Refactor MedTrackerApp and UI components for improved structure and readability

- Simplified initialization logic in init.py
- Consolidated testing_mode assignment
- Removed unnecessary else statements
- Created UIManager class to handle UI-related tasks
- Modularized input frame creation, table frame creation, and graph frame creation
- Enhanced edit window creation with better organization and error handling
- Updated data management methods to improve clarity and maintainability
- Improved logging for better debugging and tracking of application flow

src/data_manager.py

@@ -0,0 +1,120 @@
+import os
+import csv
+import logging
+from typing import List, Union
+
+import pandas as pd
+
+
+class DataManager:
+    """Handle all data operations for the application."""
+
+    def __init__(self, filename: str, logger: logging.Logger) -> None:
+        self.filename: str = filename
+        self.logger: logging.Logger = logger
+        self.initialize_csv()
+
+    def initialize_csv(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",
+                        "hydroxyzine",
+                        "gabapentin",
+                        "propranolol",
+                        "note",
+                    ]
+                )
+
+    def load_data(self) -> pd.DataFrame:
+        """Load data from CSV file."""
+        if (
+            not os.path.exists(self.filename)
+            or os.path.getsize(self.filename) == 0
+        ):
+            self.logger.warning(
+                "CSV file is empty or doesn't exist. No data to load."
+            )
+            return pd.DataFrame()
+
+        try:
+            df: pd.DataFrame = pd.read_csv(
+                self.filename,
+                dtype={
+                    "depression": int,
+                    "anxiety": int,
+                    "sleep": int,
+                    "appetite": int,
+                    "bupropion": int,
+                    "hydroxyzine": int,
+                    "gabapentin": int,
+                    "propranolol": int,
+                    "note": str,
+                    "date": str,
+                },
+            ).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.")
+            return pd.DataFrame()
+        except Exception as e:
+            self.logger.error(f"Error loading data: {str(e)}")
+            return pd.DataFrame()
+
+    def add_entry(self, entry_data: List[Union[str, int]]) -> bool:
+        """Add a new entry to the CSV file."""
+        try:
+            with open(self.filename, mode="a", newline="") as file:
+                writer = csv.writer(file)
+                writer.writerow(entry_data)
+            return True
+        except Exception as e:
+            self.logger.error(f"Error adding entry: {str(e)}")
+            return False
+
+    def update_entry(self, date: str, values: List[Union[str, int]]) -> bool:
+        """Update an existing entry identified by date."""
+        try:
+            df: pd.DataFrame = self.load_data()
+            # Find the row to update using date as a unique identifier
+            df.loc[
+                df["date"] == date,
+                [
+                    "date",
+                    "depression",
+                    "anxiety",
+                    "sleep",
+                    "appetite",
+                    "bupropion",
+                    "hydroxyzine",
+                    "gabapentin",
+                    "propranolol",
+                    "note",
+                ],
+            ] = values
+            df.to_csv(self.filename, index=False)
+            return True
+        except Exception as e:
+            self.logger.error(f"Error updating entry: {str(e)}")
+            return False
+
+    def delete_entry(self, date: str) -> bool:
+        """Delete an entry identified by date."""
+        try:
+            df: pd.DataFrame = self.load_data()
+            # Remove the row with the matching date
+            df = df[df["date"] != date]
+            # Write the updated dataframe back to the CSV
+            df.to_csv(self.filename, index=False)
+            return True
+        except Exception as e:
+            self.logger.error(f"Error deleting entry: {str(e)}")
+            return False