Update app.py

app.py

@@ -12,10 +12,10 @@ def numbers_to_xlsx(numbers_file):
     Efficiently converts a Numbers file to XLSX format with optimized memory usage.
 
     Args:
-        numbers_file: The uploaded Numbers file object.
+        numbers_file: The uploaded Numbers file object from Gradio.
 
     Returns:
-        str: Path to the converted xlsx file, or error message if conversion fails.
+        str: Path to the converted xlsx file, or None if conversion fails.
     """
     if not numbers_file:
         return None
@@ -26,44 +26,55 @@ def numbers_to_xlsx(numbers_file):
         os.makedirs(output_dir, exist_ok=True)
         output_path = os.path.join(output_dir, "converted.xlsx")
         
-        # Read the Numbers file efficiently
+        # Read the Numbers file efficiently using the temporary path
         doc = Document(numbers_file.name)
         
-        # Validate document structure
-        if not doc.sheets or not doc.sheets[0].tables:
+        # Get all sheets and validate
+        sheets = doc.sheets
+        if not sheets:
+            print("No sheets found in the document")
             return None
+            
+        # Process each sheet
+        writer = pd.ExcelWriter(output_path, engine='openpyxl')
         
-        # Get the first table's data efficiently
-        table = doc.sheets[0].tables[0]
-        
-        # Extract headers and data in one pass
-        rows = list(table.rows(values_only=True))
-        if not rows:
-            return None
-        
-        headers = rows[0]
-        data = rows[1:]
-        
-        # Use pandas optimized DataFrame construction
-        df = pd.DataFrame(data, columns=headers)
-        
-        # Optimize Excel writing with correct options
-        writer = pd.ExcelWriter(
-            output_path,
-            engine='openpyxl'
-        )
-        
-        df.to_excel(
-            writer,
-            index=False,
-            sheet_name='Sheet1'
-        )
+        for sheet_index, sheet in enumerate(sheets):
+            if not sheet.tables:
+                continue
+                
+            # Get the first table in the sheet
+            table = sheet.tables[0]
+            
+            # Extract data
+            rows = list(table.rows(values_only=True))
+            if not rows:
+                continue
+                
+            # Split headers and data
+            headers = rows[0] if rows else []
+            data = rows[1:] if len(rows) > 1 else []
+            
+            # Create DataFrame and write to Excel
+            df = pd.DataFrame(data, columns=headers)
+            sheet_name = f"Sheet{sheet_index + 1}"
+            
+            df.to_excel(
+                writer,
+                sheet_name=sheet_name,
+                index=False
+            )
+            
+            # Freeze the header row
+            writer.sheets[sheet_name].freeze_panes = 'A2'
         
-        # Freeze the header row using openpyxl directly
-        writer.sheets['Sheet1'].freeze_panes = 'A2'
         writer.close()
         
-        return output_path
+        # Verify the file was created and has content
+        if os.path.exists(output_path) and os.path.getsize(output_path) > 0:
+            return output_path
+        else:
+            print("Output file is empty or was not created")
+            return None
             
     except Exception as e:
         print(f"Error converting file: {str(e)}")