_path, index=False)
+        dump(count_vectorizer, count_vectorizer_file)
+        dump(tf_matrix, tf_matrix_file)
         
-        st.write(f"DEBUG: Se ha guardado la nueva cesta en {file_path}")
+        # Debugging messages
+        st.write(f"DEBUG: Se ha generado la nueva versión del count_vectorizer: {count_vectorizer_file}")
+        st.write(f"DEBUG: Se ha generado la nueva versión del tf_matrix: {tf_matrix_file}")
     else:
-        st.warning("⚠️ La cesta ya existe en el DataFrame.")
-    
-    # Re-vectorize the basket DataFrame
-    count_vectorizer = CountVectorizer()
-    count_vectorizer.fit(cestas['Cestas'])
-    count_matrix = count_vectorizer.transform(cestas['Cestas'])
-    tf_matrix = normalize(count_matrix, norm='l1')
-
-    # Save new versions of the vectorizer and matrix
-    count_vectorizer_file = get_next_version('count_vectorizer')
-    tf_matrix_file = get_next_version('tf_matrix')
-    
-    dump(count_vectorizer, count_vectorizer_file)
-    dump(tf_matrix, tf_matrix_file)
-    
-    # Debugging messages
-    st.write(f"DEBUG: Se ha generado la nueva versión del count_vectorizer: {count_vectorizer_file}")
-    st.write(f"DEBUG: Se ha generado la nueva versión del tf_matrix: {tf_matrix_file}")
+        st.error("No se puede escribir en la carpeta 'RecommendationFiles/'. Verifica los permisos.")
 
-    return None
+    return None