Feat: add export functionality with GUI for data and graphs

- Implemented ExportWindow class for exporting data and graphs in various formats (JSON, XML, PDF).
- Integrated ExportManager to handle export logic.
- Added export option in the main application menu.
- Enhanced user interface with data summary and export options.
- Included error handling and success messages for export operations.
- Updated dependencies in the lock file to include reportlab and lxml for PDF generation.

.gitignore

@@ -47,7 +47,7 @@ htmlcov/
 .pylint.d/
 
 # IDEs and editors
-#.vscode/
+.vscode/
 !.vscode/tasks.json
 !.vscode/launch.json
 .idea/
@@ -81,3 +81,4 @@ Thumbs.db
 .Trashes
 ehthumbs.db
 Thumbs.db
+integration_test_exports/

Makefile

@@ -1,5 +1,5 @@
 TARGET=thechart
-VERSION=1.6.1
+VERSION=1.8.5
 ROOT=/home/will
 ICON=chart-671.png
 SHELL=fish
@@ -85,7 +85,7 @@ install: ## Set up the development environment
 	@echo "To run tests: make test"
 build: ## Build the Docker image
 	@echo "Building the Docker image..."
-	docker buildx build --platform linux/amd64,linux/arm64 -t ${IMAGE} --push .
+	docker buildx build --platform linux/amd64 -t ${IMAGE} --push .
 deploy: ## Deploy the application as a standalone executable
 	@echo "Deploying the application..."
 	pyinstaller --name ${TARGET} --optimize 2 --onefile --windowed --hidden-import='PIL._tkinter_finder' --icon='${ICON}' --add-data="./.env:." --add-data='./chart-671.png:.' --add-data='./thechart_data.csv:.' --log-level=DEBUG src/main.py
@@ -121,21 +121,6 @@ test-watch: ## Run tests in watch mode
 test-debug: ## Run tests with debug output
 	@echo "Running tests with debug output..."
 	.venv/bin/python -m pytest tests/ -v -s --tb=long --cov=src
-test-dose-tracking: ## Test the dose tracking functionality
-	@echo "Testing dose tracking functionality..."
-	.venv/bin/python scripts/test_dose_tracking.py
-test-scrollable-input: ## Test the scrollable input frame UI
-	@echo "Testing scrollable input frame..."
-	.venv/bin/python scripts/test_scrollable_input.py
-test-edit-functionality: ## Test the enhanced edit functionality
-	@echo "Testing edit functionality..."
-	.venv/bin/python scripts/test_edit_functionality.py
-test-edit-window: $(VENV_ACTIVATE)  ## Test edit window functionality (save and delete)
-	@echo "Running edit window functionality test..."
-	$(PYTHON) scripts/test_edit_window_functionality.py
-test-dose-editing: $(VENV_ACTIVATE)  ## Test dose editing functionality in edit window
-	@echo "Running dose editing functionality test..."
-	$(PYTHON) scripts/test_dose_editing_functionality.py
 lint: ## Run the linter
 	@echo "Running the linter..."
 	docker-compose exec ${TARGET} pipenv run pre-commit run --all-files
@@ -157,4 +142,4 @@ commit-emergency: ## Emergency commit (bypasses pre-commit hooks) - USE SPARINGL
 	@read -p "Enter commit message: " msg; \
 	git add . && git commit --no-verify -m "$$msg"
 	@echo "✅ Emergency commit completed. Please run tests manually when possible."
-.PHONY: install clean reinstall check-env build attach deploy run start stop test lint format shell requirements commit-emergency test-dose-tracking test-scrollable-input test-edit-functionality test-edit-window test-dose-editing migrate-csv help
+.PHONY: install clean reinstall check-env build attach deploy run start stop test lint format shell requirements commit-emergency help

README.md

@@ -15,6 +15,7 @@ make test
 
 ## 📚 Documentation
 - **[Features Guide](docs/FEATURES.md)** - Complete feature documentation
+- **[Export System](docs/EXPORT_SYSTEM.md)** - Data export functionality and formats
 - **[Development Guide](docs/DEVELOPMENT.md)** - Testing, development, and architecture
 - **[Changelog](docs/CHANGELOG.md)** - Version history and feature evolution
 - **[Quick Reference](#quick-reference)** - Common commands and shortcuts
@@ -226,6 +227,13 @@ On first run, the application will:
 - **Backward Compatibility**: Seamless upgrades without data loss
 - **Dynamic Columns**: Adapts to new medicines and pathologies
 
+### 📋 Data Export System
+- **Multiple Formats**: Export to JSON, XML, and PDF formats
+- **Comprehensive Reports**: PDF exports with optional graph visualization
+- **Metadata Inclusion**: Export includes date ranges, pathologies, and medicines
+- **User-Friendly Interface**: Easy access through File menu with format selection
+- **Data Portability**: Structured exports for analysis or backup purposes
+
 For complete feature documentation, see **[docs/FEATURES.md](docs/FEATURES.md)**.
 
 ## Development

docker-build.sh

@@ -1,19 +1,19 @@
 #!/usr/bin/bash
 
 CONTAINER_ENGINE="docker" # podman | docker
-VERSION="v1.0.0"
+VERSION="v1.7.5"
 REGISTRY="gitea-http.taildb3494.ts.net/will/thechart"
 
 if [ "$CONTAINER_ENGINE" == "podman" ];
 then
     buildah build \
     -t $REGISTRY:$VERSION \
-    --platform linux/amd64,linux/arm64/v8 \
+    --platform linux/amd64 \
     --no-cache .
 else
     DOCKER_BUILDKIT=1 \
     docker buildx build \
-    --platform linux/amd64,linux/arm64/v8 \
+    --platform linux/amd64 \
     -t $REGISTRY:$VERSION \
     --no-cache \
     --push .

docs/EXPORT_SYSTEM.md

@@ -0,0 +1,215 @@
+# TheChart Export System Documentation
+
+## Overview
+
+The TheChart application now includes a comprehensive data export system that allows users to export their medication tracking data and visualizations to multiple formats:
+
+- **JSON** - Structured data format with metadata
+- **XML** - Hierarchical data format
+- **PDF** - Formatted report with optional graph visualization
+
+## Features
+
+### Export Formats
+
+#### JSON Export
+- Exports all CSV data to structured JSON format
+- Includes metadata about the export (date, total entries, date range)
+- Lists all pathologies and medicines being tracked
+- Data is exported as an array of entry objects
+
+#### XML Export
+- Exports data to hierarchical XML format
+- Includes comprehensive metadata section
+- All entries are properly structured with XML tags
+- Column names are sanitized for valid XML element names
+
+#### PDF Export
+- Creates a formatted report document
+- Includes export metadata and summary information
+- Optional graph visualization inclusion
+- Data table with all entries
+- Proper pagination and styling
+- Notes are truncated for better table formatting
+
+### User Interface
+
+The export functionality is accessible through:
+1. **File Menu** - "Export Data..." option in the main menu bar
+2. **Export Window** - Modal dialog with export options
+3. **Format Selection** - Radio buttons for JSON, XML, or PDF
+4. **Graph Option** - Checkbox to include graph in PDF exports
+5. **File Dialog** - Standard save dialog for choosing export location
+
+### Export Manager Architecture
+
+The export system consists of three main components:
+
+#### ExportManager Class (`src/export_manager.py`)
+- Core export functionality
+- Handles data transformation and file generation
+- Integrates with existing data and graph managers
+- Supports all three export formats
+
+#### ExportWindow Class (`src/export_window.py`)
+- GUI interface for export operations
+- Modal dialog with export options
+- File save dialog integration
+- Progress feedback and error handling
+
+#### Integration in MedTrackerApp (`src/main.py`)
+- Export manager initialization
+- Menu integration
+- Seamless integration with existing managers
+
+## Technical Implementation
+
+### Dependencies Added
+- `reportlab` - PDF generation library
+- `lxml` - XML processing (added for future enhancements)
+- `charset-normalizer` - Character encoding support
+
+### Data Flow
+1. User selects export format and options
+2. ExportManager loads data from DataManager
+3. Data is transformed according to selected format
+4. Graph image is optionally generated for PDF
+5. Output file is created and saved
+6. User receives success/failure feedback
+
+### Error Handling
+- Graceful handling of missing data
+- File system error management
+- User-friendly error messages
+- Logging of export operations
+
+## Usage Examples
+
+### Basic Export Process
+1. Open TheChart application
+2. Go to File → Export Data...
+3. Select desired format (JSON/XML/PDF)
+4. For PDF: choose whether to include graph
+5. Click "Export..." button
+6. Choose save location and filename
+7. Confirm successful export
+
+### Export File Examples
+
+#### JSON Structure
+```json
+{
+  "metadata": {
+    "export_date": "2025-08-02T09:03:22.580489",
+    "total_entries": 32,
+    "date_range": {
+      "start": "07/02/2025",
+      "end": "08/02/2025"
+    },
+    "pathologies": ["depression", "anxiety", "sleep", "appetite"],
+    "medicines": ["bupropion", "hydroxyzine", "gabapentin", "propranolol", "quetiapine"]
+  },
+  "entries": [
+    {
+      "date": "07/02/2025",
+      "depression": 8,
+      "anxiety": 5,
+      "sleep": 3,
+      "appetite": 1,
+      "bupropion": 0,
+      "bupropion_doses": "",
+      "note": "Starting medication tracking"
+    }
+  ]
+}
+```
+
+#### XML Structure
+```xml
+<?xml version="1.0" encoding="UTF-8"?>
+<thechart_data>
+  <metadata>
+    <export_date>2025-08-02T09:03:22.613013</export_date>
+    <total_entries>32</total_entries>
+    <date_range>
+      <start>07/02/2025</start>
+      <end>08/02/2025</end>
+    </date_range>
+  </metadata>
+  <entries>
+    <entry>
+      <date>07/02/2025</date>
+      <depression>8</depression>
+      <anxiety>5</anxiety>
+      <note>Starting medication tracking</note>
+    </entry>
+  </entries>
+</thechart_data>
+```
+
+## Testing
+
+### Automated Tests
+- Export functionality is tested through `simple_export_test.py`
+- Creates sample exports in all three formats
+- Validates file creation and basic content structure
+
+### Manual Testing
+- GUI testing available through `test_export_gui.py`
+- Opens export window for interactive testing
+- Allows testing of all user interface components
+
+### Test Files Location
+Exported test files are created in the `test_exports/` directory:
+- `export.json` - JSON format export
+- `export.xml` - XML format export
+- `export.csv` - CSV format copy
+- `test_export.pdf` - PDF format with graph
+
+## File Locations
+
+### Source Files
+- `src/export_manager.py` - Core export functionality
+- `src/export_window.py` - GUI export interface
+
+### Test Files
+- `simple_export_test.py` - Basic export functionality test
+- `test_export_gui.py` - GUI testing interface
+- `scripts/test_export_functionality.py` - Comprehensive export tests
+
+### Dependencies
+- Added to `requirements.txt` and managed by `uv`
+- PDF generation requires `reportlab`
+- XML processing enhanced with `lxml`
+
+## Future Enhancements
+
+Potential improvements for the export system:
+1. **Additional Formats** - Excel, CSV with formatting
+2. **Export Filtering** - Date range selection, specific pathologies/medicines
+3. **Batch Exports** - Multiple formats at once
+4. **Email Integration** - Direct email export
+5. **Cloud Storage** - Export to cloud services
+6. **Export Scheduling** - Automated periodic exports
+7. **Advanced PDF Styling** - Charts, graphs, custom layouts
+
+## Troubleshooting
+
+### Common Issues
+1. **No Data to Export** - Ensure CSV file has entries before exporting
+2. **PDF Generation Fails** - Check ReportLab installation and permissions
+3. **File Save Errors** - Verify write permissions to selected directory
+4. **Large File Exports** - PDF exports may take longer for large datasets
+
+### Debugging
+- Check application logs for detailed error messages
+- Export operations are logged with DEBUG level information
+- File system errors are captured and reported to user
+
+## Integration Notes
+
+The export system integrates seamlessly with existing TheChart functionality:
+- Uses same data validation and loading mechanisms
+- Respects existing pathology and medicine configurations
+- Maintains data integrity and formatting consistency
+- Follows existing logging and error handling patterns

pyproject.toml

@@ -1,14 +1,16 @@
 [project]
 name = "thechart"
-version = "1.6.1"
+version = "1.8.5"
 description = "Chart to monitor your medication intake over time."
 readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [
     "colorlog>=6.9.0",
     "dotenv>=0.9.9",
+    "lxml>=6.0.0",
     "matplotlib>=3.10.3",
     "pandas>=2.3.1",
+    "reportlab>=4.4.3",
     "tk>=0.1.0",
 ]
 

scripts/README.md

@@ -0,0 +1,61 @@
+# TheChart Scripts Directory
+
+This directory contains testing and utility scripts for TheChart application.
+
+## Scripts Overview
+
+### Testing Scripts
+
+#### `run_tests.py`
+Main test runner for the application.
+```bash
+cd /home/will/Code/thechart
+.venv/bin/python scripts/run_tests.py
+```
+
+#### `integration_test.py`
+Comprehensive integration test for the export system.
+- Tests all export formats (JSON, XML, PDF)
+- Validates data integrity and file creation
+- No GUI dependencies - safe for automated testing
+
+```bash
+cd /home/will/Code/thechart
+.venv/bin/python scripts/integration_test.py
+```
+
+### Feature Testing Scripts
+
+#### `test_note_saving.py`
+Tests note saving and retrieval functionality.
+- Validates note persistence in CSV files
+- Tests special characters and formatting
+
+#### `test_update_entry.py`
+Tests entry update functionality.
+- Validates data modification operations
+- Tests date validation and duplicate handling
+
+## Usage
+
+All scripts should be run from the project root directory:
+
+```bash
+cd /home/will/Code/thechart
+.venv/bin/python scripts/<script_name>.py
+```
+
+## Test Data
+
+- Integration tests create temporary export files in `integration_test_exports/` (auto-cleaned)
+- Test scripts use the main `thechart_data.csv` file unless specified otherwise
+- No test data is committed to the repository
+
+## Development
+
+When adding new scripts:
+1. Place them in this directory
+2. Use the standard shebang: `#!/usr/bin/env python3`
+3. Add proper docstrings and error handling
+4. Update this README with script documentation
+5. Follow the project's linting and formatting standards

scripts/integration_test.py

@@ -0,0 +1,128 @@
+#!/usr/bin/env python3
+"""
+Integration test for TheChart export system
+Tests the complete export workflow without GUI dependencies
+"""
+
+import sys
+from pathlib import Path
+
+# Add src to path
+sys.path.insert(0, "src")
+
+from data_manager import DataManager
+from export_manager import ExportManager
+from init import logger
+from medicine_manager import MedicineManager
+from pathology_manager import PathologyManager
+
+
+class MockGraphManager:
+    """Mock graph manager for testing."""
+
+    def __init__(self):
+        self.fig = None
+
+
+def test_integration():
+    """Test complete export system integration."""
+    print("TheChart Export System Integration Test")
+    print("=" * 45)
+
+    # 1. Initialize all managers
+    print("\n1. Initializing managers...")
+    try:
+        medicine_manager = MedicineManager(logger=logger)
+        pathology_manager = PathologyManager(logger=logger)
+        data_manager = DataManager(
+            "thechart_data.csv", logger, medicine_manager, pathology_manager
+        )
+
+        # Mock graph manager (no GUI dependencies)
+        graph_manager = MockGraphManager()
+
+        export_manager = ExportManager(
+            data_manager, graph_manager, medicine_manager, pathology_manager, logger
+        )
+        print("   ✓ All managers initialized successfully")
+    except Exception as e:
+        print(f"   ✗ Manager initialization failed: {e}")
+        return False
+
+    # 2. Check data availability
+    print("\n2. Checking data availability...")
+    try:
+        export_info = export_manager.get_export_info()
+        print(f"   Total entries: {export_info['total_entries']}")
+        print(f"   Has data: {export_info['has_data']}")
+
+        if not export_info["has_data"]:
+            print("   ✗ No data available for export")
+            return False
+
+        print(
+            f"   Date range: {export_info['date_range']['start']} "
+            f"to {export_info['date_range']['end']}"
+        )
+        print(f"   Pathologies: {len(export_info['pathologies'])}")
+        print(f"   Medicines: {len(export_info['medicines'])}")
+        print("   ✓ Data is available for export")
+    except Exception as e:
+        print(f"   ✗ Data check failed: {e}")
+        return False
+
+    # 3. Test all export formats
+    export_dir = Path("integration_test_exports")
+    export_dir.mkdir(exist_ok=True)
+
+    formats_to_test = [
+        ("JSON", "integration_test.json", export_manager.export_data_to_json),
+        ("XML", "integration_test.xml", export_manager.export_data_to_xml),
+        (
+            "PDF",
+            "integration_test.pdf",
+            lambda path: export_manager.export_to_pdf(path, include_graph=False),
+        ),
+    ]
+
+    results = []
+
+    for format_name, filename, export_func in formats_to_test:
+        print(f"\n3.{len(results) + 1}. Testing {format_name} export...")
+        try:
+            file_path = export_dir / filename
+            success = export_func(str(file_path))
+
+            if success and file_path.exists():
+                file_size = file_path.stat().st_size
+                print(
+                    f"   ✓ {format_name} export successful: {filename} "
+                    f"({file_size} bytes)"
+                )
+                results.append(True)
+            else:
+                print(f"   ✗ {format_name} export failed")
+                results.append(False)
+
+        except Exception as e:
+            print(f"   ✗ {format_name} export error: {e}")
+            results.append(False)
+
+    # 4. Summary
+    print("\n4. Test Summary")
+    print(f"   Total tests: {len(results)}")
+    print(f"   Passed: {sum(results)}")
+    print(f"   Failed: {len(results) - sum(results)}")
+
+    if all(results):
+        print("   ✓ All export formats working correctly!")
+        print(f"   Check '{export_dir}' directory for exported files.")
+        return True
+    else:
+        print("   ✗ Some export formats failed")
+        return False
+
+
+if __name__ == "__main__":
+    success = test_integration()
+    sys.exit(0 if success else 1)

scripts/test_note_saving.py

@@ -0,0 +1,69 @@
+#!/usr/bin/env python3
+"""
+Test script to verify note field saving functionality
+"""
+
+import logging
+import os
+import sys
+
+import pandas as pd
+
+# Add src directory to path to import modules
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "src"))
+
+from data_manager import DataManager
+from medicine_manager import MedicineManager
+from pathology_manager import PathologyManager
+
+
+def test_note_saving():
+    """Test note saving functionality by checking current data"""
+    print("Testing note saving functionality...")
+
+    # Initialize logger
+    logger = logging.getLogger("test")
+    logger.setLevel(logging.INFO)
+
+    # Initialize managers
+    medicine_manager = MedicineManager("medicines.json")
+    pathology_manager = PathologyManager("pathologies.json")
+    data_manager = DataManager(
+        "thechart_data.csv", logger, medicine_manager, pathology_manager
+    )
+
+    # Load current data
+    df = data_manager.load_data()
+
+    if df.empty:
+        print("No data found in CSV file")
+        return
+
+    print(f"Found {len(df)} entries in the data file")
+
+    # Check if we have any entries with notes
+    entries_with_notes = df[df["note"].notna() & (df["note"] != "")].copy()
+
+    print(f"Entries with notes: {len(entries_with_notes)}")
+
+    if len(entries_with_notes) > 0:
+        print("\nEntries with notes:")
+        for _, row in entries_with_notes.iterrows():
+            note_preview = (
+                row["note"][:50] + "..." if len(str(row["note"])) > 50 else row["note"]
+            )
+            print(f"  Date: {row['date']}, Note: {note_preview}")
+
+    # Show the most recent entry
+    if len(df) > 0:
+        latest_entry = df.iloc[-1]
+        print("\nMost recent entry:")
+        print(f"  Date: {latest_entry['date']}")
+        print(f"  Note: '{latest_entry['note']}'")
+        print(f"  Note length: {len(str(latest_entry['note']))}")
+        is_empty = pd.isna(latest_entry["note"]) or latest_entry["note"] == ""
+        print(f"  Note is empty/null: {is_empty}")
+
+
+if __name__ == "__main__":
+    test_note_saving()

scripts/test_update_entry.py

@@ -0,0 +1,102 @@
+#!/usr/bin/env python3
+"""
+Test the update_entry functionality with notes
+"""
+
+import logging
+import os
+import sys
+
+# Add src directory to path to import modules
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "src"))
+
+from data_manager import DataManager
+from medicine_manager import MedicineManager
+from pathology_manager import PathologyManager
+
+
+def test_update_entry_with_note():
+    """Test updating an entry with a note"""
+    print("Testing update_entry functionality with notes...")
+
+    # Initialize logger
+    logger = logging.getLogger("test")
+    logger.setLevel(logging.DEBUG)
+
+    # Add console handler to see debug output
+    handler = logging.StreamHandler()
+    handler.setLevel(logging.DEBUG)
+    formatter = logging.Formatter("%(levelname)s - %(message)s")
+    handler.setFormatter(formatter)
+    logger.addHandler(handler)
+
+    # Initialize managers
+    medicine_manager = MedicineManager("medicines.json")
+    pathology_manager = PathologyManager("pathologies.json")
+    data_manager = DataManager(
+        "thechart_data.csv", logger, medicine_manager, pathology_manager
+    )
+
+    # Load current data
+    df = data_manager.load_data()
+
+    if df.empty:
+        print("No data found in CSV file")
+        return
+
+    print(f"Found {len(df)} entries in the data file")
+
+    # Find the most recent entry to test with
+    latest_entry = df.iloc[-1].copy()
+    original_date = latest_entry["date"]
+
+    print(f"Testing with entry: {original_date}")
+    print(f"Current note: '{latest_entry['note']}'")
+
+    # Create test values - keep everything the same but change the note
+    test_note = "This is a test note to verify saving functionality!"
+
+    # Build values list (same format as the UI would send)
+    values = [original_date]  # date
+
+    # Add pathology values
+    pathology_keys = pathology_manager.get_pathology_keys()
+    for key in pathology_keys:
+        values.append(latest_entry.get(key, 0))
+
+    # Add medicine values and doses
+    medicine_keys = medicine_manager.get_medicine_keys()
+    for key in medicine_keys:
+        values.append(latest_entry.get(key, 0))  # medicine checkbox
+        values.append(latest_entry.get(f"{key}_doses", ""))  # medicine doses
+
+    # Add the test note
+    values.append(test_note)
+
+    print(f"Values to save: {values}")
+    print(f"Note in values: '{values[-1]}'")
+
+    # Test the update
+    success = data_manager.update_entry(original_date, values)
+
+    if success:
+        print("Update successful!")
+
+        # Reload and verify
+        df_after = data_manager.load_data()
+        updated_entry = df_after[df_after["date"] == original_date].iloc[0]
+
+        print(f"Note after update: '{updated_entry['note']}'")
+        print(f"Note correctly saved: {updated_entry['note'] == test_note}")
+
+        # Reset the note back to original
+        values[-1] = latest_entry["note"]
+        data_manager.update_entry(original_date, values)
+        print("Reverted note back to original")
+
+    else:
+        print("Update failed!")
+
+
+if __name__ == "__main__":
+    test_update_entry_with_note()

src/data_manager.py

@@ -9,7 +9,7 @@ from pathology_manager import PathologyManager
 
 
 class DataManager:
-    """Handle all data operations for the application."""
+    """Handle all data operations for the application with performance optimizations."""
 
     def __init__(
         self,
@@ -22,10 +22,21 @@ class DataManager:
         self.logger: logging.Logger = logger
         self.medicine_manager = medicine_manager
         self.pathology_manager = pathology_manager
+
+        # Cache for loaded data to avoid repeated file I/O
+        self._data_cache: pd.DataFrame | None = None
+        self._cache_timestamp: float = 0
+        self._headers_cache: tuple[str, ...] | None = None
+        self._dtype_cache: dict[str, type] | None = None
+
         self._initialize_csv_file()
 
-    def _get_csv_headers(self) -> list[str]:
+    def _get_csv_headers(self) -> tuple[str, ...]:
-        """Get CSV headers based on current pathology and medicine configuration."""
+        """Get CSV headers based on current pathology and medicine configuration.
+        Cached to avoid repeated computation."""
+        if self._headers_cache is not None:
+            return self._headers_cache
+
         # Start with date
         headers = ["date"]
 
@@ -37,7 +48,9 @@ class DataManager:
         for medicine_key in self.medicine_manager.get_medicine_keys():
             headers.extend([medicine_key, f"{medicine_key}_doses"])
 
-        return headers + ["note"]
+        result = tuple(headers + ["note"])
+        self._headers_cache = result
+        return result
 
     def _initialize_csv_file(self) -> None:
         """Create CSV file with headers if it doesn't exist or is empty."""
@@ -46,27 +59,74 @@ class DataManager:
                 writer = csv.writer(file)
                 writer.writerow(self._get_csv_headers())
 
+    def _invalidate_cache(self) -> None:
+        """Invalidate the data cache when data changes."""
+        self._data_cache = None
+        self._cache_timestamp = 0
+
+    def _should_reload_data(self) -> bool:
+        """Check if data should be reloaded based on file modification time."""
+        if self._data_cache is None:
+            return True
+
+        try:
+            file_mtime = os.path.getmtime(self.filename)
+            return file_mtime > self._cache_timestamp
+        except OSError:
+            return True
+
+    def _get_dtype_dict(self) -> dict[str, type]:
+        """Get pandas dtype dictionary for efficient reading.
+        Cached to avoid recreation."""
+        if self._dtype_cache is not None:
+            return self._dtype_cache
+
+        dtype_dict = {"date": str, "note": str}
+
+        # Add pathology types
+        for pathology_key in self.pathology_manager.get_pathology_keys():
+            dtype_dict[pathology_key] = int
+
+        # 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
+
+        self._dtype_cache = dtype_dict
+        return dtype_dict
+
     def load_data(self) -> pd.DataFrame:
-        """Load data from CSV file."""
+        """Load data from CSV file with caching for better performance."""
         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()
 
+        # Use cached data if available and file hasn't changed
+        if not self._should_reload_data():
+            return self._data_cache.copy()
+
         try:
-            # Build dtype dictionary dynamically
+            # Use pre-built dtype dictionary for faster parsing
-            dtype_dict = {"date": str, "note": str}
+            dtype_dict = self._get_dtype_dict()
 
-            # Add pathology types
+            # Read with optimized settings
-            for pathology_key in self.pathology_manager.get_pathology_keys():
+            df: pd.DataFrame = pd.read_csv(
-                dtype_dict[pathology_key] = int
+                self.filename,
+                dtype=dtype_dict,
+                na_filter=False,  # Don't convert to NaN, keep as empty strings
+                engine="c",  # Use faster C engine
+            )
 
-            # Add medicine types
+            # Sort only if needed (check if already sorted)
-            for medicine_key in self.medicine_manager.get_medicine_keys():
+            if len(df) > 1 and not df["date"].is_monotonic_increasing:
-                dtype_dict[medicine_key] = int
+                df = df.sort_values(by="date").reset_index(drop=True)
-                dtype_dict[f"{medicine_key}_doses"] = str
+
+            # Cache the data and timestamp
+            self._data_cache = df.copy()
+            self._cache_timestamp = os.path.getmtime(self.filename)
+
+            return df.copy()
 
-            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.")
             return pd.DataFrame()
@@ -75,69 +135,104 @@ class DataManager:
             return pd.DataFrame()
 
     def add_entry(self, entry_data: list[str | int]) -> bool:
-        """Add a new entry to the CSV file."""
+        """Add a new entry to the CSV file with optimized duplicate checking."""
         try:
-            # Check if date already exists
+            # Quick duplicate check using cached data if available
-            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:
+            if self._data_cache is not None:
-                self.logger.warning(f"Entry with date {date_to_add} already exists.")
+                # Use cached data for duplicate check
-                return False
+                if date_to_add in self._data_cache["date"].values:
+                    self.logger.warning(
+                        f"Entry with date {date_to_add} already exists."
+                    )
+                    return False
+            else:
+                # Fallback to loading data if no cache
+                df: pd.DataFrame = self.load_data()
+                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
 
+            # Write to file
             with open(self.filename, mode="a", newline="") as file:
                 writer = csv.writer(file)
                 writer.writerow(entry_data)
+
+            # Invalidate cache since data changed
+            self._invalidate_cache()
             return True
+
         except Exception as e:
             self.logger.error(f"Error adding entry: {str(e)}")
             return False
 
     def update_entry(self, original_date: str, values: list[str | int]) -> bool:
-        """Update an existing entry identified by original_date."""
+        """Update an existing entry identified by original_date
+        with optimized processing."""
         try:
             df: pd.DataFrame = self.load_data()
             new_date: str = str(values[0])
 
-            # If the date is being changed, check if the new date already exists
+            # Optimized duplicate check
-            if original_date != new_date and new_date in df["date"].values:
+            if original_date != new_date:
+                date_exists = (df["date"] == new_date).any()
+                if date_exists:
+                    self.logger.warning(
+                        f"Cannot update: entry with date {new_date} already exists."
+                    )
+                    return False
+
+            # Get current CSV headers to match with values
+            headers = list(self._get_csv_headers())
+
+            # Ensure we have the right number of values with optimized padding
+            if len(values) < len(headers):
+                # Pad with defaults efficiently
+                padding_needed = len(headers) - len(values)
+                for i in range(padding_needed):
+                    header_idx = len(values) + i
+                    if header_idx < len(headers):
+                        header = headers[header_idx]
+                        if header == "note" or header.endswith("_doses"):
+                            values.append("")
+                        else:
+                            values.append(0)
+
+            # Use vectorized update for better performance
+            mask = df["date"] == original_date
+            if mask.any():
+                df.loc[mask, headers] = values
+                # Write back to CSV with optimized method
+                df.to_csv(self.filename, index=False, mode="w")
+                self._invalidate_cache()
+                return True
+            else:
                 self.logger.warning(
-                    f"Cannot update: entry with date {new_date} already exists."
+                    f"Entry with date {original_date} not found for update."
                 )
                 return False
 
-            # Get current CSV headers to match with values
-            headers = self._get_csv_headers()
-
-            # Ensure we have the right number of values
-            if len(values) != len(headers):
-                self.logger.warning(
-                    f"Value count mismatch: expected {len(headers)}, got {len(values)}"
-                )
-                # Pad with defaults if too few values
-                while len(values) < len(headers):
-                    header = headers[len(values)]
-                    if header == "note" or header.endswith("_doses"):
-                        values.append("")
-                    else:
-                        values.append(0)
-
-            # Update the row using column names
-            df.loc[df["date"] == original_date, headers] = 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."""
+        """Delete an entry identified by date with optimized processing."""
         try:
             df: pd.DataFrame = self.load_data()
-            # Remove the row with the matching date
+            original_len = len(df)
+
+            # Use vectorized filtering for better performance
             df = df[df["date"] != date]
-            # Write the updated dataframe back to the CSV
+
-            df.to_csv(self.filename, index=False)
+            # Only write if something was actually deleted
+            if len(df) < original_len:
+                df.to_csv(self.filename, index=False, mode="w")
+                self._invalidate_cache()
+
             return True
         except Exception as e:
             self.logger.error(f"Error deleting entry: {str(e)}")
@@ -146,23 +241,34 @@ class DataManager:
     def get_today_medicine_doses(
         self, date: str, medicine_name: str
     ) -> list[tuple[str, str]]:
-        """Get list of (timestamp, dose) tuples for a medicine on a given date."""
+        """Get list of (timestamp, dose) tuples for a medicine on a given date
+        with caching."""
         try:
             df: pd.DataFrame = self.load_data()
-            if df.empty or date not in df["date"].values:
+            if df.empty:
+                return []
+
+            # Use vectorized filtering for better performance
+            date_mask = df["date"] == date
+            if not date_mask.any():
                 return []
 
             dose_column = f"{medicine_name}_doses"
-            doses_str = df.loc[df["date"] == date, dose_column].iloc[0]
+            if dose_column not in df.columns:
+                return []
+
+            doses_str = df.loc[date_mask, dose_column].iloc[0]
 
             if not doses_str:
                 return []
 
+            # Optimized dose parsing
             doses = []
             for dose_entry in doses_str.split("|"):
                 if ":" in dose_entry:
-                    timestamp, dose = dose_entry.split(":", 1)
+                    parts = dose_entry.split(":", 1)
-                    doses.append((timestamp, dose))
+                    if len(parts) == 2:
+                        doses.append((parts[0], parts[1]))
 
             return doses
         except Exception as e:

src/export_manager.py

@@ -0,0 +1,385 @@
+"""
+Export Manager for TheChart Application
+
+Handles exporting data and graphs to various formats:
+- CSV data to JSON, XML
+- Graphs to PDF (with data tables)
+"""
+
+import contextlib
+import json
+import logging
+import os
+from datetime import datetime
+from pathlib import Path
+from typing import Any
+from xml.dom import minidom
+from xml.etree.ElementTree import Element, SubElement, tostring
+
+import pandas as pd
+from reportlab.lib import colors
+from reportlab.lib.pagesizes import A4
+from reportlab.lib.styles import ParagraphStyle, getSampleStyleSheet
+from reportlab.lib.units import inch
+from reportlab.platypus import (
+    Image,
+    Paragraph,
+    SimpleDocTemplate,
+    Spacer,
+    Table,
+    TableStyle,
+)
+
+from data_manager import DataManager
+from graph_manager import GraphManager
+from medicine_manager import MedicineManager
+from pathology_manager import PathologyManager
+
+
+class ExportManager:
+    """Handle data and graph export operations."""
+
+    def __init__(
+        self,
+        data_manager: DataManager,
+        graph_manager: GraphManager,
+        medicine_manager: MedicineManager,
+        pathology_manager: PathologyManager,
+        logger: logging.Logger,
+    ) -> None:
+        self.data_manager = data_manager
+        self.graph_manager = graph_manager
+        self.medicine_manager = medicine_manager
+        self.pathology_manager = pathology_manager
+        self.logger = logger
+
+    def export_data_to_json(self, export_path: str) -> bool:
+        """Export CSV data to JSON format."""
+        try:
+            df = self.data_manager.load_data()
+            if df.empty:
+                self.logger.warning("No data to export")
+                return False
+
+            # Convert DataFrame to dictionary with better structure
+            export_data = {
+                "metadata": {
+                    "export_date": datetime.now().isoformat(),
+                    "total_entries": len(df),
+                    "date_range": {
+                        "start": df["date"].min() if not df.empty else None,
+                        "end": df["date"].max() if not df.empty else None,
+                    },
+                    "pathologies": list(self.pathology_manager.get_pathology_keys()),
+                    "medicines": list(self.medicine_manager.get_medicine_keys()),
+                },
+                "entries": df.to_dict(orient="records"),
+            }
+
+            with open(export_path, "w", encoding="utf-8") as f:
+                json.dump(export_data, f, indent=2, ensure_ascii=False)
+
+            self.logger.info(f"Data exported to JSON: {export_path}")
+            return True
+
+        except Exception as e:
+            self.logger.error(f"Error exporting to JSON: {str(e)}")
+            return False
+
+    def export_data_to_xml(self, export_path: str) -> bool:
+        """Export CSV data to XML format."""
+        try:
+            df = self.data_manager.load_data()
+            if df.empty:
+                self.logger.warning("No data to export")
+                return False
+
+            # Create root element
+            root = Element("thechart_data")
+
+            # Add metadata
+            metadata = SubElement(root, "metadata")
+            SubElement(metadata, "export_date").text = datetime.now().isoformat()
+            SubElement(metadata, "total_entries").text = str(len(df))
+
+            # Date range
+            date_range = SubElement(metadata, "date_range")
+            SubElement(date_range, "start").text = (
+                df["date"].min() if not df.empty else ""
+            )
+            SubElement(date_range, "end").text = (
+                df["date"].max() if not df.empty else ""
+            )
+
+            # Pathologies
+            pathologies = SubElement(metadata, "pathologies")
+            for pathology in self.pathology_manager.get_pathology_keys():
+                SubElement(pathologies, "pathology").text = pathology
+
+            # Medicines
+            medicines = SubElement(metadata, "medicines")
+            for medicine in self.medicine_manager.get_medicine_keys():
+                SubElement(medicines, "medicine").text = medicine
+
+            # Add entries
+            entries = SubElement(root, "entries")
+            for _, row in df.iterrows():
+                entry = SubElement(entries, "entry")
+                for column, value in row.items():
+                    elem = SubElement(entry, column.replace(" ", "_"))
+                    elem.text = str(value) if pd.notna(value) else ""
+
+            # Pretty print XML
+            rough_string = tostring(root, "utf-8")
+            reparsed = minidom.parseString(rough_string)
+            pretty_xml = reparsed.toprettyxml(indent="  ")
+
+            with open(export_path, "w", encoding="utf-8") as f:
+                f.write(pretty_xml)
+
+            self.logger.info(f"Data exported to XML: {export_path}")
+            return True
+
+        except Exception as e:
+            self.logger.error(f"Error exporting to XML: {str(e)}")
+            return False
+
+    def _save_graph_as_image(self, temp_dir: Path) -> str | None:
+        """Save current graph as temporary image for PDF inclusion."""
+        try:
+            # Check if graph manager exists
+            if self.graph_manager is None:
+                self.logger.warning("No graph manager available for export")
+                return None
+
+            # Check if graph manager and figure exist
+            if not hasattr(self.graph_manager, "fig") or self.graph_manager.fig is None:
+                self.logger.warning("No graph figure available for export")
+                return None
+
+            # Ensure graph is up to date with current data
+            df = self.data_manager.load_data()
+            if not df.empty:
+                self.graph_manager.update_graph(df)
+            else:
+                self.logger.warning("No data available to update graph for export")
+                return None
+
+            # Ensure temp directory exists
+            temp_dir.mkdir(parents=True, exist_ok=True)
+            temp_image_path = temp_dir / "graph.png"
+
+            # Save the current figure
+            self.graph_manager.fig.savefig(
+                str(temp_image_path),
+                dpi=150,
+                bbox_inches="tight",
+                facecolor="white",
+                edgecolor="none",
+            )
+
+            # Verify the file was actually created
+            if not temp_image_path.exists():
+                self.logger.error(
+                    f"Graph image file was not created: {temp_image_path}"
+                )
+                return None
+
+            self.logger.info(f"Graph image saved successfully: {temp_image_path}")
+            return str(temp_image_path)
+
+        except Exception as e:
+            self.logger.error(f"Error saving graph image: {str(e)}")
+            return None
+
+    def export_to_pdf(self, export_path: str, include_graph: bool = True) -> bool:
+        """Export data and optionally graph to PDF format."""
+        try:
+            df = self.data_manager.load_data()
+
+            # Create PDF document
+            doc = SimpleDocTemplate(
+                export_path,
+                pagesize=A4,
+                rightMargin=72,
+                leftMargin=72,
+                topMargin=72,
+                bottomMargin=18,
+            )
+
+            # Get styles
+            styles = getSampleStyleSheet()
+            title_style = ParagraphStyle(
+                "CustomTitle",
+                parent=styles["Heading1"],
+                fontSize=18,
+                spaceAfter=30,
+                textColor=colors.darkblue,
+            )
+
+            story = []
+
+            # Title
+            story.append(Paragraph("TheChart - Medication Tracker Export", title_style))
+            story.append(Spacer(1, 20))
+
+            # Export metadata
+            export_info = [
+                f"Export Date: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}",
+                f"Total Entries: {len(df) if not df.empty else 0}",
+            ]
+
+            if not df.empty:
+                export_info.extend(
+                    [
+                        f"Date Range: {df['date'].min()} to {df['date'].max()}",
+                        (
+                            "Pathologies: "
+                            + ", ".join(self.pathology_manager.get_pathology_keys())
+                        ),
+                        (
+                            "Medicines: "
+                            + ", ".join(self.medicine_manager.get_medicine_keys())
+                        ),
+                    ]
+                )
+
+            for info in export_info:
+                story.append(Paragraph(info, styles["Normal"]))
+
+            story.append(Spacer(1, 20))
+
+            # Include graph if requested and available
+            if include_graph:
+                temp_dir = Path(export_path).parent / "temp_export"
+
+                try:
+                    graph_path = self._save_graph_as_image(temp_dir)
+                    if graph_path and os.path.exists(graph_path):
+                        story.append(
+                            Paragraph("Data Visualization", styles["Heading2"])
+                        )
+                        story.append(Spacer(1, 10))
+
+                        # Add graph image
+                        img = Image(graph_path, width=6 * inch, height=3.6 * inch)
+                        story.append(img)
+                        story.append(Spacer(1, 20))
+
+                        # Clean up temp image
+                        os.remove(graph_path)
+                    else:
+                        # Graph not available, add a note instead
+                        story.append(
+                            Paragraph("Data Visualization", styles["Heading2"])
+                        )
+                        story.append(Spacer(1, 10))
+                        story.append(
+                            Paragraph(
+                                "Graph not available - no data to visualize or graph "
+                                "not generated yet.",
+                                styles["Normal"],
+                            )
+                        )
+                        story.append(Spacer(1, 20))
+
+                except Exception as e:
+                    self.logger.error(f"Error including graph in PDF: {str(e)}")
+                    # Add error note instead of failing completely
+                    story.append(Paragraph("Data Visualization", styles["Heading2"]))
+                    story.append(Spacer(1, 10))
+                    story.append(
+                        Paragraph(
+                            f"Graph could not be included: {str(e)}", styles["Normal"]
+                        )
+                    )
+                    story.append(Spacer(1, 20))
+
+                finally:
+                    # Clean up temp directory
+                    if temp_dir.exists():
+                        with contextlib.suppress(OSError):
+                            temp_dir.rmdir()
+
+            # Add data table if we have data
+            if not df.empty:
+                story.append(Paragraph("Data Table", styles["Heading2"]))
+                story.append(Spacer(1, 10))
+
+                # Prepare table data - limit columns for better PDF formatting
+                display_columns = ["date"]
+                for pathology_key in self.pathology_manager.get_pathology_keys():
+                    display_columns.append(pathology_key)
+                for medicine_key in self.medicine_manager.get_medicine_keys():
+                    display_columns.append(medicine_key)
+                display_columns.append("note")
+
+                # Filter dataframe to display columns that exist
+                available_columns = [
+                    col for col in display_columns if col in df.columns
+                ]
+                display_df = df[available_columns].copy()
+
+                # Truncate long notes for better table formatting
+                if "note" in display_df.columns:
+                    display_df["note"] = display_df["note"].apply(
+                        lambda x: (str(x)[:50] + "...") if len(str(x)) > 50 else str(x)
+                    )
+
+                # Convert to table data
+                table_data = [available_columns]  # Headers
+                for _, row in display_df.iterrows():
+                    table_data.append(
+                        [str(val) if pd.notna(val) else "" for val in row]
+                    )
+
+                # Create table with styling
+                table = Table(table_data, repeatRows=1)
+                table.setStyle(
+                    TableStyle(
+                        [
+                            ("BACKGROUND", (0, 0), (-1, 0), colors.grey),
+                            ("TEXTCOLOR", (0, 0), (-1, 0), colors.whitesmoke),
+                            ("ALIGN", (0, 0), (-1, -1), "CENTER"),
+                            ("FONTNAME", (0, 0), (-1, 0), "Helvetica-Bold"),
+                            ("FONTSIZE", (0, 0), (-1, 0), 10),
+                            ("BOTTOMPADDING", (0, 0), (-1, 0), 12),
+                            ("BACKGROUND", (0, 1), (-1, -1), colors.beige),
+                            ("FONTNAME", (0, 1), (-1, -1), "Helvetica"),
+                            ("FONTSIZE", (0, 1), (-1, -1), 8),
+                            ("GRID", (0, 0), (-1, -1), 1, colors.black),
+                            ("VALIGN", (0, 0), (-1, -1), "TOP"),
+                        ]
+                    )
+                )
+
+                story.append(table)
+            else:
+                story.append(
+                    Paragraph("No data available to export.", styles["Normal"])
+                )
+
+            # Build PDF
+            doc.build(story)
+
+            self.logger.info(f"Data exported to PDF: {export_path}")
+            return True
+
+        except Exception as e:
+            self.logger.error(f"Error exporting to PDF: {str(e)}")
+            return False
+
+    def get_export_info(self) -> dict[str, Any]:
+        """Get information about available data for export."""
+        df = self.data_manager.load_data()
+
+        return {
+            "total_entries": len(df) if not df.empty else 0,
+            "date_range": {
+                "start": df["date"].min() if not df.empty else None,
+                "end": df["date"].max() if not df.empty else None,
+            },
+            "pathologies": list(self.pathology_manager.get_pathology_keys()),
+            "medicines": list(self.medicine_manager.get_medicine_keys()),
+            "has_data": not df.empty,
+        }

src/export_window.py

@@ -0,0 +1,247 @@
+"""
+Export Window for TheChart Application
+
+Provides a GUI interface for exporting data and graphs to various formats.
+"""
+
+import tkinter as tk
+from pathlib import Path
+from tkinter import filedialog, messagebox, ttk
+
+from export_manager import ExportManager
+
+
+class ExportWindow:
+    """Export window for data and graph export functionality."""
+
+    def __init__(self, parent: tk.Tk, export_manager: ExportManager) -> None:
+        self.parent = parent
+        self.export_manager = export_manager
+
+        # Create the export window
+        self.window = tk.Toplevel(parent)
+        self.window.title("Export Data")
+        self.window.geometry("500x450")  # Made taller to ensure buttons are visible
+        self.window.resizable(False, False)
+
+        # Center the window
+        self._center_window()
+
+        # Make window modal
+        self.window.transient(parent)
+        self.window.grab_set()
+
+        # Setup the UI
+        self._setup_ui()
+
+    def _center_window(self) -> None:
+        """Center the export window on the parent window."""
+        self.window.update_idletasks()
+
+        # Get window dimensions
+        width = self.window.winfo_width()
+        height = self.window.winfo_height()
+
+        # Get parent window position and size
+        parent_x = self.parent.winfo_rootx()
+        parent_y = self.parent.winfo_rooty()
+        parent_width = self.parent.winfo_width()
+        parent_height = self.parent.winfo_height()
+
+        # Calculate position to center on parent
+        x = parent_x + (parent_width // 2) - (width // 2)
+        y = parent_y + (parent_height // 2) - (height // 2)
+
+        self.window.geometry(f"{width}x{height}+{x}+{y}")
+
+    def _setup_ui(self) -> None:
+        """Setup the export window UI."""
+        # Main frame
+        main_frame = ttk.Frame(self.window, padding="15")
+        main_frame.pack(fill=tk.BOTH, expand=True)
+
+        # Title
+        title_label = ttk.Label(
+            main_frame, text="Export Data & Graphs", font=("Arial", 14, "bold")
+        )
+        title_label.pack(pady=(0, 15))
+
+        # Create scrollable content area for the main content
+        content_frame = ttk.Frame(main_frame)
+        content_frame.pack(fill=tk.BOTH, expand=True)
+
+        # Export info section
+        self._create_info_section(content_frame)
+
+        # Export options section
+        self._create_options_section(content_frame)
+
+        # Buttons section - always at the bottom
+        self._create_buttons_section(main_frame)
+
+    def _create_info_section(self, parent: ttk.Frame) -> None:
+        """Create the data information section."""
+        info_frame = ttk.LabelFrame(parent, text="Data Summary", padding="10")
+        info_frame.pack(fill=tk.X, pady=(0, 20))
+
+        # Get export info
+        export_info = self.export_manager.get_export_info()
+
+        # Display information
+        if export_info["has_data"]:
+            info_text = f"""Total Entries: {export_info["total_entries"]}
+Date Range: {export_info["date_range"]["start"]} to {export_info["date_range"]["end"]}
+Pathologies: {", ".join(export_info["pathologies"])}
+Medicines: {", ".join(export_info["medicines"])}"""
+        else:
+            info_text = "No data available for export."
+
+        info_label = ttk.Label(info_frame, text=info_text, justify=tk.LEFT)
+        info_label.pack(anchor=tk.W)
+
+    def _create_options_section(self, parent: ttk.Frame) -> None:
+        """Create the export options section."""
+        options_frame = ttk.LabelFrame(parent, text="Export Options", padding="10")
+        options_frame.pack(fill=tk.X, pady=(0, 20))
+
+        # Include graph option (for PDF export)
+        self.include_graph_var = tk.BooleanVar(value=True)
+        graph_check = ttk.Checkbutton(
+            options_frame,
+            text="Include graph in PDF export",
+            variable=self.include_graph_var,
+        )
+        graph_check.pack(anchor=tk.W, pady=(0, 10))
+
+        # Format selection
+        format_label = ttk.Label(options_frame, text="Export Format:")
+        format_label.pack(anchor=tk.W)
+
+        self.format_var = tk.StringVar(value="JSON")
+        formats = ["JSON", "XML", "PDF"]
+
+        for fmt in formats:
+            radio = ttk.Radiobutton(
+                options_frame, text=fmt, variable=self.format_var, value=fmt
+            )
+            radio.pack(anchor=tk.W, padx=(20, 0))
+
+    def _create_buttons_section(self, parent: ttk.Frame) -> None:
+        """Create the buttons section."""
+        # Add a separator for visual clarity
+        separator = ttk.Separator(parent, orient="horizontal")
+        separator.pack(fill=tk.X, pady=(10, 10))
+
+        button_frame = ttk.Frame(parent)
+        button_frame.pack(fill=tk.X, pady=(0, 10))
+
+        # Export button with more prominent styling
+        export_btn = ttk.Button(
+            button_frame, text="Export...", command=self._handle_export
+        )
+        export_btn.pack(side=tk.LEFT, padx=(10, 10), pady=5)
+
+        # Cancel button
+        cancel_btn = ttk.Button(
+            button_frame, text="Cancel", command=self.window.destroy
+        )
+        cancel_btn.pack(side=tk.RIGHT, padx=(10, 10), pady=5)
+
+    def _handle_export(self) -> None:
+        """Handle the export button click."""
+        # Check if we have data to export
+        export_info = self.export_manager.get_export_info()
+        if not export_info["has_data"]:
+            messagebox.showwarning(
+                "No Data", "There is no data available to export.", parent=self.window
+            )
+            return
+
+        # Get selected format
+        selected_format = self.format_var.get()
+
+        # Define file types for dialog
+        file_types = {
+            "JSON": [("JSON files", "*.json"), ("All files", "*.*")],
+            "XML": [("XML files", "*.xml"), ("All files", "*.*")],
+            "PDF": [("PDF files", "*.pdf"), ("All files", "*.*")],
+        }
+
+        # Default filename
+        default_name = f"thechart_export.{selected_format.lower()}"
+
+        # Show save dialog
+        filename = filedialog.asksaveasfilename(
+            parent=self.window,
+            title=f"Export as {selected_format}",
+            defaultextension=f".{selected_format.lower()}",
+            filetypes=file_types[selected_format],
+            initialfile=default_name,
+        )
+
+        if not filename:
+            return
+
+        # Perform export based on selected format
+        success = False
+        try:
+            if selected_format == "JSON":
+                success = self.export_manager.export_data_to_json(filename)
+            elif selected_format == "XML":
+                success = self.export_manager.export_data_to_xml(filename)
+            elif selected_format == "PDF":
+                include_graph = self.include_graph_var.get()
+                success = self.export_manager.export_to_pdf(
+                    filename, include_graph=include_graph
+                )
+
+            if success:
+                messagebox.showinfo(
+                    "Export Successful",
+                    f"Data exported successfully to:\n{filename}",
+                    parent=self.window,
+                )
+                # Ask if user wants to open the file location
+                if messagebox.askyesno(
+                    "Open Location",
+                    "Would you like to open the file location?",
+                    parent=self.window,
+                ):
+                    self._open_file_location(filename)
+
+                self.window.destroy()
+            else:
+                messagebox.showerror(
+                    "Export Failed",
+                    f"Failed to export data as {selected_format}. "
+                    "Please check the logs for more details.",
+                    parent=self.window,
+                )
+
+        except Exception as e:
+            messagebox.showerror(
+                "Export Error",
+                f"An error occurred during export:\n{str(e)}",
+                parent=self.window,
+            )
+
+    def _open_file_location(self, filepath: str) -> None:
+        """Open the file location in the system file manager."""
+        try:
+            file_path = Path(filepath)
+            directory = file_path.parent
+
+            # Use system-specific command to open file manager
+            import subprocess
+            import sys
+
+            if sys.platform == "win32":
+                subprocess.run(["explorer", str(directory)], check=False)
+            elif sys.platform == "darwin":
+                subprocess.run(["open", str(directory)], check=False)
+            else:  # Linux and other Unix-like systems
+                subprocess.run(["xdg-open", str(directory)], check=False)
+
+        except Exception:
+            # If opening file location fails, just ignore silently
+            pass

src/graph_manager.py

@@ -12,7 +12,8 @@ from pathology_manager import PathologyManager
 
 
 class GraphManager:
-    """Handle all graph-related operations for the application."""
+    """Optimized version - Handle all graph-related operations for the
+    application with performance improvements."""
 
     def __init__(
         self,
@@ -24,166 +25,206 @@ class GraphManager:
         self.medicine_manager = medicine_manager
         self.pathology_manager = pathology_manager
 
-        # Configure graph frame to expand
+        # Initialize matplotlib with optimized settings
-        self.parent_frame.grid_rowconfigure(0, weight=1)
+        self.fig: matplotlib.figure.Figure = plt.figure(figsize=(10, 6), dpi=80)
-        self.parent_frame.grid_columnconfigure(0, weight=1)
+        self.ax: Axes = self.fig.add_subplot(111)
 
-        self._initialize_toggle_vars()
+        # Cache for current data to avoid reprocessing
+        self.current_data: pd.DataFrame = pd.DataFrame()
+        self._last_plot_hash: str = ""
+
+        # Initialize UI components
+        self.toggle_vars: dict[str, tk.IntVar] = {}
         self._setup_ui()
-
+        self._initialize_toggle_vars()
-    def _initialize_toggle_vars(self) -> None:
-        """Initialize toggle variables for chart elements."""
-        self.toggle_vars: dict[str, tk.BooleanVar] = {}
-
-        # Initialize pathology toggles dynamically
-        for pathology_key in self.pathology_manager.get_pathology_keys():
-            pathology = self.pathology_manager.get_pathology(pathology_key)
-            default_value = pathology.default_enabled if pathology else True
-            self.toggle_vars[pathology_key] = tk.BooleanVar(value=default_value)
-
-        # Add medicine toggles dynamically
-        for medicine_key in self.medicine_manager.get_medicine_keys():
-            medicine = self.medicine_manager.get_medicine(medicine_key)
-            default_value = medicine.default_enabled if medicine else False
-            self.toggle_vars[medicine_key] = tk.BooleanVar(value=default_value)
-
-    def _setup_ui(self) -> None:
-        """Set up the UI components."""
-        # Create control frame for toggles
-        self.control_frame: ttk.Frame = ttk.Frame(self.parent_frame)
-        self.control_frame.grid(row=0, column=0, sticky="ew", padx=5, pady=5)
-
-        # Create toggle checkboxes
         self._create_chart_toggles()
 
-        # Create graph frame
+    def _initialize_toggle_vars(self) -> None:
-        self.graph_frame: ttk.Frame = ttk.Frame(self.parent_frame)
+        """Initialize toggle variables for chart elements with optimization."""
-        self.graph_frame.grid(row=1, column=0, sticky="nsew", padx=5, pady=5)
+        # Initialize pathology toggles
+        for pathology_key in self.pathology_manager.get_pathology_keys():
+            self.toggle_vars[pathology_key] = tk.IntVar(value=1)
 
-        # Reconfigure parent frame for new layout
+        # Initialize medicine toggles (unchecked by default)
-        self.parent_frame.grid_rowconfigure(1, weight=1)
+        for medicine_key in self.medicine_manager.get_medicine_keys():
-        self.parent_frame.grid_columnconfigure(0, weight=1)
+            self.toggle_vars[medicine_key] = tk.IntVar(value=0)
 
-        # Initialize matplotlib figure and canvas
+    def _setup_ui(self) -> None:
-        self.fig: matplotlib.figure.Figure
+        """Set up the UI components with performance optimizations."""
-        self.ax: Axes
+        # Create canvas with optimized settings
-        self.fig, self.ax = plt.subplots()
+        self.canvas = FigureCanvasTkAgg(self.fig, master=self.parent_frame)
-        self.canvas: FigureCanvasTkAgg = FigureCanvasTkAgg(
+        self.canvas.draw_idle()  # Use draw_idle for better performance
-            figure=self.fig, master=self.graph_frame
-        )
-        self.canvas.get_tk_widget().pack(fill="both", expand=True)
 
-        # Store current data for replotting
+        # Pack canvas
-        self.current_data: pd.DataFrame = pd.DataFrame()
+        canvas_widget = self.canvas.get_tk_widget()
+        canvas_widget.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
+
+        # Create control frame
+        self.control_frame = ttk.Frame(self.parent_frame)
+        self.control_frame.pack(side=tk.BOTTOM, fill=tk.X, padx=5, pady=2)
 
     def _create_chart_toggles(self) -> None:
-        """Create toggle controls for chart elements."""
+        """Create toggle controls for chart elements with improved layout."""
-        ttk.Label(self.control_frame, text="Show/Hide Elements:").pack(
+        # Pathology toggles
-            side="left", padx=5
+        pathology_frame = ttk.LabelFrame(
+            self.control_frame, text="Pathologies", padding="5"
         )
+        pathology_frame.pack(side=tk.LEFT, fill=tk.X, expand=True, padx=2)
 
-        # Pathologies toggles - dynamic based on pathology manager
+        # Use grid for better layout
-        pathologies_frame = ttk.LabelFrame(self.control_frame, text="Pathologies")
+        row, col = 0, 0
-        pathologies_frame.pack(side="left", padx=5, pady=2)
-
         for pathology_key in self.pathology_manager.get_pathology_keys():
             pathology = self.pathology_manager.get_pathology(pathology_key)
             if pathology:
-                checkbox = ttk.Checkbutton(
+                display_name = pathology.display_name
-                    pathologies_frame,
+                text = (
-                    text=pathology.display_name,
+                    display_name[:10] + "..."
+                    if len(display_name) > 10
+                    else display_name
+                )
+                cb = ttk.Checkbutton(
+                    pathology_frame,
+                    text=text,
                     variable=self.toggle_vars[pathology_key],
                     command=self._handle_toggle_changed,
                 )
-                checkbox.pack(side="left", padx=3)
+                cb.grid(row=row, column=col, sticky="w", padx=2)
+                col += 1
+                if col > 1:  # 2 columns max
+                    col = 0
+                    row += 1
 
-        # Medicines toggles - dynamic based on medicine manager
+        # Medicine toggles
-        medicines_frame = ttk.LabelFrame(self.control_frame, text="Medicines")
+        medicine_frame = ttk.LabelFrame(
-        medicines_frame.pack(side="left", padx=5, pady=2)
+            self.control_frame, text="Medicines", padding="5"
+        )
+        medicine_frame.pack(side=tk.RIGHT, fill=tk.X, expand=True, padx=2)
 
+        # Use grid for medicines too
+        row, col = 0, 0
         for medicine_key in self.medicine_manager.get_medicine_keys():
             medicine = self.medicine_manager.get_medicine(medicine_key)
             if medicine:
-                checkbox = ttk.Checkbutton(
+                med_name = medicine.display_name
-                    medicines_frame,
+                text = med_name[:10] + "..." if len(med_name) > 10 else med_name
-                    text=medicine.display_name,
+                cb = ttk.Checkbutton(
+                    medicine_frame,
+                    text=text,
                     variable=self.toggle_vars[medicine_key],
                     command=self._handle_toggle_changed,
                 )
-                checkbox.pack(side="left", padx=3)
+                cb.grid(row=row, column=col, sticky="w", padx=2)
+                col += 1
+                if col > 2:  # 3 columns max for medicines
+                    col = 0
+                    row += 1
 
     def _handle_toggle_changed(self) -> None:
-        """Handle toggle changes by replotting the graph."""
+        """Handle toggle changes by replotting the graph with optimization."""
         if not self.current_data.empty:
             self._plot_graph_data(self.current_data)
 
     def update_graph(self, df: pd.DataFrame) -> None:
-        """Update the graph with new data."""
+        """Update the graph with new data using optimization checks."""
-        self.current_data = df.copy() if not df.empty else pd.DataFrame()
+        # Create hash of data to avoid unnecessary redraws
-        self._plot_graph_data(df)
+        data_hash = str(hash(str(df.values.tobytes()) if not df.empty else "empty"))
+
+        # Only update if data actually changed
+        if data_hash != self._last_plot_hash or self.current_data.empty:
+            self.current_data = df.copy() if not df.empty else pd.DataFrame()
+            self._last_plot_hash = data_hash
+            self._plot_graph_data(df)
 
     def _plot_graph_data(self, df: pd.DataFrame) -> None:
-        """Plot the graph data with current toggle settings."""
+        """Plot the graph data with current toggle settings using optimizations."""
-        self.ax.clear()
+        # Use batch updates to reduce redraws
-        if not df.empty:
+        with plt.ioff():  # Turn off interactive mode for batch updates
-            # Convert dates and sort
+            self.ax.clear()
-            df = df.copy()  # Create a copy to avoid modifying the original
-            df["date"] = pd.to_datetime(df["date"])
-            df = df.sort_values(by="date")
-            df.set_index(keys="date", inplace=True)
 
-            # Track if any series are plotted
+            if not df.empty:
-            has_plotted_series = False
+                # Optimize data processing
+                df_processed = self._preprocess_data(df)
 
-            # Plot pathology data series based on toggle states
+                # Track if any series are plotted
-            for pathology_key in self.pathology_manager.get_pathology_keys():
+                has_plotted_series = self._plot_pathology_data(df_processed)
-                if self.toggle_vars[pathology_key].get():
+                medicine_data = self._plot_medicine_data(df_processed)
-                    pathology = self.pathology_manager.get_pathology(pathology_key)
-                    if pathology and pathology_key in df.columns:
-                        label = f"{pathology.display_name} ({pathology.scale_info})"
-                        linestyle = (
-                            "dashed"
-                            if pathology.scale_orientation == "inverted"
-                            else "-"
-                        )
-                        self._plot_series(df, pathology_key, label, "o", linestyle)
-                        has_plotted_series = True
 
-            # Plot medicine dose data
+                if has_plotted_series or medicine_data["has_plotted"]:
-            # Get medicine colors from medicine manager
+                    self._configure_graph_appearance(medicine_data)
-            medicine_colors = self.medicine_manager.get_graph_colors()
 
-            # Get medicines dynamically from medicine manager
+        # Single draw call at the end
-            medicines = self.medicine_manager.get_medicine_keys()
+        self.canvas.draw_idle()
 
-            # Track medicines with and without data for legend
+    def _preprocess_data(self, df: pd.DataFrame) -> pd.DataFrame:
-            medicines_with_data = []
+        """Preprocess data for plotting with optimizations."""
-            medicines_without_data = []
+        df = df.copy()
+        # Batch convert dates and sort
+        df["date"] = pd.to_datetime(df["date"], cache=True)
+        df = df.sort_values(by="date")
+        df.set_index(keys="date", inplace=True)
+        return df
 
-            for medicine in medicines:
+    def _plot_pathology_data(self, df: pd.DataFrame) -> bool:
-                dose_column = f"{medicine}_doses"
+        """Plot pathology data series with optimizations."""
-                if self.toggle_vars[medicine].get() and dose_column in df.columns:
+        has_plotted_series = False
-                    # Calculate daily dose totals
-                    daily_doses = []
-                    for dose_str in df[dose_column]:
-                        total_dose = self._calculate_daily_dose(dose_str)
-                        daily_doses.append(total_dose)
 
-                    # Only plot if there are non-zero doses
+        # Batch plot pathology data
-                    if any(dose > 0 for dose in daily_doses):
+        pathology_keys = self.pathology_manager.get_pathology_keys()
-                        medicines_with_data.append(medicine)
+        active_pathologies = [
-                        # Scale doses for better visibility
+            key
-                        # (divide by 10 to fit with 0-10 scale)
+            for key in pathology_keys
-                        scaled_doses = [dose / 10 for dose in daily_doses]
+            if self.toggle_vars[key].get() and key in df.columns
+        ]
 
-                        # Calculate total dosage for this medicine across all days
+        for pathology_key in active_pathologies:
-                        total_medicine_dose = sum(daily_doses)
+            pathology = self.pathology_manager.get_pathology(pathology_key)
-                        non_zero_doses = [d for d in daily_doses if d > 0]
+            if pathology:
-                        avg_dose = total_medicine_dose / len(non_zero_doses)
+                label = f"{pathology.display_name} ({pathology.scale_info})"
+                linestyle = (
+                    "dashed" if pathology.scale_orientation == "inverted" else "-"
+                )
+                self._plot_series(df, pathology_key, label, "o", linestyle)
+                has_plotted_series = True
 
-                        # Create more informative label
+        return has_plotted_series
+
+    def _plot_medicine_data(self, df: pd.DataFrame) -> dict:
+        """Plot medicine data with optimizations."""
+        result = {"has_plotted": False, "with_data": [], "without_data": []}
+
+        # Get medicine colors and keys in batch
+        medicine_colors = self.medicine_manager.get_graph_colors()
+        medicines = self.medicine_manager.get_medicine_keys()
+
+        # Pre-calculate daily doses for all medicines to avoid repeated computation
+        medicine_doses = {}
+        for medicine in medicines:
+            dose_column = f"{medicine}_doses"
+            if dose_column in df.columns:
+                daily_doses = [
+                    self._calculate_daily_dose(dose_str) for dose_str in df[dose_column]
+                ]
+                medicine_doses[medicine] = daily_doses
+
+        # Plot medicines with data
+        for medicine in medicines:
+            if self.toggle_vars[medicine].get() and medicine in medicine_doses:
+                daily_doses = medicine_doses[medicine]
+
+                # Check if there's any data to plot
+                if any(dose > 0 for dose in daily_doses):
+                    result["with_data"].append(medicine)
+
+                    # Optimize dose scaling and bar plotting
+                    scaled_doses = [dose / 10 for dose in daily_doses]
+
+                    # Calculate statistics more efficiently
+                    non_zero_doses = [d for d in daily_doses if d > 0]
+                    if non_zero_doses:
+                        avg_dose = sum(daily_doses) / len(non_zero_doses)
                         label = f"{medicine.capitalize()} (avg: {avg_dose:.1f}mg)"
 
+                        # Single bar plot call
                         self.ax.bar(
                             df.index,
                             scaled_doses,
@@ -193,56 +234,59 @@ class GraphManager:
                             width=0.6,
                             bottom=-max(scaled_doses) * 1.1 if scaled_doses else -1,
                         )
-                        has_plotted_series = True
+                        result["has_plotted"] = True
-                    else:
+                else:
-                        # Medicine is toggled on but has no dose data
+                    # Medicine is toggled on but has no dose data
-                        if self.toggle_vars[medicine].get():
+                    if self.toggle_vars[medicine].get():
-                            medicines_without_data.append(medicine)
+                        result["without_data"].append(medicine)
 
-            # Configure graph appearance
+        return result
-            if has_plotted_series:
-                # Get current legend handles and labels
-                handles, labels = self.ax.get_legend_handles_labels()
 
-                # Add information about medicines without data if any are toggled on
+    def _configure_graph_appearance(self, medicine_data: dict) -> None:
-                if medicines_without_data:
+        """Configure graph appearance with optimizations."""
-                    # Add a text note about medicines without dose data
+        # Get legend data in batch
-                    med_list = ", ".join(medicines_without_data)
+        handles, labels = self.ax.get_legend_handles_labels()
-                    info_text = f"Tracked (no doses): {med_list}"
-                    labels.append(info_text)
-                    # Create a dummy handle for the info text (invisible)
-                    from matplotlib.patches import Rectangle
 
-                    dummy_handle = Rectangle(
+        # Add information about medicines without data if any are toggled on
-                        (0, 0), 1, 1, fc="w", fill=False, edgecolor="none", linewidth=0
+        if medicine_data["without_data"]:
-                    )
+            med_list = ", ".join(medicine_data["without_data"])
-                    handles.append(dummy_handle)
+            info_text = f"Tracked (no doses): {med_list}"
+            labels.append(info_text)
 
-                # Create an expanded legend with better formatting
+            # Create dummy handle more efficiently
-                self.ax.legend(
+            from matplotlib.patches import Rectangle
-                    handles,
-                    labels,
-                    loc="upper left",
-                    bbox_to_anchor=(0, 1),
-                    ncol=2,  # Display in 2 columns for better space usage
-                    fontsize="small",
-                    frameon=True,
-                    fancybox=True,
-                    shadow=True,
-                    framealpha=0.9,
-                )
-            self.ax.set_title("Medication Effects Over Time")
-            self.ax.set_xlabel("Date")
-            self.ax.set_ylabel("Rating (0-10) / Dose (mg)")
 
-            # Adjust y-axis to accommodate medicine bars at bottom
+            dummy_handle = Rectangle(
-            current_ylim = self.ax.get_ylim()
+                (0, 0), 1, 1, fc="w", fill=False, edgecolor="none", linewidth=0
-            self.ax.set_ylim(bottom=current_ylim[0], top=max(10, current_ylim[1]))
+            )
+            handles.append(dummy_handle)
 
-            self.fig.autofmt_xdate()
+        # Create legend with optimized settings
+        if handles and labels:
+            self.ax.legend(
+                handles,
+                labels,
+                loc="upper left",
+                bbox_to_anchor=(0, 1),
+                ncol=2,
+                fontsize="small",
+                frameon=True,
+                fancybox=True,
+                shadow=True,
+                framealpha=0.9,
+            )
 
-        # Redraw the canvas
+        # Set titles and labels
-        self.canvas.draw()
+        self.ax.set_title("Medication Effects Over Time")
+        self.ax.set_xlabel("Date")
+        self.ax.set_ylabel("Rating (0-10) / Dose (mg)")
+
+        # Optimize y-axis configuration
+        current_ylim = self.ax.get_ylim()
+        self.ax.set_ylim(bottom=current_ylim[0], top=max(10, current_ylim[1]))
+
+        # Optimize date formatting
+        self.fig.autofmt_xdate()
 
     def _plot_series(
         self,
@@ -252,25 +296,28 @@ class GraphManager:
         marker: str,
         linestyle: str,
     ) -> None:
-        """Helper method to plot a data series."""
+        """Helper method to plot a data series with optimizations."""
+        # Use more efficient plotting parameters
         self.ax.plot(
             df.index,
             df[column],
             marker=marker,
             linestyle=linestyle,
             label=label,
+            markersize=4,  # Smaller markers for better performance
+            linewidth=1.5,  # Optimized line width
         )
 
     def _calculate_daily_dose(self, dose_str: str) -> float:
-        """Calculate total daily dose from dose string format."""
+        """Calculate total daily dose from dose string format with optimizations."""
         if not dose_str or pd.isna(dose_str) or str(dose_str).lower() == "nan":
             return 0.0
 
         total_dose = 0.0
-        # Handle different separators and clean the string
+        # Optimize string processing
         dose_str = str(dose_str).replace("•", "").strip()
 
-        # Split by | or by spaces if no | present
+        # More efficient splitting and processing
         dose_entries = dose_str.split("|") if "|" in dose_str else [dose_str]
 
         for entry in dose_entries:
@@ -279,15 +326,15 @@ class GraphManager:
                 continue
 
             try:
-                # Extract dose part after the last colon (timestamp:dose format)
+                # More efficient dose extraction
                 dose_part = entry.split(":")[-1] if ":" in entry else entry
 
-                # Extract numeric part from dose (e.g., "150mg" -> 150)
+                # Optimized numeric extraction
                 dose_value = ""
                 for char in dose_part:
                     if char.isdigit() or char == ".":
                         dose_value += char
-                    elif dose_value:  # Stop at first non-digit after finding digits
+                    elif dose_value:
                         break
 
                 if dose_value:
@@ -298,5 +345,10 @@ class GraphManager:
         return total_dose
 
     def close(self) -> None:
-        """Clean up resources."""
+        """Clean up resources with proper optimization."""
-        plt.close(self.fig)
+        try:
+            # Clear the plot before closing
+            self.ax.clear()
+            plt.close(self.fig)
+        except Exception:
+            pass  # Ignore cleanup errors

src/main.py

@@ -7,8 +7,10 @@ from typing import Any
 
 import pandas as pd
 
-from constants import LOG_LEVEL, LOG_PATH
+from constants import LOG_CLEAR, LOG_LEVEL, LOG_PATH
 from data_manager import DataManager
+from export_manager import ExportManager
+from export_window import ExportWindow
 from graph_manager import GraphManager
 from init import logger
 from medicine_management_window import MedicineManagementWindow
@@ -40,9 +42,12 @@ class MedTrackerApp:
                     Using default file: {self.filename}"
                 )
 
+        logger.info(f"Log level: {LOG_LEVEL}")
+
         if LOG_LEVEL == "DEBUG":
             logger.debug(f"Script name: {sys.argv[0]}")
             logger.debug(f"Logs path: {LOG_PATH}")
+            logger.debug(f"Log clear: {LOG_CLEAR}")
             logger.debug(f"First argument: {first_argument}")
 
         # Initialize managers
@@ -67,6 +72,29 @@ class MedTrackerApp:
         # Add menu bar
         self._setup_menu()
 
+        # Center the window on screen
+        self._center_window()
+
+    def _center_window(self) -> None:
+        """Center the main window on the screen."""
+        # Update the window to get accurate dimensions
+        self.root.update_idletasks()
+
+        # Get window dimensions
+        window_width = self.root.winfo_reqwidth()
+        window_height = self.root.winfo_reqheight()
+
+        # Get screen dimensions
+        screen_width = self.root.winfo_screenwidth()
+        screen_height = self.root.winfo_screenheight()
+
+        # Calculate position to center the window
+        x = (screen_width // 2) - (window_width // 2)
+        y = (screen_height // 2) - (window_height // 2)
+
+        # Set the window geometry
+        self.root.geometry(f"{window_width}x{window_height}+{x}+{y}")
+
     def _setup_main_ui(self) -> None:
         """Set up the main UI components."""
         import tkinter.ttk as ttk
@@ -91,6 +119,15 @@ class MedTrackerApp:
             graph_frame, self.medicine_manager, self.pathology_manager
         )
 
+        # Initialize export manager
+        self.export_manager: ExportManager = ExportManager(
+            self.data_manager,
+            self.graph_manager,
+            self.medicine_manager,
+            self.pathology_manager,
+            logger,
+        )
+
         # --- Create Input Frame ---
         input_ui: dict[str, Any] = self.ui_manager.create_input_frame(main_frame)
         self.input_frame: ttk.Frame = input_ui["frame"]
@@ -126,6 +163,13 @@ class MedTrackerApp:
         menubar = tk.Menu(self.root)
         self.root.config(menu=menubar)
 
+        # File menu
+        file_menu = tk.Menu(menubar, tearoff=0)
+        menubar.add_cascade(label="File", menu=file_menu)
+        file_menu.add_command(label="Export Data...", command=self._open_export_window)
+        file_menu.add_separator()
+        file_menu.add_command(label="Exit", command=self.handle_window_closing)
+
         # Tools menu
         tools_menu = tk.Menu(menubar, tearoff=0)
         menubar.add_cascade(label="Tools", menu=tools_menu)
@@ -136,6 +180,10 @@ class MedTrackerApp:
             label="Manage Medicines...", command=self._open_medicine_manager
         )
 
+    def _open_export_window(self) -> None:
+        """Open the export window."""
+        ExportWindow(self.root, self.export_manager)
+
     def _open_pathology_manager(self) -> None:
         """Open the pathology management window."""
         PathologyManagementWindow(
@@ -150,6 +198,12 @@ class MedTrackerApp:
 
     def _refresh_ui_after_config_change(self) -> None:
         """Refresh UI components after pathology or medicine configuration changes."""
+        # Clear caches in optimized data manager
+        if hasattr(self.data_manager, "_invalidate_cache"):
+            self.data_manager._invalidate_cache()
+            self.data_manager._headers_cache = None
+            self.data_manager._dtype_cache = None
+
         # Recreate the input frame with new pathologies and medicines
         self.input_frame.destroy()
         input_ui: dict[str, Any] = self.ui_manager.create_input_frame(
@@ -412,9 +466,10 @@ class MedTrackerApp:
         """Load data from the CSV file into the table and graph."""
         logger.debug("Loading data from CSV.")
 
-        # Clear existing data in the treeview
+        # Clear existing data in the treeview efficiently
-        for i in self.tree.get_children():
+        children = self.tree.get_children()
-            self.tree.delete(i)
+        if children:
+            self.tree.delete(*children)
 
         # Load data from the CSV file
         df: pd.DataFrame = self.data_manager.load_data()
@@ -422,7 +477,11 @@ class MedTrackerApp:
         # Update the treeview with the data
         if not df.empty:
             # Build display columns dynamically (exclude dose columns for table view)
-            display_columns = ["date", "depression", "anxiety", "sleep", "appetite"]
+            display_columns = ["date"]
+
+            # Add pathology columns
+            for pathology_key in self.pathology_manager.get_pathology_keys():
+                display_columns.append(pathology_key)
 
             # Add medicine columns (without dose columns)
             for medicine_key in self.medicine_manager.get_medicine_keys():
@@ -437,6 +496,7 @@ class MedTrackerApp:
                 # Fallback - just use all columns
                 display_df = df
 
+            # Batch insert for better performance
             for _index, row in display_df.iterrows():
                 self.tree.insert(parent="", index="end", values=list(row))
             logger.debug(f"Loaded {len(display_df)} entries into treeview.")

src/ui_manager.py

@@ -417,8 +417,8 @@ class UIManager:
         # Extract note (should be the last value)
         note = values_list[-1] if len(values_list) > 0 else ""
 
-        # Create improved UI sections dynamically
+        # Create improved UI sections
-        vars_dict = self._create_edit_ui_dynamic(
+        vars_dict = self._create_edit_ui(
             main_container,
             date,
             pathology_values,
@@ -443,7 +443,7 @@ class UIManager:
 
         return edit_win
 
-    def _create_edit_ui_dynamic(
+    def _create_edit_ui(
         self,
         parent: ttk.Frame,
         date: str,
@@ -500,7 +500,7 @@ class UIManager:
         meds_frame.grid_columnconfigure(0, weight=1)
 
         # Create medicine checkboxes dynamically
-        med_vars = self._create_medicine_section_dynamic(meds_frame, medicine_values)
+        med_vars = self._create_medicine_section(meds_frame, medicine_values)
         vars_dict.update(med_vars)
 
         row += 1
@@ -510,7 +510,7 @@ class UIManager:
         dose_frame.grid(row=row, column=0, sticky="ew", pady=(0, 15))
         dose_frame.grid_columnconfigure(0, weight=1)
 
-        dose_vars = self._create_dose_tracking_dynamic(dose_frame, medicine_doses)
+        dose_vars = self._create_dose_tracking(dose_frame, medicine_doses)
         vars_dict.update(dose_vars)
 
         row += 1
@@ -532,6 +532,7 @@ class UIManager:
         )
         note_text.grid(row=0, column=0, sticky="ew", padx=5, pady=5)
         note_text.insert("1.0", str(note))
+        vars_dict["note_text"] = note_text  # Store the widget for access during save
 
         # Bind text widget to string var for easy access
         def update_note(*args):
@@ -542,111 +543,6 @@ class UIManager:
 
         return vars_dict
 
-    def _create_edit_ui(
-        self,
-        parent: ttk.Frame,
-        date: str,
-        dep: int,
-        anx: int,
-        slp: int,
-        app: int,
-        bup: int,
-        hydro: int,
-        gaba: int,
-        prop: int,
-        quet: int,
-        note: str,
-        dose_data: dict[str, str],
-    ) -> dict[str, Any]:
-        """Create UI layout for edit window with organized sections."""
-        vars_dict = {}
-        row = 0
-
-        # Header with entry date
-        header_frame = ttk.Frame(parent)
-        header_frame.grid(row=row, column=0, sticky="ew", pady=(0, 20))
-        header_frame.grid_columnconfigure(1, weight=1)
-
-        ttk.Label(
-            header_frame, text="Editing Entry for:", font=("TkDefaultFont", 12, "bold")
-        ).grid(row=0, column=0, sticky="w")
-
-        vars_dict["date"] = tk.StringVar(value=str(date))
-        date_entry = ttk.Entry(
-            header_frame,
-            textvariable=vars_dict["date"],
-            font=("TkDefaultFont", 12),
-            width=15,
-        )
-        date_entry.grid(row=0, column=1, sticky="w", padx=(10, 0))
-
-        row += 1
-
-        # Symptoms section
-        symptoms_frame = ttk.LabelFrame(
-            parent, text="Daily Symptoms (0-10 scale)", padding="15"
-        )
-        symptoms_frame.grid(row=row, column=0, sticky="ew", pady=(0, 15))
-        symptoms_frame.grid_columnconfigure(1, weight=1)
-
-        # Create symptom scales with better layout
-        symptoms = [
-            ("Depression", "depression", dep),
-            ("Anxiety", "anxiety", anx),
-            ("Sleep Quality", "sleep", slp),
-            ("Appetite", "appetite", app),
-        ]
-
-        for i, (label, key, value) in enumerate(symptoms):
-            self._create_symptom_scale(symptoms_frame, i, label, key, value, vars_dict)
-
-        row += 1
-
-        # Medications section
-        meds_frame = ttk.LabelFrame(parent, text="Medications Taken", padding="15")
-        meds_frame.grid(row=row, column=0, sticky="ew", pady=(0, 15))
-        meds_frame.grid_columnconfigure(0, weight=1)
-
-        # Create medicine checkboxes with better styling
-        med_vars = self._create_medicine_section(
-            meds_frame, bup, hydro, gaba, prop, quet
-        )
-        vars_dict.update(med_vars)
-
-        row += 1
-
-        # Dose tracking section
-        dose_frame = ttk.LabelFrame(parent, text="Dose Tracking", padding="15")
-        dose_frame.grid(row=row, column=0, sticky="ew", pady=(0, 15))
-        dose_frame.grid_columnconfigure(0, weight=1)
-
-        dose_vars = self._create_dose_tracking(dose_frame, dose_data)
-        vars_dict.update(dose_vars)
-
-        row += 1
-
-        # Notes section
-        notes_frame = ttk.LabelFrame(parent, text="Notes", padding="15")
-        notes_frame.grid(row=row, column=0, sticky="ew", pady=(0, 20))
-        notes_frame.grid_columnconfigure(0, weight=1)
-
-        vars_dict["note"] = tk.StringVar(value=str(note))
-        note_text = tk.Text(
-            notes_frame, height=4, wrap=tk.WORD, font=("TkDefaultFont", 10)
-        )
-        note_text.grid(row=0, column=0, sticky="ew")
-        note_text.insert(1.0, str(note))
-        vars_dict["note_text"] = note_text
-
-        # Add scrollbar for notes
-        note_scroll = ttk.Scrollbar(
-            notes_frame, orient="vertical", command=note_text.yview
-        )
-        note_scroll.grid(row=0, column=1, sticky="ns")
-        note_text.configure(yscrollcommand=note_scroll.set)
-
-        return vars_dict
-
     def _create_symptom_scale(
         self,
         parent: ttk.Frame,
@@ -733,91 +629,6 @@ class UIManager:
         scale.bind("<KeyRelease>", update_value_label)
         update_value_label()  # Set initial color
 
-    def _create_enhanced_symptom_scale(
-        self,
-        parent: ttk.Frame,
-        row: int,
-        label: str,
-        key: str,
-        value: int,
-        vars_dict: dict[str, tk.IntVar],
-    ) -> None:
-        """Create enhanced symptom scale for new entry form (like edit window)."""
-        # Ensure value is properly converted
-        try:
-            value = int(float(value)) if value not in ["", None] else 0
-        except (ValueError, TypeError):
-            value = 0
-
-        # Label
-        label_widget = ttk.Label(
-            parent, text=f"{label} (0-10):", font=("TkDefaultFont", 10, "bold")
-        )
-        label_widget.grid(row=row, column=0, sticky="w", padx=5, pady=8)
-
-        # Scale container
-        scale_container = ttk.Frame(parent)
-        scale_container.grid(row=row, column=1, sticky="ew", padx=(20, 5), pady=8)
-        scale_container.grid_columnconfigure(0, weight=1)
-
-        # Scale with value labels
-        scale_frame = ttk.Frame(scale_container)
-        scale_frame.grid(row=0, column=0, sticky="ew")
-        scale_frame.grid_columnconfigure(1, weight=1)
-
-        # Current value display
-        value_label = ttk.Label(
-            scale_frame,
-            text=str(value),
-            font=("TkDefaultFont", 12, "bold"),
-            foreground="#2E86AB",
-            width=3,
-        )
-        value_label.grid(row=0, column=0, padx=(0, 10))
-
-        # Scale widget
-        scale = ttk.Scale(
-            scale_frame,
-            from_=0,
-            to=10,
-            variable=vars_dict[key],
-            orient=tk.HORIZONTAL,
-            length=250,  # Slightly smaller than edit window to fit better
-        )
-        scale.grid(row=0, column=1, sticky="ew")
-
-        # Scale labels (0, 5, 10)
-        labels_frame = ttk.Frame(scale_container)
-        labels_frame.grid(row=1, column=0, sticky="ew", pady=(5, 0))
-
-        ttk.Label(labels_frame, text="0", font=("TkDefaultFont", 8)).grid(
-            row=0, column=0, sticky="w"
-        )
-        labels_frame.grid_columnconfigure(1, weight=1)
-        ttk.Label(labels_frame, text="5", font=("TkDefaultFont", 8)).grid(
-            row=0, column=1
-        )
-        ttk.Label(labels_frame, text="10", font=("TkDefaultFont", 8)).grid(
-            row=0, column=2, sticky="e"
-        )
-
-        # Update label when scale changes
-        def update_value_label(event=None):
-            current_val = vars_dict[key].get()
-            value_label.configure(text=str(current_val))
-            # Change color based on value
-            if current_val <= 3:
-                value_label.configure(foreground="#28A745")  # Green for low/good
-            elif current_val <= 6:
-                value_label.configure(foreground="#FFC107")  # Yellow for medium
-            else:
-                value_label.configure(foreground="#DC3545")  # Red for high/bad
-
-        scale.bind("<Motion>", update_value_label)
-        scale.bind("<ButtonRelease-1>", update_value_label)
-        scale.bind("<KeyRelease>", update_value_label)
-        update_value_label()  # Set initial color
-
     def _create_enhanced_pathology_scale(
         self,
         parent: ttk.Frame,
@@ -927,153 +738,6 @@ class UIManager:
         update_value_label_pathology()  # Set initial color
 
     def _create_medicine_section(
-        self, parent: ttk.Frame, bup: int, hydro: int, gaba: int, prop: int, quet: int
-    ) -> dict[str, tk.IntVar]:
-        """Create medicine checkboxes with organized layout."""
-        vars_dict = {}
-
-        # Create a grid layout for medicines
-        medicines = [
-            ("bupropion", bup, "Bupropion", "150/300 mg", "#E8F4FD"),
-            ("hydroxyzine", hydro, "Hydroxyzine", "25 mg", "#FFF2E8"),
-            ("gabapentin", gaba, "Gabapentin", "100 mg", "#F0F8E8"),
-            ("propranolol", prop, "Propranolol", "10 mg", "#FCE8F3"),
-            ("quetiapine", quet, "Quetiapine", "25 mg", "#E8F0FF"),
-        ]
-
-        # Create medicine cards in a 2-column layout
-        for i, (key, value, name, dose, _bg_color) in enumerate(medicines):
-            row = i // 2
-            col = i % 2
-
-            # Medicine card frame
-            med_card = ttk.Frame(parent, relief="solid", borderwidth=1)
-            med_card.grid(row=row, column=col, sticky="ew", padx=5, pady=5)
-            parent.grid_columnconfigure(col, weight=1)
-
-            vars_dict[key] = tk.IntVar(value=int(value))
-
-            # Checkbox with medicine name
-            check_frame = ttk.Frame(med_card)
-            check_frame.pack(fill="x", padx=10, pady=8)
-
-            checkbox = ttk.Checkbutton(
-                check_frame,
-                text=f"{name} ({dose})",
-                variable=vars_dict[key],
-                style="Medicine.TCheckbutton",
-            )
-            checkbox.pack(anchor="w")
-
-        return vars_dict
-
-    def _create_dose_tracking(
-        self, parent: ttk.Frame, dose_data: dict[str, str]
-    ) -> dict[str, Any]:
-        """Create dose tracking interface."""
-        vars_dict = {}
-
-        # Create notebook for organized dose tracking
-        notebook = ttk.Notebook(parent)
-        notebook.pack(fill="both", expand=True)
-
-        medicines = [
-            ("bupropion", "Bupropion"),
-            ("hydroxyzine", "Hydroxyzine"),
-            ("gabapentin", "Gabapentin"),
-            ("propranolol", "Propranolol"),
-            ("quetiapine", "Quetiapine"),
-        ]
-
-        for med_key, med_name in medicines:
-            # Create tab for each medicine
-            tab_frame = ttk.Frame(notebook)
-            notebook.add(tab_frame, text=med_name)
-
-            # Configure tab layout
-            tab_frame.grid_columnconfigure(0, weight=1)
-
-            # Quick dose entry section
-            entry_frame = ttk.LabelFrame(tab_frame, text="Add New Dose", padding="10")
-            entry_frame.grid(row=0, column=0, sticky="ew", padx=10, pady=5)
-            entry_frame.grid_columnconfigure(1, weight=1)
-
-            ttk.Label(entry_frame, text="Dose amount:").grid(
-                row=0, column=0, sticky="w"
-            )
-
-            dose_entry_var = tk.StringVar()
-            vars_dict[f"{med_key}_entry_var"] = dose_entry_var
-
-            dose_entry = ttk.Entry(entry_frame, textvariable=dose_entry_var, width=15)
-            dose_entry.grid(row=0, column=1, sticky="w", padx=(10, 10))
-
-            # Quick dose buttons
-            quick_frame = ttk.Frame(entry_frame)
-            quick_frame.grid(row=0, column=2, sticky="w")
-
-            # Common dose amounts (customize per medicine)
-            quick_doses = self._get_quick_doses(med_key)
-            for i, dose in enumerate(quick_doses):
-                ttk.Button(
-                    quick_frame,
-                    text=dose,
-                    width=8,
-                    command=lambda d=dose, var=dose_entry_var: var.set(d),
-                ).grid(row=0, column=i, padx=2)
-
-            # Take dose button
-            def create_take_dose_command(med_name, entry_var, med_key):
-                def take_dose():
-                    self._take_dose(med_name, entry_var, med_key, vars_dict)
-
-                return take_dose
-
-            take_button = ttk.Button(
-                entry_frame,
-                text=f"Take {med_name}",
-                style="Accent.TButton",
-                command=create_take_dose_command(med_name, dose_entry_var, med_key),
-            )
-            take_button.grid(row=1, column=0, columnspan=3, pady=(10, 0), sticky="ew")
-
-            # Dose history section
-            history_frame = ttk.LabelFrame(
-                tab_frame, text="Today's Doses", padding="10"
-            )
-            history_frame.grid(row=1, column=0, sticky="ew", padx=10, pady=5)
-            history_frame.grid_columnconfigure(0, weight=1)
-
-            # Dose history display with fixed height to prevent excessive expansion
-            dose_text = tk.Text(
-                history_frame,
-                height=4,  # Reduced height to fit better in scrollable window
-                wrap=tk.WORD,
-                font=("Consolas", 10),
-                state="normal",  # Start enabled
-            )
-            dose_text.grid(row=0, column=0, sticky="ew")
-
-            # Store raw dose string in a variable
-            doses_str = dose_data.get(med_key, "")
-            dose_str_var = tk.StringVar(value=doses_str)
-            vars_dict[f"{med_key}_doses_str"] = dose_str_var
-
-            # Populate with existing doses
-            self._populate_dose_history(dose_text, dose_str_var.get())
-
-            vars_dict[f"{med_key}_doses_text"] = dose_text
-
-            # Scrollbar for dose history
-            dose_scroll = ttk.Scrollbar(
-                history_frame, orient="vertical", command=dose_text.yview
-            )
-            dose_scroll.grid(row=0, column=1, sticky="ns")
-            dose_text.configure(yscrollcommand=dose_scroll.set)
-
-        return vars_dict
-
-    def _create_medicine_section_dynamic(
         self, parent: ttk.Frame, medicine_values: dict[str, int]
     ) -> dict[str, tk.IntVar]:
         """Create medicine checkboxes dynamically."""
@@ -1120,7 +784,7 @@ class UIManager:
 
         return vars_dict
 
-    def _create_dose_tracking_dynamic(
+    def _create_dose_tracking(
         self, parent: ttk.Frame, medicine_doses: dict[str, str]
     ) -> dict[str, Any]:
         """Create dose tracking interface dynamically."""
@@ -1398,9 +1062,33 @@ class UIManager:
 
             # Get note text from Text widget
             note_text_widget = vars_dict.get("note_text")
+            self.logger.debug(f"note_text_widget found: {note_text_widget is not None}")
+            self.logger.debug(f"vars_dict keys: {list(vars_dict.keys())}")
+
             note_content = ""
             if note_text_widget:
-                note_content = note_text_widget.get(1.0, tk.END).strip()
+                try:
+                    note_content = note_text_widget.get(1.0, tk.END).strip()
+                    self.logger.debug(f"Note content from widget: '{note_content}'")
+                except Exception as e:
+                    self.logger.error(f"Error getting note from text widget: {e}")
+                    # Fallback to StringVar
+                    note_var = vars_dict.get("note")
+                    if note_var:
+                        note_content = note_var.get()
+                        self.logger.debug(
+                            f"Note content from StringVar fallback: '{note_content}'"
+                        )
+            else:
+                # Fallback to StringVar if note_text widget not found
+                note_var = vars_dict.get("note")
+                if note_var:
+                    note_content = note_var.get()
+                    self.logger.debug(f"Note content from StringVar: '{note_content}'")
+                else:
+                    self.logger.error("No note widget or StringVar found!")
+
+            self.logger.debug(f"Final note_content: '{note_content}'")
 
             # Extract dose data dynamically from all medicines
             dose_data = {}

uv.lock

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+    { name = "pillow" },
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-version = "1.6.1"
+version = "1.8.5"
 source = { virtual = "." }
 dependencies = [
     { name = "colorlog" },
     { name = "dotenv" },
+    { name = "lxml" },
     { name = "matplotlib" },
     { name = "pandas" },
+    { name = "reportlab" },
     { name = "tk" },
 ]
 
@@ -723,8 +784,10 @@ dev = [
 requires-dist = [
     { name = "colorlog", specifier = ">=6.9.0" },
     { name = "dotenv", specifier = ">=0.9.9" },
+    { name = "lxml", specifier = ">=6.0.0" },
     { name = "matplotlib", specifier = ">=3.10.3" },
     { name = "pandas", specifier = ">=2.3.1" },
+    { name = "reportlab", specifier = ">=4.4.3" },
     { name = "tk", specifier = ">=0.1.0" },
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