Add medicine management functionality with UI and data handling

- Implemented MedicineManagementWindow for adding, editing, and removing medicines.
- Created MedicineManager to handle medicine configurations, including loading and saving to JSON.
- Updated UIManager to dynamically generate medicine-related UI components based on the MedicineManager.
- Enhanced test suite with mock objects for MedicineManager to ensure proper functionality in DataManager tests.
- Added validation for medicine input fields in the UI.
- Introduced default medicine configurations for initial setup.

src/data_manager.py

@@ -4,40 +4,37 @@ import os
 
 import pandas as pd
 
+from medicine_manager import MedicineManager
+
 
 class DataManager:
     """Handle all data operations for the application."""
 
-    def __init__(self, filename: str, logger: logging.Logger) -> None:
+    def __init__(
+        self, filename: str, logger: logging.Logger, medicine_manager: MedicineManager
+    ) -> None:
         self.filename: str = filename
         self.logger: logging.Logger = logger
+        self.medicine_manager = medicine_manager
         self._initialize_csv_file()
 
+    def _get_csv_headers(self) -> list[str]:
+        """Get CSV headers based on current medicine configuration."""
+        base_headers = ["date", "depression", "anxiety", "sleep", "appetite"]
+
+        # Add medicine headers
+        medicine_headers = []
+        for medicine_key in self.medicine_manager.get_medicine_keys():
+            medicine_headers.extend([medicine_key, f"{medicine_key}_doses"])
+
+        return base_headers + medicine_headers + ["note"]
+
     def _initialize_csv_file(self) -> None:
         """Create CSV file with headers if it doesn't exist."""
         if not os.path.exists(self.filename):
             with open(self.filename, mode="w", newline="") as file:
                 writer = csv.writer(file)
-                writer.writerow(
-                    [
-                        "date",
-                        "depression",
-                        "anxiety",
-                        "sleep",
-                        "appetite",
-                        "bupropion",
-                        "bupropion_doses",
-                        "hydroxyzine",
-                        "hydroxyzine_doses",
-                        "gabapentin",
-                        "gabapentin_doses",
-                        "propranolol",
-                        "propranolol_doses",
-                        "quetiapine",
-                        "quetiapine_doses",
-                        "note",
-                    ]
-                )
+                writer.writerow(self._get_csv_headers())
 
     def load_data(self) -> pd.DataFrame:
         """Load data from CSV file."""
@@ -46,27 +43,22 @@ class DataManager:
             return pd.DataFrame()
 
         try:
-            df: pd.DataFrame = pd.read_csv(
-                self.filename,
-                dtype={
-                    "depression": int,
-                    "anxiety": int,
-                    "sleep": int,
-                    "appetite": int,
-                    "bupropion": int,
-                    "bupropion_doses": str,
-                    "hydroxyzine": int,
-                    "hydroxyzine_doses": str,
-                    "gabapentin": int,
-                    "gabapentin_doses": str,
-                    "propranolol": int,
-                    "propranolol_doses": str,
-                    "quetiapine": int,
-                    "quetiapine_doses": str,
-                    "note": str,
-                    "date": str,
-                },
-            ).fillna("")
+            # Build dtype dictionary dynamically
+            dtype_dict = {
+                "depression": int,
+                "anxiety": int,
+                "sleep": int,
+                "appetite": int,
+                "date": str,
+                "note": str,
+            }
+
+            # Add medicine types
+            for medicine_key in self.medicine_manager.get_medicine_keys():
+                dtype_dict[medicine_key] = int
+                dtype_dict[f"{medicine_key}_doses"] = str
+
+            df: pd.DataFrame = pd.read_csv(self.filename, dtype=dtype_dict).fillna("")
             return df.sort_values(by="date").reset_index(drop=True)
         except pd.errors.EmptyDataError:
             self.logger.warning("CSV file is empty. No data to load.")
@@ -207,18 +199,14 @@ class DataManager:
                     "anxiety": 0,
                     "sleep": 0,
                     "appetite": 0,
-                    "bupropion": 0,
-                    "bupropion_doses": "",
-                    "hydroxyzine": 0,
-                    "hydroxyzine_doses": "",
-                    "gabapentin": 0,
-                    "gabapentin_doses": "",
-                    "propranolol": 0,
-                    "propranolol_doses": "",
-                    "quetiapine": 0,
-                    "quetiapine_doses": "",
                     "note": "",
                 }
+
+                # Add medicine columns dynamically
+                for medicine_key in self.medicine_manager.get_medicine_keys():
+                    new_entry[medicine_key] = 0
+                    new_entry[f"{medicine_key}_doses"] = ""
+
                 df = pd.concat([df, pd.DataFrame([new_entry])], ignore_index=True)
 
             # Add dose to the appropriate medicine