feat: Update DataManager to support new quetiapine medication format and adjust VSCode task command

.gitignore

@@ -47,7 +47,7 @@ htmlcov/
 .pylint.d/
 
 # IDEs and editors
-.vscode/
+#.vscode/
 !.vscode/tasks.json
 !.vscode/launch.json
 .idea/

.vscode/tasks.json

@@ -4,7 +4,13 @@
 		{
 			"label": "Run TheChart App",
 			"type": "shell",
-			"command": "cd /home/will/Code/thechart && python -m src.main",
+			"command": "/home/will/Code/thechart/.venv/bin/python",
+			"args": [
+				"src/main.py"
+			],
+			"options": {
+				"cwd": "/home/will/Code/thechart"
+			},
 			"group": "build",
 			"isBackground": false,
 			"problemMatcher": []

src/data_manager.py

@@ -108,9 +108,32 @@ class DataManager:
                 return False
 
             # Find the row to update using original_date as a unique identifier
-            # Handle both old format (10 columns) and new format (14 columns)
+            # Handle both old format (10 columns) and new format (16 columns)
-            if len(values) == 14:
+            if len(values) == 16:
-                # New format with dose columns
+                # New format with all dose columns including quetiapine
+                df.loc[
+                    df["date"] == original_date,
+                    [
+                        "date",
+                        "depression",
+                        "anxiety",
+                        "sleep",
+                        "appetite",
+                        "bupropion",
+                        "bupropion_doses",
+                        "hydroxyzine",
+                        "hydroxyzine_doses",
+                        "gabapentin",
+                        "gabapentin_doses",
+                        "propranolol",
+                        "propranolol_doses",
+                        "quetiapine",
+                        "quetiapine_doses",
+                        "note",
+                    ],
+                ] = values
+            elif len(values) == 14:
+                # Format without quetiapine
                 df.loc[
                     df["date"] == original_date,
                     [
@@ -192,6 +215,8 @@ class DataManager:
                     "gabapentin_doses": "",
                     "propranolol": 0,
                     "propranolol_doses": "",
+                    "quetiapine": 0,
+                    "quetiapine_doses": "",
                     "note": "",
                 }
                 df = pd.concat([df, pd.DataFrame([new_entry])], ignore_index=True)