Implement date uniqueness validation in DataManager and update MedTrackerApp for duplicate checks

src/data_manager.py

@@ -66,6 +66,14 @@ class DataManager:
     def add_entry(self, entry_data: list[str | int]) -> bool:
         """Add a new entry to the CSV file."""
         try:
+            # Check if date already exists
+            df: pd.DataFrame = self.load_data()
+            date_to_add: str = str(entry_data[0])
+
+            if not df.empty and date_to_add in df["date"].values:
+                self.logger.warning(f"Entry with date {date_to_add} already exists.")
+                return False
+
             with open(self.filename, mode="a", newline="") as file:
                 writer = csv.writer(file)
                 writer.writerow(entry_data)
@@ -74,13 +82,22 @@ class DataManager:
             self.logger.error(f"Error adding entry: {str(e)}")
             return False
 
-    def update_entry(self, date: str, values: list[str | int]) -> bool:
-        """Update an existing entry identified by date."""
+    def update_entry(self, original_date: str, values: list[str | int]) -> bool:
+        """Update an existing entry identified by original_date."""
         try:
             df: pd.DataFrame = self.load_data()
-            # Find the row to update using date as a unique identifier
+            new_date: str = str(values[0])
+
+            # If the date is being changed, check if the new date already exists
+            if original_date != new_date and new_date in df["date"].values:
+                self.logger.warning(
+                    f"Cannot update: entry with date {new_date} already exists."
+                )
+                return False
+
+            # Find the row to update using original_date as a unique identifier
             df.loc[
-                df["date"] == date,
+                df["date"] == original_date,
                 [
                     "date",
                     "depression",