Add comprehensive tests for dose tracking functionality

- Implemented `test_dose_parsing_simple.py` to validate the dose parsing workflow.
- Created `test_dose_save.py` to verify the saving functionality of dose tracking.
- Added `test_dose_save_simple.py` for programmatic testing of dose saving without UI interaction.
- Developed `test_final_workflow.py` to test the complete dose tracking workflow, ensuring doses are preserved during edits.
- Enhanced `conftest.py` with a mock pathology manager for testing.
- Updated `test_data_manager.py` to include pathology manager in DataManager tests and ensure compatibility with new features.

test_final_workflow.py

@@ -0,0 +1,146 @@
+#!/usr/bin/env python3
+"""Test the complete dose tracking workflow after fixing the parsing issues."""
+
+import os
+import shutil
+import sys
+import tempfile
+from unittest.mock import Mock
+
+import pandas as pd
+
+sys.path.append("src")
+from data_manager import DataManager
+from ui_manager import UIManager
+
+
+def test_dose_workflow():
+    """Test that doses are preserved when editing through the UI."""
+
+    # Create temporary directory and CSV file
+    temp_dir = tempfile.mkdtemp()
+    csv_file = os.path.join(temp_dir, "test.csv")
+    print(f"Using temporary CSV: {csv_file}")
+
+    try:
+        # Create mock managers with known configurations
+        mock_medicine_manager = Mock()
+        mock_medicine_manager.get_dynamic_columns.return_value = [
+            "Medicine A",
+            "Medicine B",
+        ]
+        mock_medicine_manager.get_medicines.return_value = {
+            "med1": {"name": "Medicine A"},
+            "med2": {"name": "Medicine B"},
+        }
+        mock_medicine_manager.get_medicine_keys.return_value = ["med1", "med2"]
+
+        mock_pathology_manager = Mock()
+        mock_pathology_manager.get_dynamic_columns.return_value = [
+            "Pathology X",
+            "Pathology Y",
+        ]
+        mock_pathology_manager.get_pathology_keys.return_value = ["path1", "path2"]
+
+        # Create DataManager and UIManager
+        import logging
+        import tkinter as tk
+
+        logger = logging.getLogger("test")
+        root = tk.Tk()
+        root.withdraw()  # Hide the window during testing
+
+        data_manager = DataManager(
+            csv_file, logger, mock_medicine_manager, mock_pathology_manager
+        )
+        ui_manager = UIManager(
+            root, logger, mock_medicine_manager, mock_pathology_manager
+        )
+
+        # Add initial entry with some doses
+        print("\n1. Adding initial entry with two doses...")
+        initial_data = {
+            "Date": "2025-01-30",
+            "Depression": 3,
+            "Anxiety": 4,
+            "Sleep": 7,
+            "Appetite": 6,
+            "Medicine A": "2025-01-30 08:00:00:150mg|2025-01-30 14:00:00:25mg",
+            "Medicine B": "",
+            "Pathology X": 2,
+            "Pathology Y": 1,
+            "Notes": "Initial entry",
+        }
+        data_manager.add_entry(initial_data)
+
+        # Check what was saved
+        df = pd.read_csv(csv_file)
+        print(f'Medicine A after initial save: "{df.iloc[0]["Medicine A"]}"')
+
+        # Now simulate the UI editing workflow
+        print("\n2. Simulating UI edit workflow...")
+
+        # Get the saved data (as it would appear in edit window)
+        saved_medicine_a = df.iloc[0]["Medicine A"]
+        print(f'Saved Medicine A doses: "{saved_medicine_a}"')
+
+        # Create mock text widget to simulate _populate_dose_history
+        class MockText:
+            def __init__(self):
+                self.content = ""
+
+            def configure(self, state):
+                pass
+
+            def delete(self, start, end):
+                self.content = ""
+
+            def insert(self, pos, text):
+                self.content = text
+
+            def get(self, start, end):
+                return self.content
+
+        mock_text = MockText()
+        ui_manager._populate_dose_history(mock_text, saved_medicine_a)
+        print(f'UI display after _populate_dose_history: "{mock_text.content}"')
+
+        # Simulate user adding a new dose to the text widget
+        user_edited_content = mock_text.content + "\n• 06:00 PM - 50mg"
+        print(f'User adds new dose, text widget now contains: "{user_edited_content}"')
+
+        # Parse this back for saving
+        parsed_doses = ui_manager._parse_dose_history_for_saving(
+            user_edited_content, "2025-01-30"
+        )
+        print(f'Parsed for saving: "{parsed_doses}"')
+
+        # Update the entry
+        update_data = initial_data.copy()
+        update_data["Medicine A"] = parsed_doses
+        data_manager.update_entry("2025-01-30", update_data)
+
+        # Check final result
+        df = pd.read_csv(csv_file)
+        final_medicine_a = df.iloc[0]["Medicine A"]
+        print(f'\n3. Final Medicine A after update: "{final_medicine_a}"')
+
+        # Count doses
+        dose_count = len([d for d in final_medicine_a.split("|") if d.strip()])
+        print(f"Final dose count: {dose_count}")
+
+        if dose_count == 3:
+            print("✅ SUCCESS: All doses preserved!")
+            return True
+        else:
+            print("❌ FAILURE: Doses were lost!")
+            return False
+
+    finally:
+        # Clean up
+        shutil.rmtree(temp_dir)
+
+
+if __name__ == "__main__":
+    success = test_dose_workflow()
+    sys.exit(0 if success else 1)