Update task_operations.py

task_operations.py

@@ -14,15 +14,15 @@ class TaskManager:
         self.create_table()
 
     def create_table(self):
-        # Create tasks table with unique id
+        # Create tasks table with essential fields
         query = """
         CREATE TABLE IF NOT EXISTS tasks (
             id INTEGER PRIMARY KEY AUTOINCREMENT,
-            task_name TEXT,
-            task_time TEXT,
-            task_duration_hours INTEGER,
-            task_duration_minutes INTEGER,
-            category TEXT
+            task_name TEXT NOT NULL,
+            task_time TEXT NOT NULL,
+            task_duration_hours INTEGER NOT NULL,
+            task_duration_minutes INTEGER NOT NULL,
+            category TEXT NOT NULL
         );
         """
         self.conn.execute(query)
@@ -34,17 +34,28 @@ class TaskManager:
         df = pd.read_sql_query(query, self.conn)
 
         if not df.empty:
-            # Ensure 'Task Time' is in datetime format and id is an integer
-            df['Task Time'] = pd.to_datetime(df['task_time'])  # Convert task_time to datetime
-            df['id'] = df['id'].astype(int)  # Ensure id is an integer
-            df = df.rename(columns={
+            # Rename columns explicitly to avoid conflicts
+            column_mapping = {
                 'task_name': 'Task Name', 
                 'task_time': 'Task Time',
                 'task_duration_hours': 'Task Duration (hours)',
                 'task_duration_minutes': 'Task Duration (minutes)', 
                 'category': 'Category', 
-                'id': 'Task ID'  # Rename id to 'Task ID'
-            })
+                'id': 'Task ID'
+            }
+
+            # Check for any conflicts before renaming
+            existing_columns = set(df.columns)
+            for original, new_name in column_mapping.items():
+                if new_name in existing_columns and original != new_name:
+                    raise ValueError(f"Conflict detected: Column '{new_name}' already exists in the DataFrame.")
+
+            # Rename columns in the DataFrame
+            df.rename(columns=column_mapping, inplace=True)
+
+            # Convert 'task_time' to datetime after renaming
+            df['Task Time'] = pd.to_datetime(df['Task Time'])
+
             return df.to_dict(orient='records')
         else:
             return []