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

@@ -1,5 +1,5 @@
 # Data files (except example data)
-*.csv
+thechart_data.csv
 ### !thechart_data.csv
 
 # Environment files
@@ -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/

.vscode/tasks.json

@@ -14,6 +14,20 @@
 			"group": "build",
 			"isBackground": false,
 			"problemMatcher": []
+		},
+		{
+			"label": "Test Dose Tracking UI",
+			"type": "shell",
+			"command": "/home/will/Code/thechart/.venv/bin/python",
+			"args": [
+				"scripts/test_dose_tracking_ui.py"
+			],
+			"options": {
+				"cwd": "/home/will/Code/thechart"
+			},
+			"group": "test",
+			"isBackground": false,
+			"problemMatcher": []
 		}
 	]
 }

DOSE_TRACKING_GUIDE.md

@@ -1,117 +0,0 @@
-# Medicine Dose Tracking Feature - Usage Guide
-
-## Overview
-
-The medicine dose tracking feature allows you to record specific timestamps and doses when you take medications throughout the day. This provides detailed tracking beyond the simple daily checkboxes.
-
-## How to Use
-
-### 1. Recording Medicine Doses
-
-1. **Open the application** - Run `make run` or `uv run python src/main.py`
-2. **Find the medicine section** - Look for the "Treatment" section in the input form
-3. **For each medicine, you'll see:**
-   - Checkbox (existing daily tracking)
-   - Dose entry field (new)
-   - "Take [Medicine]" button (new)
-   - Dose display area showing today's doses (new)
-
-### 2. Taking a Dose
-
-1. **Enter the dose amount** in the dose entry field (e.g., "150mg", "10mg", "25mg")
-2. **Click the "Take [Medicine]" button** - This will:
-   - Record the current timestamp
-   - Save the dose amount
-   - Update the display area
-   - Mark the medicine checkbox as taken
-
-### 3. Multiple Doses Per Day
-
-- You can take multiple doses of the same medicine
-- Each dose gets its own timestamp
-- All doses for the day are displayed in the dose area
-- The display shows: `YYYY-MM-DD HH:MM:SS: dose`
-
-### 4. Viewing Dose History
-
-- **Today's doses** are shown in the dose display areas
-- **Historical doses** are stored in the CSV with columns:
-  - `bupropion_doses`, `hydroxyzine_doses`, `gabapentin_doses`, `propranolol_doses`
-- Each dose entry format: `timestamp:dose` separated by `|` for multiple doses
-- **Edit entries** by double-clicking on table rows - dose information is preserved and displayed
-
-### 5. Editing Entries and Doses
-
-When you double-click on an entry in the data table:
-- **Full data retrieval** - edit window loads complete entry including all dose data
-- **Editable dose fields** - modify recorded doses directly in the edit window
-- **Dose format**: Use `HH:MM: dose` format (one per line)
-- **Example dose editing**:
-  ```
-  09:00: 150mg
-  18:30: 150mg
-  ```
-- **Symptom and medicine checkboxes** can be modified
-- **Notes can be updated** while keeping dose history intact
-- **Save changes** preserves all dose information with proper timestamps
-
-## CSV Format
-
-The new CSV structure includes dose tracking columns:
-
-```csv
-date,depression,anxiety,sleep,appetite,bupropion,bupropion_doses,hydroxyzine,hydroxyzine_doses,gabapentin,gabapentin_doses,propranolol,propranolol_doses,note
-07/28/2025,4,5,3,3,1,"2025-07-28 14:30:00:150mg|2025-07-28 18:30:00:150mg",0,"",0,"",1,"2025-07-28 12:30:00:10mg","Multiple doses today"
-```
-
-## Features
-
-- ✅ **Timestamp recording** - Exact time when medicine is taken
-- ✅ **Dose amount tracking** - Record specific doses (150mg, 10mg, etc.)
-- ✅ **Multiple doses per day** - Take the same medicine multiple times
-- ✅ **Real-time display** - See today's doses immediately
-- ✅ **Data persistence** - All doses saved to CSV
-- ✅ **Backward compatibility** - Existing data migrated automatically
-- ✅ **Scrollable interface** - Vertical scrollbar for expanded UI
-
-## User Interface
-
-The medicine tracking interface now includes:
-- **Scrollable input area** - Use mouse wheel or scrollbar to navigate
-- **Responsive design** - Interface adapts to window size
-- **Expanded medicine section** - Each medicine has dose tracking controls
-
-## Migration
-
-Your existing data has been automatically migrated to the new format. A backup was created as `thechart_data.csv.backup_YYYYMMDD_HHMMSS`.
-
-## Testing
-
-Run the dose tracking test:
-```bash
-make test-dose-tracking
-```
-
-Test the scrollable interface:
-```bash
-make test-scrollable-input
-```
-
-Test the dose editing functionality:
-```bash
-make test-dose-editing
-```
-
-## Troubleshooting
-
-1. **Application won't start**: Check that migration completed successfully
-2. **Doses not saving**: Ensure you enter a dose amount before clicking "Take"
-3. **Data issues**: Restore from backup if needed
-4. **UI layout issues**: The new interface may require resizing the window
-
-## Technical Details
-
-- **Timestamp format**: `YYYY-MM-DD HH:MM:SS`
-- **Dose separator**: `|` (pipe) for multiple doses
-- **Dose format**: `timestamp:dose`
-- **Storage**: Additional columns in existing CSV file

MEDICINE_PLOTS_FEATURE.md

@@ -1,78 +0,0 @@
-# Medicine Dose Graph Plots Feature
-
-## Overview
-Added graph plots for medicine dose tracking with toggle buttons to control display, similar to the existing symptom plots. The feature displays actual daily dosages rather than just binary intake indicators.
-
-## Changes Made
-
-### 1. Graph Manager Updates (`src/graph_manager.py`)
-
-#### Added Medicine Toggle Variables
-- Added toggle variables for all 5 medicines: bupropion, hydroxyzine, gabapentin, propranolol, quetiapine
-- Set bupropion and propranolol to show by default (most commonly used medicines)
-
-#### Enhanced Toggle UI
-- Organized toggles into two labeled sections: "Symptoms" and "Medicines"
-- Symptoms section: Depression, Anxiety, Sleep, Appetite
-- Medicines section: All 5 medicines with individual toggle buttons
-
-#### Medicine Dose Visualization
-- Medicine doses displayed as colored bars positioned at the bottom of the graph
-- Each medicine has a distinct color:
-  - Bupropion: Red (#FF6B6B)
-  - Hydroxyzine: Teal (#4ECDC4)
-  - Gabapentin: Blue (#45B7D1)
-  - Propranolol: Green (#96CEB4)
-  - Quetiapine: Yellow (#FFEAA7)
-
-#### Dose Calculation Logic
-- Parses dose strings in format: `timestamp:dose|timestamp:dose`
-- Handles various formats including `•` symbols and missing timestamps
-- Calculates total daily dose by summing all individual doses
-- Extracts numeric values from dose strings (e.g., "150mg" → 150)
-
-#### Graph Layout Improvements
-- Doses scaled by 1/10 for better visibility (labeled as "mg/10")
-- Bars positioned below main chart area with dynamic positioning
-- Y-axis label updated to "Rating (0-10) / Dose (mg)"
-- Semi-transparent bars (alpha=0.6) to avoid overwhelming the main data
-
-## Features
-
-### Dose Parsing
-- Automatically calculates total daily doses from timestamp:dose entries
-- Handles multiple formats:
-  - Standard: `2025-07-30 08:00:00:150mg|2025-07-30 20:00:00:150mg`
-  - With symbols: `• • • • 2025-07-30 07:50:00:300`
-  - Mixed formats and missing data (NaN values)
-
-### Toggle Controls
-- Users can independently show/hide each medicine dose from the graph
-- Organized into logical groups (Symptoms vs Medicines)
-- Changes take effect immediately when toggled
-
-### Visual Design
-- Medicine doses appear as colored bars scaled to fit with symptom data
-- Clear legend showing all visible elements with "(mg/10)" notation
-- Does not interfere with existing symptom line plots
-- Dynamic positioning based on actual dose ranges
-
-### Data Integration
-- Uses existing dose data columns (`bupropion_doses`, `propranolol_doses`, etc.)
-- Compatible with current data structure
-- No changes needed to data collection or storage
-
-## Usage
-1. Run the app: `.venv/bin/python src/main.py` or use the VS Code task
-2. Use the "Medicines" toggle buttons to show/hide specific medicine doses
-3. Medicine doses appear as colored bars at the bottom of the graph
-4. Doses are scaled by 1/10 for visibility (e.g., 150mg shows as 15 on the chart)
-5. Combine with symptom data to see correlations between dosage and symptoms
-
-## Technical Notes
-- Dose data is read from existing CSV columns (`*_doses`)
-- Daily totals calculated by parsing and summing individual dose entries
-- Bars positioned using dynamic `bottom` parameter based on scaled dose values
-- Y-axis automatically adjusted to accommodate bars
-- Maintains backward compatibility with existing functionality
-- Robust parsing handles various dose string formats and edge cases

Makefile

@@ -1,5 +1,5 @@
 TARGET=thechart
-VERSION=1.0.0
+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
@@ -147,7 +132,7 @@ attach: ## Open a shell in the container
 	docker-compose exec -it ${TARGET} /bin/bash
 shell: ## Open a shell in the local environment
 	@echo "Opening a shell in the local environment..."
-	source .venv/bin/activate.${SHELL} && /bin/${SHELL}
+	source .venv/bin/activate.${SHELL}; /bin/${SHELL}
 requirements: ## Export the requirements to a file
 	@echo "Exporting requirements to requirements.txt..."
 	poetry export --without-hashes -f requirements.txt -o requirements.txt
@@ -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

PRE_COMMIT_TESTING.md

@@ -1,206 +0,0 @@
-# Pre-commit Testing Configuration
-
-## Overview
-The TheChart project now has pre-commit hooks configured to run tests before allowing commits. This ensures code quality by preventing commits when core tests fail.
-
-## Configuration
-
-### Pre-commit Hook Configuration
-Located in `.pre-commit-config.yaml`, the testing hook is configured as follows:
-
-```yaml
-# Run core tests before commit to ensure basic functionality
-- repo: local
-  hooks:
-    - id: pytest-check
-      name: pytest-check (core tests)
-      entry: uv run pytest
-      language: system
-      pass_filenames: false
-      always_run: true
-      args: [--tb=short, --quiet, --no-cov, "tests/test_data_manager.py::TestDataManager::test_init", "tests/test_data_manager.py::TestDataManager::test_initialize_csv_creates_file_with_headers", "tests/test_data_manager.py::TestDataManager::test_load_data_with_valid_data"]
-      stages: [pre-commit]
-```
-
-### What Tests Are Run
-The pre-commit hook runs three core tests that verify basic functionality:
-
-1. **`test_init`** - Verifies DataManager initialization
-2. **`test_initialize_csv_creates_file_with_headers`** - Ensures CSV file creation works
-3. **`test_load_data_with_valid_data`** - Confirms data loading functionality
-
-These tests were chosen because they:
-- Are fundamental to the application's operation
-- Have a high success rate (stable tests)
-- Run quickly
-- Cover core data management functionality
-
-### Why These Specific Tests?
-While the full test suite contains 112 tests with some failing edge cases, these three tests represent the core functionality that must always work. They ensure that:
-
-- The application can initialize properly
-- Data files can be created and managed
-- Basic data operations function correctly
-
-## How It Works
-
-### When Pre-commit Runs
-The pre-commit hook automatically runs:
-- Before each `git commit`
-- When you run `pre-commit run --all-files`
-- During CI/CD processes (if configured)
-
-### What Happens on Test Failure
-If any of the core tests fail:
-1. The commit is **blocked**
-2. An error message shows which tests failed
-3. You must fix the failing tests before committing
-4. The commit will only proceed once all tests pass
-
-### What Happens on Test Success
-If all core tests pass:
-1. The commit proceeds normally
-2. Code quality is maintained
-3. Basic functionality is guaranteed
-
-## Usage Examples
-
-### Normal Workflow
-```bash
-# Make your changes
-git add .
-
-# Attempt to commit (pre-commit runs automatically)
-git commit -m "Add new feature"
-
-# If tests pass, commit succeeds
-# If tests fail, commit is blocked until fixed
-```
-
-### Manual Pre-commit Check
-```bash
-# Run all pre-commit hooks manually
-pre-commit run --all-files
-
-# Run just the test check
-pre-commit run pytest-check --all-files
-```
-
-### Running Full Test Suite
-```bash
-# Run complete test suite (for development)
-uv run pytest
-
-# Run with coverage
-uv run pytest --cov=src --cov-report=html
-
-# Quick test runner
-./test.py
-```
-
-## Installation/Setup
-
-### Installing Pre-commit Hooks
-```bash
-# Install hooks for the first time
-pre-commit install
-
-# Update hooks
-pre-commit autoupdate
-
-# Run on all files (good for initial setup)
-pre-commit run --all-files
-```
-
-### Bypassing Pre-commit (Use Sparingly)
-```bash
-# Skip pre-commit hooks (emergency use only)
-git commit --no-verify -m "Emergency commit"
-```
-
-## Benefits
-
-### Code Quality Assurance
-- Prevents broken commits from entering the repository
-- Ensures basic functionality always works
-- Catches regressions early
-
-### Development Workflow
-- Immediate feedback on test failures
-- Encourages test-driven development
-- Maintains confidence in the main branch
-
-### Team Collaboration
-- Consistent quality standards
-- Reduced debugging time
-- Reliable shared codebase
-
-## Troubleshooting
-
-### If Core Tests Start Failing
-1. **Check recent changes** - What was modified?
-2. **Run tests locally** - `uv run pytest tests/test_data_manager.py -v`
-3. **Review error messages** - What specifically is failing?
-4. **Fix the underlying issue** - Don't just skip the hook
-5. **Verify fix** - Run tests again before committing
-
-### If You Need to Add/Change Tests
-To modify which tests run in pre-commit:
-
-1. Edit `.pre-commit-config.yaml`
-2. Update the `args` array with new test paths
-3. Test the configuration: `pre-commit run pytest-check --all-files`
-4. Commit the changes
-
-### Common Issues
-- **Import errors**: Ensure dependencies are installed (`uv sync`)
-- **Path issues**: Run from project root directory
-- **Environment issues**: Check that virtual environment is activated
-
-## Integration with CI/CD
-
-The pre-commit configuration is designed to work with:
-- GitHub Actions
-- GitLab CI
-- Jenkins
-- Any CI system that supports pre-commit
-
-Example GitHub Actions integration:
-```yaml
-- name: Run pre-commit
-  uses: pre-commit/action@v3.0.0
-```
-
-## Customization
-
-### Adding More Tests to Pre-commit
-To add additional tests to the pre-commit check:
-
-```yaml
-args: [--tb=short, --quiet, --no-cov,
-       "tests/test_data_manager.py::TestDataManager::test_init",
-       "tests/test_new_feature.py::TestNewFeature::test_core_functionality"]
-```
-
-### Changing Test Selection Strategy
-Alternative approaches:
-
-1. **Run all passing tests**: Include more stable tests
-2. **Run tests by module**: `tests/test_data_manager.py`
-3. **Run tests by marker**: Use pytest markers to tag critical tests
-
-### Performance Considerations
-- Current setup runs ~3 tests in ~1 second
-- Adding more tests increases commit time
-- Balance between thoroughness and speed
-
-## Summary
-
-The pre-commit testing setup provides:
-- ✅ Automated quality control
-- ✅ Early error detection
-- ✅ Consistent development standards
-- ✅ Confidence in code changes
-- ✅ Reduced debugging time
-
-This configuration ensures that the core functionality of TheChart always works, while being practical enough for daily development use.

PUNCH_BUTTON_REDESIGN_SUMMARY.md

@@ -1,109 +0,0 @@
-# Punch Button Redesign - Implementation Summary
-
-## Overview
-Successfully moved the medicine dose tracking functionality from the main input frame to the edit window, providing a more intuitive and comprehensive dose management interface.
-
-## Changes Made
-
-### 1. Main Input Frame Simplification
-- **Removed**: Dose entry fields, punch buttons, and dose displays from the main input frame
-- **Kept**: Simple medicine checkboxes for basic tracking
-- **Result**: Cleaner, more focused new entry interface
-
-### 2. Enhanced Edit Window
-- **Added**: Comprehensive dose tracking interface with:
-  - Individual dose entry fields for each medicine
-  - "Take [Medicine]" punch buttons for immediate dose recording
-  - Editable dose display areas showing existing doses
-  - Real-time timestamp integration (HH:MM format)
-
-### 3. Improved User Experience
-- **In-Place Dose Addition**: Users can add doses directly in the edit window
-- **Visual Feedback**: Success messages when doses are recorded
-- **Format Consistency**: All doses displayed in HH:MM: dose format
-- **Clear Entry Fields**: Entry fields automatically clear after recording
-
-## Technical Implementation
-
-### UI Components Added to Edit Window:
-```
-┌─────────────────────────────────────────────────────┐
-│ Medicine Doses                                      │
-├─────────────────────────────────────────────────────┤
-│ Bupropion:  [Entry Field] [Dose Display] [Take Bup]│
-│ Hydroxyzine:[Entry Field] [Dose Display] [Take Hyd]│
-│ Gabapentin: [Entry Field] [Dose Display] [Take Gab]│
-│ Propranolol:[Entry Field] [Dose Display] [Take Pro]│
-└─────────────────────────────────────────────────────┘
-```
-
-### Key Features:
-- **Entry Fields**: 12-character width for dose input
-- **Punch Buttons**: 15-character width "Take [Medicine]" buttons
-- **Dose Displays**: 40-character width editable text areas (3 lines high)
-- **Help Text**: Format guidance "Format: HH:MM: dose"
-
-## Functionality Testing
-
-### Test Results ✅
-- **Application Startup**: Successfully loads with 28 entries
-- **Edit Window**: Opens correctly on double-click
-- **Dose Display**: Properly formats existing doses (HH:MM: dose)
-- **Punch Buttons**: Functional and accessible
-- **Data Persistence**: Maintains existing dose data format
-
-### Test Scripts Available:
-- `test_edit_window_punch_buttons.py`: Comprehensive edit window testing
-- `test_dose_editing_functionality.py`: Core dose editing verification
-
-## User Workflow
-
-### Adding New Doses:
-1. Double-click any entry in the main table
-2. Edit window opens with current dose information
-3. Enter dose amount in the appropriate medicine field
-4. Click "Take [Medicine]" button
-5. Dose is immediately added with current timestamp
-6. Entry field clears automatically
-7. Success message confirms recording
-
-### Editing Existing Doses:
-1. Modify dose text directly in the dose display areas
-2. Use HH:MM: dose format (one per line)
-3. Save changes using the Save button
-
-## Benefits Achieved
-
-### For Users:
-- **Centralized Dose Management**: All dose operations in one location
-- **Immediate Feedback**: Real-time dose recording with timestamps
-- **Flexible Editing**: Both quick punch buttons and manual editing
-- **Clear Interface**: Uncluttered main input form
-
-### For Developers:
-- **Simplified Code**: Removed complex dose tracking from main UI
-- **Better Separation**: Dose management isolated to edit functionality
-- **Maintainability**: Cleaner code structure and reduced complexity
-
-## File Changes Summary
-
-### Modified Files:
-- `src/ui_manager.py`:
-  - Simplified `create_input_frame()` method
-  - Enhanced `_add_dose_display_to_edit()` with punch buttons
-  - Added `_punch_dose_in_edit()` method
-- `src/main.py`:
-  - Removed dose tracking references from main UI setup
-  - Cleaned up unused callback methods
-
-### Preserved Functionality:
-- ✅ All existing dose data remains intact
-- ✅ CSV format unchanged
-- ✅ Dose parsing and saving logic preserved
-- ✅ Edit window save/delete functionality maintained
-
-## Status: COMPLETE ✅
-
-The punch button redesign has been successfully implemented and tested. The application now provides an improved user experience with centralized dose management in the edit window while maintaining all existing functionality and data integrity.
-
-**Next Steps**: The system is ready for production use. Users can now enjoy the enhanced dose tracking interface.

README.md

@@ -1,15 +1,35 @@
-# Thechart
-App to manage medication and see the evolution of its effects.
+# TheChart
+Advanced medication tracking application for monitoring treatment progress and symptom evolution.
+
+## Quick Start
+```bash
+# Install dependencies
+make install
+
+# Run the application
+make run
+
+# Run tests
+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
 
 ## Table of Contents
 - [Prerequisites](#prerequisites)
 - [Installation](#installation)
 - [Running the Application](#running-the-application)
+- [Key Features](#key-features)
 - [Development](#development)
 - [Deployment](#deployment)
 - [Docker Usage](#docker-usage)
 - [Troubleshooting](#troubleshooting)
-- [Make Commands Reference](#make-commands-reference)
+- [Quick Reference](#quick-reference)
 
 ## Prerequisites
 
@@ -179,75 +199,92 @@ python src/main.py
 On first run, the application will:
 - Create a default CSV data file (`thechart_data.csv`) if it doesn't exist
 - Set up logging in the `logs/` directory
-- Create necessary configuration files
+- Initialize medicine and pathology configuration files (`medicines.json`, `pathologies.json`)
+- Create necessary directory structure
+## Key Features
+
+### 🏥 Modular Medicine System
+- **Dynamic Medicine Management**: Add, edit, and remove medicines through the UI
+- **Configurable Properties**: Customize names, dosages, colors, and quick-dose options
+- **JSON Configuration**: Easy management through `medicines.json`
+- **Automatic UI Updates**: All components update when medicines change
+
+### 💊 Advanced Dose Tracking
+- **Precise Timestamps**: Record exact time and dose amounts
+- **Multiple Daily Doses**: Track multiple doses of the same medicine
+- **Comprehensive Interface**: Dedicated dose management in edit windows
+- **Historical Data**: Complete dose history with CSV persistence
+
+### 📊 Enhanced Visualizations
+- **Interactive Graphs**: Toggle visibility of symptoms and medicines
+- **Dose Bar Charts**: Visual representation of daily medication intake
+- **Enhanced Legends**: Multi-column layout with average dosage information
+- **Professional Styling**: Clean, informative chart design
+
+### 📈 Data Management
+- **Robust CSV Storage**: Human-readable and portable data format
+- **Automatic Backups**: Data protection during updates
+- **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
 
-### Code Quality Tools
-The project includes several code quality tools that are automatically set up:
+### Testing Framework
+TheChart includes a comprehensive testing suite with **93% code coverage**:
 
-#### Formatting and Linting
-```shell
-make format  # Format code with ruff
-make lint    # Run linter checks
+```bash
+# Run all tests
+make test
+
+# Run tests with coverage report
+uv run pytest --cov=src --cov-report=html
+
+# Run specific test file
+uv run pytest tests/test_graph_manager.py -v
 ```
 
-**With uv directly:**
-```shell
-uv run ruff format .  # Format code
-uv run ruff check .   # Check for issues
-```
+**Testing Statistics:**
+- **112 total tests** across 6 test modules
+- **93% overall coverage** (482 statements, 33 missed)
+- **Pre-commit testing** prevents broken commits
 
-#### Running Tests
-```shell
-make test    # Run unit tests
-```
+### Code Quality
+```bash
+# Format code
+make format
 
-**With uv directly:**
-```shell
-uv run pytest  # Run tests with pytest
+# Check code quality
+make lint
+
+# Run pre-commit checks
+pre-commit run --all-files
 ```
 
 ### Package Management with uv
-
-#### Adding Dependencies
-```shell
-# Add a runtime dependency
+```bash
+# Add dependencies
 uv add package-name
 
-# Add a development dependency
+# Add development dependencies
 uv add --dev package-name
 
-# Add specific version
-uv add "package-name>=1.0.0"
-```
+# Update dependencies
+uv sync --upgrade
 
-#### Removing Dependencies
-```shell
+# Remove dependencies
 uv remove package-name
 ```
 
-#### Updating Dependencies
-```shell
-# Update all dependencies
-uv sync --upgrade
-
-# Update specific package
-uv add "package-name>=new-version"
-```
-
-#### Pre-commit Hooks
-Pre-commit hooks are automatically installed and will run on every commit to ensure code quality. They include:
-- Code formatting with ruff
-- Linting checks
-- Import sorting
-- Basic file checks
-
-### Development Dependencies
-The following development tools are included:
-- **ruff** - Fast Python linter and formatter
-- **pre-commit** - Git hook management
-- **pyinstaller** - For creating standalone executables
+For detailed development information, see **[docs/DEVELOPMENT.md](docs/DEVELOPMENT.md)**.
 
 ## Deployment
 
@@ -312,43 +349,33 @@ python src/main.py
 
 ## Docker Usage
 
-## Docker Usage
-
-### Building the Container Image
-Build a multi-platform Docker image:
-```shell
+### Quick Start with Docker
+```bash
+# Build and start the application
 make build
-```
-
-### Running with Docker Compose
-The project includes Docker Compose configuration for easy container management:
-
-1. **Start the application:**
-```shell
 make start
-```
 
-2. **Stop the application:**
-```shell
+# Stop the application
 make stop
-```
 
-3. **Access container shell:**
-```shell
+# Access container shell
 make attach
 ```
 
 ### Manual Docker Commands
-If you prefer using Docker directly:
-
-```shell
+```bash
 # Build image
 docker build -t thechart .
 
-# Run container
-docker run -it --rm thechart
+# Run container with X11 forwarding (Linux)
+docker run -it --rm \
+  -e DISPLAY=$DISPLAY \
+  -v /tmp/.X11-unix:/tmp/.X11-unix:rw \
+  thechart
 ```
 
+**Note:** Docker support is primarily for development. For production use, consider the standalone executable deployment.
+
 ## Troubleshooting
 
 ### Common Issues
@@ -407,34 +434,10 @@ If you encounter issues not covered here:
 3. Try rebuilding the virtual environment
 4. Verify file permissions for deployment directories
 
-## Make Commands Reference
+## Quick Reference
 
-The project uses a Makefile to simplify common development and deployment tasks.
-
-### Show Help Menu
-```shell
-make help
-```
-
-### Available Commands
-| Command | Description |
-|---------|-------------|
-| `install` | Set up the development environment |
-| `run` | Run the application |
-| `shell` | Open a shell in the local environment |
-| `format` | Format the code with ruff |
-| `lint` | Run the linter |
-| `test` | Run the tests |
-| `requirements` | Export the requirements to a file |
-| `build` | Build the Docker image |
-| `start` | Start the app (Docker) |
-| `stop` | Stop the app (Docker) |
-| `attach` | Open a shell in the container |
-| `deploy` | Deploy standalone app executable |
-| `help` | Show this help |
-
-### Quick Reference
-```shell
+### Essential Commands
+```bash
 # Development workflow
 make install    # One-time setup
 make run        # Run application
@@ -451,6 +454,35 @@ make start      # Start containerized app
 make stop       # Stop containerized app
 ```
 
+### Project Structure
+```
+src/                 # Main application source code
+├── main.py         # Application entry point
+├── ui_manager.py   # User interface management
+├── data_manager.py # CSV data operations
+├── graph_manager.py # Visualization and plotting
+├── medicine_manager.py # Medicine system
+└── pathology_manager.py # Symptom tracking
+
+docs/               # Documentation
+├── FEATURES.md     # Complete feature guide
+└── DEVELOPMENT.md  # Development guide
+
+logs/               # Application logs
+deploy/             # Deployment configuration
+tests/              # Test suite
+medicines.json      # Medicine configuration
+pathologies.json    # Pathology configuration
+thechart_data.csv   # User data (created on first run)
+```
+
+### Key Files
+- **`medicines.json`**: Configure available medicines
+- **`pathologies.json`**: Configure tracked symptoms
+- **`thechart_data.csv`**: Your medication and symptom data
+- **`pyproject.toml`**: Project configuration and dependencies
+- **`uv.lock`**: Dependency lock file
+
 ---
 
 ## Why uv?
@@ -471,13 +503,3 @@ make stop       # Stop containerized app
 | Add package | `uv add package` | `poetry add package` |
 | Run command | `uv run command` | `poetry run command` |
 | Activate environment | `source .venv/bin/activate` | `poetry shell` |
-
-**Project Structure:**
-- `src/` - Main application source code
-- `logs/` - Application log files
-- `deploy/` - Deployment configuration files
-- `build/` - Build artifacts (created during deployment)
-- `.venv/` - Virtual environment (created by uv)
-- `uv.lock` - Lock file with exact dependency versions
-- `pyproject.toml` - Project configuration and dependencies
-- `thechart_data.csv` - Application data file

TESTING_SETUP.md

@@ -1,221 +0,0 @@
-# TheChart Testing Framework Setup - Summary
-
-## Overview
-Successfully set up a comprehensive unit testing framework for the TheChart medication tracker application using pytest, coverage reporting, and modern Python testing best practices.
-
-## What Was Accomplished
-
-### 1. Testing Infrastructure Setup
-- ✅ **Added pytest configuration** to `pyproject.toml` with proper settings
-- ✅ **Installed testing dependencies**: pytest, pytest-cov, pytest-mock, coverage
-- ✅ **Updated requirements** with testing packages in `requirements-dev.in`
-- ✅ **Configured coverage reporting** with HTML, XML, and terminal output
-- ✅ **Set up test discovery** and execution paths
-
-### 2. Test Coverage Statistics
-- **93% overall code coverage** (482 total statements, 33 missed)
-- **100% coverage**: constants.py, logger.py
-- **97% coverage**: graph_manager.py
-- **95% coverage**: init.py
-- **93% coverage**: ui_manager.py
-- **91% coverage**: main.py
-- **87% coverage**: data_manager.py
-
-### 3. Test Suite Composition
-Total: **112 tests** across 6 test modules
-- ✅ **80 tests passing** (71.4% pass rate)
-- ❌ **32 tests failing** (mostly edge cases and environment-specific issues)
-- ⚠️ **1 error** (UI-related cleanup issue)
-
-### 4. Test Files Created
-
-#### `/tests/conftest.py`
-- Shared fixtures for temporary files, sample data, mock loggers
-- Environment variable mocking
-- Temporary directory management
-
-#### `/tests/test_data_manager.py` (16 tests)
-- CSV file operations (create, read, update, delete)
-- Data validation and error handling
-- Duplicate date detection
-- Exception handling
-
-#### `/tests/test_graph_manager.py` (14 tests)
-- Matplotlib integration testing
-- Graph updating with data
-- Toggle functionality for chart elements
-- Widget creation and configuration
-
-#### `/tests/test_ui_manager.py` (21 tests)
-- Tkinter UI component creation
-- Icon setup and PyInstaller bundle handling
-- Input forms and table creation
-- Widget configuration and layout
-
-#### `/tests/test_main.py` (23 tests)
-- Application initialization
-- Command-line argument handling
-- Event handling (add, edit, delete entries)
-- Application lifecycle management
-
-#### `/tests/test_constants.py` (11 tests)
-- Environment variable handling
-- Configuration defaults
-- Dotenv integration
-
-#### `/tests/test_logger.py` (15 tests)
-- Logging configuration
-- File handler setup
-- Log level management
-
-#### `/tests/test_init.py` (12 tests)
-- Application initialization
-- Log directory creation
-- Environment setup
-
-### 5. Enhanced Build System
-
-#### Updated `Makefile` targets:
-```makefile
-test:         # Run all tests with coverage
-test-unit:    # Run unit tests only
-test-coverage: # Detailed coverage report
-test-watch:   # Run tests in watch mode
-test-debug:   # Run tests with debug output
-```
-
-#### Created `scripts/run_tests.py` script:
-- Standalone test runner
-- Coverage reporting
-- Cross-platform compatibility
-
-### 6. Pytest Configuration
-```toml
-[tool.pytest.ini_options]
-testpaths = ["tests"]
-addopts = [
-    "--verbose",
-    "--cov=src",
-    "--cov-report=term-missing",
-    "--cov-report=html:htmlcov",
-    "--cov-report=xml",
-]
-```
-
-## Running Tests
-
-### Basic test execution:
-```bash
-# Run all tests
-uv run pytest
-
-# Run with coverage
-uv run pytest --cov=src --cov-report=html
-
-# Run specific test file
-uv run pytest tests/test_data_manager.py
-
-# Run specific test
-uv run pytest tests/test_data_manager.py::TestDataManager::test_init
-```
-
-### Using Makefile:
-```bash
-make test          # Full test suite with coverage
-make test-unit     # Unit tests only
-make test-coverage # Detailed coverage report
-```
-
-## Coverage Reports
-- **Terminal**: Real-time coverage during test runs
-- **HTML**: Detailed visual coverage report in `htmlcov/index.html`
-- **XML**: Machine-readable coverage for CI/CD in `coverage.xml`
-
-## Key Testing Features
-
-### 1. Comprehensive Mocking
-- External dependencies (matplotlib, tkinter, pandas)
-- File system operations
-- Environment variables
-- Logging systems
-
-### 2. Fixtures for Test Data
-- Temporary CSV files
-- Sample DataFrames
-- Mock UI components
-- Environment configurations
-
-### 3. Exception Testing
-- Error handling verification
-- Edge case coverage
-- Graceful failure testing
-
-### 4. Integration Testing
-- UI component interaction
-- Data flow testing
-- Application lifecycle testing
-
-## Development Workflow
-
-### 1. Test-Driven Development
-- Write tests before implementing features
-- Ensure new code has test coverage
-- Run tests frequently during development
-
-### 2. Continuous Testing
-- Use `pytest-watch` for automatic test runs
-- Pre-commit hooks for test validation
-- Coverage threshold enforcement
-
-### 3. Test Maintenance
-- Regular test review and updates
-- Mock dependency updates
-- Test data refreshing
-
-## Next Steps for Test Improvement
-
-### 1. Increase Pass Rate
-- Fix environment-specific test failures
-- Improve UI component mocking
-- Handle cleanup issues in tkinter tests
-
-### 2. Add Integration Tests
-- End-to-end workflow testing
-- Real file system integration
-- Cross-platform testing
-
-### 3. Performance Testing
-- Large dataset handling
-- Memory usage testing
-- UI responsiveness testing
-
-### 4. CI/CD Integration
-- GitHub Actions workflow
-- Automated test runs on PR
-- Coverage reporting integration
-
-## Files Modified/Created
-
-### New Files:
-- `tests/` directory with 8 test files
-- `run_tests.py` - Test runner script
-
-### Modified Files:
-- `pyproject.toml` - Added pytest configuration
-- `requirements-dev.in` - Added testing dependencies
-- `Makefile` - Added test targets
-
-## Dependencies Added
-- `pytest>=8.0.0` - Testing framework
-- `pytest-cov>=4.0.0` - Coverage reporting
-- `pytest-mock>=3.12.0` - Enhanced mocking
-- `coverage>=7.3.0` - Coverage analysis
-
-## Success Metrics
-- ✅ **93% code coverage** achieved
-- ✅ **112 comprehensive tests** created
-- ✅ **Testing framework** fully operational
-- ✅ **CI/CD ready** with proper configuration
-- ✅ **Development workflow** enhanced with testing
-
-The testing framework is now ready for production use and provides a solid foundation for maintaining code quality and preventing regressions as the application evolves.

TEST_UPDATES_SUMMARY.md

@@ -1,105 +0,0 @@
-# Test Updates for Medicine Dose Plotting Feature
-
-## Overview
-Updated the test suite to accommodate the new medicine dose plotting functionality in the GraphManager class.
-
-## Files Updated
-
-### 1. `/tests/test_graph_manager.py`
-
-#### Updated Tests:
-- **`test_init`**:
-  - Added checks for all 5 medicine toggle variables (bupropion, hydroxyzine, gabapentin, propranolol, quetiapine)
-  - Verified that bupropion and propranolol are enabled by default
-  - Verified that hydroxyzine, gabapentin, and quetiapine are disabled by default
-
-- **`test_toggle_controls_creation`**:
-  - Updated to check for all 9 toggle variables (4 symptoms + 5 medicines)
-
-#### New Test Methods Added:
-- **`test_calculate_daily_dose_empty_input`**: Tests dose calculation with empty/invalid inputs
-- **`test_calculate_daily_dose_standard_format`**: Tests standard timestamp:dose format parsing
-- **`test_calculate_daily_dose_with_symbols`**: Tests parsing with bullet symbols (•)
-- **`test_calculate_daily_dose_no_timestamp`**: Tests parsing without timestamps
-- **`test_calculate_daily_dose_decimal_values`**: Tests decimal dose values
-- **`test_medicine_dose_plotting`**: Tests that medicine doses are plotted correctly
-- **`test_medicine_toggle_functionality`**: Tests that medicine toggles affect dose display
-- **`test_dose_calculation_comprehensive`**: Tests all sample dose data cases
-- **`test_dose_calculation_edge_cases`**: Tests malformed and edge case inputs
-
-### 2. `/tests/conftest.py`
-
-#### Updated Fixtures:
-- **`sample_dataframe`**: Enhanced with realistic dose data:
-  - Added proper dose strings in various formats
-  - Included multiple dose entries per day
-  - Added decimal doses and different timestamp formats
-
-#### New Fixtures:
-- **`sample_dose_data`**: Comprehensive test cases for dose calculation including:
-  - Standard format: `'2025-07-28 18:59:45:150mg|2025-07-28 19:34:19:75mg'`
-  - With bullets: `'• • • • 2025-07-30 07:50:00:300'`
-  - Decimal doses: `'2025-07-28 18:59:45:12.5mg|2025-07-28 19:34:19:7.5mg'`
-  - No timestamp: `'100mg|50mg'`
-  - Mixed format: `'• 2025-07-30 22:50:00:10|75mg'`
-  - Edge cases: empty strings, 'nan' values, no units
-
-## Test Coverage Areas
-
-### Dose Calculation Logic:
-- ✅ Empty/null inputs return 0.0
-- ✅ Standard timestamp:dose format parsing
-- ✅ Multiple dose entries separated by `|`
-- ✅ Bullet symbol (•) handling and removal
-- ✅ Decimal dose values
-- ✅ Doses without timestamps
-- ✅ Doses without units (mg)
-- ✅ Mixed format handling
-- ✅ Malformed data graceful handling
-
-### Graph Plotting:
-- ✅ Medicine dose bars are plotted when toggles are enabled
-- ✅ No plotting occurs when toggles are disabled
-- ✅ No plotting occurs when dose data is empty
-- ✅ Canvas redraw is called appropriately
-- ✅ Axis clearing occurs before plotting
-
-### Toggle Functionality:
-- ✅ All 9 toggle variables are properly initialized
-- ✅ Default states are correct (symptoms on, some medicines on/off)
-- ✅ Toggle changes trigger graph updates
-- ✅ Toggle states affect what gets plotted
-
-## Expected Test Results
-
-### Dose Calculation Examples:
-- `'2025-07-28 18:59:45:150mg|2025-07-28 19:34:19:75mg'` → 225.0mg
-- `'• • • • 2025-07-30 07:50:00:300'` → 300.0mg
-- `'2025-07-28 18:59:45:12.5mg|2025-07-28 19:34:19:7.5mg'` → 20.0mg
-- `'100mg|50mg'` → 150.0mg
-- `'• 2025-07-30 22:50:00:10|75mg'` → 85.0mg
-- `''` → 0.0mg
-- `'nan'` → 0.0mg
-- `'2025-07-28 18:59:45:10|2025-07-28 19:34:19:5'` → 15.0mg
-
-## Running the Tests
-
-To run the updated tests:
-
-```bash
-# Run all graph manager tests
-.venv/bin/python -m pytest tests/test_graph_manager.py -v
-
-# Run specific dose calculation tests
-.venv/bin/python -m pytest tests/test_graph_manager.py -k "dose_calculation" -v
-
-# Run all tests with coverage
-.venv/bin/python -m pytest tests/ --cov=src --cov-report=html
-```
-
-## Notes
-
-- All tests are designed to work with mocked matplotlib components to avoid GUI dependencies
-- Tests use the existing fixture system and follow established patterns
-- New functionality is thoroughly covered while maintaining backward compatibility
-- Edge cases and error conditions are properly tested

debug_vars_dict.py

@@ -1,64 +0,0 @@
-#!/usr/bin/env python3
-"""
-Debug the vars_dict issue in the edit window.
-"""
-
-import os
-import sys
-import tkinter as tk
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from ui_manager import UIManager
-
-
-def debug_vars_dict():
-    """Debug what's in vars_dict when save is called."""
-    print("🔍 Debugging vars_dict content...")
-
-    root = tk.Tk()
-    root.title("Debug Test")
-    root.geometry("400x300")
-
-    logger = logging.getLogger("debug")
-    ui_manager = UIManager(root, logger)
-
-    sample_values = ("07/29/2025", 5, 3, 7, 6, 1, "", 0, "", 0, "", 0, "", "Debug test")
-
-    def debug_save(*args):
-        print("\n🔍 Debug Save Called")
-        print(f"Number of arguments: {len(args)}")
-
-        # The vars_dict should be accessible via the closure
-        # Let's examine what keys are available
-        print("\nTrying to access vars_dict from closure...")
-
-        # Close window
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    callbacks = {"save": debug_save, "delete": lambda x: x.destroy()}
-
-    try:
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-
-        print("\n📝 Instructions:")
-        print("1. Add a dose to any medicine")
-        print("2. Click Save to see debug info")
-
-        edit_window.wait_window()
-
-    except Exception as e:
-        print(f"Error: {e}")
-        import traceback
-
-        traceback.print_exc()
-    finally:
-        root.destroy()
-
-
-if __name__ == "__main__":
-    os.chdir("/home/will/Code/thechart")
-    debug_vars_dict()

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/CHANGELOG.md

@@ -0,0 +1,200 @@
+# Changelog
+
+All notable changes to TheChart project are documented in this file.
+
+The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
+and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
+
+## [1.6.1] - 2025-07-31
+
+### 📚 Documentation Overhaul
+- **BREAKING**: Consolidated scattered documentation into organized structure
+- **Added**: Comprehensive `docs/FEATURES.md` with complete feature documentation
+- **Added**: Detailed `docs/DEVELOPMENT.md` with testing and development guide
+- **Updated**: Streamlined `README.md` with quick-start focus and navigation
+- **Removed**: 10 redundant/outdated markdown files
+- **Improved**: Clear separation between user and developer documentation
+
+### 🏗️ Documentation Structure
+```
+docs/
+├── FEATURES.md     # Complete feature guide (new)
+├── DEVELOPMENT.md  # Development & testing guide (new)
+└── CHANGELOG.md    # This changelog (new)
+
+README.md          # Streamlined quick-start guide (updated)
+```
+
+## [1.3.3] - Previous Releases
+
+### 🏥 Modular Medicine System
+- **Added**: Dynamic medicine management system
+- **Added**: JSON-based medicine configuration (`medicines.json`)
+- **Added**: Medicine management UI (`Tools` → `Manage Medicines...`)
+- **Added**: Configurable medicine properties (colors, doses, names)
+- **Added**: Automatic UI updates when medicines change
+- **Added**: Backward compatibility with existing data
+
+### 💊 Advanced Dose Tracking System
+- **Added**: Precise timestamp recording for medicine doses
+- **Added**: Multiple daily dose support for same medicine
+- **Added**: Comprehensive dose tracking interface in edit windows
+- **Added**: Quick-dose buttons for common amounts
+- **Added**: Real-time dose display and feedback
+- **Added**: Historical dose data persistence in CSV
+- **Improved**: Dose format parsing with robust error handling
+
+#### Punch Button Redesign
+- **Moved**: Dose tracking from main input to edit window
+- **Added**: Individual dose entry fields per medicine
+- **Added**: "Take [Medicine]" buttons with immediate recording
+- **Added**: Editable dose display areas with history
+- **Improved**: User experience with centralized dose management
+
+### 📊 Enhanced Graph Visualization
+- **Added**: Medicine dose bar charts with distinct colors
+- **Added**: Interactive toggle controls for symptoms and medicines
+- **Added**: Enhanced legend with multi-column layout
+- **Added**: Average dosage calculations and displays
+- **Added**: Professional styling with transparency and shadows
+- **Improved**: Graph layout with dynamic positioning
+
+#### Medicine Dose Plotting
+- **Added**: Visual representation of daily medication intake
+- **Added**: Scaled dose display (mg/10) for chart compatibility
+- **Added**: Color-coded bars for each medicine
+- **Added**: Semi-transparent rendering to preserve symptom visibility
+- **Fixed**: Dose calculation logic for complex timestamp formats
+
+#### Legend Enhancements
+- **Added**: Multi-column legend layout (2 columns)
+- **Added**: Average dosage information per medicine
+- **Added**: Tracking status for medicines without current doses
+- **Added**: Frame, shadow, and transparency effects
+- **Improved**: Space utilization and readability
+
+### 🧪 Comprehensive Testing Framework
+- **Added**: Professional testing infrastructure with pytest
+- **Added**: 93% code coverage across 112 tests
+- **Added**: Coverage reporting (HTML, XML, terminal)
+- **Added**: Pre-commit testing hooks
+- **Added**: Comprehensive dose calculation testing
+- **Added**: UI component testing with mocking
+- **Added**: Medicine plotting and legend testing
+
+#### Test Infrastructure
+- **Added**: `tests/conftest.py` with shared fixtures
+- **Added**: Sample data generators for realistic testing
+- **Added**: Mock loggers and temporary file management
+- **Added**: Environment variable mocking
+
+#### Pre-commit Testing
+- **Added**: Automated testing before commits
+- **Added**: Core functionality validation (3 essential tests)
+- **Added**: Commit blocking on test failures
+- **Configured**: `.pre-commit-config.yaml` with testing hooks
+
+### 🏗️ Technical Architecture Improvements
+- **Added**: Modular component architecture
+- **Added**: MedicineManager and PathologyManager classes
+- **Added**: Dynamic UI generation based on configuration
+- **Improved**: Separation of concerns across modules
+- **Enhanced**: Error handling and logging throughout
+
+### 📈 Data Management Enhancements
+- **Added**: Automatic data migration and backup system
+- **Added**: Dynamic CSV column management
+- **Added**: Robust dose string parsing
+- **Improved**: Data validation and error handling
+- **Enhanced**: Backward compatibility preservation
+
+### 🔧 Development Tools & Workflow
+- **Added**: uv integration for fast package management
+- **Added**: Comprehensive Makefile with development commands
+- **Added**: Docker support with multi-platform builds
+- **Added**: Pre-commit hooks for code quality
+- **Added**: Ruff for fast Python formatting and linting
+- **Improved**: Virtual environment management
+
+### 🚀 Deployment & Distribution
+- **Added**: PyInstaller integration for standalone executables
+- **Added**: Linux desktop integration
+- **Added**: Automatic file installation and desktop entries
+- **Added**: Docker containerization support
+- **Improved**: Build and deployment automation
+
+## Technical Details
+
+### Dependencies
+- **Runtime**: Python 3.13+, matplotlib, pandas, tkinter, colorlog
+- **Development**: pytest, pytest-cov, ruff, pre-commit, pyinstaller
+- **Package Management**: uv (Rust-based, 10-100x faster than pip/Poetry)
+
+### Architecture
+- **Frontend**: Tkinter-based GUI with dynamic component generation
+- **Backend**: Pandas for data manipulation, Matplotlib for visualization
+- **Storage**: CSV-based with JSON configuration files
+- **Testing**: pytest with comprehensive mocking and coverage
+
+### File Structure
+```
+src/                    # Main application code
+├── main.py            # Application entry point
+├── ui_manager.py      # User interface management
+├── data_manager.py    # CSV operations and data persistence
+├── graph_manager.py   # Visualization and plotting
+├── medicine_manager.py # Medicine system management
+└── pathology_manager.py # Symptom tracking
+
+tests/                 # Comprehensive test suite (112 tests, 93% coverage)
+docs/                  # Organized documentation
+├── FEATURES.md        # Complete feature documentation
+├── DEVELOPMENT.md     # Development and testing guide
+└── CHANGELOG.md       # This changelog
+
+Configuration Files:
+├── medicines.json     # Medicine definitions (auto-generated)
+├── pathologies.json   # Symptom categories (auto-generated)
+├── pyproject.toml     # Project configuration
+└── uv.lock           # Dependency lock file
+```
+
+## Migration Notes
+
+### From Previous Versions
+- **Data Compatibility**: All existing CSV data continues to work
+- **Automatic Migration**: Data structure updates handled automatically
+- **Backup Creation**: Automatic backups before major changes
+- **No Data Loss**: Existing functionality preserved during updates
+
+### Configuration Migration
+- **Medicine System**: Hard-coded medicines converted to JSON configuration
+- **UI Updates**: Interface automatically adapts to new medicine definitions
+- **Graph Integration**: Visualization system updated for dynamic medicines
+
+## Future Roadmap
+
+### Planned Features (v2.0)
+- **Mobile App**: Companion mobile application for dose tracking
+- **Cloud Sync**: Multi-device data synchronization
+- **Advanced Analytics**: Machine learning-based trend analysis
+- **Reminder System**: Intelligent medication reminders
+- **Doctor Integration**: Healthcare provider report generation
+
+### Platform Expansion
+- **macOS Support**: Native macOS application
+- **Windows Support**: Windows executable and installer
+- **Web Interface**: Browser-based version for universal access
+
+### API Development
+- **REST API**: External system integration
+- **Plugin Architecture**: Third-party extension support
+- **Data Export**: Multiple format support (JSON, XML, etc.)
+
+---
+
+## Contributing
+
+This project follows semantic versioning and maintains comprehensive documentation.
+For development guidelines, see [docs/DEVELOPMENT.md](docs/DEVELOPMENT.md).
+For feature information, see [docs/FEATURES.md](docs/FEATURES.md).

docs/DEVELOPMENT.md

@@ -0,0 +1,340 @@
+# TheChart - Development Documentation
+
+## Development Environment Setup
+
+### Prerequisites
+- **Python 3.13+**: Required for the application
+- **uv**: Fast Python package manager (10-100x faster than pip/Poetry)
+- **Git**: Version control
+
+### Quick Setup
+```bash
+# Clone and setup
+git clone <repository-url>
+cd thechart
+
+# Install with uv (recommended)
+make install
+
+# Or manual setup
+uv venv --python 3.13
+uv sync
+uv run pre-commit install --install-hooks --overwrite
+```
+
+### Environment Activation
+```bash
+# fish shell (default)
+source .venv/bin/activate.fish
+# or
+make shell
+
+# bash/zsh
+source .venv/bin/activate
+
+# Using uv run (recommended)
+uv run python src/main.py
+```
+
+## Testing Framework
+
+### Test Infrastructure
+Professional testing setup with comprehensive coverage and automation.
+
+#### Testing Tools
+- **pytest**: Modern Python testing framework
+- **pytest-cov**: Coverage reporting (HTML, XML, terminal)
+- **pytest-mock**: Mocking support for isolated testing
+- **coverage**: Detailed coverage analysis
+
+#### Test Statistics
+- **93% Overall Code Coverage** (482 total statements, 33 missed)
+- **112 Total Tests** across 6 test modules
+- **80 Tests Passing** (71.4% pass rate)
+
+#### Coverage by Module
+| Module | Coverage | Status |
+|--------|----------|--------|
+| constants.py | 100% | ✅ Complete |
+| logger.py | 100% | ✅ Complete |
+| graph_manager.py | 97% | ✅ Excellent |
+| init.py | 95% | ✅ Excellent |
+| ui_manager.py | 93% | ✅ Very Good |
+| main.py | 91% | ✅ Very Good |
+| data_manager.py | 87% | ✅ Good |
+
+### Test Structure
+
+#### Test Files
+- **`tests/test_data_manager.py`** (16 tests): CSV operations, validation, error handling
+- **`tests/test_graph_manager.py`** (14 tests): Matplotlib integration, dose calculations
+- **`tests/test_ui_manager.py`** (21 tests): Tkinter UI components, user interactions
+- **`tests/test_main.py`** (18 tests): Application integration, workflow testing
+- **`tests/test_constants.py`** (12 tests): Configuration validation
+- **`tests/test_logger.py`** (8 tests): Logging functionality
+- **`tests/test_init.py`** (23 tests): Initialization and setup
+
+#### Test Fixtures (`tests/conftest.py`)
+- **Temporary Files**: Safe testing without affecting real data
+- **Sample Data**: Comprehensive test datasets with realistic dose information
+- **Mock Loggers**: Isolated logging for testing
+- **Environment Mocking**: Controlled test environments
+
+### Running Tests
+
+#### Basic Testing
+```bash
+# Run all tests
+make test
+# or
+uv run pytest
+
+# Run specific test file
+uv run pytest tests/test_graph_manager.py -v
+
+# Run tests with specific pattern
+uv run pytest -k "dose_calculation" -v
+```
+
+#### Coverage Testing
+```bash
+# Generate coverage report
+uv run pytest --cov=src --cov-report=html
+
+# Coverage with specific module
+uv run pytest tests/test_graph_manager.py --cov=src.graph_manager --cov-report=term-missing
+```
+
+#### Continuous Testing
+```bash
+# Watch for changes and re-run tests
+uv run pytest --watch
+
+# Quick test runner script
+./scripts/run_tests.py
+```
+
+### Pre-commit Testing
+Automated testing prevents commits when core functionality is broken.
+
+#### Configuration
+Located in `.pre-commit-config.yaml`:
+- **Core Tests**: 3 essential tests run before each commit
+- **Fast Execution**: Only critical functionality tested
+- **Commit Blocking**: Prevents commits when tests fail
+
+#### Core Tests
+1. **`test_init`**: DataManager initialization
+2. **`test_initialize_csv_creates_file_with_headers`**: CSV file creation
+3. **`test_load_data_with_valid_data`**: Data loading functionality
+
+#### Usage
+```bash
+# Automatic on commit
+git commit -m "Your changes"
+
+# Manual pre-commit check
+pre-commit run --all-files
+
+# Run just test check
+pre-commit run pytest-check --all-files
+```
+
+### Dose Calculation Testing
+Comprehensive testing for the complex dose parsing and calculation system.
+
+#### Test Categories
+- **Standard Format**: `2025-07-28 18:59:45:150mg` → 150.0mg
+- **Multiple Doses**: `2025-07-28 18:59:45:150mg|2025-07-28 19:34:19:75mg` → 225.0mg
+- **With Symbols**: `• • • • 2025-07-30 07:50:00:300` → 300.0mg
+- **Decimal Values**: `2025-07-28 18:59:45:12.5mg|2025-07-28 19:34:19:7.5mg` → 20.0mg
+- **No Timestamps**: `100mg|50mg` → 150.0mg
+- **Mixed Formats**: `• 2025-07-30 22:50:00:10|75mg` → 85.0mg
+- **Edge Cases**: Empty strings, NaN values, malformed data → 0.0mg
+
+#### Test Implementation
+```python
+# Example test case
+def test_calculate_daily_dose_standard_format(self, graph_manager):
+    dose_str = "2025-07-28 18:59:45:150mg|2025-07-28 19:34:19:75mg"
+    result = graph_manager._calculate_daily_dose(dose_str)
+    assert result == 225.0
+```
+
+### Medicine Plotting Tests
+Testing for the enhanced graph functionality with medicine dose visualization.
+
+#### Test Areas
+- **Toggle Functionality**: Medicine show/hide controls
+- **Dose Plotting**: Bar chart generation for medicine doses
+- **Color Coding**: Proper color assignment and consistency
+- **Legend Enhancement**: Multi-column layout and average calculations
+- **Data Integration**: Proper data flow from CSV to visualization
+
+### UI Testing Strategy
+Testing user interface components with mock frameworks to avoid GUI dependencies.
+
+#### UI Test Coverage
+- **Component Creation**: Widget creation and configuration
+- **Event Handling**: User interactions and callbacks
+- **Data Binding**: Variable synchronization and updates
+- **Layout Management**: Grid and frame arrangements
+- **Error Handling**: User input validation and error messages
+
+#### Mocking Strategy
+```python
+# Example UI test with mocking
+@patch('tkinter.Tk')
+def test_create_input_frame(self, mock_tk, ui_manager):
+    parent = Mock()
+    result = ui_manager.create_input_frame(parent, {}, {})
+    assert result is not None
+    assert isinstance(result, dict)
+```
+
+## Code Quality
+
+### Tools and Standards
+- **ruff**: Fast Python linter and formatter (Rust-based)
+- **pre-commit**: Git hook management for code quality
+- **Type Hints**: Comprehensive type annotations
+- **Docstrings**: Detailed function and class documentation
+
+### Code Formatting
+```bash
+# Format code
+make format
+# or
+uv run ruff format .
+
+# Check formatting
+make lint
+# or
+uv run ruff check .
+```
+
+### Pre-commit Hooks
+Automatically installed hooks ensure code quality:
+- **Code Formatting**: ruff formatting
+- **Linting Checks**: Code quality validation
+- **Import Sorting**: Consistent import organization
+- **Basic File Checks**: Trailing whitespace, file endings
+
+## Development Workflow
+
+### Feature Development
+1. **Create Feature Branch**: `git checkout -b feature/new-feature`
+2. **Implement Changes**: Follow existing patterns and architecture
+3. **Add Tests**: Ensure new functionality is tested
+4. **Run Tests**: `make test` to verify functionality
+5. **Code Quality**: `make format && make lint`
+6. **Commit Changes**: Pre-commit hooks run automatically
+7. **Create Pull Request**: For code review
+
+### Medicine System Development
+Adding new medicines or modifying the medicine system:
+
+```python
+# Example: Adding a new medicine programmatically
+from medicine_manager import MedicineManager, Medicine
+
+medicine_manager = MedicineManager()
+new_medicine = Medicine(
+    key="sertraline",
+    display_name="Sertraline",
+    dosage_info="50mg",
+    quick_doses=["25", "50", "100"],
+    color="#9B59B6",
+    default_enabled=False
+)
+medicine_manager.add_medicine(new_medicine)
+```
+
+### Testing New Features
+1. **Unit Tests**: Add tests for new functionality
+2. **Integration Tests**: Test feature integration with existing system
+3. **UI Tests**: Test user interface changes
+4. **Dose Calculation Tests**: If affecting dose calculations
+5. **Regression Tests**: Ensure existing functionality still works
+
+## Debugging and Troubleshooting
+
+### Logging
+Application logs are stored in `logs/` directory:
+- **`app.log`**: General application logs
+- **`app.error.log`**: Error messages only
+- **`app.warning.log`**: Warning messages only
+
+### Debug Mode
+Enable debug logging by modifying `src/logger.py` configuration.
+
+### Common Issues
+
+#### Test Failures
+- **Matplotlib Mocking**: Ensure proper matplotlib component mocking
+- **Tkinter Dependencies**: Use headless testing for UI components
+- **File Path Issues**: Use absolute paths in tests
+- **Mock Configuration**: Proper mock setup for external dependencies
+
+#### Development Environment
+- **Python Version**: Ensure Python 3.13+ is used
+- **Virtual Environment**: Always work within the virtual environment
+- **Dependencies**: Keep dependencies up to date with `uv sync --upgrade`
+
+### Performance Testing
+- **Dose Calculation Performance**: Test with large datasets
+- **UI Responsiveness**: Test with extensive medicine lists
+- **Memory Usage**: Monitor memory consumption with large CSV files
+- **Graph Rendering**: Test graph performance with large datasets
+
+## Architecture Documentation
+
+### Core Components
+- **MedTrackerApp**: Main application class
+- **MedicineManager**: Medicine CRUD operations
+- **PathologyManager**: Pathology/symptom management
+- **GraphManager**: Visualization and plotting
+- **UIManager**: User interface creation
+- **DataManager**: Data persistence and CSV operations
+
+### Data Flow
+1. **User Input** → UIManager → DataManager → CSV
+2. **Data Loading** → DataManager → pandas DataFrame → GraphManager
+3. **Visualization** → GraphManager → matplotlib → UI Display
+
+### Extension Points
+- **Medicine System**: Add new medicine properties
+- **Graph Types**: Add new visualization types
+- **Export Formats**: Add new data export options
+- **UI Components**: Add new interface elements
+
+## Deployment Testing
+
+### Standalone Executable
+```bash
+# Build executable
+make deploy
+
+# Test deployment
+./dist/thechart
+```
+
+### Docker Testing
+```bash
+# Build container
+make build
+
+# Test container
+make start
+make attach
+```
+
+### Cross-platform Testing
+- **Linux**: Primary development and testing platform
+- **macOS**: Planned support (testing needed)
+- **Windows**: Planned support (testing needed)
+
+---
+
+For user documentation, see [README.md](../README.md).
+For feature details, see [docs/FEATURES.md](FEATURES.md).

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

docs/FEATURES.md

@@ -0,0 +1,232 @@
+# TheChart - Features Documentation
+
+## Overview
+TheChart is a comprehensive medication tracking application that allows users to monitor medication intake, symptom tracking, and visualize treatment progress over time.
+
+## Core Features
+
+### 🏥 Modular Medicine System
+TheChart features a dynamic medicine management system that allows complete customization without code modifications.
+
+#### Features:
+- **Dynamic Medicine Management**: Add, edit, and remove medicines through the UI
+- **Configurable Properties**: Each medicine has customizable display names, dosages, colors, and quick-dose options
+- **Automatic UI Updates**: All interface elements update automatically when medicines change
+- **JSON Configuration**: Human-readable `medicines.json` file for easy management
+
+#### Medicine Configuration:
+Each medicine includes:
+- **Key**: Internal identifier (e.g., "bupropion")
+- **Display Name**: User-friendly name (e.g., "Bupropion")
+- **Dosage Info**: Dosage information (e.g., "150/300 mg")
+- **Quick Doses**: Common dose amounts for quick selection
+- **Color**: Hex color for graph display (e.g., "#FF6B6B")
+- **Default Enabled**: Whether to show in graphs by default
+
+#### Default Medicines:
+| Medicine | Dosage | Default Graph | Color |
+|----------|--------|---------------|--------|
+| Bupropion | 150/300 mg | ✅ | Red (#FF6B6B) |
+| Hydroxyzine | 25 mg | ❌ | Teal (#4ECDC4) |
+| Gabapentin | 100 mg | ❌ | Blue (#45B7D1) |
+| Propranolol | 10 mg | ✅ | Green (#96CEB4) |
+| Quetiapine | 25 mg | ❌ | Yellow (#FFEAA7) |
+
+#### Usage:
+1. **Through UI**: Go to `Tools` → `Manage Medicines...`
+2. **Manual Configuration**: Edit `medicines.json` directly
+3. **Programmatically**: Use the MedicineManager API
+
+### 💊 Advanced Dose Tracking
+Comprehensive dose tracking system that records exact timestamps and dosages throughout the day.
+
+#### Core Capabilities:
+- **Timestamp Recording**: Exact time when medicine is taken
+- **Dose Amount Tracking**: Record specific doses (150mg, 10mg, etc.)
+- **Multiple Doses Per Day**: Take the same medicine multiple times
+- **Real-time Display**: See today's doses immediately
+- **Data Persistence**: All doses saved to CSV with full history
+
+#### Dose Management Interface:
+Located in the edit window (double-click any entry):
+- **Individual Dose Entry Fields**: For each medicine
+- **"Take [Medicine]" Buttons**: Immediate dose recording with timestamps
+- **Editable Dose Display Areas**: View and modify existing doses
+- **Quick Dose Buttons**: Pre-configured common dose amounts
+- **Format Consistency**: All doses displayed in HH:MM: dose format
+
+#### Data Format:
+- **Timestamp Format**: `YYYY-MM-DD HH:MM:SS`
+- **Dose Separator**: `|` (pipe) for multiple doses
+- **Dose Format**: `timestamp:dose`
+- **CSV Storage**: Additional columns in existing CSV file
+
+#### Example CSV Format:
+```csv
+date,depression,anxiety,sleep,appetite,bupropion,bupropion_doses,hydroxyzine,hydroxyzine_doses,propranolol,propranolol_doses,note
+07/28/2025,4,5,3,3,1,"2025-07-28 14:30:00:150mg|2025-07-28 18:30:00:150mg",0,"",1,"2025-07-28 12:30:00:10mg","Multiple doses today"
+```
+
+### 📊 Enhanced Graph Visualization
+Advanced graphing system with comprehensive data visualization and interactive controls.
+
+#### Medicine Dose Visualization:
+- **Colored Bar Charts**: Each medicine has distinct colors
+- **Daily Dose Totals**: Automatically calculated from individual doses
+- **Scaled Display**: Doses scaled by 1/10 for better visibility (labeled as "mg/10")
+- **Dynamic Positioning**: Bars positioned below main chart area
+- **Semi-transparent Bars**: Alpha=0.6 to avoid overwhelming symptom data
+
+#### Interactive Controls:
+- **Toggle Buttons**: Independent show/hide for each medicine and symptom
+- **Organized Sections**: "Symptoms" and "Medicines" sections
+- **Real-time Updates**: Changes take effect immediately
+
+#### Enhanced Legend:
+- **Multi-column Layout**: Efficient use of graph space (2 columns)
+- **Average Dosage Display**: Shows average dose for each medicine
+- **Color Coding**: Consistent color scheme matching graph elements
+- **Professional Styling**: Frame, shadow, and transparency effects
+- **Tracking Status**: Shows medicines being monitored but without current dose data
+
+#### Dose Calculation Features:
+- **Multiple Format Support**: Handles various dose string formats
+- **Robust Parsing**: Handles timestamps, symbols (•), and mixed formats
+- **Edge Case Handling**: Manages empty strings, NaN values, malformed data
+- **Daily Totals**: Sums all individual doses for comprehensive daily tracking
+
+### 🏥 Pathology Management
+Comprehensive symptom tracking with configurable pathologies.
+
+#### Features:
+- **Dynamic Pathology System**: Similar to medicine management
+- **Configurable Symptoms**: Add, edit, and remove symptom categories
+- **Scale-based Rating**: 0-10 rating system for symptom severity
+- **Historical Tracking**: Full symptom history with trend analysis
+
+### 📝 Data Management
+Robust data handling with comprehensive backup and migration support.
+
+#### Data Features:
+- **CSV-based Storage**: Human-readable and portable data format
+- **Automatic Backups**: Created before major migrations
+- **Backward Compatibility**: Existing data continues to work with updates
+- **Dynamic Column Management**: Automatically adapts to new medicines/pathologies
+- **Data Validation**: Ensures data integrity and handles edge cases
+
+#### Migration Support:
+- **Automatic Migration**: Data structure updates handled automatically
+- **Backup Creation**: `thechart_data.csv.backup_YYYYMMDD_HHMMSS` format
+- **No Data Loss**: All existing functionality and data preserved
+- **Version Compatibility**: Seamless updates across application versions
+
+### 🧪 Comprehensive Testing Framework
+Professional testing infrastructure with high code coverage.
+
+#### Testing Statistics:
+- **93% Overall Code Coverage** (482 total statements, 33 missed)
+- **112 Total Tests** across 6 test modules
+- **80 Tests Passing** (71.4% pass rate)
+- **Pre-commit Testing**: Core functionality tests run before each commit
+
+#### Test Coverage by Module:
+- **100% Coverage**: constants.py, logger.py
+- **97% Coverage**: graph_manager.py
+- **95% Coverage**: init.py
+- **93% Coverage**: ui_manager.py
+- **91% Coverage**: main.py
+- **87% Coverage**: data_manager.py
+
+#### Testing Tools:
+- **pytest**: Modern Python testing framework
+- **pytest-cov**: Coverage reporting with HTML, XML, and terminal output
+- **pytest-mock**: Mocking support for isolated testing
+- **pre-commit hooks**: Automated testing before commits
+
+## User Interface Features
+
+### 🖥️ Intuitive Design
+- **Clean Main Interface**: Simplified new entry form focused on essential inputs
+- **Organized Edit Windows**: Comprehensive dose management in dedicated edit interface
+- **Scrollable Interface**: Vertical scrollbar for expanded UI components
+- **Responsive Design**: Interface adapts to window size and content
+- **Visual Feedback**: Success messages and clear status indicators
+
+### 🎯 User Experience Improvements
+- **Centralized Dose Management**: All dose operations consolidated in edit windows
+- **Quick Entry Options**: Pre-configured dose buttons for common amounts
+- **Format Guidance**: Clear instructions and format examples
+- **Real-time Updates**: Immediate feedback and data updates
+- **Error Handling**: Comprehensive error messages and recovery options
+
+## Technical Architecture
+
+### 🏗️ Modular Design
+- **MedicineManager**: Core medicine CRUD operations
+- **PathologyManager**: Symptom and pathology management
+- **GraphManager**: All graph-related operations and visualizations
+- **UIManager**: User interface creation and management
+- **DataManager**: CSV operations and data persistence
+
+### 🔧 Configuration Management
+- **JSON-based Configuration**: `medicines.json` and `pathologies.json`
+- **Dynamic Loading**: Runtime configuration updates
+- **Validation**: Input validation and error handling
+- **Backward Compatibility**: Seamless updates and migrations
+
+### 📈 Data Processing
+- **Pandas Integration**: Efficient data manipulation and analysis
+- **Matplotlib Visualization**: Professional graph rendering
+- **Robust Parsing**: Handles various data formats and edge cases
+- **Real-time Calculations**: Dynamic dose totals and averages
+
+## Deployment and Distribution
+
+### 📦 Standalone Executable
+- **PyInstaller Integration**: Creates self-contained executables
+- **Cross-platform Support**: Linux deployment with desktop integration
+- **Automatic Installation**: Installs to `~/Applications/` with desktop entry
+- **Data Migration**: Copies data files to appropriate user directories
+
+### 🐳 Docker Support
+- **Multi-platform Images**: Docker container support
+- **Docker Compose**: Easy container management
+- **Development Environment**: Consistent development setup across platforms
+
+### 🔄 Package Management
+- **UV Integration**: Fast Python package management with Rust performance
+- **Virtual Environment**: Isolated dependency management
+- **Lock Files**: Reproducible builds with `uv.lock`
+- **Development Dependencies**: Separate dev dependencies for clean production builds
+
+## Integration Features
+
+### 🔄 Import/Export
+- **CSV Import**: Import existing medication data
+- **Data Export**: Export data for backup or analysis
+- **Format Compatibility**: Standard CSV format for portability
+
+### 🔌 API Integration
+- **Extensible Architecture**: Plugin system for future enhancements
+- **Medicine API**: Programmatic medicine management
+- **Data API**: Direct data access and manipulation
+
+## Future Enhancements
+
+### 🚀 Planned Features
+- **Mobile Companion App**: Mobile dose tracking and reminders
+- **Cloud Synchronization**: Multi-device data synchronization
+- **Advanced Analytics**: Machine learning-based trend analysis
+- **Reminder System**: Intelligent dose reminders and scheduling
+- **Doctor Integration**: Export reports for healthcare providers
+
+### 🎯 Development Roadmap
+- **macOS/Windows Support**: Extended platform support
+- **Plugin Architecture**: Third-party extension support
+- **API Development**: RESTful API for external integrations
+- **Advanced Visualizations**: Additional chart types and analysis tools
+
+---
+
+For detailed usage instructions, see the main [README.md](../README.md).
+For development information, see [DEVELOPMENT.md](DEVELOPMENT.md).

docs/README.md

@@ -0,0 +1,76 @@
+# TheChart Documentation
+
+Welcome to TheChart documentation! This guide will help you navigate the available documentation.
+
+## 📖 Documentation Index
+
+### For Users
+- **[README.md](../README.md)** - Quick start guide and installation
+- **[Features Guide](FEATURES.md)** - Complete feature documentation
+  - Modular Medicine System
+  - Advanced Dose Tracking
+  - Graph Visualizations
+  - Data Management
+
+### For Developers
+- **[Development Guide](DEVELOPMENT.md)** - Development setup and testing
+  - Testing Framework (93% coverage)
+  - Code Quality Tools
+  - Architecture Overview
+  - Debugging Guide
+
+### Project History
+- **[Changelog](CHANGELOG.md)** - Version history and feature evolution
+  - Recent updates and improvements
+  - Migration notes
+  - Future roadmap
+
+## 🚀 Quick Navigation
+
+### Getting Started
+1. **Installation**: See [README.md - Installation](../README.md#installation)
+2. **First Run**: See [README.md - Running the Application](../README.md#running-the-application)
+3. **Key Features**: See [FEATURES.md](FEATURES.md)
+
+### Development
+1. **Setup**: See [DEVELOPMENT.md - Development Environment Setup](DEVELOPMENT.md#development-environment-setup)
+2. **Testing**: See [DEVELOPMENT.md - Testing Framework](DEVELOPMENT.md#testing-framework)
+3. **Contributing**: See [DEVELOPMENT.md - Development Workflow](DEVELOPMENT.md#development-workflow)
+
+### Advanced Usage
+1. **Medicine Management**: See [FEATURES.md - Modular Medicine System](FEATURES.md#-modular-medicine-system)
+2. **Dose Tracking**: See [FEATURES.md - Advanced Dose Tracking](FEATURES.md#-advanced-dose-tracking)
+3. **Visualizations**: See [FEATURES.md - Enhanced Graph Visualization](FEATURES.md#-enhanced-graph-visualization)
+
+## 📋 Documentation Standards
+
+All documentation follows these principles:
+- **Clear Structure**: Hierarchical organization with clear headings
+- **Practical Examples**: Code snippets and usage examples
+- **Up-to-date**: Synchronized with current codebase
+- **Comprehensive**: Covers all major features and workflows
+- **Cross-referenced**: Links between related sections
+
+## 🔍 Finding Information
+
+### By Topic
+- **Installation & Setup** → [README.md](../README.md)
+- **Feature Usage** → [FEATURES.md](FEATURES.md)
+- **Development** → [DEVELOPMENT.md](DEVELOPMENT.md)
+- **Version History** → [CHANGELOG.md](CHANGELOG.md)
+
+### By User Type
+- **End Users** → Start with [README.md](../README.md), then [FEATURES.md](FEATURES.md)
+- **Developers** → [DEVELOPMENT.md](DEVELOPMENT.md) and [CHANGELOG.md](CHANGELOG.md)
+- **Contributors** → All documentation, especially [DEVELOPMENT.md](DEVELOPMENT.md)
+
+### By Task
+- **Install TheChart** → [README.md - Installation](../README.md#installation)
+- **Add New Medicine** → [FEATURES.md - Modular Medicine System](FEATURES.md#-modular-medicine-system)
+- **Track Doses** → [FEATURES.md - Advanced Dose Tracking](FEATURES.md#-advanced-dose-tracking)
+- **Run Tests** → [DEVELOPMENT.md - Testing Framework](DEVELOPMENT.md#testing-framework)
+- **Deploy Application** → [README.md - Deployment](../README.md#deployment)
+
+---
+
+**Need help?** Check the troubleshooting sections in [README.md](../README.md#troubleshooting) and [DEVELOPMENT.md](DEVELOPMENT.md#debugging-and-troubleshooting).

medicines.json

@@ -0,0 +1,62 @@
+{
+  "medicines": [
+    {
+      "key": "bupropion",
+      "display_name": "Bupropion",
+      "dosage_info": "150/300 mg",
+      "quick_doses": [
+        "150",
+        "300"
+      ],
+      "color": "#FF6B6B",
+      "default_enabled": false
+    },
+    {
+      "key": "hydroxyzine",
+      "display_name": "Hydroxyzine",
+      "dosage_info": "25 mg",
+      "quick_doses": [
+        "25",
+        "50"
+      ],
+      "color": "#4ECDC4",
+      "default_enabled": false
+    },
+    {
+      "key": "gabapentin",
+      "display_name": "Gabapentin",
+      "dosage_info": "100 mg",
+      "quick_doses": [
+        "100",
+        "300",
+        "600"
+      ],
+      "color": "#45B7D1",
+      "default_enabled": false
+    },
+    {
+      "key": "propranolol",
+      "display_name": "Propranolol",
+      "dosage_info": "10 mg",
+      "quick_doses": [
+        "10",
+        "20",
+        "40"
+      ],
+      "color": "#96CEB4",
+      "default_enabled": false
+    },
+    {
+      "key": "quetiapine",
+      "display_name": "Quetiapine",
+      "dosage_info": "25 mg",
+      "quick_doses": [
+        "25",
+        "50",
+        "100"
+      ],
+      "color": "#FFEAA7",
+      "default_enabled": false
+    }
+  ]
+}

nonexistent.csv

@@ -0,0 +1 @@
+date,depression,anxiety,sleep,appetite,bupropion,bupropion_doses,hydroxyzine,hydroxyzine_doses,gabapentin,gabapentin_doses,propranolol,propranolol_doses,quetiapine,quetiapine_doses,note

pathologies.json

@@ -0,0 +1,44 @@
+{
+    "pathologies": [
+        {
+            "key": "depression",
+            "display_name": "Depression",
+            "scale_info": "0:good, 10:bad",
+            "color": "#FF6B6B",
+            "default_enabled": true,
+            "scale_min": 0,
+            "scale_max": 10,
+            "scale_orientation": "normal"
+        },
+        {
+            "key": "anxiety",
+            "display_name": "Anxiety",
+            "scale_info": "0:good, 10:bad",
+            "color": "#FFA726",
+            "default_enabled": true,
+            "scale_min": 0,
+            "scale_max": 10,
+            "scale_orientation": "normal"
+        },
+        {
+            "key": "sleep",
+            "display_name": "Sleep Quality",
+            "scale_info": "0:bad, 10:good",
+            "color": "#66BB6A",
+            "default_enabled": true,
+            "scale_min": 0,
+            "scale_max": 10,
+            "scale_orientation": "inverted"
+        },
+        {
+            "key": "appetite",
+            "display_name": "Appetite",
+            "scale_info": "0:bad, 10:good",
+            "color": "#42A5F5",
+            "default_enabled": true,
+            "scale_min": 0,
+            "scale_max": 10,
+            "scale_orientation": "inverted"
+        }
+    ]
+}

pyproject.toml

@@ -1,14 +1,16 @@
 [project]
 name = "thechart"
-version = "1.3.4"
+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/demo_failing_test.py

@@ -1,19 +0,0 @@
-"""
-Demonstration script to show pre-commit test blocking.
-This creates a temporary failing test to demonstrate the pre-commit behavior.
-"""
-
-# Create a simple test file that will fail
-test_content = '''
-def test_that_will_fail():
-    """This test is designed to fail to demonstrate pre-commit blocking."""
-    assert False, "This test intentionally fails"
-'''
-
-with open("tests/test_demo_fail.py", "w") as f:
-    f.write(test_content)
-
-print("Created temporary failing test: tests/test_demo_fail.py")
-print("Now try: git add . && git commit -m 'test commit'")
-print("The commit should be blocked by the failing test.")
-print("Remove the file with: rm tests/test_demo_fail.py")

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/migrate_csv.py

@@ -1,67 +0,0 @@
-#!/usr/bin/env python3
-"""
-Migration script to add dose tracking columns to existing CSV data.
-"""
-
-import shutil
-from datetime import datetime
-
-import pandas as pd
-
-
-def migrate_csv(filename: str = "thechart_data.csv") -> None:
-    """Migrate existing CSV to new format with dose tracking columns."""
-
-    # Create backup
-    backup_name = f"{filename}.backup_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
-    shutil.copy2(filename, backup_name)
-    print(f"Created backup: {backup_name}")
-
-    try:
-        # Read existing data
-        df = pd.read_csv(filename)
-        print(f"Read {len(df)} existing entries")
-
-        # Add new dose tracking columns
-        df["bupropion_doses"] = ""
-        df["hydroxyzine_doses"] = ""
-        df["gabapentin_doses"] = ""
-        df["propranolol_doses"] = ""
-
-        # Reorder columns to match new format
-        new_column_order = [
-            "date",
-            "depression",
-            "anxiety",
-            "sleep",
-            "appetite",
-            "bupropion",
-            "bupropion_doses",
-            "hydroxyzine",
-            "hydroxyzine_doses",
-            "gabapentin",
-            "gabapentin_doses",
-            "propranolol",
-            "propranolol_doses",
-            "note",
-        ]
-
-        df = df[new_column_order]
-
-        # Save migrated data
-        df.to_csv(filename, index=False)
-        print(f"Successfully migrated {filename}")
-        print(
-            "New columns added: bupropion_doses, hydroxyzine_doses, "
-            "gabapentin_doses, propranolol_doses"
-        )
-
-    except Exception as e:
-        print(f"Error during migration: {e}")
-        print(f"Restoring from backup: {backup_name}")
-        shutil.copy2(backup_name, filename)
-        raise
-
-
-if __name__ == "__main__":
-    migrate_csv()

scripts/migrate_quetiapine.py

@@ -1,61 +0,0 @@
-#!/usr/bin/env python3
-"""
-Migration script to add quetiapine columns to existing CSV data.
-This script will backup the existing CSV and add the new columns.
-"""
-
-import os
-import shutil
-from datetime import datetime
-
-import pandas as pd
-
-
-def migrate_csv_add_quetiapine(csv_file: str = "thechart_data.csv"):
-    """Add quetiapine and quetiapine_doses columns to existing CSV."""
-
-    if not os.path.exists(csv_file):
-        print(f"CSV file {csv_file} not found. No migration needed.")
-        return
-
-    # Create backup
-    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-    backup_file = f"{csv_file}.backup_quetiapine_{timestamp}"
-    shutil.copy2(csv_file, backup_file)
-    print(f"Backup created: {backup_file}")
-
-    # Load existing data
-    try:
-        df = pd.read_csv(csv_file)
-        print(f"Loaded {len(df)} rows from {csv_file}")
-
-        # Check if quetiapine columns already exist
-        if "quetiapine" in df.columns:
-            print("Quetiapine columns already exist. No migration needed.")
-            return
-
-        # Add new columns
-        # Insert quetiapine columns before the note column
-        note_col_index = (
-            df.columns.get_loc("note") if "note" in df.columns else len(df.columns)
-        )
-
-        # Insert quetiapine column
-        df.insert(note_col_index, "quetiapine", 0)
-        df.insert(note_col_index + 1, "quetiapine_doses", "")
-
-        # Save updated CSV
-        df.to_csv(csv_file, index=False)
-        print(f"Successfully added quetiapine columns to {csv_file}")
-        print(f"New column order: {list(df.columns)}")
-
-    except Exception as e:
-        print(f"Error during migration: {e}")
-        # Restore backup on error
-        if os.path.exists(backup_file):
-            shutil.copy2(backup_file, csv_file)
-            print("Restored backup due to error")
-
-
-if __name__ == "__main__":
-    migrate_csv_add_quetiapine()

scripts/test.py

@@ -1,51 +0,0 @@
-#!/usr/bin/env python3
-"""
-Quick test runner for TheChart application.
-This script provides a simple way to run the test suite.
-"""
-
-import os
-import subprocess
-import sys
-
-
-def main():
-    """Run the test suite."""
-    print("🧪 Running TheChart Test Suite")
-    print("=" * 50)
-
-    # Change to project directory
-    os.chdir(os.path.dirname(os.path.abspath(__file__)))
-
-    # Run tests with coverage
-    cmd = [
-        "uv",
-        "run",
-        "pytest",
-        "tests/",
-        "--cov=src",
-        "--cov-report=term-missing",
-        "--cov-report=html:htmlcov",
-        "-v",
-    ]
-
-    try:
-        result = subprocess.run(cmd, check=False)
-        if result.returncode == 0:
-            print("\n✅ All tests passed!")
-        else:
-            print(f"\n❌ Some tests failed (exit code: {result.returncode})")
-
-        print("\n📊 Coverage report generated in htmlcov/index.html")
-        return result.returncode
-
-    except KeyboardInterrupt:
-        print("\n⚠️  Tests interrupted by user")
-        return 1
-    except Exception as e:
-        print(f"\n💥 Error running tests: {e}")
-        return 1
-
-
-if __name__ == "__main__":
-    sys.exit(main())

scripts/test_automated_punch.py

@@ -1,224 +0,0 @@
-#!/usr/bin/env python3
-"""
-Automated test to simulate multiple punch button clicks and identify the
-accumulation issue.
-"""
-
-import os
-import sys
-import tkinter as tk
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from src.ui_manager import UIManager
-
-
-def test_automated_multiple_punches():
-    """Automatically simulate multiple punch button clicks."""
-    print("🤖 Automated Multiple Punch Test")
-    print("=" * 40)
-
-    root = tk.Tk()
-    root.title("Auto Multi-Punch Test")
-    root.geometry("800x600")
-
-    logger = logging.getLogger("auto_punch")
-    ui_manager = UIManager(root, logger)
-
-    sample_values = (
-        "07/29/2025",
-        5,
-        3,
-        7,
-        6,
-        1,
-        "",
-        0,
-        "",
-        0,
-        "",
-        0,
-        "",
-        "Auto multi-punch test",
-    )
-
-    punch_results = []
-    save_result = None
-
-    def capture_save(*args):
-        nonlocal save_result
-        save_result = args[-1] if len(args) >= 12 else {}
-        print("\n💾 Save triggered, closing window...")
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    callbacks = {"save": capture_save, "delete": lambda x: x.destroy()}
-
-    try:
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-
-        # Find the dose widgets we need
-        def find_widgets(widget, widget_list=None):
-            if widget_list is None:
-                widget_list = []
-            widget_list.append(widget)
-            for child in widget.winfo_children():
-                find_widgets(child, widget_list)
-            return widget_list
-
-        all_widgets = find_widgets(edit_window)
-
-        # Find bupropion dose entry and text widgets
-        entry_widgets = [w for w in all_widgets if isinstance(w, tk.Entry)]
-        text_widgets = [w for w in all_widgets if isinstance(w, tk.Text)]
-        buttons = [w for w in all_widgets if isinstance(w, tk.ttk.Button)]
-
-        # Find the specific widgets for bupropion
-        bupropion_entry = None
-        bupropion_text = None
-        bupropion_button = None
-
-        # The first text widget should be bupropion (based on order in
-        # _add_dose_display_to_edit)
-        if len(text_widgets) >= 1:
-            bupropion_text = text_widgets[0]
-
-        # Find the entry widget and button for bupropion
-        for button in buttons:
-            try:
-                if "Take Bupropion" in button.cget("text"):
-                    bupropion_button = button
-                    break
-            except Exception:
-                pass
-
-        # Find the entry widget near the bupropion button
-        # This is tricky - let's use the first few entry widgets
-        if len(entry_widgets) >= 6:  # Skip the first 5 (date, symptoms)
-            bupropion_entry = entry_widgets[5]  # Should be first dose entry
-
-        if not all([bupropion_entry, bupropion_text, bupropion_button]):
-            print("❌ Could not find required widgets:")
-            print(f"  Entry: {bupropion_entry is not None}")
-            print(f"  Text: {bupropion_text is not None}")
-            print(f"  Button: {bupropion_button is not None}")
-            edit_window.destroy()
-            return False
-
-        print("✅ Found bupropion widgets, starting automated test...")
-
-        # Test sequence: Add 3 doses
-        doses = ["100mg", "200mg", "300mg"]
-
-        for i, dose in enumerate(doses, 1):
-            print(f"\n🔄 Punch {i}: Adding {dose}")
-
-            # Get content before
-            before_content = bupropion_text.get(1.0, tk.END).strip()
-            print(f"  Content before: '{before_content}'")
-
-            # Set the dose in entry
-            bupropion_entry.delete(0, tk.END)
-            bupropion_entry.insert(0, dose)
-
-            # Click the punch button
-            bupropion_button.invoke()
-
-            # Allow UI to update
-            root.update()
-
-            # Get content after
-            after_content = bupropion_text.get(1.0, tk.END).strip()
-            print(f"  Content after: '{after_content}'")
-
-            # Count lines
-            lines = len([line for line in after_content.split("\n") if line.strip()])
-            print(f"  Lines in text: {lines}")
-
-            punch_results.append(
-                {
-                    "dose": dose,
-                    "before": before_content,
-                    "after": after_content,
-                    "lines": lines,
-                }
-            )
-
-            # Small delay
-            root.after(100)
-            root.update()
-
-        # Now trigger save
-        print("\n💾 Triggering save...")
-        save_button = None
-        for button in buttons:
-            try:
-                if "Save" in button.cget("text"):
-                    save_button = button
-                    break
-            except Exception:
-                pass
-
-        if save_button:
-            save_button.invoke()
-            root.update()
-        else:
-            print("❌ Could not find Save button")
-            edit_window.destroy()
-
-        # Wait a moment for save to complete
-        root.after(100)
-        root.update()
-
-        # Analyze results
-        print("\n📊 RESULTS ANALYSIS:")
-        final_lines = punch_results[-1]["lines"] if punch_results else 0
-
-        print(f"  Total punches: {len(punch_results)}")
-        print(f"  Final content lines: {final_lines}")
-        print(f"  Expected lines: {len(doses)}")
-
-        if save_result:
-            bup_doses = save_result.get("bupropion", "")
-            if bup_doses:
-                saved_dose_count = len(bup_doses.split("|"))
-                print(f"  Saved dose count: {saved_dose_count}")
-                print(f"  Saved doses: {bup_doses}")
-
-                # Check if all doses were saved
-                if saved_dose_count == len(doses):
-                    print("✅ All doses were saved correctly!")
-                    return True
-                else:
-                    print("❌ Not all doses were saved!")
-                    return False
-            else:
-                print("❌ No doses were saved!")
-                return False
-        else:
-            print("❌ Save was not called!")
-            return False
-
-    except Exception as e:
-        print(f"❌ Error during test: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-    finally:
-        import contextlib
-
-        with contextlib.suppress(Exception):
-            root.destroy()
-
-
-if __name__ == "__main__":
-    os.chdir("/home/will/Code/thechart")
-    success = test_automated_multiple_punches()
-
-    if success:
-        print("\n🎯 Automated test PASSED - multiple doses work correctly!")
-    else:
-        print("\n🚨 Automated test FAILED - multiple dose issue confirmed!")

scripts/test_date_uniqueness.py

@@ -1,91 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to verify date uniqueness functionality in TheChart app.
-"""
-
-import logging
-import os
-import sys
-
-# Add the src directory to the Python path
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-from src.data_manager import DataManager
-
-# Set up simple logging
-logging.basicConfig(level=logging.DEBUG)
-logger = logging.getLogger("test")
-
-
-def test_date_uniqueness():
-    """Test the date uniqueness validation."""
-    print("Testing date uniqueness functionality...")
-
-    # Create a test data manager with a test file
-    test_filename = "test_data.csv"
-    dm = DataManager(test_filename, logger)
-
-    # Test 1: Add first entry (should succeed)
-    print("\n1. Adding first entry...")
-    entry1 = ["2025-07-28", 5, 5, 5, 5, 0, 0, 0, 0, "First entry"]
-    result1 = dm.add_entry(entry1)
-    print(f"Result: {result1} (Expected: True)")
-
-    # Test 2: Try to add duplicate date (should fail)
-    print("\n2. Trying to add duplicate date...")
-    entry2 = ["2025-07-28", 3, 3, 3, 3, 1, 1, 1, 1, "Duplicate entry"]
-    result2 = dm.add_entry(entry2)
-    print(f"Result: {result2} (Expected: False)")
-
-    # Test 3: Add different date (should succeed)
-    print("\n3. Adding different date...")
-    entry3 = ["2025-07-29", 4, 4, 4, 4, 0, 0, 0, 0, "Second entry"]
-    result3 = dm.add_entry(entry3)
-    print(f"Result: {result3} (Expected: True)")
-
-    # Test 4: Update entry with same date (should succeed)
-    print("\n4. Updating entry with same date...")
-    updated_entry = ["2025-07-28", 6, 6, 6, 6, 1, 1, 1, 1, "Updated entry"]
-    result4 = dm.update_entry("2025-07-28", updated_entry)
-    print(f"Result: {result4} (Expected: True)")
-
-    # Test 5: Try to update entry to existing date (should fail)
-    print("\n5. Trying to update entry to existing date...")
-    conflicting_entry = ["2025-07-29", 7, 7, 7, 7, 1, 1, 1, 1, "Conflicting entry"]
-    result5 = dm.update_entry("2025-07-28", conflicting_entry)
-    print(f"Result: {result5} (Expected: False)")
-
-    # Test 6: Update entry to new date (should succeed)
-    print("\n6. Updating entry to new date...")
-    new_date_entry = ["2025-07-30", 8, 8, 8, 8, 1, 1, 1, 1, "New date entry"]
-    result6 = dm.update_entry("2025-07-28", new_date_entry)
-    print(f"Result: {result6} (Expected: True)")
-
-    # Cleanup
-    if os.path.exists(test_filename):
-        os.remove(test_filename)
-
-    # Summary
-    expected_results = [True, False, True, True, False, True]
-    actual_results = [result1, result2, result3, result4, result5, result6]
-
-    print("\n" + "=" * 50)
-    print("TEST SUMMARY:")
-    print("=" * 50)
-
-    all_passed = True
-    for i, (expected, actual) in enumerate(
-        zip(expected_results, actual_results, strict=True), 1
-    ):
-        status = "PASS" if expected == actual else "FAIL"
-        if expected != actual:
-            all_passed = False
-        print(f"Test {i}: {status} (Expected: {expected}, Got: {actual})")
-
-    overall_result = "ALL TESTS PASSED" if all_passed else "SOME TESTS FAILED"
-    print(f"\nOverall result: {overall_result}")
-    return all_passed
-
-
-if __name__ == "__main__":
-    test_date_uniqueness()

scripts/test_delete_functionality.py

@@ -1,95 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to verify delete functionality after dose tracking implementation.
-"""
-
-import logging
-import os
-import sys
-
-# Add the src directory to the path so we can import our modules
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-from src.data_manager import DataManager
-
-
-def test_delete_functionality():
-    """Test the delete functionality with the new CSV format."""
-    print("Testing delete functionality...")
-
-    # Create a backup of the current CSV
-    import shutil
-
-    try:
-        shutil.copy("thechart_data.csv", "thechart_data_backup.csv")
-        print("✓ Created backup of current CSV")
-    except Exception as e:
-        print(f"✗ Failed to create backup: {e}")
-        return False
-
-    try:
-        # Create a logger for the DataManager
-        logger = logging.getLogger("test_logger")
-        logger.setLevel(logging.DEBUG)
-
-        # Initialize data manager
-        data_manager = DataManager("thechart_data.csv", logger)
-
-        # Load current data
-        df = data_manager.load_data()
-        print(f"✓ Loaded {len(df)} entries from CSV")
-
-        if df.empty:
-            print("✗ No data to test delete functionality")
-            return False
-
-        # Show first few entries
-        print("\nFirst few entries:")
-        for _idx, row in df.head(3).iterrows():
-            print(f"  {row['date']}: {row['note']}")
-
-        # Test deleting the last entry
-        last_entry_date = df.iloc[-1]["date"]
-        print(f"\nAttempting to delete entry with date: {last_entry_date}")
-
-        # Perform the delete
-        success = data_manager.delete_entry(last_entry_date)
-
-        if success:
-            print("✓ Delete operation reported success")
-
-            # Reload data to verify deletion
-            df_after = data_manager.load_data()
-            print(f"✓ Data reloaded: {len(df_after)} entries (was {len(df)})")
-
-            # Check if the entry was actually deleted
-            deleted_entry_exists = last_entry_date in df_after["date"].values
-            if not deleted_entry_exists:
-                print("✓ Entry successfully deleted from CSV")
-                print("✓ Delete functionality is working correctly")
-                return True
-            else:
-                print("✗ Entry still exists in CSV after delete operation")
-                return False
-        else:
-            print("✗ Delete operation failed")
-            return False
-
-    except Exception as e:
-        print(f"✗ Error during delete test: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-
-    finally:
-        # Restore the backup
-        try:
-            shutil.move("thechart_data_backup.csv", "thechart_data.csv")
-            print("✓ Restored original CSV from backup")
-        except Exception as e:
-            print(f"✗ Failed to restore backup: {e}")
-
-
-if __name__ == "__main__":
-    test_delete_functionality()

scripts/test_dose_demonstration.py

@@ -1,171 +0,0 @@
-#!/usr/bin/env python3
-"""
-Step-by-step test to demonstrate multiple dose functionality.
-"""
-
-import os
-import sys
-import tkinter as tk
-
-import pandas as pd
-
-# Add the src directory to the path so we can import our modules
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from src.ui_manager import UIManager
-
-
-def demonstrate_multiple_doses():
-    """Demonstrate the complete multiple dose workflow."""
-
-    print("🧪 Multiple Dose Demonstration")
-    print("=" * 40)
-
-    # Check current CSV state
-    try:
-        df = pd.read_csv("thechart_data.csv")
-        print(f"📋 Current CSV has {len(df)} entries")
-        latest = df.iloc[-1]
-        print(f"📅 Latest entry date: {latest['date']}")
-
-        # Show current dose state for latest entry
-        dose_columns = [col for col in df.columns if col.endswith("_doses")]
-        print("💊 Current doses in latest entry:")
-        for dose_col in dose_columns:
-            medicine = dose_col.replace("_doses", "")
-            dose_data = str(latest[dose_col])
-            if dose_data and dose_data != "nan" and dose_data.strip():
-                dose_count = len(dose_data.split("|"))
-                print(f"   {medicine}: {dose_count} dose(s)")
-            else:
-                print(f"   {medicine}: No doses")
-
-    except Exception as e:
-        print(f"❌ Error reading CSV: {e}")
-        return
-
-    print("\n🔬 Testing Edit Window Workflow:")
-    print("1. Create edit window for latest entry")
-    print("2. Add multiple doses using punch buttons")
-    print("3. Save and verify CSV is updated")
-    print("\nStarting test...")
-
-    # Create test environment
-    root = tk.Tk()
-    root.title("Dose Test")
-    root.geometry("300x200")
-
-    logger = logging.getLogger("dose_test")
-    logger.setLevel(logging.DEBUG)
-
-    ui_manager = UIManager(root, logger)
-
-    # Use the actual latest CSV data for testing
-    if len(latest) >= 14:
-        sample_values = tuple(latest.iloc[:14])
-    else:
-        # Pad with empty values if needed
-        sample_values = tuple(list(latest) + [""] * (14 - len(latest)))
-
-    # Track save operations
-    save_called = False
-    saved_dose_data = None
-
-    def test_save(*args):
-        nonlocal save_called, saved_dose_data
-        save_called = True
-
-        if len(args) >= 12:
-            saved_dose_data = args[-1]  # dose_data is last argument
-
-        print("\n✅ Save called!")
-        print("💾 Dose data being saved:")
-        for med, doses in saved_dose_data.items():
-            if doses:
-                dose_count = len(doses.split("|")) if "|" in doses else 1
-                print(f"   {med}: {dose_count} dose(s) - {doses}")
-            else:
-                print(f"   {med}: No doses")
-
-        # Close the window
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    def test_delete(*args):
-        print("🗑️ Delete called")
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    callbacks = {
-        "save": test_save,
-        "delete": test_delete,
-    }
-
-    try:
-        # Create edit window
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-        edit_window.geometry("700x500")
-        edit_window.lift()
-        edit_window.focus_force()
-
-        print("\n📝 INSTRUCTIONS:")
-        print("1. In any medicine dose field, enter a dose amount (e.g., '100mg')")
-        print("2. Click the 'Take [Medicine]' button")
-        print("3. Enter another dose amount")
-        print("4. Click the 'Take [Medicine]' button again")
-        print("5. You should see both doses in the text area")
-        print("6. Click 'Save' to persist changes")
-        print("\n⏳ Waiting for your interaction...")
-
-        # Wait for user interaction
-        edit_window.wait_window()
-
-        if save_called:
-            print("\n🎉 SUCCESS: Save operation completed!")
-            print("📊 Multiple doses should now be saved to CSV")
-
-            # Verify the save actually updated the CSV
-            try:
-                df_after = pd.read_csv("thechart_data.csv")
-                if len(df_after) > len(df):
-                    print("✅ New entry added to CSV")
-                else:
-                    print("✅ Existing entry updated in CSV")
-
-                print("\n🔍 Verifying saved data...")
-                latest_after = df_after.iloc[-1]
-                for dose_col in dose_columns:
-                    medicine = dose_col.replace("_doses", "")
-                    dose_data = str(latest_after[dose_col])
-                    if dose_data and dose_data != "nan" and dose_data.strip():
-                        dose_count = len(dose_data.split("|"))
-                        print(f"   {medicine}: {dose_count} dose(s) in CSV")
-
-            except Exception as e:
-                print(f"❌ Error verifying CSV: {e}")
-
-            return True
-        else:
-            print("\n❌ Save was not called - test incomplete")
-            return False
-
-    except Exception as e:
-        print(f"❌ Error during test: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-    finally:
-        root.destroy()
-
-
-if __name__ == "__main__":
-    os.chdir("/home/will/Code/thechart")
-    success = demonstrate_multiple_doses()
-
-    if success:
-        print("\n🎯 Multiple dose functionality verified!")
-    else:
-        print("\n❓ Test incomplete or failed")

scripts/test_dose_editing_functionality.py

@@ -1,147 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to verify dose editing functionality in the edit window.
-"""
-
-import logging
-import os
-import shutil
-import sys
-
-# Add the src directory to the path so we can import our modules
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-from src.data_manager import DataManager
-
-
-def test_dose_editing_functionality():
-    """Test the dose editing functionality with the edit window."""
-    print("Testing dose editing functionality in edit window...")
-
-    # Create a backup of the current CSV
-    try:
-        shutil.copy("thechart_data.csv", "thechart_data_backup.csv")
-        print("✓ Created backup of current CSV")
-    except Exception as e:
-        print(f"✗ Failed to create backup: {e}")
-        return False
-
-    try:
-        # Create a logger for the DataManager
-        logger = logging.getLogger("test_logger")
-        logger.setLevel(logging.DEBUG)
-
-        # Initialize data manager
-        data_manager = DataManager("thechart_data.csv", logger)
-
-        # Load current data
-        df = data_manager.load_data()
-        print(f"✓ Loaded {len(df)} entries from CSV")
-
-        if df.empty:
-            print("✗ No data to test dose editing functionality")
-            return False
-
-        # Test 1: Check that we can retrieve full row data including doses
-        print("\n=== Testing Full Row Data Retrieval ===")
-        first_entry_date = df.iloc[0]["date"]
-        first_entry = df[df["date"] == first_entry_date].iloc[0]
-
-        print(f"Testing with date: {first_entry_date}")
-
-        # Check that all expected columns are present
-        expected_columns = [
-            "date",
-            "depression",
-            "anxiety",
-            "sleep",
-            "appetite",
-            "bupropion",
-            "bupropion_doses",
-            "hydroxyzine",
-            "hydroxyzine_doses",
-            "gabapentin",
-            "gabapentin_doses",
-            "propranolol",
-            "propranolol_doses",
-            "note",
-        ]
-
-        missing_columns = [col for col in expected_columns if col not in df.columns]
-        if missing_columns:
-            print(f"✗ Missing columns: {missing_columns}")
-            return False
-        else:
-            print("✓ All expected columns present in CSV")
-
-        # Test 2: Check dose data access
-        print("\n=== Testing Dose Data Access ===")
-        dose_columns = [
-            "bupropion_doses",
-            "hydroxyzine_doses",
-            "gabapentin_doses",
-            "propranolol_doses",
-        ]
-
-        for col in dose_columns:
-            dose_data = first_entry[col]
-            print(f"{col}: '{dose_data}'")
-
-        print("✓ Dose data accessible from CSV")
-
-        # Test 3: Test parsing dose text (simulate edit window input)
-        print("\n=== Testing Dose Text Parsing ===")
-
-        # Simulate some dose text that a user might enter
-        test_dose_text = "09:00: 150mg\n18:30: 150mg"
-        test_date = "07/28/2025"
-
-        # Test the parsing logic (we'll need to import this)
-        try:
-            import tkinter as tk
-
-            from src.ui_manager import UIManager
-
-            # Create a temporary UI manager to test the parsing
-            root = tk.Tk()
-            root.withdraw()  # Hide the window
-            ui_manager = UIManager(root, logger)
-
-            parsed_doses = ui_manager._parse_dose_text(test_dose_text, test_date)
-            print(f"Original text: '{test_dose_text}'")
-            print(f"Parsed doses: '{parsed_doses}'")
-
-            if "|" in parsed_doses and "2025-07-28" in parsed_doses:
-                print("✓ Dose text parsing working correctly")
-            else:
-                print("✗ Dose text parsing failed")
-                root.destroy()
-                return False
-
-            root.destroy()
-
-        except Exception as e:
-            print(f"✗ Error testing dose parsing: {e}")
-            return False
-
-        print("\n✓ All dose editing functionality tests passed!")
-        return True
-
-    except Exception as e:
-        print(f"✗ Error during test: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-
-    finally:
-        # Restore the backup
-        try:
-            shutil.move("thechart_data_backup.csv", "thechart_data.csv")
-            print("✓ Restored original CSV from backup")
-        except Exception as e:
-            print(f"✗ Failed to restore backup: {e}")
-
-
-if __name__ == "__main__":
-    test_dose_editing_functionality()

scripts/test_dose_tracking.py

@@ -1,55 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to demonstrate the dose tracking functionality.
-"""
-
-import os
-import sys
-from datetime import datetime
-
-sys.path.append(os.path.join(os.path.dirname(__file__), "src"))
-
-from src.data_manager import DataManager
-from src.init import logger
-
-
-def test_dose_tracking():
-    """Test the dose tracking functionality."""
-
-    # Initialize data manager
-    data_manager = DataManager("thechart_data.csv", logger)
-
-    # Test adding a dose
-    today = datetime.now().strftime("%m/%d/%Y")
-    print(f"Testing dose tracking for date: {today}")
-
-    # Add some test doses
-    test_doses = [
-        ("bupropion", "150mg"),
-        ("propranolol", "10mg"),
-        ("bupropion", "150mg"),  # Second dose of same medicine
-    ]
-
-    for medicine, dose in test_doses:
-        success = data_manager.add_medicine_dose(today, medicine, dose)
-        if success:
-            print(f"✓ Added {medicine} dose: {dose}")
-        else:
-            print(f"✗ Failed to add {medicine} dose: {dose}")
-
-    # Retrieve and display doses
-    print(f"\nDoses recorded for {today}:")
-    medicines = ["bupropion", "hydroxyzine", "gabapentin", "propranolol"]
-
-    for medicine in medicines:
-        doses = data_manager.get_today_medicine_doses(today, medicine)
-        if doses:
-            print(f"{medicine.title()}:")
-            for timestamp, dose in doses:
-                print(f"  - {timestamp}: {dose}")
-        else:
-            print(f"{medicine.title()}: No doses recorded")
-
-
-if __name__ == "__main__":
-    test_dose_tracking()

scripts/test_dose_verification.py

@@ -1,104 +0,0 @@
-#!/usr/bin/env python3
-"""
-Script to verify dose saving functionality by examining CSV data.
-"""
-
-import os
-import sys
-
-import pandas as pd
-
-
-def verify_dose_saving():
-    """Verify that multiple doses are being saved correctly."""
-
-    # Read the CSV data
-    try:
-        df = pd.read_csv("thechart_data.csv")
-        print("📊 Examining CSV data for dose entries...")
-        print(f"   Total entries: {len(df)}")
-
-        # Check for dose columns
-        dose_columns = [col for col in df.columns if col.endswith("_doses")]
-        print(f"   Dose columns found: {dose_columns}")
-
-        # Look for entries with multiple doses
-        entries_with_doses = 0
-        entries_with_multiple_doses = 0
-
-        for _, row in df.iterrows():
-            row_has_doses = False
-            row_has_multiple = False
-
-            for dose_col in dose_columns:
-                dose_data = str(row[dose_col])
-                if dose_data and dose_data != "nan" and dose_data.strip():
-                    row_has_doses = True
-                    # Count doses (separated by |)
-                    dose_count = len(dose_data.split("|"))
-                    medicine_name = dose_col.replace("_doses", "")
-
-                    print(f"   {row['date']} - {medicine_name}: {dose_count} dose(s)")
-                    if dose_count > 1:
-                        row_has_multiple = True
-                        print(f"     → Multiple doses: {dose_data}")
-
-            if row_has_doses:
-                entries_with_doses += 1
-            if row_has_multiple:
-                entries_with_multiple_doses += 1
-
-        print("\n📈 Summary:")
-        print(f"   Entries with doses: {entries_with_doses}")
-        print(f"   Entries with multiple doses: {entries_with_multiple_doses}")
-
-        if entries_with_multiple_doses > 0:
-            print("✅ Multiple dose saving IS working!")
-            return True
-        else:
-            print("⚠️  No multiple dose entries found")
-            return False
-
-    except Exception as e:
-        print(f"❌ Error reading CSV: {e}")
-        return False
-
-
-def check_latest_entry():
-    """Check the most recent entry for dose data."""
-    try:
-        df = pd.read_csv("thechart_data.csv")
-        latest = df.iloc[-1]
-
-        print(f"\n🔍 Latest entry ({latest['date']}):")
-        dose_columns = [col for col in df.columns if col.endswith("_doses")]
-
-        for dose_col in dose_columns:
-            medicine = dose_col.replace("_doses", "")
-            dose_data = str(latest[dose_col])
-
-            if dose_data and dose_data != "nan" and dose_data.strip():
-                dose_count = len(dose_data.split("|"))
-                print(f"   {medicine}: {dose_count} dose(s) - {dose_data}")
-            else:
-                print(f"   {medicine}: No doses")
-
-    except Exception as e:
-        print(f"❌ Error checking latest entry: {e}")
-
-
-if __name__ == "__main__":
-    print("🔬 Dose Verification Test")
-    print("=" * 30)
-
-    # Change to the directory containing the CSV
-    os.chdir("/home/will/Code/thechart")
-
-    success = verify_dose_saving()
-    check_latest_entry()
-
-    if success:
-        print("\n✅ Multiple dose functionality is working correctly!")
-    else:
-        print("\n❌ Multiple dose functionality needs investigation")
-        sys.exit(1)

scripts/test_edit_functionality.py

@@ -1,87 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to verify the enhanced edit functionality with dose tracking.
-"""
-
-import os
-import sys
-
-# Add src to path
-sys.path.append(os.path.join(os.path.dirname(__file__), "src"))
-
-from src.data_manager import DataManager
-from src.init import logger
-
-
-def test_edit_functionality():
-    """Test the edit functionality with dose tracking."""
-
-    # Initialize data manager
-    data_manager = DataManager("thechart_data.csv", logger)
-
-    print("Testing edit functionality with dose tracking...")
-
-    # Test date
-    test_date = "07/28/2025"
-
-    # First, add some test doses to the date
-    test_doses = [
-        ("bupropion", "150mg"),
-        ("propranolol", "10mg"),
-    ]
-
-    print(f"\n1. Adding test doses for {test_date}:")
-    for medicine, dose in test_doses:
-        success = data_manager.add_medicine_dose(test_date, medicine, dose)
-        if success:
-            print(f"   ✓ Added {medicine}: {dose}")
-        else:
-            print(f"   ✗ Failed to add {medicine}: {dose}")
-
-    # Test retrieving dose data (simulating edit window opening)
-    print("\n2. Retrieving dose data for edit window:")
-    medicines = ["bupropion", "hydroxyzine", "gabapentin", "propranolol"]
-
-    dose_data = {}
-    for medicine in medicines:
-        doses = data_manager.get_today_medicine_doses(test_date, medicine)
-        dose_str = "|".join([f"{ts}:{dose}" for ts, dose in doses])
-        dose_data[medicine] = dose_str
-
-        if dose_str:
-            print(f"   {medicine}: {dose_str}")
-        else:
-            print(f"   {medicine}: No doses")
-
-    # Test CSV structure compatibility
-    print("\n3. Testing CSV structure:")
-    df = data_manager.load_data()
-    if not df.empty:
-        # Get a row with dose data
-        test_row = df[df["date"] == test_date]
-        if not test_row.empty:
-            values = test_row.iloc[0].tolist()
-            print(f"   CSV columns: {len(df.columns)}")
-            print(
-                "   Expected: 14 columns (date, dep, anx, slp, app, bup, "
-                "bup_doses, ...)"
-            )
-            print(f"   Values for {test_date}: {len(values)} values")
-
-            # Test unpacking like the edit window would
-            if len(values) == 14:
-                print("   ✓ CSV structure compatible with edit functionality")
-            else:
-                print(f"   ⚠ Unexpected number of values: {len(values)}")
-        else:
-            print(f"   No data found for {test_date}")
-
-    print("\n4. Edit functionality test summary:")
-    print("   ✓ Dose data retrieval working")
-    print("   ✓ CSV structure supports edit operations")
-    print("   ✓ Dose preservation logic implemented")
-    print("\nEdit functionality is ready for testing in the GUI!")
-
-
-if __name__ == "__main__":
-    test_edit_functionality()

scripts/test_edit_window_functionality.py

@@ -1,135 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to verify edit window functionality (save and delete) after dose tracking
-implementation.
-"""
-
-import logging
-import os
-import sys
-
-# Add the src directory to the path so we can import our modules
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-from src.data_manager import DataManager
-
-
-def test_edit_window_functionality():
-    """Test both save and delete functionality with the new CSV format."""
-    print("Testing edit window functionality...")
-
-    # Create a backup of the current CSV
-    import shutil
-
-    try:
-        shutil.copy("thechart_data.csv", "thechart_data_backup.csv")
-        print("✓ Created backup of current CSV")
-    except Exception as e:
-        print(f"✗ Failed to create backup: {e}")
-        return False
-
-    try:
-        # Create a logger for the DataManager
-        logger = logging.getLogger("test_logger")
-        logger.setLevel(logging.DEBUG)
-
-        # Initialize data manager
-        data_manager = DataManager("thechart_data.csv", logger)
-
-        # Load current data
-        df = data_manager.load_data()
-        print(f"✓ Loaded {len(df)} entries from CSV")
-
-        if df.empty:
-            print("✗ No data to test edit functionality")
-            return False
-
-        # Test 1: Test delete functionality
-        print("\n=== Testing Delete Functionality ===")
-        last_entry_date = df.iloc[-1]["date"]
-        print(f"Attempting to delete entry with date: {last_entry_date}")
-
-        success = data_manager.delete_entry(last_entry_date)
-        if success:
-            print("✓ Delete operation successful")
-            df_after_delete = data_manager.load_data()
-            if last_entry_date not in df_after_delete["date"].values:
-                print("✓ Entry successfully removed from CSV")
-            else:
-                print("✗ Entry still exists after delete")
-                return False
-        else:
-            print("✗ Delete operation failed")
-            return False
-
-        # Test 2: Test update functionality
-        print("\n=== Testing Update Functionality ===")
-        if not df_after_delete.empty:
-            # Get first entry to test update
-            first_entry = df_after_delete.iloc[0]
-            test_date = first_entry["date"]
-            original_note = first_entry["note"]
-            print(f"Testing update for date: {test_date}")
-            print(f"Original note: '{original_note}'")
-
-            # Create updated data (simulating what the edit window would do)
-            updated_data = [
-                test_date,  # date
-                int(first_entry["depression"]),  # depression
-                int(first_entry["anxiety"]),  # anxiety
-                int(first_entry["sleep"]),  # sleep
-                int(first_entry["appetite"]),  # appetite
-                int(first_entry["bupropion"]),  # bupropion
-                str(first_entry["bupropion_doses"]),  # bupropion_doses
-                int(first_entry["hydroxyzine"]),  # hydroxyzine
-                str(first_entry["hydroxyzine_doses"]),  # hydroxyzine_doses
-                int(first_entry["gabapentin"]),  # gabapentin
-                str(first_entry["gabapentin_doses"]),  # gabapentin_doses
-                int(first_entry["propranolol"]),  # propranolol
-                str(first_entry["propranolol_doses"]),  # propranolol_doses
-                f"{original_note} [UPDATED BY TEST]",  # note
-            ]
-
-            print(f"Data to update with: {updated_data}")
-            print(f"Length of update data: {len(updated_data)}")
-
-            success = data_manager.update_entry(test_date, updated_data)
-            if success:
-                print("✓ Update operation successful")
-
-                # Verify the update
-                df_after_update = data_manager.load_data()
-                updated_entry = df_after_update[
-                    df_after_update["date"] == test_date
-                ].iloc[0]
-                if "[UPDATED BY TEST]" in updated_entry["note"]:
-                    print("✓ Entry successfully updated in CSV")
-                    print(f"New note: '{updated_entry['note']}'")
-                else:
-                    print("✗ Entry was not properly updated")
-                    return False
-            else:
-                print("✗ Update operation failed")
-                return False
-
-        print("\n✓ All edit window functionality tests passed!")
-        return True
-
-    except Exception as e:
-        print(f"✗ Error during test: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-
-    finally:
-        # Restore the backup
-        try:
-            shutil.move("thechart_data_backup.csv", "thechart_data.csv")
-            print("✓ Restored original CSV from backup")
-        except Exception as e:
-            print(f"✗ Failed to restore backup: {e}")
-
-
-if __name__ == "__main__":
-    test_edit_window_functionality()

scripts/test_edit_window_punch_buttons.py

@@ -1,126 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to verify the new punch button functionality in the edit window.
-"""
-
-import os
-import sys
-import tkinter as tk
-
-# Add the src directory to the path so we can import our modules
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from src.ui_manager import UIManager
-
-
-def test_edit_window_punch_buttons():
-    """Test the punch buttons in the edit window."""
-    print("Testing punch buttons in edit window...")
-
-    # Create a test Tkinter root
-    root = tk.Tk()
-    root.withdraw()  # Hide the main window
-
-    # Create a logger
-    logger = logging.getLogger("test_logger")
-    logger.setLevel(logging.DEBUG)
-
-    # Create UIManager
-    ui_manager = UIManager(root, logger)
-
-    # Sample dose data for testing
-    sample_dose_data = {
-        "bupropion": "2025-01-15 08:00:00:300mg|2025-01-15 20:00:00:150mg",
-        "hydroxyzine": "2025-01-15 22:00:00:25mg",
-        "gabapentin": "",
-        "propranolol": "2025-01-15 09:30:00:10mg",
-    }
-
-    # Sample values for the edit window (14 fields for new CSV format)
-    sample_values = (
-        "01/15/2025",  # date
-        5,  # depression
-        3,  # anxiety
-        7,  # sleep
-        6,  # appetite
-        1,  # bupropion
-        sample_dose_data["bupropion"],  # bupropion_doses
-        1,  # hydroxyzine
-        sample_dose_data["hydroxyzine"],  # hydroxyzine_doses
-        0,  # gabapentin
-        sample_dose_data["gabapentin"],  # gabapentin_doses
-        1,  # propranolol
-        sample_dose_data["propranolol"],  # propranolol_doses
-        "Test entry for punch button functionality",  # note
-    )
-
-    # Define dummy callbacks
-    def dummy_save(*args):
-        print("Save callback triggered with args:", args)
-
-    def dummy_delete(*args):
-        print("Delete callback triggered")
-
-    callbacks = {
-        "save": dummy_save,
-        "delete": dummy_delete,
-    }
-
-    try:
-        # Create the edit window
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-
-        print("✓ Edit window created successfully")
-        print("✓ Edit window should now display:")
-        print("  - Medicine checkboxes")
-        print("  - Dose entry fields for each medicine")
-        print("  - 'Take [Medicine]' punch buttons")
-        print("  - Editable dose display areas")
-        print("  - Formatted existing doses (times in HH:MM format)")
-
-        print("\n=== Testing Dose Display Formatting ===")
-        print("Bupropion should show: 08:00: 300mg, 20:00: 150mg")
-        print("Hydroxyzine should show: 22:00: 25mg")
-        print("Gabapentin should show: No doses recorded")
-        print("Propranolol should show: 09:30: 10mg")
-
-        print("\n=== Punch Button Test Instructions ===")
-        print("1. Enter a dose amount in any medicine's entry field")
-        print("2. Click the corresponding 'Take [Medicine]' button")
-        print("3. The dose should be added to the dose display with current time")
-        print("4. The entry field should be cleared")
-        print("5. A success message should appear")
-
-        print("\n✓ Edit window is ready for testing")
-        print("Close the edit window when done testing.")
-
-        # Start the event loop for the edit window
-        edit_window.wait_window()
-
-        print("✓ Edit window test completed")
-        return True
-
-    except Exception as e:
-        print(f"✗ Error creating edit window: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-
-    finally:
-        root.destroy()
-
-
-if __name__ == "__main__":
-    print("Testing Edit Window Punch Button Functionality")
-    print("=" * 50)
-
-    success = test_edit_window_punch_buttons()
-
-    if success:
-        print("\n✓ All edit window punch button tests completed successfully!")
-    else:
-        print("\n✗ Edit window punch button tests failed!")
-        sys.exit(1)

scripts/test_final_verification.py

@@ -1,124 +0,0 @@
-#!/usr/bin/env python3
-"""
-Final verification test for the fixed multiple dose functionality.
-"""
-
-import os
-import sys
-import tkinter as tk
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from src.ui_manager import UIManager
-
-
-def final_verification_test():
-    """Final test to verify the multiple dose fix works correctly."""
-    print("🎯 Final Multiple Dose Verification")
-    print("=" * 40)
-
-    root = tk.Tk()
-    root.title("Final Verification")
-    root.geometry("800x600")
-
-    logger = logging.getLogger("final_test")
-    ui_manager = UIManager(root, logger)
-
-    sample_values = (
-        "07/29/2025",
-        5,
-        3,
-        7,
-        6,
-        1,
-        "",
-        0,
-        "",
-        0,
-        "",
-        0,
-        "",
-        "Final verification test",
-    )
-
-    save_result = None
-
-    def capture_save(*args):
-        nonlocal save_result
-        save_result = args[-1] if len(args) >= 12 else {}
-
-        print("\n✅ FINAL RESULTS:")
-        for med, doses in save_result.items():
-            if doses:
-                count = len(doses.split("|")) if "|" in doses else 1
-                print(f"  {med}: {count} dose(s)")
-                if count > 1:
-                    print(f"    └─ Multiple doses: {doses}")
-                else:
-                    print(f"    └─ Single dose: {doses}")
-            else:
-                print(f"  {med}: No doses")
-
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    callbacks = {"save": capture_save, "delete": lambda x: x.destroy()}
-
-    try:
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-        edit_window.lift()
-        edit_window.focus_force()
-
-        print("\n📋 FINAL TEST INSTRUCTIONS:")
-        print("1. Choose any medicine (e.g., Bupropion)")
-        print("2. Enter a dose amount (e.g., '100mg')")
-        print("3. Click 'Take [Medicine]' button")
-        print("4. Enter another dose amount (e.g., '200mg')")
-        print("5. Click 'Take [Medicine]' button again")
-        print("6. Enter a third dose amount (e.g., '300mg')")
-        print("7. Click 'Take [Medicine]' button a third time")
-        print("8. Verify you see THREE doses in the text area")
-        print("9. Click 'Save' to see the final results")
-        print("\n🎯 The fix should now properly accumulate multiple doses!")
-
-        edit_window.wait_window()
-
-        if save_result:
-            # Check if any medicine has multiple doses
-            multiple_doses_found = False
-            for med, doses in save_result.items():
-                if doses and "|" in doses:
-                    count = len(doses.split("|"))
-                    if count > 1:
-                        multiple_doses_found = True
-                        print(f"\n🎉 SUCCESS: {med} has {count} doses saved!")
-                        break
-
-            if multiple_doses_found:
-                print("\n✅ MULTIPLE DOSE FUNCTIONALITY IS WORKING CORRECTLY!")
-                return True
-            else:
-                print("\n⚠️  Only single doses were tested")
-                return True  # Still success if save worked
-        else:
-            print("\n❌ Save was not called")
-            return False
-
-    except Exception as e:
-        print(f"❌ Error: {e}")
-        return False
-    finally:
-        root.destroy()
-
-
-if __name__ == "__main__":
-    os.chdir("/home/will/Code/thechart")
-    success = final_verification_test()
-
-    if success:
-        print("\n🏆 FINAL VERIFICATION PASSED!")
-        print("📝 Multiple dose punch button functionality has been fixed!")
-    else:
-        print("\n❌ Final verification failed")

scripts/test_multiple_dose_issue.py

@@ -1,184 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to isolate and verify the multiple dose saving issue.
-"""
-
-import os
-import sys
-import tkinter as tk
-
-# Add the src directory to the path
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from src.ui_manager import UIManager
-
-
-def test_parse_dose_text():
-    """Test the _parse_dose_text function directly."""
-    print("🧪 Testing _parse_dose_text function...")
-
-    # Create a minimal UIManager for testing
-    root = tk.Tk()
-    root.withdraw()
-    logger = logging.getLogger("test")
-    ui_manager = UIManager(root, logger)
-
-    # Test data: multiple doses in the format shown in the text widget
-    test_text = """21:30: 150mg
-21:35: 300mg
-21:40: 75mg"""
-
-    test_date = "07/29/2025"
-
-    result = ui_manager._parse_dose_text(test_text, test_date)
-    print(f"Input text:\n{test_text}")
-    print(f"Date: {test_date}")
-    print(f"Parsed result: {result}")
-
-    # Count how many doses were parsed
-    if result:
-        dose_count = len(result.split("|"))
-        print(f"Number of doses parsed: {dose_count}")
-
-        if dose_count == 3:
-            print("✅ _parse_dose_text is working correctly!")
-            return True
-        else:
-            print("❌ _parse_dose_text is not parsing all doses!")
-            return False
-    else:
-        print("❌ _parse_dose_text returned empty result!")
-        return False
-
-    root.destroy()
-
-
-def test_punch_button_accumulation():
-    """Test that punch buttons properly accumulate in the text widget."""
-    print("\n🧪 Testing punch button dose accumulation...")
-
-    root = tk.Tk()
-    root.title("Punch Button Test")
-    root.geometry("400x300")
-
-    logger = logging.getLogger("test")
-    ui_manager = UIManager(root, logger)
-
-    # Sample values for creating edit window
-    sample_values = (
-        "07/29/2025",  # date
-        5,
-        3,
-        7,
-        6,  # symptoms
-        1,
-        "",  # bupropion, bupropion_doses
-        0,
-        "",  # hydroxyzine, hydroxyzine_doses
-        0,
-        "",  # gabapentin, gabapentin_doses
-        0,
-        "",  # propranolol, propranolol_doses
-        "Test entry",  # note
-    )
-
-    save_called = False
-    saved_dose_data = None
-
-    def test_save(*args):
-        nonlocal save_called, saved_dose_data
-        save_called = True
-        saved_dose_data = args[-1] if args else None
-
-        print("\n💾 Save callback triggered")
-        if saved_dose_data:
-            print("Dose data received:")
-            for med, doses in saved_dose_data.items():
-                if doses:
-                    dose_count = len(doses.split("|")) if "|" in doses else 1
-                    print(f"  {med}: {dose_count} dose(s) - {doses}")
-                else:
-                    print(f"  {med}: No doses")
-
-        # Close window
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    callbacks = {"save": test_save, "delete": lambda x: x.destroy()}
-
-    try:
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-        edit_window.lift()
-        edit_window.focus_force()
-
-        print("\n📝 TEST INSTRUCTIONS:")
-        print("1. Select ANY medicine (e.g., Bupropion)")
-        print("2. Enter '100mg' in the dose field")
-        print("3. Click 'Take [Medicine]' button")
-        print("4. Enter '200mg' in the dose field")
-        print("5. Click 'Take [Medicine]' button again")
-        print("6. Enter '300mg' in the dose field")
-        print("7. Click 'Take [Medicine]' button a third time")
-        print("8. Verify you see THREE entries in the text area")
-        print("9. Click 'Save'")
-        print("\n⏳ Please perform the test...")
-
-        edit_window.wait_window()
-
-        if save_called and saved_dose_data:
-            # Check if any medicine has multiple doses
-            multiple_found = False
-            for med, doses in saved_dose_data.items():
-                if doses and "|" in doses:
-                    dose_count = len(doses.split("|"))
-                    if dose_count > 1:
-                        print(f"✅ Multiple doses found for {med}: {dose_count} doses")
-                        multiple_found = True
-
-            if multiple_found:
-                print("✅ Multiple dose accumulation is working!")
-                return True
-            else:
-                print("❌ No multiple doses found in save data")
-                return False
-        else:
-            print("❌ Save was not called or no dose data received")
-            return False
-
-    except Exception as e:
-        print(f"❌ Error during test: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-    finally:
-        root.destroy()
-
-
-def main():
-    print("🔬 Multiple Dose Issue Investigation")
-    print("=" * 50)
-
-    os.chdir("/home/will/Code/thechart")
-
-    # Test 1: Parse function
-    parse_test = test_parse_dose_text()
-
-    # Test 2: UI workflow
-    ui_test = test_punch_button_accumulation()
-
-    print("\n📊 Results:")
-    print(f"  Parse function test: {'✅ PASS' if parse_test else '❌ FAIL'}")
-    print(f"  UI workflow test: {'✅ PASS' if ui_test else '❌ FAIL'}")
-
-    if parse_test and ui_test:
-        print("\n🎯 Multiple dose functionality appears to be working correctly")
-        print("If you're still experiencing issues, please describe the exact steps")
-    else:
-        print("\n🚨 Issues found with multiple dose functionality")
-
-
-if __name__ == "__main__":
-    main()

scripts/test_multiple_punch_save.py

@@ -1,141 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to verify multiple dose punching and saving behavior.
-"""
-
-import os
-import sys
-import tkinter as tk
-
-# Add the src directory to the path so we can import our modules
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from src.ui_manager import UIManager
-
-
-def test_multiple_punch_and_save():
-    """Test multiple dose punching followed by save."""
-    print("Testing multiple dose punching and save functionality...")
-
-    # Create a test Tkinter root
-    root = tk.Tk()
-    root.title("Test Root Window")
-    root.geometry("200x100")  # Small root window
-
-    # Create a logger
-    logger = logging.getLogger("test_logger")
-    logger.setLevel(logging.DEBUG)
-
-    # Create UIManager
-    ui_manager = UIManager(root, logger)
-
-    # Sample dose data for testing
-    sample_dose_data = {
-        "bupropion": "2025-01-15 08:00:00:300mg",
-        "hydroxyzine": "",
-        "gabapentin": "",
-        "propranolol": "",
-    }
-
-    # Sample values for the edit window (14 fields for new CSV format)
-    sample_values = (
-        "01/15/2025",  # date
-        5,  # depression
-        3,  # anxiety
-        7,  # sleep
-        6,  # appetite
-        1,  # bupropion
-        sample_dose_data["bupropion"],  # bupropion_doses
-        0,  # hydroxyzine
-        sample_dose_data["hydroxyzine"],  # hydroxyzine_doses
-        0,  # gabapentin
-        sample_dose_data["gabapentin"],  # gabapentin_doses
-        0,  # propranolol
-        sample_dose_data["propranolol"],  # propranolol_doses
-        "Test entry for multiple punch testing",  # note
-    )
-
-    # Track save calls
-    save_calls = []
-
-    # Define test callbacks
-    def test_save(*args):
-        save_calls.append(args)
-        print(f"✓ Save called with {len(args)} arguments")
-
-        # Print dose data specifically
-        if len(args) >= 12:  # Should have dose_data as last argument
-            dose_data = args[-1]  # Last argument should be dose_data
-            print("  Dose data received:")
-            for med, doses in dose_data.items():
-                print(f"    {med}: {doses}")
-
-        # Close window after save
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    def test_delete(*args):
-        print("Delete callback triggered")
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    callbacks = {
-        "save": test_save,
-        "delete": test_delete,
-    }
-
-    try:
-        # Create the edit window
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-        edit_window.geometry("600x400")  # Set a reasonable size
-        edit_window.lift()  # Bring to front
-        edit_window.focus_force()  # Force focus
-
-        print("✓ Edit window created")
-        print("✓ Now simulating multiple dose punches...")
-
-        # Let's simulate the manual process
-
-        print("\n=== Manual Test Instructions ===")
-        print("1. In the Bupropion field, enter '150mg' and click 'Take Bupropion'")
-        print("2. Enter '300mg' and click 'Take Bupropion' again")
-        print("3. You should see both doses in the text area")
-        print("4. Click 'Save' to persist the changes")
-        print("5. Check if both doses are saved to the CSV")
-        print("\nWindow will stay open for manual testing...")
-
-        # Wait for user to manually test
-        edit_window.wait_window()
-
-        # Check if save was called
-        if save_calls:
-            print("✓ Save was called successfully")
-            return True
-        else:
-            print("✗ Save was not called")
-            return False
-
-    except Exception as e:
-        print(f"✗ Error during test: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-
-    finally:
-        root.destroy()
-
-
-if __name__ == "__main__":
-    print("Testing Multiple Dose Punching and Save")
-    print("=" * 40)
-
-    success = test_multiple_punch_and_save()
-
-    if success:
-        print("\n✅ Multiple punch and save test completed!")
-    else:
-        print("\n❌ Multiple punch and save test failed!")
-        sys.exit(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_programmatic_punch.py

@@ -1,174 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test that programmatically clicks punch buttons to verify functionality.
-"""
-
-import os
-import sys
-import tkinter as tk
-from datetime import datetime
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from src.ui_manager import UIManager
-
-
-def test_programmatic_punch():
-    """Test punch buttons programmatically."""
-    print("🤖 Programmatic Punch Button Test")
-    print("=" * 40)
-
-    root = tk.Tk()
-    root.title("Auto Punch Test")
-    root.geometry("800x600")
-
-    logger = logging.getLogger("auto_punch")
-    ui_manager = UIManager(root, logger)
-
-    sample_values = (
-        "07/29/2025",
-        5,
-        3,
-        7,
-        6,
-        1,
-        "",
-        0,
-        "",
-        0,
-        "",
-        0,
-        "",
-        "Auto punch test",
-    )
-
-    save_called = False
-    saved_doses = None
-
-    def capture_save(*args):
-        nonlocal save_called, saved_doses
-        save_called = True
-        if len(args) >= 12:
-            saved_doses = args[-1]
-
-        print("💾 Save captured doses:")
-        for med, doses in saved_doses.items():
-            if doses:
-                count = len(doses.split("|")) if "|" in doses else 1
-                print(f"  {med}: {count} dose(s) - {doses}")
-            else:
-                print(f"  {med}: No doses")
-
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    callbacks = {"save": capture_save, "delete": lambda x: x.destroy()}
-
-    try:
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-
-        # Find the dose variables that were created
-        # We need to access them through the ui_manager somehow
-        print("🔍 Attempting to find dose widgets...")
-
-        # Let's manually trigger the punch button functionality
-        # by calling the _punch_dose_in_edit method directly
-
-        # Find the text widgets in the edit window
-        def find_widgets(widget, widget_list=None):
-            if widget_list is None:
-                widget_list = []
-
-            widget_list.append(widget)
-            for child in widget.winfo_children():
-                find_widgets(child, widget_list)
-
-            return widget_list
-
-        all_widgets = find_widgets(edit_window)
-
-        # Find Text widgets and Entry widgets
-        text_widgets = [w for w in all_widgets if isinstance(w, tk.Text)]
-        entry_widgets = [w for w in all_widgets if isinstance(w, tk.Entry)]
-
-        print(
-            f"Found {len(text_widgets)} Text widgets and "
-            f"{len(entry_widgets)} Entry widgets"
-        )
-
-        if len(text_widgets) >= 4:  # Should have 4 dose text widgets
-            # Let's manually add doses to the first text widget (bupropion)
-            bupropion_text = text_widgets[0]
-
-            print("📝 Manually adding doses to bupropion text widget...")
-
-            # Clear and add multiple doses
-            bupropion_text.delete(1.0, tk.END)
-            now = datetime.now()
-            time1 = now.strftime("%H:%M")
-            time2 = (now.replace(minute=now.minute + 1)).strftime("%H:%M")
-            time3 = (now.replace(minute=now.minute + 2)).strftime("%H:%M")
-
-            dose_content = f"{time1}: 100mg\n{time2}: 200mg\n{time3}: 300mg"
-            bupropion_text.insert(1.0, dose_content)
-
-            print(f"Added content: {dose_content}")
-
-            # Verify content was added
-            actual_content = bupropion_text.get(1.0, tk.END).strip()
-            print(f"Actual content in widget: '{actual_content}'")
-
-            # Now trigger save
-            print("🔄 Triggering save...")
-
-            # We need to find the save button
-            buttons = [w for w in all_widgets if isinstance(w, tk.ttk.Button)]
-            save_button = None
-
-            for button in buttons:
-                try:
-                    if "Save" in button.cget("text"):
-                        save_button = button
-                        break
-                except Exception:
-                    pass
-
-            if save_button:
-                print("💾 Found Save button, clicking it...")
-                save_button.invoke()
-            else:
-                print("❌ Could not find Save button")
-                edit_window.destroy()
-        else:
-            print("❌ Could not find expected Text widgets")
-            edit_window.destroy()
-
-        # Wait for save to complete
-        root.update()
-
-        if save_called:
-            return True
-        else:
-            print("❌ Save was not called")
-            return False
-
-    except Exception as e:
-        print(f"❌ Error: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-    finally:
-        root.destroy()
-
-
-if __name__ == "__main__":
-    os.chdir("/home/will/Code/thechart")
-    success = test_programmatic_punch()
-
-    if success:
-        print("\n✅ Programmatic test completed successfully!")
-    else:
-        print("\n❌ Programmatic test failed!")

scripts/test_punch_diagnosis.py

@@ -1,179 +0,0 @@
-#!/usr/bin/env python3
-"""
-Comprehensive test to diagnose and fix punch button accumulation issue.
-"""
-
-import os
-import sys
-import tkinter as tk
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from src.ui_manager import UIManager
-
-
-def test_punch_button_step_by_step():
-    """Test punch button functionality step by step with detailed logging."""
-    print("🔬 Punch Button Step-by-Step Diagnosis")
-    print("=" * 50)
-
-    root = tk.Tk()
-    root.title("Punch Button Diagnosis")
-    root.geometry("800x600")
-
-    logger = logging.getLogger("punch_diagnosis")
-    logger.setLevel(logging.DEBUG)
-
-    ui_manager = UIManager(root, logger)
-
-    sample_values = (
-        "07/29/2025",
-        5,
-        3,
-        7,
-        6,
-        1,
-        "",
-        0,
-        "",
-        0,
-        "",
-        0,
-        "",
-        "Punch diagnosis test",
-    )
-
-    punch_calls = []
-    save_calls = []
-
-    def track_save(*args):
-        save_calls.append(args)
-        if len(args) >= 12:
-            dose_data = args[-1]
-            print("\n💾 SAVE CAPTURED:")
-            for med, doses in dose_data.items():
-                if doses:
-                    count = len(doses.split("|")) if "|" in doses else 1
-                    print(f"  {med}: {count} dose(s) - {doses}")
-                else:
-                    print(f"  {med}: No doses")
-
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    callbacks = {"save": track_save, "delete": lambda x: x.destroy()}
-
-    try:
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-
-        # Let's manually patch the _punch_dose_in_edit method to add logging
-        original_punch = ui_manager._punch_dose_in_edit
-
-        def logged_punch(medicine_name, dose_vars):
-            print(f"\n🥊 PUNCH CALLED: {medicine_name}")
-
-            dose_entry_var = dose_vars.get(f"{medicine_name}_entry_var")
-            dose_text_widget = dose_vars.get(f"{medicine_name}_doses_text")
-
-            if not dose_entry_var or not dose_text_widget:
-                print(f"❌ Missing variables for {medicine_name}")
-                return
-
-            dose = dose_entry_var.get().strip()
-            print(f"📝 Dose entered: '{dose}'")
-
-            if not dose:
-                print("❌ No dose entered")
-                return
-
-            # Get current content BEFORE modification
-            before_content = dose_text_widget.get(1.0, tk.END).strip()
-            print(f"📋 Content BEFORE: '{before_content}'")
-
-            # Call original method
-            result = original_punch(medicine_name, dose_vars)
-
-            # Get content AFTER modification
-            after_content = dose_text_widget.get(1.0, tk.END).strip()
-            print(f"📋 Content AFTER: '{after_content}'")
-
-            punch_calls.append(
-                {
-                    "medicine": medicine_name,
-                    "dose": dose,
-                    "before": before_content,
-                    "after": after_content,
-                }
-            )
-
-            return result
-
-        # Patch the method
-        ui_manager._punch_dose_in_edit = logged_punch
-
-        print("\n📝 TEST INSTRUCTIONS:")
-        print("1. Enter '100mg' in Bupropion dose field")
-        print("2. Click 'Take Bupropion' - watch for PUNCH CALLED message")
-        print("3. Enter '200mg' in Bupropion dose field")
-        print("4. Click 'Take Bupropion' again - watch content changes")
-        print("5. Enter '300mg' in Bupropion dose field")
-        print("6. Click 'Take Bupropion' a third time")
-        print("7. Verify the text area shows all three doses")
-        print("8. Click Save")
-        print("\n⏳ Please perform the test sequence...")
-
-        edit_window.wait_window()
-
-        print("\n📊 ANALYSIS:")
-        print(f"  Punch calls made: {len(punch_calls)}")
-        print(f"  Save calls made: {len(save_calls)}")
-
-        if punch_calls:
-            print("\n🥊 PUNCH CALL DETAILS:")
-            for i, call in enumerate(punch_calls, 1):
-                print(f"  Call {i}: {call['medicine']} - {call['dose']}")
-                print(f"    Before: '{call['before']}'")
-                print(f"    After:  '{call['after']}'")
-                print()
-
-        # Check if multiple punches accumulated properly
-        if len(punch_calls) >= 2:
-            last_call = punch_calls[-1]
-            lines_in_final = (
-                last_call["after"].count("\n") + 1 if last_call["after"] else 0
-            )
-
-            print("🔍 ACCUMULATION CHECK:")
-            print(f"  Final content has {lines_in_final} lines")
-            print(f"  Expected: {len(punch_calls)} lines")
-
-            if lines_in_final >= len(punch_calls):
-                print("✅ Punch button accumulation appears to be working!")
-                return True
-            else:
-                print("❌ Punch button accumulation is NOT working correctly!")
-                return False
-        else:
-            print("⚠️  Not enough punch calls to test accumulation")
-            return False
-
-    except Exception as e:
-        print(f"❌ Error during test: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-    finally:
-        root.destroy()
-
-
-if __name__ == "__main__":
-    os.chdir("/home/will/Code/thechart")
-    success = test_punch_button_step_by_step()
-
-    if success:
-        print("\n🎯 Punch button test completed - accumulation working!")
-    else:
-        print("\n🚨 Punch button test revealed accumulation issues!")

scripts/test_punch_only.py

@@ -1,81 +0,0 @@
-#!/usr/bin/env python3
-"""
-Simple test to just verify punch button functionality works in isolation.
-"""
-
-import os
-import sys
-import tkinter as tk
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from src.ui_manager import UIManager
-
-
-def test_punch_button_only():
-    """Test just the punch button functionality."""
-    print("🎯 Testing Punch Button Functionality Only")
-    print("=" * 45)
-
-    root = tk.Tk()
-    root.title("Punch Button Test")
-    root.geometry("800x600")
-
-    logger = logging.getLogger("punch_test")
-    ui_manager = UIManager(root, logger)
-
-    # Simple test values
-    sample_values = (
-        "07/29/2025",
-        5,
-        3,
-        7,
-        6,
-        1,
-        "",
-        0,
-        "",
-        0,
-        "",
-        0,
-        "",
-        "Punch button test",
-    )
-
-    def simple_save(*args):
-        print("Save button clicked - closing window")
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    callbacks = {"save": simple_save, "delete": lambda x: x.destroy()}
-
-    try:
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-        edit_window.lift()
-        edit_window.focus_force()
-
-        print("\n🔨 SIMPLE TEST:")
-        print("1. Enter '100mg' in the Bupropion dose field")
-        print("2. Click 'Take Bupropion' button")
-        print("3. Look for DEBUG PUNCH messages in the console")
-        print("4. Check if the dose appears in the text area")
-        print("5. Click Save when done")
-        print("\n⏳ Performing test...")
-
-        edit_window.wait_window()
-        print("✅ Test completed")
-
-    except Exception as e:
-        print(f"❌ Error: {e}")
-        import traceback
-
-        traceback.print_exc()
-    finally:
-        root.destroy()
-
-
-if __name__ == "__main__":
-    os.chdir("/home/will/Code/thechart")
-    test_punch_button_only()

scripts/test_save_functionality.py

@@ -1,151 +0,0 @@
-#!/usr/bin/env python3
-"""
-Quick test to verify the save functionality works correctly.
-"""
-
-import os
-import sys
-import tkinter as tk
-
-# Add the src directory to the path so we can import our modules
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import logging
-
-from src.ui_manager import UIManager
-
-
-def test_save_functionality():
-    """Test that the save button works without errors."""
-    print("Testing save functionality in edit window...")
-
-    # Create a test Tkinter root
-    root = tk.Tk()
-    root.withdraw()  # Hide the main window
-
-    # Create a logger
-    logger = logging.getLogger("test_logger")
-    logger.setLevel(logging.DEBUG)
-
-    # Create UIManager
-    ui_manager = UIManager(root, logger)
-
-    # Sample dose data for testing
-    sample_dose_data = {
-        "bupropion": "2025-01-15 08:00:00:300mg|2025-01-15 20:00:00:150mg",
-        "hydroxyzine": "2025-01-15 22:00:00:25mg",
-        "gabapentin": "",
-        "propranolol": "2025-01-15 09:30:00:10mg",
-    }
-
-    # Sample values for the edit window (14 fields for new CSV format)
-    sample_values = (
-        "01/15/2025",  # date
-        5,  # depression
-        3,  # anxiety
-        7,  # sleep
-        6,  # appetite
-        1,  # bupropion
-        sample_dose_data["bupropion"],  # bupropion_doses
-        1,  # hydroxyzine
-        sample_dose_data["hydroxyzine"],  # hydroxyzine_doses
-        0,  # gabapentin
-        sample_dose_data["gabapentin"],  # gabapentin_doses
-        1,  # propranolol
-        sample_dose_data["propranolol"],  # propranolol_doses
-        "Test entry for save functionality",  # note
-    )
-
-    # Track if save was called successfully
-    save_called = False
-    save_args = None
-
-    # Define test callbacks
-    def test_save(*args):
-        nonlocal save_called, save_args
-        save_called = True
-        save_args = args
-        print("✓ Save callback executed successfully")
-        print(f"  Arguments received: {len(args)} args")
-        # Close the edit window after save
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    def test_delete(*args):
-        print("Delete callback triggered")
-        if args and hasattr(args[0], "destroy"):
-            args[0].destroy()
-
-    callbacks = {
-        "save": test_save,
-        "delete": test_delete,
-    }
-
-    try:
-        # Create the edit window
-        edit_window = ui_manager.create_edit_window(sample_values, callbacks)
-
-        print("✓ Edit window created successfully")
-        print("✓ Testing automatic save...")
-
-        # Simulate clicking save button by calling the save function directly
-        # First, we need to get the vars_dict from the window
-        # We'll trigger a save by simulating the button press
-
-        # Find the save button and trigger it
-        def find_save_button(widget):
-            """Recursively find the save button."""
-            if isinstance(widget, tk.Button) and widget.cget("text") == "Save":
-                return widget
-            for child in widget.winfo_children():
-                result = find_save_button(child)
-                if result:
-                    return result
-            return None
-
-        # Wait a moment for the window to fully initialize
-        edit_window.update_idletasks()
-
-        # Find and click the save button
-        save_button = find_save_button(edit_window)
-        if save_button:
-            print("✓ Found save button, triggering click...")
-            save_button.invoke()
-        else:
-            print("✗ Could not find save button")
-            edit_window.destroy()
-            return False
-
-        # Check if save was called
-        if save_called:
-            print("✓ Save functionality test PASSED")
-            print(
-                f"✓ Save was called with {len(save_args) if save_args else 0} arguments"
-            )
-            return True
-        else:
-            print("✗ Save functionality test FAILED - save was not called")
-            return False
-
-    except Exception as e:
-        print(f"✗ Error during save test: {e}")
-        import traceback
-
-        traceback.print_exc()
-        return False
-
-    finally:
-        root.destroy()
-
-
-if __name__ == "__main__":
-    print("Testing Save Functionality")
-    print("=" * 30)
-
-    success = test_save_functionality()
-
-    if success:
-        print("\n✅ Save functionality test completed successfully!")
-    else:
-        print("\n❌ Save functionality test failed!")
-        sys.exit(1)

scripts/test_scrollable_input.py

@@ -1,63 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to verify the scrollable input frame functionality.
-"""
-
-import os
-import sys
-import tkinter as tk
-from tkinter import ttk
-
-# Add src to path
-sys.path.append(os.path.join(os.path.dirname(__file__), "src"))
-
-
-def test_scrollable_input():
-    """Test the scrollable input frame."""
-    from src.init import logger
-    from src.ui_manager import UIManager
-
-    # Create a test window
-    root = tk.Tk()
-    root.title("Scrollable Input Frame Test")
-    root.geometry("400x600")  # Smaller window to test scrolling
-
-    # Create UI manager
-    ui_manager = UIManager(root, logger)
-
-    # Create main frame
-    main_frame = ttk.Frame(root, padding="10")
-    main_frame.grid(row=0, column=0, sticky="nsew")
-    root.grid_rowconfigure(0, weight=1)
-    root.grid_columnconfigure(0, weight=1)
-    main_frame.grid_rowconfigure(1, weight=1)
-    main_frame.grid_columnconfigure(0, weight=1)
-
-    # Create the scrollable input frame
-    _input_ui = ui_manager.create_input_frame(main_frame)
-
-    # Add instructions
-    instructions = ttk.Label(
-        root,
-        text="Test the scrolling functionality:\n"
-        "1. Try mouse wheel scrolling over the input area\n"
-        "2. Use the scrollbar on the right\n"
-        "3. Test dose tracking buttons\n"
-        "4. Resize the window to test responsiveness",
-        justify="left",
-    )
-    instructions.grid(row=1, column=0, padx=10, pady=10, sticky="ew")
-
-    # Print success message
-    print("✓ Scrollable input frame created successfully!")
-    print("✓ Medicine dose tracking UI elements loaded")
-    print("✓ Scrollbar functionality active")
-    print("✓ Mouse wheel scrolling enabled")
-    print("\nTest window opened. Close the window when done testing.")
-
-    # Start the test GUI
-    root.mainloop()
-
-
-if __name__ == "__main__":
-    test_scrollable_input()

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

@@ -4,70 +4,129 @@ import os
 
 import pandas as pd
 
+from medicine_manager import MedicineManager
+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, filename: str, logger: logging.Logger) -> None:
+    def __init__(
+        self,
+        filename: str,
+        logger: logging.Logger,
+        medicine_manager: MedicineManager,
+        pathology_manager: PathologyManager,
+    ) -> None:
         self.filename: str = filename
         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) -> tuple[str, ...]:
+        """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"]
+
+        # Add pathology headers
+        for pathology_key in self.pathology_manager.get_pathology_keys():
+            headers.append(pathology_key)
+
+        # Add medicine headers
+        for medicine_key in self.medicine_manager.get_medicine_keys():
+            headers.extend([medicine_key, f"{medicine_key}_doses"])
+
+        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."""
-        if not os.path.exists(self.filename):
+        """Create CSV file with headers if it doesn't exist or is empty."""
+        if not os.path.exists(self.filename) or os.path.getsize(self.filename) == 0:
             with open(self.filename, mode="w", newline="") as file:
                 writer = csv.writer(file)
-                writer.writerow(
-                    [
-                        "date",
-                        "depression",
-                        "anxiety",
-                        "sleep",
-                        "appetite",
-                        "bupropion",
-                        "bupropion_doses",
-                        "hydroxyzine",
-                        "hydroxyzine_doses",
-                        "gabapentin",
-                        "gabapentin_doses",
-                        "propranolol",
-                        "propranolol_doses",
-                        "quetiapine",
-                        "quetiapine_doses",
-                        "note",
-                    ]
-                )
+                writer.writerow(self._get_csv_headers())
+
+    def _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:
+            # Use pre-built dtype dictionary for faster parsing
+            dtype_dict = self._get_dtype_dict()
+
+            # Read with optimized settings
             df: pd.DataFrame = pd.read_csv(
                 self.filename,
-                dtype={
-                    "depression": int,
-                    "anxiety": int,
-                    "sleep": int,
-                    "appetite": int,
-                    "bupropion": int,
-                    "bupropion_doses": str,
-                    "hydroxyzine": int,
-                    "hydroxyzine_doses": str,
-                    "gabapentin": int,
-                    "gabapentin_doses": str,
-                    "propranolol": int,
-                    "propranolol_doses": str,
-                    "quetiapine": int,
-                    "quetiapine_doses": str,
-                    "note": str,
-                    "date": str,
-                },
-            ).fillna("")
-            return df.sort_values(by="date").reset_index(drop=True)
+                dtype=dtype_dict,
+                na_filter=False,  # Don't convert to NaN, keep as empty strings
+                engine="c",  # Use faster C engine
+            )
+
+            # Sort only if needed (check if already sorted)
+            if len(df) > 1 and not df["date"].is_monotonic_increasing:
+                df = df.sort_values(by="date").reset_index(drop=True)
+
+            # Cache the data and timestamp
+            self._data_cache = df.copy()
+            self._cache_timestamp = os.path.getmtime(self.filename)
+
+            return df.copy()
+
         except pd.errors.EmptyDataError:
             self.logger.warning("CSV file is empty. No data to load.")
             return pd.DataFrame()
@@ -76,190 +135,140 @@ 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
-            df: pd.DataFrame = self.load_data()
+            # Quick duplicate check using cached data if available
             date_to_add: str = str(entry_data[0])
 
-            if not df.empty and date_to_add in df["date"].values:
-                self.logger.warning(f"Entry with date {date_to_add} already exists.")
-                return False
+            if self._data_cache is not None:
+                # Use cached data for duplicate check
+                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
-            if original_date != new_date and new_date in df["date"].values:
+            # Optimized duplicate check
+            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
 
-            # Find the row to update using original_date as a unique identifier
-            # Handle both old format (10 columns) and new format (16 columns)
-            if len(values) == 16:
-                # New format with all dose columns including quetiapine
-                df.loc[
-                    df["date"] == original_date,
-                    [
-                        "date",
-                        "depression",
-                        "anxiety",
-                        "sleep",
-                        "appetite",
-                        "bupropion",
-                        "bupropion_doses",
-                        "hydroxyzine",
-                        "hydroxyzine_doses",
-                        "gabapentin",
-                        "gabapentin_doses",
-                        "propranolol",
-                        "propranolol_doses",
-                        "quetiapine",
-                        "quetiapine_doses",
-                        "note",
-                    ],
-                ] = values
-            elif len(values) == 14:
-                # Format without quetiapine
-                df.loc[
-                    df["date"] == original_date,
-                    [
-                        "date",
-                        "depression",
-                        "anxiety",
-                        "sleep",
-                        "appetite",
-                        "bupropion",
-                        "bupropion_doses",
-                        "hydroxyzine",
-                        "hydroxyzine_doses",
-                        "gabapentin",
-                        "gabapentin_doses",
-                        "propranolol",
-                        "propranolol_doses",
-                        "note",
-                    ],
-                ] = values
-            else:
-                # Old format - only update the user-editable columns
-                df.loc[
-                    df["date"] == original_date,
-                    [
-                        "date",
-                        "depression",
-                        "anxiety",
-                        "sleep",
-                        "appetite",
-                        "bupropion",
-                        "hydroxyzine",
-                        "gabapentin",
-                        "propranolol",
-                        "note",
-                    ],
-                ] = values
-            df.to_csv(self.filename, index=False)
-            return True
         except Exception as e:
             self.logger.error(f"Error updating entry: {str(e)}")
             return False
 
     def delete_entry(self, date: str) -> bool:
-        """Delete an entry identified by date."""
+        """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)}")
             return False
 
-    def add_medicine_dose(self, date: str, medicine_name: str, dose: str) -> bool:
-        """Add a medicine dose to today's entry."""
-        from datetime import datetime
-
-        try:
-            df: pd.DataFrame = self.load_data()
-            timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-            dose_entry = f"{timestamp}:{dose}"
-
-            # Find or create entry for the given date
-            if df.empty or date not in df["date"].values:
-                # Create new entry for today with default values
-                new_entry = {
-                    "date": date,
-                    "depression": 0,
-                    "anxiety": 0,
-                    "sleep": 0,
-                    "appetite": 0,
-                    "bupropion": 0,
-                    "bupropion_doses": "",
-                    "hydroxyzine": 0,
-                    "hydroxyzine_doses": "",
-                    "gabapentin": 0,
-                    "gabapentin_doses": "",
-                    "propranolol": 0,
-                    "propranolol_doses": "",
-                    "quetiapine": 0,
-                    "quetiapine_doses": "",
-                    "note": "",
-                }
-                df = pd.concat([df, pd.DataFrame([new_entry])], ignore_index=True)
-
-            # Add dose to the appropriate medicine
-            dose_column = f"{medicine_name}_doses"
-            mask = df["date"] == date
-            current_doses = df.loc[mask, dose_column].iloc[0]
-
-            if current_doses:
-                df.loc[mask, dose_column] = current_doses + "|" + dose_entry
-            else:
-                df.loc[mask, dose_column] = dose_entry
-
-            # Mark medicine as taken (set to 1)
-            df.loc[mask, medicine_name] = 1
-
-            df.to_csv(self.filename, index=False)
-            return True
-        except Exception as e:
-            self.logger.error(f"Error adding medicine dose: {str(e)}")
-            return False
-
     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)
-                    doses.append((timestamp, dose))
+                    parts = dose_entry.split(":", 1)
+                    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

@@ -7,202 +7,286 @@ import pandas as pd
 from matplotlib.axes import Axes
 from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
 
+from medicine_manager import MedicineManager
+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, parent_frame: ttk.LabelFrame) -> None:
+    def __init__(
+        self,
+        parent_frame: ttk.LabelFrame,
+        medicine_manager: MedicineManager,
+        pathology_manager: PathologyManager,
+    ) -> None:
         self.parent_frame: ttk.LabelFrame = parent_frame
+        self.medicine_manager = medicine_manager
+        self.pathology_manager = pathology_manager
 
-        # Configure graph frame to expand
-        self.parent_frame.grid_rowconfigure(0, weight=1)
-        self.parent_frame.grid_columnconfigure(0, weight=1)
+        # Initialize matplotlib with optimized settings
+        self.fig: matplotlib.figure.Figure = plt.figure(figsize=(10, 6), dpi=80)
+        self.ax: Axes = self.fig.add_subplot(111)
 
-        # Initialize toggle variables for chart elements
-        self.toggle_vars: dict[str, tk.BooleanVar] = {
-            "depression": tk.BooleanVar(value=True),
-            "anxiety": tk.BooleanVar(value=True),
-            "sleep": tk.BooleanVar(value=True),
-            "appetite": tk.BooleanVar(value=True),
-            "bupropion": tk.BooleanVar(value=True),  # Show by default (most used)
-            "hydroxyzine": tk.BooleanVar(value=False),
-            "gabapentin": tk.BooleanVar(value=False),
-            "propranolol": tk.BooleanVar(value=True),  # Show by default (commonly used)
-            "quetiapine": tk.BooleanVar(value=False),
-        }
+        # Cache for current data to avoid reprocessing
+        self.current_data: pd.DataFrame = pd.DataFrame()
+        self._last_plot_hash: str = ""
 
-        # 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
+        # Initialize UI components
+        self.toggle_vars: dict[str, tk.IntVar] = {}
+        self._setup_ui()
+        self._initialize_toggle_vars()
         self._create_chart_toggles()
 
-        # Create graph frame
-        self.graph_frame: ttk.Frame = ttk.Frame(self.parent_frame)
-        self.graph_frame.grid(row=1, column=0, sticky="nsew", padx=5, pady=5)
+    def _initialize_toggle_vars(self) -> None:
+        """Initialize toggle variables for chart elements with optimization."""
+        # 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
-        self.parent_frame.grid_rowconfigure(1, weight=1)
-        self.parent_frame.grid_columnconfigure(0, weight=1)
+        # Initialize medicine toggles (unchecked by default)
+        for medicine_key in self.medicine_manager.get_medicine_keys():
+            self.toggle_vars[medicine_key] = tk.IntVar(value=0)
 
-        # Initialize matplotlib figure and canvas
-        self.fig: matplotlib.figure.Figure
-        self.ax: Axes
-        self.fig, self.ax = plt.subplots()
-        self.canvas: FigureCanvasTkAgg = FigureCanvasTkAgg(
-            figure=self.fig, master=self.graph_frame
-        )
-        self.canvas.get_tk_widget().pack(fill="both", expand=True)
+    def _setup_ui(self) -> None:
+        """Set up the UI components with performance optimizations."""
+        # Create canvas with optimized settings
+        self.canvas = FigureCanvasTkAgg(self.fig, master=self.parent_frame)
+        self.canvas.draw_idle()  # Use draw_idle for better performance
 
-        # Store current data for replotting
-        self.current_data: pd.DataFrame = pd.DataFrame()
+        # Pack canvas
+        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."""
-        ttk.Label(self.control_frame, text="Show/Hide Elements:").pack(
-            side="left", padx=5
+        """Create toggle controls for chart elements with improved layout."""
+        # Pathology toggles
+        pathology_frame = ttk.LabelFrame(
+            self.control_frame, text="Pathologies", padding="5"
         )
+        pathology_frame.pack(side=tk.LEFT, fill=tk.X, expand=True, padx=2)
 
-        # Symptoms toggles
-        symptoms_frame = ttk.LabelFrame(self.control_frame, text="Symptoms")
-        symptoms_frame.pack(side="left", padx=5, pady=2)
+        # Use grid for better layout
+        row, col = 0, 0
+        for pathology_key in self.pathology_manager.get_pathology_keys():
+            pathology = self.pathology_manager.get_pathology(pathology_key)
+            if pathology:
+                display_name = pathology.display_name
+                text = (
+                    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,
+                )
+                cb.grid(row=row, column=col, sticky="w", padx=2)
+                col += 1
+                if col > 1:  # 2 columns max
+                    col = 0
+                    row += 1
 
-        symptom_configs = [
-            ("depression", "Depression"),
-            ("anxiety", "Anxiety"),
-            ("sleep", "Sleep"),
-            ("appetite", "Appetite"),
-        ]
+        # Medicine toggles
+        medicine_frame = ttk.LabelFrame(
+            self.control_frame, text="Medicines", padding="5"
+        )
+        medicine_frame.pack(side=tk.RIGHT, fill=tk.X, expand=True, padx=2)
 
-        for key, label in symptom_configs:
-            checkbox = ttk.Checkbutton(
-                symptoms_frame,
-                text=label,
-                variable=self.toggle_vars[key],
-                command=self._handle_toggle_changed,
-            )
-            checkbox.pack(side="left", padx=3)
-
-        # Medicines toggles
-        medicines_frame = ttk.LabelFrame(self.control_frame, text="Medicines")
-        medicines_frame.pack(side="left", padx=5, pady=2)
-
-        medicine_configs = [
-            ("bupropion", "Bupropion"),
-            ("hydroxyzine", "Hydroxyzine"),
-            ("gabapentin", "Gabapentin"),
-            ("propranolol", "Propranolol"),
-            ("quetiapine", "Quetiapine"),
-        ]
-
-        for key, label in medicine_configs:
-            checkbox = ttk.Checkbutton(
-                medicines_frame,
-                text=label,
-                variable=self.toggle_vars[key],
-                command=self._handle_toggle_changed,
-            )
-            checkbox.pack(side="left", padx=3)
+        # 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:
+                med_name = medicine.display_name
+                text = med_name[:10] + "..." if len(med_name) > 10 else med_name
+                cb = ttk.Checkbutton(
+                    medicine_frame,
+                    text=text,
+                    variable=self.toggle_vars[medicine_key],
+                    command=self._handle_toggle_changed,
+                )
+                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."""
-        self.current_data = df.copy() if not df.empty else pd.DataFrame()
-        self._plot_graph_data(df)
+        """Update the graph with new data using optimization checks."""
+        # Create hash of data to avoid unnecessary redraws
+        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."""
-        self.ax.clear()
-        if not df.empty:
-            # Convert dates and sort
-            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)
+        """Plot the graph data with current toggle settings using optimizations."""
+        # Use batch updates to reduce redraws
+        with plt.ioff():  # Turn off interactive mode for batch updates
+            self.ax.clear()
 
-            # Track if any series are plotted
-            has_plotted_series = False
+            if not df.empty:
+                # Optimize data processing
+                df_processed = self._preprocess_data(df)
 
-            # Plot data series based on toggle states
-            if self.toggle_vars["depression"].get():
-                self._plot_series(
-                    df, "depression", "Depression (0:good, 10:bad)", "o", "-"
-                )
-                has_plotted_series = True
-            if self.toggle_vars["anxiety"].get():
-                self._plot_series(df, "anxiety", "Anxiety (0:good, 10:bad)", "o", "-")
-                has_plotted_series = True
-            if self.toggle_vars["sleep"].get():
-                self._plot_series(df, "sleep", "Sleep (0:bad, 10:good)", "o", "dashed")
-                has_plotted_series = True
-            if self.toggle_vars["appetite"].get():
-                self._plot_series(
-                    df, "appetite", "Appetite (0:bad, 10:good)", "o", "dashed"
+                # Track if any series are plotted
+                has_plotted_series = self._plot_pathology_data(df_processed)
+                medicine_data = self._plot_medicine_data(df_processed)
+
+                if has_plotted_series or medicine_data["has_plotted"]:
+                    self._configure_graph_appearance(medicine_data)
+
+        # Single draw call at the end
+        self.canvas.draw_idle()
+
+    def _preprocess_data(self, df: pd.DataFrame) -> pd.DataFrame:
+        """Preprocess data for plotting with optimizations."""
+        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
+
+    def _plot_pathology_data(self, df: pd.DataFrame) -> bool:
+        """Plot pathology data series with optimizations."""
+        has_plotted_series = False
+
+        # Batch plot pathology data
+        pathology_keys = self.pathology_manager.get_pathology_keys()
+        active_pathologies = [
+            key
+            for key in pathology_keys
+            if self.toggle_vars[key].get() and key in df.columns
+        ]
+
+        for pathology_key in active_pathologies:
+            pathology = self.pathology_manager.get_pathology(pathology_key)
+            if pathology:
+                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
-            medicine_colors = {
-                "bupropion": "#FF6B6B",  # Red
-                "hydroxyzine": "#4ECDC4",  # Teal
-                "gabapentin": "#45B7D1",  # Blue
-                "propranolol": "#96CEB4",  # Green
-                "quetiapine": "#FFEAA7",  # Yellow
-            }
+        return has_plotted_series
 
-            medicines = [
-                "bupropion",
-                "hydroxyzine",
-                "gabapentin",
-                "propranolol",
-                "quetiapine",
-            ]
+    def _plot_medicine_data(self, df: pd.DataFrame) -> dict:
+        """Plot medicine data with optimizations."""
+        result = {"has_plotted": False, "with_data": [], "without_data": []}
 
-            for medicine in medicines:
-                dose_column = f"{medicine}_doses"
-                if self.toggle_vars[medicine].get() and dose_column in df.columns:
-                    # 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)
+        # Get medicine colors and keys in batch
+        medicine_colors = self.medicine_manager.get_graph_colors()
+        medicines = self.medicine_manager.get_medicine_keys()
 
-                    # Only plot if there are non-zero doses
-                    if any(dose > 0 for dose in daily_doses):
-                        # Scale doses for better visibility
-                        # (divide by 10 to fit with 0-10 scale)
-                        scaled_doses = [dose / 10 for dose in daily_doses]
+        # 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,
                             alpha=0.6,
                             color=medicine_colors.get(medicine, "#DDA0DD"),
-                            label=f"{medicine.capitalize()} (mg/10)",
+                            label=label,
                             width=0.6,
                             bottom=-max(scaled_doses) * 1.1 if scaled_doses else -1,
                         )
-                        has_plotted_series = True
+                        result["has_plotted"] = True
+                else:
+                    # Medicine is toggled on but has no dose data
+                    if self.toggle_vars[medicine].get():
+                        result["without_data"].append(medicine)
 
-            # Configure graph appearance
-            if has_plotted_series:
-                self.ax.legend()
-            self.ax.set_title("Medication Effects Over Time")
-            self.ax.set_xlabel("Date")
-            self.ax.set_ylabel("Rating (0-10) / Dose (mg)")
+        return result
 
-            # Adjust y-axis to accommodate medicine bars at bottom
-            current_ylim = self.ax.get_ylim()
-            self.ax.set_ylim(bottom=current_ylim[0], top=max(10, current_ylim[1]))
+    def _configure_graph_appearance(self, medicine_data: dict) -> None:
+        """Configure graph appearance with optimizations."""
+        # Get legend data in batch
+        handles, labels = self.ax.get_legend_handles_labels()
 
-            self.fig.autofmt_xdate()
+        # Add information about medicines without data if any are toggled on
+        if medicine_data["without_data"]:
+            med_list = ", ".join(medicine_data["without_data"])
+            info_text = f"Tracked (no doses): {med_list}"
+            labels.append(info_text)
 
-        # Redraw the canvas
-        self.canvas.draw()
+            # Create dummy handle more efficiently
+            from matplotlib.patches import Rectangle
+
+            dummy_handle = Rectangle(
+                (0, 0), 1, 1, fc="w", fill=False, edgecolor="none", linewidth=0
+            )
+            handles.append(dummy_handle)
+
+        # 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,
+            )
+
+        # Set titles and labels
+        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,
@@ -212,25 +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:
@@ -239,19 +326,15 @@ class GraphManager:
                 continue
 
             try:
-                if ":" in entry:
-                    # Extract dose part after the timestamp
-                    _, dose_part = entry.split(":", 1)
-                else:
-                    # Handle cases where there's no timestamp
-                    dose_part = entry
+                # 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:
@@ -262,5 +345,10 @@ class GraphManager:
         return total_dose
 
     def close(self) -> None:
-        """Clean up resources."""
-        plt.close(self.fig)
+        """Clean up resources with proper optimization."""
+        try:
+            # Clear the plot before closing
+            self.ax.clear()
+            plt.close(self.fig)
+        except Exception:
+            pass  # Ignore cleanup errors

src/main.py

@@ -2,15 +2,21 @@ import os
 import sys
 import tkinter as tk
 from collections.abc import Callable
-from tkinter import messagebox
+from tkinter import messagebox, ttk
 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
+from medicine_manager import MedicineManager
+from pathology_management_window import PathologyManagementWindow
+from pathology_manager import PathologyManager
 from ui_manager import UIManager
 
 
@@ -36,14 +42,23 @@ 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
-        self.ui_manager: UIManager = UIManager(root, logger)
-        self.data_manager: DataManager = DataManager(self.filename, logger)
+        self.medicine_manager: MedicineManager = MedicineManager(logger=logger)
+        self.pathology_manager: PathologyManager = PathologyManager(logger=logger)
+        self.ui_manager: UIManager = UIManager(
+            root, logger, self.medicine_manager, self.pathology_manager
+        )
+        self.data_manager: DataManager = DataManager(
+            self.filename, logger, self.medicine_manager, self.pathology_manager
+        )
 
         # Set up application icon
         icon_path: str = "chart-671.png"
@@ -54,6 +69,32 @@ class MedTrackerApp:
         # Set up the main application UI
         self._setup_main_ui()
 
+        # 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
@@ -74,12 +115,23 @@ class MedTrackerApp:
 
         # --- Create Graph Frame ---
         graph_frame: ttk.Frame = self.ui_manager.create_graph_frame(main_frame)
-        self.graph_manager: GraphManager = GraphManager(graph_frame)
+        self.graph_manager: GraphManager = GraphManager(
+            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"]
-        self.symptom_vars: dict[str, tk.IntVar] = input_ui["symptom_vars"]
+        self.pathology_vars: dict[str, tk.IntVar] = input_ui["pathology_vars"]
         self.medicine_vars: dict[str, tuple[tk.IntVar, str]] = input_ui["medicine_vars"]
         self.note_var: tk.StringVar = input_ui["note_var"]
         self.date_var: tk.StringVar = input_ui["date_var"]
@@ -106,6 +158,86 @@ class MedTrackerApp:
         # Load data
         self.refresh_data_display()
 
+    def _setup_menu(self) -> None:
+        """Set up the menu bar."""
+        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)
+        tools_menu.add_command(
+            label="Manage Pathologies...", command=self._open_pathology_manager
+        )
+        tools_menu.add_command(
+            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(
+            self.root, self.pathology_manager, self._refresh_ui_after_config_change
+        )
+
+    def _open_medicine_manager(self) -> None:
+        """Open the medicine management window."""
+        MedicineManagementWindow(
+            self.root, self.medicine_manager, self._refresh_ui_after_config_change
+        )
+
+    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(
+            self.input_frame.master
+        )
+        self.input_frame: ttk.Frame = input_ui["frame"]
+        self.pathology_vars: dict[str, tk.IntVar] = input_ui["pathology_vars"]
+        self.medicine_vars: dict[str, tuple[tk.IntVar, str]] = input_ui["medicine_vars"]
+
+        # Add buttons to input frame
+        self.ui_manager.add_action_buttons(
+            self.input_frame,
+            [
+                {
+                    "text": "Add Entry",
+                    "command": self.add_new_entry,
+                    "fill": "both",
+                    "expand": True,
+                },
+                {"text": "Quit", "command": self.handle_window_closing},
+            ],
+        )
+
+        # Recreate the table with new columns
+        self.tree.destroy()
+        table_ui: dict[str, Any] = self.ui_manager.create_table_frame(
+            self.tree.master.master
+        )
+        self.tree: ttk.Treeview = table_ui["tree"]
+        self.tree.bind("<Double-1>", self.handle_double_click)
+
+        # Refresh data display
+        self.refresh_data_display()
+
     def handle_double_click(self, event: tk.Event) -> None:
         """Handle double-click event to edit an entry."""
         logger.debug("Double-click event triggered on treeview.")
@@ -124,24 +256,25 @@ class MedTrackerApp:
         if not df.empty and original_date in df["date"].values:
             full_row = df[df["date"] == original_date].iloc[0]
             # Convert to tuple in the expected order for the edit window
-            full_values = (
-                full_row["date"],
-                full_row["depression"],
-                full_row["anxiety"],
-                full_row["sleep"],
-                full_row["appetite"],
-                full_row["bupropion"],
-                full_row["bupropion_doses"],
-                full_row["hydroxyzine"],
-                full_row["hydroxyzine_doses"],
-                full_row["gabapentin"],
-                full_row["gabapentin_doses"],
-                full_row["propranolol"],
-                full_row["propranolol_doses"],
-                full_row["quetiapine"],
-                full_row["quetiapine_doses"],
-                full_row["note"],
-            )
+            full_values = [full_row["date"]]
+
+            # Add pathology data dynamically
+            for pathology_key in self.pathology_manager.get_pathology_keys():
+                if pathology_key in full_row:
+                    full_values.append(full_row[pathology_key])
+                else:
+                    full_values.append(0)
+
+            # Add medicine data dynamically
+            for medicine_key in self.medicine_manager.get_medicine_keys():
+                if medicine_key in full_row:
+                    full_values.append(full_row[medicine_key])
+                    full_values.append(full_row.get(f"{medicine_key}_doses", ""))
+                else:
+                    full_values.extend([0, ""])
+
+            full_values.append(full_row["note"])
+            full_values = tuple(full_values)
         else:
             # Fallback to the table values if full data not found
             full_values = values
@@ -159,38 +292,60 @@ class MedTrackerApp:
         self,
         edit_win: tk.Toplevel,
         original_date: str,
-        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],
+        *args,
     ) -> None:
-        """Save the edited data to the CSV file."""
-        values: list[str | int] = [
-            date,
-            dep,
-            anx,
-            slp,
-            app,
-            bup,
-            dose_data.get("bupropion", ""),
-            hydro,
-            dose_data.get("hydroxyzine", ""),
-            gaba,
-            dose_data.get("gabapentin", ""),
-            prop,
-            dose_data.get("propranolol", ""),
-            quet,
-            dose_data.get("quetiapine", ""),
-            note,
-        ]
+        """Save edited data to CSV file with dynamic pathology/medicine support."""
+        # Parse dynamic arguments
+        # Format: date, pathology1, pathology2, ..., medicine1, medicine2,
+        # ..., note, dose_data
+
+        if len(args) < 2:  # At minimum need date and note
+            messagebox.showerror("Error", "Invalid save data format", parent=edit_win)
+            return
+
+        # Extract arguments
+        date = args[0]
+
+        # Get pathology count to extract values
+        pathology_keys = self.pathology_manager.get_pathology_keys()
+        medicine_keys = self.medicine_manager.get_medicine_keys()
+
+        # Expected format: date, pathology_values..., medicine_values...,
+        # note, dose_data
+        expected_pathology_count = len(pathology_keys)
+        expected_medicine_count = len(medicine_keys)
+
+        # Extract pathology values
+        pathology_values = []
+        for i in range(expected_pathology_count):
+            if i + 1 < len(args):
+                pathology_values.append(args[i + 1])
+            else:
+                pathology_values.append(0)
+
+        # Extract medicine values
+        medicine_values = []
+        medicine_start_idx = 1 + expected_pathology_count
+        for i in range(expected_medicine_count):
+            if medicine_start_idx + i < len(args):
+                medicine_values.append(args[medicine_start_idx + i])
+            else:
+                medicine_values.append(0)
+
+        # Extract note and dose data (last two arguments)
+        note = args[-2] if len(args) >= 2 else ""
+        dose_data = args[-1] if len(args) >= 1 else {}
+
+        # Build the values list for data manager
+        values = [date]
+        values.extend(pathology_values)
+
+        # Add medicine data dynamically
+        for i, medicine_key in enumerate(medicine_keys):
+            values.append(medicine_values[i] if i < len(medicine_values) else 0)
+            values.append(dose_data.get(medicine_key, ""))
+
+        values.append(note)
 
         if self.data_manager.update_entry(original_date, values):
             edit_win.destroy()
@@ -223,49 +378,33 @@ class MedTrackerApp:
         """Add a new entry to the CSV file."""
         # Get current doses for today
         today = self.date_var.get()
-        bupropion_doses = ""
-        hydroxyzine_doses = ""
-        gabapentin_doses = ""
-        propranolol_doses = ""
-        quetiapine_doses = ""
+        dose_values = {}
 
         if today:
-            bup_doses = self.data_manager.get_today_medicine_doses(today, "bupropion")
-            hydroxyzine_doses_list = self.data_manager.get_today_medicine_doses(
-                today, "hydroxyzine"
-            )
-            gaba_doses = self.data_manager.get_today_medicine_doses(today, "gabapentin")
-            prop_doses = self.data_manager.get_today_medicine_doses(
-                today, "propranolol"
-            )
-            quet_doses = self.data_manager.get_today_medicine_doses(today, "quetiapine")
+            # Get doses for all medicines dynamically
+            for medicine_key in self.medicine_manager.get_medicine_keys():
+                doses = self.data_manager.get_today_medicine_doses(today, medicine_key)
+                dose_values[f"{medicine_key}_doses"] = "|".join(
+                    [f"{ts}:{dose}" for ts, dose in doses]
+                )
+        else:
+            # Set empty doses for all medicines
+            for medicine_key in self.medicine_manager.get_medicine_keys():
+                dose_values[f"{medicine_key}_doses"] = ""
 
-            bupropion_doses = "|".join([f"{ts}:{dose}" for ts, dose in bup_doses])
-            hydroxyzine_doses = "|".join(
-                [f"{ts}:{dose}" for ts, dose in hydroxyzine_doses_list]
-            )
-            gabapentin_doses = "|".join([f"{ts}:{dose}" for ts, dose in gaba_doses])
-            propranolol_doses = "|".join([f"{ts}:{dose}" for ts, dose in prop_doses])
-            quetiapine_doses = "|".join([f"{ts}:{dose}" for ts, dose in quet_doses])
+        # Build entry dynamically
+        entry: list[str | int] = [self.date_var.get()]
 
-        entry: list[str | int] = [
-            self.date_var.get(),
-            self.symptom_vars["depression"].get(),
-            self.symptom_vars["anxiety"].get(),
-            self.symptom_vars["sleep"].get(),
-            self.symptom_vars["appetite"].get(),
-            self.medicine_vars["bupropion"][0].get(),
-            bupropion_doses,
-            self.medicine_vars["hydroxyzine"][0].get(),
-            hydroxyzine_doses,
-            self.medicine_vars["gabapentin"][0].get(),
-            gabapentin_doses,
-            self.medicine_vars["propranolol"][0].get(),
-            propranolol_doses,
-            self.medicine_vars["quetiapine"][0].get(),
-            quetiapine_doses,
-            self.note_var.get(),
-        ]
+        # Add pathology data dynamically
+        for pathology_key in self.pathology_manager.get_pathology_keys():
+            entry.append(self.pathology_vars[pathology_key].get())
+
+        # Add medicine data
+        for medicine_key in self.medicine_manager.get_medicine_keys():
+            entry.append(self.medicine_vars[medicine_key][0].get())
+            entry.append(dose_values[f"{medicine_key}_doses"])
+
+        entry.append(self.note_var.get())
         logger.debug(f"Adding entry: {entry}")
 
         # Check if date is empty
@@ -317,8 +456,8 @@ class MedTrackerApp:
         """Clear all input fields."""
         logger.debug("Clearing input fields.")
         self.date_var.set("")
-        for key in self.symptom_vars:
-            self.symptom_vars[key].set(0)
+        for key in self.pathology_vars:
+            self.pathology_vars[key].set(0)
         for key in self.medicine_vars:
             self.medicine_vars[key][0].set(0)
         self.note_var.set("")
@@ -327,37 +466,37 @@ 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
-        for i in self.tree.get_children():
-            self.tree.delete(i)
+        # Clear existing data in the treeview efficiently
+        children = self.tree.get_children()
+        if children:
+            self.tree.delete(*children)
 
         # Load data from the CSV file
         df: pd.DataFrame = self.data_manager.load_data()
 
         # Update the treeview with the data
         if not df.empty:
-            # Only show user-friendly columns in the table (not the dose columns)
-            display_columns = [
-                "date",
-                "depression",
-                "anxiety",
-                "sleep",
-                "appetite",
-                "bupropion",
-                "hydroxyzine",
-                "gabapentin",
-                "propranolol",
-                "quetiapine",
-                "note",
-            ]
+            # Build display columns dynamically (exclude dose columns for table view)
+            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():
+                display_columns.append(medicine_key)
+
+            display_columns.append("note")
 
             # Filter to only the columns we want to display
             if all(col in df.columns for col in display_columns):
                 display_df = df[display_columns]
             else:
-                # Fallback for old CSV format - just use all columns
+                # 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/medicine_management_window.py

@@ -0,0 +1,401 @@
+"""
+Medicine management window for adding, editing, and removing medicines.
+"""
+
+import tkinter as tk
+from tkinter import messagebox, ttk
+
+from medicine_manager import Medicine, MedicineManager
+
+
+class MedicineManagementWindow:
+    """Window for managing medicine configurations."""
+
+    def __init__(
+        self, parent: tk.Tk, medicine_manager: MedicineManager, refresh_callback
+    ):
+        self.parent = parent
+        self.medicine_manager = medicine_manager
+        self.refresh_callback = refresh_callback
+
+        # Create the window
+        self.window = tk.Toplevel(parent)
+        self.window.title("Manage Medicines")
+        self.window.geometry("600x500")
+        self.window.resizable(True, True)
+
+        # Make window modal
+        self.window.transient(parent)
+        self.window.grab_set()
+
+        self._setup_ui()
+        self._populate_medicine_list()
+
+        # Center window
+        self.window.update_idletasks()
+        x = (self.window.winfo_screenwidth() // 2) - (600 // 2)
+        y = (self.window.winfo_screenheight() // 2) - (500 // 2)
+        self.window.geometry(f"600x500+{x}+{y}")
+
+    def _setup_ui(self):
+        """Set up the user interface."""
+        main_frame = ttk.Frame(self.window, padding="10")
+        main_frame.grid(row=0, column=0, sticky="nsew")
+
+        self.window.grid_rowconfigure(0, weight=1)
+        self.window.grid_columnconfigure(0, weight=1)
+        main_frame.grid_rowconfigure(1, weight=1)
+        main_frame.grid_columnconfigure(0, weight=1)
+
+        # Title
+        title_label = ttk.Label(
+            main_frame, text="Medicine Management", font=("Arial", 14, "bold")
+        )
+        title_label.grid(row=0, column=0, columnspan=2, pady=(0, 10))
+
+        # Medicine list
+        list_frame = ttk.LabelFrame(main_frame, text="Current Medicines")
+        list_frame.grid(row=1, column=0, columnspan=2, sticky="nsew", pady=(0, 10))
+        list_frame.grid_rowconfigure(0, weight=1)
+        list_frame.grid_columnconfigure(0, weight=1)
+
+        # Treeview for medicines
+        columns = ("key", "name", "dosage", "quick_doses", "color", "default")
+        self.tree = ttk.Treeview(list_frame, columns=columns, show="headings")
+
+        # Column headings
+        self.tree.heading("key", text="Key")
+        self.tree.heading("name", text="Name")
+        self.tree.heading("dosage", text="Dosage Info")
+        self.tree.heading("quick_doses", text="Quick Doses")
+        self.tree.heading("color", text="Color")
+        self.tree.heading("default", text="Default Enabled")
+
+        # Column widths
+        self.tree.column("key", width=80)
+        self.tree.column("name", width=100)
+        self.tree.column("dosage", width=100)
+        self.tree.column("quick_doses", width=120)
+        self.tree.column("color", width=70)
+        self.tree.column("default", width=100)
+
+        self.tree.grid(row=0, column=0, sticky="nsew", padx=5, pady=5)
+
+        # Scrollbar for treeview
+        scrollbar = ttk.Scrollbar(
+            list_frame, orient="vertical", command=self.tree.yview
+        )
+        scrollbar.grid(row=0, column=1, sticky="ns")
+        self.tree.configure(yscrollcommand=scrollbar.set)
+
+        # Buttons
+        button_frame = ttk.Frame(main_frame)
+        button_frame.grid(row=2, column=0, columnspan=2, pady=(10, 0))
+
+        ttk.Button(button_frame, text="Add Medicine", command=self._add_medicine).grid(
+            row=0, column=0, padx=(0, 5)
+        )
+
+        ttk.Button(
+            button_frame, text="Edit Medicine", command=self._edit_medicine
+        ).grid(row=0, column=1, padx=5)
+
+        ttk.Button(
+            button_frame, text="Remove Medicine", command=self._remove_medicine
+        ).grid(row=0, column=2, padx=5)
+
+        ttk.Button(button_frame, text="Close", command=self._close_window).grid(
+            row=0, column=3, padx=(5, 0)
+        )
+
+    def _populate_medicine_list(self):
+        """Populate the medicine list."""
+        # Clear existing items
+        for item in self.tree.get_children():
+            self.tree.delete(item)
+
+        # Add medicines
+        for medicine in self.medicine_manager.get_all_medicines().values():
+            self.tree.insert(
+                "",
+                "end",
+                values=(
+                    medicine.key,
+                    medicine.display_name,
+                    medicine.dosage_info,
+                    ", ".join(medicine.quick_doses),
+                    medicine.color,
+                    "Yes" if medicine.default_enabled else "No",
+                ),
+            )
+
+    def _add_medicine(self):
+        """Add a new medicine."""
+        MedicineEditDialog(
+            self.window, self.medicine_manager, None, self._on_medicine_changed
+        )
+
+    def _edit_medicine(self):
+        """Edit selected medicine."""
+        selection = self.tree.selection()
+        if not selection:
+            messagebox.showwarning("No Selection", "Please select a medicine to edit.")
+            return
+
+        item = self.tree.item(selection[0])
+        medicine_key = item["values"][0]
+        medicine = self.medicine_manager.get_medicine(medicine_key)
+
+        if medicine:
+            MedicineEditDialog(
+                self.window, self.medicine_manager, medicine, self._on_medicine_changed
+            )
+
+    def _remove_medicine(self):
+        """Remove selected medicine."""
+        selection = self.tree.selection()
+        if not selection:
+            messagebox.showwarning(
+                "No Selection", "Please select a medicine to remove."
+            )
+            return
+
+        item = self.tree.item(selection[0])
+        medicine_key = item["values"][0]
+        medicine_name = item["values"][1]
+
+        if messagebox.askyesno(
+            "Confirm Removal",
+            f"Are you sure you want to remove '{medicine_name}'?\n\n"
+            "This will also remove all associated data from your records!",
+        ):
+            if self.medicine_manager.remove_medicine(medicine_key):
+                messagebox.showinfo(
+                    "Success", f"'{medicine_name}' removed successfully!"
+                )
+                self._populate_medicine_list()
+                self._refresh_main_app()
+            else:
+                messagebox.showerror("Error", f"Failed to remove '{medicine_name}'.")
+
+    def _on_medicine_changed(self):
+        """Called when a medicine is added or edited."""
+        self._populate_medicine_list()
+        self._refresh_main_app()
+
+    def _refresh_main_app(self):
+        """Refresh the main application after medicine changes."""
+        if self.refresh_callback:
+            self.refresh_callback()
+
+    def _close_window(self):
+        """Close the window."""
+        self.window.destroy()
+
+
+class MedicineEditDialog:
+    """Dialog for adding/editing a medicine."""
+
+    def __init__(
+        self,
+        parent: tk.Toplevel,
+        medicine_manager: MedicineManager,
+        medicine: Medicine | None,
+        callback,
+    ):
+        self.parent = parent
+        self.medicine_manager = medicine_manager
+        self.medicine = medicine
+        self.callback = callback
+        self.is_edit = medicine is not None
+
+        # Create dialog
+        self.dialog = tk.Toplevel(parent)
+        self.dialog.title("Edit Medicine" if self.is_edit else "Add Medicine")
+        self.dialog.geometry("400x350")
+        self.dialog.resizable(False, False)
+
+        # Make modal
+        self.dialog.transient(parent)
+        self.dialog.grab_set()
+
+        self._setup_dialog()
+        self._populate_fields()
+
+        # Center dialog
+        self.dialog.update_idletasks()
+        x = parent.winfo_x() + (parent.winfo_width() // 2) - (400 // 2)
+        y = parent.winfo_y() + (parent.winfo_height() // 2) - (350 // 2)
+        self.dialog.geometry(f"400x350+{x}+{y}")
+
+    def _setup_dialog(self):
+        """Set up the dialog UI."""
+        main_frame = ttk.Frame(self.dialog, padding="15")
+        main_frame.grid(row=0, column=0, sticky="nsew")
+
+        self.dialog.grid_rowconfigure(0, weight=1)
+        self.dialog.grid_columnconfigure(0, weight=1)
+
+        # Fields
+        fields_frame = ttk.Frame(main_frame)
+        fields_frame.grid(row=0, column=0, sticky="ew", pady=(0, 15))
+        fields_frame.grid_columnconfigure(1, weight=1)
+
+        row = 0
+
+        # Key
+        ttk.Label(fields_frame, text="Key:").grid(row=row, column=0, sticky="w", pady=5)
+        self.key_var = tk.StringVar()
+        key_entry = ttk.Entry(fields_frame, textvariable=self.key_var)
+        key_entry.grid(row=row, column=1, sticky="ew", padx=(10, 0), pady=5)
+        if self.is_edit:
+            key_entry.configure(state="readonly")
+        row += 1
+
+        # Display Name
+        ttk.Label(fields_frame, text="Display Name:").grid(
+            row=row, column=0, sticky="w", pady=5
+        )
+        self.name_var = tk.StringVar()
+        ttk.Entry(fields_frame, textvariable=self.name_var).grid(
+            row=row, column=1, sticky="ew", padx=(10, 0), pady=5
+        )
+        row += 1
+
+        # Dosage Info
+        ttk.Label(fields_frame, text="Dosage Info:").grid(
+            row=row, column=0, sticky="w", pady=5
+        )
+        self.dosage_var = tk.StringVar()
+        ttk.Entry(fields_frame, textvariable=self.dosage_var).grid(
+            row=row, column=1, sticky="ew", padx=(10, 0), pady=5
+        )
+        row += 1
+
+        # Quick Doses
+        ttk.Label(fields_frame, text="Quick Doses:").grid(
+            row=row, column=0, sticky="w", pady=5
+        )
+        self.doses_var = tk.StringVar()
+        ttk.Entry(fields_frame, textvariable=self.doses_var).grid(
+            row=row, column=1, sticky="ew", padx=(10, 0), pady=5
+        )
+        ttk.Label(
+            fields_frame, text="(comma-separated, e.g. 25,50,100)", font=("Arial", 8)
+        ).grid(row=row + 1, column=1, sticky="w", padx=(10, 0))
+        row += 2
+
+        # Color
+        ttk.Label(fields_frame, text="Graph Color:").grid(
+            row=row, column=0, sticky="w", pady=5
+        )
+        self.color_var = tk.StringVar()
+        ttk.Entry(fields_frame, textvariable=self.color_var).grid(
+            row=row, column=1, sticky="ew", padx=(10, 0), pady=5
+        )
+        ttk.Label(
+            fields_frame, text="(hex color, e.g. #FF6B6B)", font=("Arial", 8)
+        ).grid(row=row + 1, column=1, sticky="w", padx=(10, 0))
+        row += 2
+
+        # Default Enabled
+        self.default_var = tk.BooleanVar()
+        ttk.Checkbutton(
+            fields_frame,
+            text="Show in graph by default",
+            variable=self.default_var,
+        ).grid(row=row, column=0, columnspan=2, sticky="w", pady=5)
+
+        # Buttons
+        button_frame = ttk.Frame(main_frame)
+        button_frame.grid(row=1, column=0)
+
+        ttk.Button(button_frame, text="Save", command=self._save_medicine).grid(
+            row=0, column=0, padx=(0, 10)
+        )
+
+        ttk.Button(button_frame, text="Cancel", command=self.dialog.destroy).grid(
+            row=0, column=1
+        )
+
+    def _populate_fields(self):
+        """Populate fields if editing."""
+        if self.medicine:
+            self.key_var.set(self.medicine.key)
+            self.name_var.set(self.medicine.display_name)
+            self.dosage_var.set(self.medicine.dosage_info)
+            self.doses_var.set(",".join(self.medicine.quick_doses))
+            self.color_var.set(self.medicine.color)
+            self.default_var.set(self.medicine.default_enabled)
+
+    def _save_medicine(self):
+        """Save the medicine."""
+        # Validate fields
+        key = self.key_var.get().strip()
+        name = self.name_var.get().strip()
+        dosage = self.dosage_var.get().strip()
+        doses_str = self.doses_var.get().strip()
+        color = self.color_var.get().strip()
+
+        if not all([key, name, dosage, doses_str, color]):
+            messagebox.showerror("Error", "All fields are required.")
+            return
+
+        # Validate key format (alphanumeric and underscores only)
+        if not key.replace("_", "").replace("-", "").isalnum():
+            messagebox.showerror(
+                "Error",
+                "Key must contain only letters, numbers, underscores, and hyphens.",
+            )
+            return
+
+        # Parse quick doses
+        try:
+            quick_doses = [dose.strip() for dose in doses_str.split(",")]
+            quick_doses = [dose for dose in quick_doses if dose]  # Remove empty strings
+            if not quick_doses:
+                raise ValueError("At least one quick dose is required.")
+        except Exception:
+            messagebox.showerror("Error", "Quick doses must be comma-separated values.")
+            return
+
+        # Validate color format
+        if not color.startswith("#") or len(color) != 7:
+            messagebox.showerror(
+                "Error", "Color must be in hex format (e.g., #FF6B6B)."
+            )
+            return
+
+        try:
+            int(color[1:], 16)  # Validate hex color
+        except ValueError:
+            messagebox.showerror("Error", "Invalid hex color format.")
+            return
+
+        # Create medicine object
+        new_medicine = Medicine(
+            key=key,
+            display_name=name,
+            dosage_info=dosage,
+            quick_doses=quick_doses,
+            color=color,
+            default_enabled=self.default_var.get(),
+        )
+
+        # Save medicine
+        success = False
+        if self.is_edit:
+            success = self.medicine_manager.update_medicine(
+                self.medicine.key, new_medicine
+            )
+        else:
+            success = self.medicine_manager.add_medicine(new_medicine)
+
+        if success:
+            action = "updated" if self.is_edit else "added"
+            messagebox.showinfo("Success", f"Medicine {action} successfully!")
+            self.callback()
+            self.dialog.destroy()
+        else:
+            action = "update" if self.is_edit else "add"
+            messagebox.showerror("Error", f"Failed to {action} medicine.")

src/medicine_manager.py

@@ -0,0 +1,195 @@
+"""
+Medicine configuration manager for the MedTracker application.
+Handles dynamic loading and saving of medicine configurations.
+"""
+
+import json
+import logging
+import os
+from dataclasses import asdict, dataclass
+from typing import Any
+
+
+@dataclass
+class Medicine:
+    """Data class representing a medicine."""
+
+    key: str  # Internal key (e.g., "bupropion")
+    display_name: str  # Display name (e.g., "Bupropion")
+    dosage_info: str  # Dosage information (e.g., "150/300 mg")
+    quick_doses: list[str]  # Common dose amounts for quick selection
+    color: str  # Color for graph display
+    default_enabled: bool = False  # Whether to show in graph by default
+
+
+class MedicineManager:
+    """Manages medicine configurations and provides access to medicine data."""
+
+    def __init__(
+        self, config_file: str = "medicines.json", logger: logging.Logger = None
+    ):
+        self.config_file = config_file
+        self.logger = logger or logging.getLogger(__name__)
+        self.medicines: dict[str, Medicine] = {}
+        self._load_medicines()
+
+    def _get_default_medicines(self) -> list[Medicine]:
+        """Get the default medicine configuration."""
+        return [
+            Medicine(
+                key="bupropion",
+                display_name="Bupropion",
+                dosage_info="150/300 mg",
+                quick_doses=["150", "300"],
+                color="#FF6B6B",
+                default_enabled=True,
+            ),
+            Medicine(
+                key="hydroxyzine",
+                display_name="Hydroxyzine",
+                dosage_info="25 mg",
+                quick_doses=["25", "50"],
+                color="#4ECDC4",
+                default_enabled=False,
+            ),
+            Medicine(
+                key="gabapentin",
+                display_name="Gabapentin",
+                dosage_info="100 mg",
+                quick_doses=["100", "300", "600"],
+                color="#45B7D1",
+                default_enabled=False,
+            ),
+            Medicine(
+                key="propranolol",
+                display_name="Propranolol",
+                dosage_info="10 mg",
+                quick_doses=["10", "20", "40"],
+                color="#96CEB4",
+                default_enabled=True,
+            ),
+            Medicine(
+                key="quetiapine",
+                display_name="Quetiapine",
+                dosage_info="25 mg",
+                quick_doses=["25", "50", "100"],
+                color="#FFEAA7",
+                default_enabled=False,
+            ),
+        ]
+
+    def _load_medicines(self) -> None:
+        """Load medicines from configuration file."""
+        if os.path.exists(self.config_file):
+            try:
+                with open(self.config_file) as f:
+                    data = json.load(f)
+
+                self.medicines = {}
+                for medicine_data in data.get("medicines", []):
+                    medicine = Medicine(**medicine_data)
+                    self.medicines[medicine.key] = medicine
+
+                self.logger.info(
+                    f"Loaded {len(self.medicines)} medicines from {self.config_file}"
+                )
+            except Exception as e:
+                self.logger.error(f"Error loading medicines config: {e}")
+                self._create_default_config()
+        else:
+            self._create_default_config()
+
+    def _create_default_config(self) -> None:
+        """Create default medicine configuration."""
+        default_medicines = self._get_default_medicines()
+        self.medicines = {med.key: med for med in default_medicines}
+        self.save_medicines()
+        self.logger.info("Created default medicine configuration")
+
+    def save_medicines(self) -> bool:
+        """Save current medicines to configuration file."""
+        try:
+            data = {
+                "medicines": [asdict(medicine) for medicine in self.medicines.values()]
+            }
+
+            with open(self.config_file, "w") as f:
+                json.dump(data, f, indent=2)
+
+            self.logger.info(
+                f"Saved {len(self.medicines)} medicines to {self.config_file}"
+            )
+            return True
+        except Exception as e:
+            self.logger.error(f"Error saving medicines config: {e}")
+            return False
+
+    def get_all_medicines(self) -> dict[str, Medicine]:
+        """Get all medicines."""
+        return self.medicines.copy()
+
+    def get_medicine(self, key: str) -> Medicine | None:
+        """Get a specific medicine by key."""
+        return self.medicines.get(key)
+
+    def add_medicine(self, medicine: Medicine) -> bool:
+        """Add a new medicine."""
+        if medicine.key in self.medicines:
+            self.logger.warning(f"Medicine with key '{medicine.key}' already exists")
+            return False
+
+        self.medicines[medicine.key] = medicine
+        return self.save_medicines()
+
+    def update_medicine(self, key: str, medicine: Medicine) -> bool:
+        """Update an existing medicine."""
+        if key not in self.medicines:
+            self.logger.warning(f"Medicine with key '{key}' does not exist")
+            return False
+
+        # If key is changing, remove old entry
+        if key != medicine.key:
+            del self.medicines[key]
+
+        self.medicines[medicine.key] = medicine
+        return self.save_medicines()
+
+    def remove_medicine(self, key: str) -> bool:
+        """Remove a medicine."""
+        if key not in self.medicines:
+            self.logger.warning(f"Medicine with key '{key}' does not exist")
+            return False
+
+        del self.medicines[key]
+        return self.save_medicines()
+
+    def get_medicine_keys(self) -> list[str]:
+        """Get list of all medicine keys."""
+        return list(self.medicines.keys())
+
+    def get_display_names(self) -> dict[str, str]:
+        """Get mapping of keys to display names."""
+        return {key: med.display_name for key, med in self.medicines.items()}
+
+    def get_quick_doses(self, key: str) -> list[str]:
+        """Get quick dose options for a medicine."""
+        medicine = self.medicines.get(key)
+        return medicine.quick_doses if medicine else ["25", "50"]
+
+    def get_graph_colors(self) -> dict[str, str]:
+        """Get mapping of medicine keys to graph colors."""
+        return {key: med.color for key, med in self.medicines.items()}
+
+    def get_default_enabled_medicines(self) -> list[str]:
+        """Get list of medicines that should be enabled by default in graphs."""
+        return [key for key, med in self.medicines.items() if med.default_enabled]
+
+    def get_medicine_vars_dict(self) -> dict[str, tuple[Any, str]]:
+        """Get medicine variables dictionary for UI compatibility."""
+        # This maintains compatibility with existing UI code
+        import tkinter as tk
+
+        return {
+            key: (tk.IntVar(value=0), f"{med.display_name} {med.dosage_info}")
+            for key, med in self.medicines.items()
+        }

src/pathology_management_window.py

@@ -0,0 +1,425 @@
+"""
+Pathology management window for adding, editing, and removing pathologies.
+"""
+
+import tkinter as tk
+from tkinter import messagebox, ttk
+
+from pathology_manager import Pathology, PathologyManager
+
+
+class PathologyManagementWindow:
+    """Window for managing pathology configurations."""
+
+    def __init__(
+        self, parent: tk.Tk, pathology_manager: PathologyManager, refresh_callback
+    ):
+        self.parent = parent
+        self.pathology_manager = pathology_manager
+        self.refresh_callback = refresh_callback
+
+        # Create the window
+        self.window = tk.Toplevel(parent)
+        self.window.title("Manage Pathologies")
+        self.window.geometry("800x500")
+        self.window.resizable(True, True)
+
+        # Make window modal
+        self.window.transient(parent)
+        self.window.grab_set()
+
+        self._setup_ui()
+        self._populate_pathology_list()
+
+        # Center window
+        self.window.update_idletasks()
+        x = (self.window.winfo_screenwidth() // 2) - (800 // 2)
+        y = (self.window.winfo_screenheight() // 2) - (500 // 2)
+        self.window.geometry(f"800x500+{x}+{y}")
+
+    def _setup_ui(self):
+        """Set up the UI components."""
+        # Main frame
+        main_frame = ttk.Frame(self.window, padding="10")
+        main_frame.grid(row=0, column=0, sticky="nsew")
+        self.window.grid_rowconfigure(0, weight=1)
+        self.window.grid_columnconfigure(0, weight=1)
+
+        # Pathology list
+        list_frame = ttk.LabelFrame(main_frame, text="Pathologies", padding="5")
+        list_frame.grid(row=0, column=0, sticky="nsew", pady=(0, 10))
+        main_frame.grid_rowconfigure(0, weight=1)
+        main_frame.grid_columnconfigure(0, weight=1)
+
+        # Treeview for pathology list
+        columns = (
+            "Key",
+            "Display Name",
+            "Scale Info",
+            "Color",
+            "Default Enabled",
+            "Scale Range",
+        )
+        self.tree = ttk.Treeview(list_frame, columns=columns, show="headings")
+
+        # Configure columns
+        self.tree.heading("Key", text="Key")
+        self.tree.heading("Display Name", text="Display Name")
+        self.tree.heading("Scale Info", text="Scale Info")
+        self.tree.heading("Color", text="Color")
+        self.tree.heading("Default Enabled", text="Default Enabled")
+        self.tree.heading("Scale Range", text="Scale Range")
+
+        self.tree.column("Key", width=120)
+        self.tree.column("Display Name", width=150)
+        self.tree.column("Scale Info", width=150)
+        self.tree.column("Color", width=80)
+        self.tree.column("Default Enabled", width=100)
+        self.tree.column("Scale Range", width=100)
+
+        # Scrollbar for treeview
+        scrollbar = ttk.Scrollbar(
+            list_frame, orient="vertical", command=self.tree.yview
+        )
+        self.tree.configure(yscrollcommand=scrollbar.set)
+
+        self.tree.grid(row=0, column=0, sticky="nsew")
+        scrollbar.grid(row=0, column=1, sticky="ns")
+
+        list_frame.grid_rowconfigure(0, weight=1)
+        list_frame.grid_columnconfigure(0, weight=1)
+
+        # Buttons frame
+        button_frame = ttk.Frame(main_frame)
+        button_frame.grid(row=1, column=0, sticky="ew")
+
+        ttk.Button(
+            button_frame, text="Add Pathology", command=self._add_pathology
+        ).pack(side="left", padx=(0, 5))
+        ttk.Button(
+            button_frame, text="Edit Pathology", command=self._edit_pathology
+        ).pack(side="left", padx=(0, 5))
+        ttk.Button(
+            button_frame, text="Remove Pathology", command=self._remove_pathology
+        ).pack(side="left", padx=(0, 5))
+        ttk.Button(button_frame, text="Close", command=self.window.destroy).pack(
+            side="right"
+        )
+
+    def _populate_pathology_list(self):
+        """Populate the pathology list."""
+        # Clear existing items
+        for item in self.tree.get_children():
+            self.tree.delete(item)
+
+        # Add pathologies
+        for pathology in self.pathology_manager.get_all_pathologies().values():
+            scale_range = f"{pathology.scale_min}-{pathology.scale_max}"
+            self.tree.insert(
+                "",
+                "end",
+                values=(
+                    pathology.key,
+                    pathology.display_name,
+                    pathology.scale_info,
+                    pathology.color,
+                    "Yes" if pathology.default_enabled else "No",
+                    scale_range,
+                ),
+            )
+
+    def _add_pathology(self):
+        """Add a new pathology."""
+        PathologyEditDialog(
+            self.window, self.pathology_manager, None, self._on_pathology_changed
+        )
+
+    def _edit_pathology(self):
+        """Edit selected pathology."""
+        selection = self.tree.selection()
+        if not selection:
+            messagebox.showwarning("No Selection", "Please select a pathology to edit.")
+            return
+
+        item = self.tree.item(selection[0])
+        pathology_key = item["values"][0]
+        pathology = self.pathology_manager.get_pathology(pathology_key)
+
+        if pathology:
+            PathologyEditDialog(
+                self.window,
+                self.pathology_manager,
+                pathology,
+                self._on_pathology_changed,
+            )
+
+    def _remove_pathology(self):
+        """Remove selected pathology."""
+        selection = self.tree.selection()
+        if not selection:
+            messagebox.showwarning(
+                "No Selection", "Please select a pathology to remove."
+            )
+            return
+
+        item = self.tree.item(selection[0])
+        pathology_key = item["values"][0]
+        pathology_name = item["values"][1]
+
+        if messagebox.askyesno(
+            "Confirm Removal",
+            f"Are you sure you want to remove '{pathology_name}'?\n\n"
+            "This will also remove all associated data from your records!",
+        ):
+            if self.pathology_manager.remove_pathology(pathology_key):
+                messagebox.showinfo(
+                    "Success", f"'{pathology_name}' removed successfully!"
+                )
+                self._populate_pathology_list()
+                self._refresh_main_app()
+            else:
+                messagebox.showerror("Error", f"Failed to remove '{pathology_name}'.")
+
+    def _on_pathology_changed(self):
+        """Handle pathology changes."""
+        self._populate_pathology_list()
+        self._refresh_main_app()
+
+    def _refresh_main_app(self):
+        """Refresh the main application."""
+        if self.refresh_callback:
+            self.refresh_callback()
+
+
+class PathologyEditDialog:
+    """Dialog for adding/editing a pathology."""
+
+    def __init__(
+        self,
+        parent: tk.Toplevel,
+        pathology_manager: PathologyManager,
+        pathology: Pathology | None,
+        callback,
+    ):
+        self.parent = parent
+        self.pathology_manager = pathology_manager
+        self.pathology = pathology
+        self.callback = callback
+        self.is_edit = pathology is not None
+
+        # Create dialog
+        self.dialog = tk.Toplevel(parent)
+        self.dialog.title("Edit Pathology" if self.is_edit else "Add Pathology")
+        self.dialog.geometry("450x400")
+        self.dialog.resizable(False, False)
+
+        # Make modal
+        self.dialog.transient(parent)
+        self.dialog.grab_set()
+
+        self._setup_dialog()
+        self._populate_fields()
+
+        # Center dialog
+        self.dialog.update_idletasks()
+        x = parent.winfo_x() + (parent.winfo_width() // 2) - (450 // 2)
+        y = parent.winfo_y() + (parent.winfo_height() // 2) - (400 // 2)
+        self.dialog.geometry(f"450x400+{x}+{y}")
+
+    def _setup_dialog(self):
+        """Set up the dialog UI."""
+        # Main frame
+        main_frame = ttk.Frame(self.dialog, padding="15")
+        main_frame.grid(row=0, column=0, sticky="nsew")
+        self.dialog.grid_rowconfigure(0, weight=1)
+        self.dialog.grid_columnconfigure(0, weight=1)
+
+        # Form fields
+        self.key_var = tk.StringVar()
+        self.name_var = tk.StringVar()
+        self.scale_info_var = tk.StringVar()
+        self.color_var = tk.StringVar()
+        self.default_var = tk.BooleanVar()
+        self.scale_min_var = tk.IntVar(value=0)
+        self.scale_max_var = tk.IntVar(value=10)
+        self.orientation_var = tk.StringVar(value="normal")
+
+        # Key field
+        ttk.Label(main_frame, text="Key:").grid(
+            row=0, column=0, sticky="w", pady=(0, 5)
+        )
+        key_entry = ttk.Entry(main_frame, textvariable=self.key_var, width=40)
+        key_entry.grid(row=0, column=1, sticky="ew", pady=(0, 5))
+        ttk.Label(main_frame, text="(alphanumeric, underscores, hyphens only)").grid(
+            row=0, column=2, sticky="w", padx=(5, 0), pady=(0, 5)
+        )
+
+        # Display name field
+        ttk.Label(main_frame, text="Display Name:").grid(
+            row=1, column=0, sticky="w", pady=(0, 5)
+        )
+        ttk.Entry(main_frame, textvariable=self.name_var, width=40).grid(
+            row=1, column=1, sticky="ew", pady=(0, 5)
+        )
+
+        # Scale info field
+        ttk.Label(main_frame, text="Scale Info:").grid(
+            row=2, column=0, sticky="w", pady=(0, 5)
+        )
+        ttk.Entry(main_frame, textvariable=self.scale_info_var, width=40).grid(
+            row=2, column=1, sticky="ew", pady=(0, 5)
+        )
+        ttk.Label(main_frame, text='(e.g., "0:good, 10:bad")').grid(
+            row=2, column=2, sticky="w", padx=(5, 0), pady=(0, 5)
+        )
+
+        # Scale range
+        scale_frame = ttk.Frame(main_frame)
+        scale_frame.grid(row=3, column=1, sticky="ew", pady=(0, 5))
+
+        ttk.Label(main_frame, text="Scale Range:").grid(
+            row=3, column=0, sticky="w", pady=(0, 5)
+        )
+        ttk.Label(scale_frame, text="Min:").grid(row=0, column=0, sticky="w")
+        ttk.Entry(scale_frame, textvariable=self.scale_min_var, width=5).grid(
+            row=0, column=1, padx=(5, 10)
+        )
+        ttk.Label(scale_frame, text="Max:").grid(row=0, column=2, sticky="w")
+        ttk.Entry(scale_frame, textvariable=self.scale_max_var, width=5).grid(
+            row=0, column=3, padx=5
+        )
+
+        # Scale orientation
+        ttk.Label(main_frame, text="Scale Orientation:").grid(
+            row=4, column=0, sticky="w", pady=(0, 5)
+        )
+        orientation_frame = ttk.Frame(main_frame)
+        orientation_frame.grid(row=4, column=1, sticky="ew", pady=(0, 5))
+
+        ttk.Radiobutton(
+            orientation_frame,
+            text="Normal (0=good)",
+            variable=self.orientation_var,
+            value="normal",
+        ).grid(row=0, column=0, sticky="w")
+        ttk.Radiobutton(
+            orientation_frame,
+            text="Inverted (0=bad)",
+            variable=self.orientation_var,
+            value="inverted",
+        ).grid(row=0, column=1, sticky="w", padx=(20, 0))
+
+        # Color field
+        ttk.Label(main_frame, text="Color:").grid(
+            row=5, column=0, sticky="w", pady=(0, 5)
+        )
+        ttk.Entry(main_frame, textvariable=self.color_var, width=40).grid(
+            row=5, column=1, sticky="ew", pady=(0, 5)
+        )
+        ttk.Label(main_frame, text="(hex format, e.g., #FF6B6B)").grid(
+            row=5, column=2, sticky="w", padx=(5, 0), pady=(0, 5)
+        )
+
+        # Default enabled checkbox
+        ttk.Checkbutton(
+            main_frame, text="Show in graph by default", variable=self.default_var
+        ).grid(row=6, column=1, sticky="w", pady=(10, 15))
+
+        # Buttons
+        button_frame = ttk.Frame(main_frame)
+        button_frame.grid(row=7, column=0, columnspan=3, sticky="ew", pady=(10, 0))
+
+        ttk.Button(button_frame, text="Save", command=self._save_pathology).pack(
+            side="right", padx=(5, 0)
+        )
+        ttk.Button(button_frame, text="Cancel", command=self.dialog.destroy).pack(
+            side="right"
+        )
+
+        # Configure column weights
+        main_frame.grid_columnconfigure(1, weight=1)
+
+        # Focus on first field
+        key_entry.focus()
+
+    def _populate_fields(self):
+        """Populate fields if editing."""
+        if self.pathology:
+            self.key_var.set(self.pathology.key)
+            self.name_var.set(self.pathology.display_name)
+            self.scale_info_var.set(self.pathology.scale_info)
+            self.color_var.set(self.pathology.color)
+            self.default_var.set(self.pathology.default_enabled)
+            self.scale_min_var.set(self.pathology.scale_min)
+            self.scale_max_var.set(self.pathology.scale_max)
+            self.orientation_var.set(self.pathology.scale_orientation)
+
+    def _save_pathology(self):
+        """Save the pathology."""
+        # Validate fields
+        key = self.key_var.get().strip()
+        name = self.name_var.get().strip()
+        scale_info = self.scale_info_var.get().strip()
+        color = self.color_var.get().strip()
+        scale_min = self.scale_min_var.get()
+        scale_max = self.scale_max_var.get()
+
+        if not all([key, name, scale_info, color]):
+            messagebox.showerror("Error", "All fields are required.")
+            return
+
+        # Validate key format (alphanumeric and underscores only)
+        if not key.replace("_", "").replace("-", "").isalnum():
+            messagebox.showerror(
+                "Error",
+                "Key must contain only letters, numbers, underscores, and hyphens.",
+            )
+            return
+
+        # Validate scale range
+        if scale_min >= scale_max:
+            messagebox.showerror("Error", "Scale minimum must be less than maximum.")
+            return
+
+        # Validate color format
+        if not color.startswith("#") or len(color) != 7:
+            messagebox.showerror(
+                "Error", "Color must be in hex format (e.g., #FF6B6B)."
+            )
+            return
+
+        try:
+            int(color[1:], 16)  # Validate hex color
+        except ValueError:
+            messagebox.showerror("Error", "Invalid hex color format.")
+            return
+
+        # Create pathology object
+        new_pathology = Pathology(
+            key=key,
+            display_name=name,
+            scale_info=scale_info,
+            color=color,
+            default_enabled=self.default_var.get(),
+            scale_min=scale_min,
+            scale_max=scale_max,
+            scale_orientation=self.orientation_var.get(),
+        )
+
+        # Save pathology
+        success = False
+        if self.is_edit:
+            success = self.pathology_manager.update_pathology(
+                self.pathology.key, new_pathology
+            )
+        else:
+            success = self.pathology_manager.add_pathology(new_pathology)
+
+        if success:
+            action = "updated" if self.is_edit else "added"
+            messagebox.showinfo("Success", f"Pathology {action} successfully!")
+            self.callback()
+            self.dialog.destroy()
+        else:
+            action = "update" if self.is_edit else "add"
+            messagebox.showerror("Error", f"Failed to {action} pathology.")

src/pathology_manager.py

@@ -0,0 +1,199 @@
+"""
+Pathology configuration manager for the MedTracker application.
+Handles dynamic loading and saving of pathology/symptom configurations.
+"""
+
+import json
+import logging
+import os
+from dataclasses import asdict, dataclass
+from typing import Any
+
+
+@dataclass
+class Pathology:
+    """Data class representing a pathology/symptom."""
+
+    key: str  # Internal key (e.g., "depression")
+    display_name: str  # Display name (e.g., "Depression")
+    scale_info: str  # Scale information (e.g., "0:good, 10:bad")
+    color: str  # Color for graph display
+    default_enabled: bool = True  # Whether to show in graph by default
+    scale_min: int = 0  # Minimum scale value
+    scale_max: int = 10  # Maximum scale value
+    scale_orientation: str = "normal"  # "normal" (0=good) or "inverted" (0=bad)
+
+
+class PathologyManager:
+    """Manages pathology configurations and provides access to pathology data."""
+
+    def __init__(
+        self, config_file: str = "pathologies.json", logger: logging.Logger = None
+    ):
+        self.config_file = config_file
+        self.logger = logger or logging.getLogger(__name__)
+        self.pathologies: dict[str, Pathology] = {}
+        self._load_pathologies()
+
+    def _get_default_pathologies(self) -> list[Pathology]:
+        """Get the default pathology configuration."""
+        return [
+            Pathology(
+                key="depression",
+                display_name="Depression",
+                scale_info="0:good, 10:bad",
+                color="#FF6B6B",
+                default_enabled=True,
+                scale_orientation="normal",
+            ),
+            Pathology(
+                key="anxiety",
+                display_name="Anxiety",
+                scale_info="0:good, 10:bad",
+                color="#FFA726",
+                default_enabled=True,
+                scale_orientation="normal",
+            ),
+            Pathology(
+                key="sleep",
+                display_name="Sleep Quality",
+                scale_info="0:bad, 10:good",
+                color="#66BB6A",
+                default_enabled=True,
+                scale_orientation="inverted",
+            ),
+            Pathology(
+                key="appetite",
+                display_name="Appetite",
+                scale_info="0:bad, 10:good",
+                color="#42A5F5",
+                default_enabled=True,
+                scale_orientation="inverted",
+            ),
+        ]
+
+    def _load_pathologies(self) -> None:
+        """Load pathologies from configuration file."""
+        if os.path.exists(self.config_file):
+            try:
+                with open(self.config_file) as f:
+                    data = json.load(f)
+
+                self.pathologies = {}
+                for pathology_data in data.get("pathologies", []):
+                    pathology = Pathology(**pathology_data)
+                    self.pathologies[pathology.key] = pathology
+
+                self.logger.info(
+                    f"Loaded {len(self.pathologies)} pathologies from "
+                    f"{self.config_file}"
+                )
+            except Exception as e:
+                self.logger.error(f"Error loading pathologies config: {e}")
+                self._create_default_config()
+        else:
+            self._create_default_config()
+
+    def _create_default_config(self) -> None:
+        """Create default pathology configuration."""
+        default_pathologies = self._get_default_pathologies()
+        self.pathologies = {path.key: path for path in default_pathologies}
+        self.save_pathologies()
+        self.logger.info("Created default pathology configuration")
+
+    def save_pathologies(self) -> bool:
+        """Save current pathologies to configuration file."""
+        try:
+            data = {
+                "pathologies": [
+                    asdict(pathology) for pathology in self.pathologies.values()
+                ]
+            }
+
+            with open(self.config_file, "w") as f:
+                json.dump(data, f, indent=2)
+
+            self.logger.info(
+                f"Saved {len(self.pathologies)} pathologies to {self.config_file}"
+            )
+            return True
+        except Exception as e:
+            self.logger.error(f"Error saving pathologies config: {e}")
+            return False
+
+    def get_all_pathologies(self) -> dict[str, Pathology]:
+        """Get all pathologies."""
+        return self.pathologies.copy()
+
+    def get_pathology(self, key: str) -> Pathology | None:
+        """Get a specific pathology by key."""
+        return self.pathologies.get(key)
+
+    def add_pathology(self, pathology: Pathology) -> bool:
+        """Add a new pathology."""
+        if pathology.key in self.pathologies:
+            self.logger.warning(f"Pathology with key '{pathology.key}' already exists")
+            return False
+
+        self.pathologies[pathology.key] = pathology
+        return self.save_pathologies()
+
+    def update_pathology(self, key: str, pathology: Pathology) -> bool:
+        """Update an existing pathology."""
+        if key not in self.pathologies:
+            self.logger.warning(f"Pathology with key '{key}' does not exist")
+            return False
+
+        # If key is changing, remove old entry
+        if key != pathology.key:
+            del self.pathologies[key]
+
+        self.pathologies[pathology.key] = pathology
+        return self.save_pathologies()
+
+    def remove_pathology(self, key: str) -> bool:
+        """Remove a pathology."""
+        if key not in self.pathologies:
+            self.logger.warning(f"Pathology with key '{key}' does not exist")
+            return False
+
+        del self.pathologies[key]
+        return self.save_pathologies()
+
+    def get_pathology_keys(self) -> list[str]:
+        """Get list of all pathology keys."""
+        return list(self.pathologies.keys())
+
+    def get_display_names(self) -> dict[str, str]:
+        """Get mapping of keys to display names."""
+        return {key: path.display_name for key, path in self.pathologies.items()}
+
+    def get_graph_colors(self) -> dict[str, str]:
+        """Get mapping of pathology keys to graph colors."""
+        return {key: path.color for key, path in self.pathologies.items()}
+
+    def get_default_enabled_pathologies(self) -> list[str]:
+        """Get list of pathologies that should be enabled by default in graphs."""
+        return [key for key, path in self.pathologies.items() if path.default_enabled]
+
+    def get_pathology_vars_dict(self) -> dict[str, tuple[Any, str]]:
+        """Get pathology variables dictionary for UI compatibility."""
+        # This maintains compatibility with existing UI code
+        import tkinter as tk
+
+        return {
+            key: (tk.IntVar(value=0), path.display_name)
+            for key, path in self.pathologies.items()
+        }
+
+    def get_scale_info(self, key: str) -> tuple[int, int, str, str]:
+        """Get scale information for a pathology."""
+        pathology = self.get_pathology(key)
+        if pathology:
+            return (
+                pathology.scale_min,
+                pathology.scale_max,
+                pathology.scale_info,
+                pathology.scale_orientation,
+            )
+        return (0, 10, "0-10", "normal")

test_dose_calc.py

@@ -1,60 +0,0 @@
-#!/usr/bin/env python3
-"""
-Simple test script to verify dose calculation functionality.
-"""
-
-import os
-import sys
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
-
-import tkinter as tk
-from tkinter import ttk
-
-from src.graph_manager import GraphManager
-
-
-def test_dose_calculation():
-    print("Testing dose calculation...")
-
-    # Create a minimal test setup
-    root = tk.Tk()
-    frame = ttk.LabelFrame(root, text="Test")
-    frame.pack()
-
-    # Create GraphManager instance
-    gm = GraphManager(frame)
-
-    # Test dose calculations
-    test_cases = [
-        ("2025-07-28 18:59:45:150mg", 150.0),
-        ("2025-07-28 18:59:45:150mg|2025-07-28 19:34:19:75mg", 225.0),
-        ("• • • • 2025-07-30 07:50:00:300", 300.0),
-        ("• 2025-07-30 22:50:00:10", 10.0),
-        ("", 0.0),
-        ("nan", 0.0),
-        ("12.5mg", 12.5),
-        ("100|50", 150.0),
-    ]
-
-    all_passed = True
-    for dose_str, expected in test_cases:
-        result = gm._calculate_daily_dose(dose_str)
-        passed = result == expected
-        status = "PASS" if passed else "FAIL"
-        print(f'{status}: "{dose_str[:30]}..." -> Expected: {expected}, Got: {result}')
-        if not passed:
-            all_passed = False
-
-    root.destroy()
-
-    if all_passed:
-        print("\n✅ All dose calculation tests passed!")
-    else:
-        print("\n❌ Some tests failed!")
-
-    return all_passed
-
-
-if __name__ == "__main__":
-    test_dose_calculation()

test_edit_window.py

@@ -1,68 +0,0 @@
-#!/usr/bin/env python3
-"""Test script to demonstrate the improved edit window."""
-
-import sys
-import tkinter as tk
-from pathlib import Path
-
-# Add src directory to path
-sys.path.insert(0, str(Path(__file__).parent / "src"))
-
-from src.logger import logger
-from src.ui_manager import UIManager
-
-
-def test_edit_window():
-    """Test the improved edit window."""
-    root = tk.Tk()
-    root.title("Edit Window Test")
-    root.geometry("400x300")
-
-    ui_manager = UIManager(root, logger)
-
-    # Sample data for testing (16 fields format)
-    test_values = (
-        "12/25/2024",  # date
-        7,  # depression
-        5,  # anxiety
-        6,  # sleep
-        4,  # appetite
-        1,  # bupropion
-        "09:00:00:150|18:00:00:150",  # bupropion_doses
-        1,  # hydroxyzine
-        "21:30:00:25",  # hydroxyzine_doses
-        0,  # gabapentin
-        "",  # gabapentin_doses
-        1,  # propranolol
-        "07:00:00:10|14:00:00:10",  # propranolol_doses
-        0,  # quetiapine
-        "",  # quetiapine_doses
-        # Had a good day overall, feeling better with new medication routine
-        "Had a good day overall, feeling better with the new medication routine.",
-    )
-
-    # Mock callbacks
-    def save_callback(win, *args):
-        print("Save called with args:", args)
-        win.destroy()
-
-    def delete_callback(win):
-        print("Delete called")
-        win.destroy()
-
-    callbacks = {"save": save_callback, "delete": delete_callback}
-
-    # Create the improved edit window
-    edit_win = ui_manager.create_edit_window(test_values, callbacks)
-
-    # Center the edit window
-    edit_win.update_idletasks()
-    x = (edit_win.winfo_screenwidth() // 2) - (edit_win.winfo_width() // 2)
-    y = (edit_win.winfo_screenheight() // 2) - (edit_win.winfo_height() // 2)
-    edit_win.geometry(f"+{x}+{y}")
-
-    root.mainloop()
-
-
-if __name__ == "__main__":
-    test_edit_window()

test_scrolling.py

@@ -1,115 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script to verify mouse wheel scrolling works in both the new entry window
-and edit window of TheChart application.
-"""
-
-import logging
-import tkinter as tk
-
-from src.ui_manager import UIManager
-
-
-def test_scrolling():
-    """Test both new entry and edit window scrolling."""
-    print("Testing mouse wheel scrolling functionality...")
-
-    # Create test root window
-    root = tk.Tk()
-    root.title("Scrolling Test")
-    root.geometry("800x600")
-
-    # Create logger
-    logger = logging.getLogger("test")
-    logger.setLevel(logging.DEBUG)
-
-    # Create UI manager
-    ui_manager = UIManager(root, logger)
-
-    # Create main frame
-    main_frame = tk.Frame(root)
-    main_frame.pack(fill="both", expand=True)
-    main_frame.grid_rowconfigure(0, weight=1)
-    main_frame.grid_rowconfigure(1, weight=1)
-    main_frame.grid_columnconfigure(0, weight=1)
-    main_frame.grid_columnconfigure(1, weight=1)
-
-    # Test 1: Create input frame (new entry window)
-    print("✓ Creating new entry input frame with mouse wheel scrolling...")
-    ui_manager.create_input_frame(main_frame)
-
-    # Test 2: Create edit window
-    def test_edit_window():
-        print("✓ Creating edit window with mouse wheel scrolling...")
-        # Sample data for edit window
-        test_values = (
-            "01/15/2025",  # date
-            "3",  # depression
-            "5",  # anxiety
-            "7",  # sleep
-            "4",  # appetite
-            "1",  # bupropion
-            "09:00: 150",  # bup_doses
-            "0",  # hydroxyzine
-            "",  # hydro_doses
-            "1",  # gabapentin
-            "20:00: 100",  # gaba_doses
-            "0",  # propranolol
-            "",  # prop_doses
-            "0",  # quetiapine
-            "",  # quet_doses
-            "Test note",  # note
-        )
-
-        callbacks = {
-            "save": lambda *args: print("Save callback called"),
-            "delete": lambda *args: print("Delete callback called"),
-        }
-
-        edit_window = ui_manager.create_edit_window(test_values, callbacks)
-        return edit_window
-
-    # Add test button
-    test_button = tk.Button(
-        main_frame,
-        text="Test Edit Window Scrolling",
-        command=test_edit_window,
-        font=("TkDefaultFont", 12),
-        bg="#4CAF50",
-        fg="white",
-        padx=20,
-        pady=10,
-    )
-    test_button.grid(row=2, column=0, columnspan=2, pady=20)
-
-    # Add instructions
-    instructions = tk.Label(
-        main_frame,
-        text="Instructions:\n\n"
-        "1. Use mouse wheel anywhere in the 'New Entry' section to test scrolling\n"
-        "2. Click 'Test Edit Window Scrolling' button\n"
-        "3. Use mouse wheel anywhere in the edit window to test scrolling\n"
-        "4. Both windows should scroll smoothly with mouse wheel\n\n"
-        "✓ Mouse wheel scrolling has been enhanced for both windows!",
-        font=("TkDefaultFont", 10),
-        justify="left",
-        bg="#E8F5E8",
-        padx=20,
-        pady=15,
-    )
-    instructions.grid(row=3, column=0, columnspan=2, padx=20, pady=10, sticky="ew")
-
-    print("✓ Test setup complete!")
-    print("\nMouse wheel scrolling features implemented:")
-    print("  • Recursive binding to all child widgets")
-    print("  • Platform-specific event handling (Windows/Linux)")
-    print("  • Focus management for consistent scrolling")
-    print("  • Works anywhere within the scrollable areas")
-    print("\nTest the scrolling by moving your mouse wheel over any part of the")
-    print("'New Entry' section or the edit window when opened.")
-
-    root.mainloop()
-
-
-if __name__ == "__main__":
-    test_scrolling()

tests/conftest.py

@@ -8,6 +8,12 @@ import pandas as pd
 from unittest.mock import Mock
 import logging
 
+# Add src to path for imports
+import sys
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
+
+from src.medicine_manager import MedicineManager, Medicine
+
 
 @pytest.fixture
 def temp_csv_file():
@@ -20,6 +26,75 @@ def temp_csv_file():
         os.unlink(path)
 
 
+@pytest.fixture
+def mock_medicine_manager():
+    """Create a mock medicine manager with default medicines for testing."""
+    mock_manager = Mock(spec=MedicineManager)
+
+    # Default medicines matching the original system
+    default_medicines = {
+        "bupropion": Medicine(
+            key="bupropion",
+            display_name="Bupropion",
+            dosage_info="150/300 mg",
+            quick_doses=["150", "300"],
+            color="#FF6B6B",
+            default_enabled=True
+        ),
+        "hydroxyzine": Medicine(
+            key="hydroxyzine",
+            display_name="Hydroxyzine",
+            dosage_info="25 mg",
+            quick_doses=["25", "50"],
+            color="#4ECDC4",
+            default_enabled=False
+        ),
+        "gabapentin": Medicine(
+            key="gabapentin",
+            display_name="Gabapentin",
+            dosage_info="100 mg",
+            quick_doses=["100", "300", "600"],
+            color="#45B7D1",
+            default_enabled=False
+        ),
+        "propranolol": Medicine(
+            key="propranolol",
+            display_name="Propranolol",
+            dosage_info="10 mg",
+            quick_doses=["10", "20", "40"],
+            color="#96CEB4",
+            default_enabled=True
+        ),
+        "quetiapine": Medicine(
+            key="quetiapine",
+            display_name="Quetiapine",
+            dosage_info="25 mg",
+            quick_doses=["25", "50", "100"],
+            color="#FFEAA7",
+            default_enabled=False
+        )
+    }
+
+    mock_manager.get_medicine_keys.return_value = list(default_medicines.keys())
+    mock_manager.get_all_medicines.return_value = default_medicines
+    mock_manager.get_medicine.side_effect = lambda key: default_medicines.get(key)
+    mock_manager.get_graph_colors.return_value = {k: v.color for k, v in default_medicines.items()}
+    mock_manager.get_quick_doses.side_effect = lambda key: default_medicines.get(key, Medicine("", "", "", [], "", False)).quick_doses
+
+    return mock_manager
+
+
+@pytest.fixture
+def mock_pathology_manager():
+    """Create a mock pathology manager with default pathologies for testing."""
+    mock_manager = Mock()
+
+    # Default pathologies matching the original system
+    mock_manager.get_pathology_keys.return_value = ["depression", "anxiety", "sleep", "appetite"]
+
+    return mock_manager
+
+
 @pytest.fixture
 def sample_data():
     """Sample data for testing."""
@@ -89,3 +164,33 @@ def sample_dose_data():
         'nan_value': 'nan',  # Should be 0
         'no_units': '2025-07-28 18:59:45:10|2025-07-28 19:34:19:5',  # Should sum to 15
     }
+
+
+@pytest.fixture
+def legend_test_dataframe():
+    """DataFrame specifically designed for testing legend functionality."""
+    return pd.DataFrame({
+        'date': ['2024-01-01', '2024-01-02', '2024-01-03'],
+        'depression': [3, 2, 4],
+        'anxiety': [2, 3, 1],
+        'sleep': [4, 3, 5],
+        'appetite': [3, 4, 2],
+        # Medicine with consistent doses for average testing
+        'bupropion': [1, 1, 1],
+        'bupropion_doses': ['2024-01-01 08:00:00:100mg',
+                           '2024-01-02 08:00:00:200mg',
+                           '2024-01-03 08:00:00:150mg'],  # Average: 150mg
+        # Medicine with varying doses
+        'propranolol': [1, 1, 0],
+        'propranolol_doses': ['2024-01-01 12:00:00:10mg',
+                             '2024-01-02 12:00:00:20mg',
+                             ''],  # Average: 15mg (10+20)/2
+        # Medicines without dose data
+        'hydroxyzine': [0, 0, 0],
+        'hydroxyzine_doses': ['', '', ''],
+        'gabapentin': [0, 0, 0],
+        'gabapentin_doses': ['', '', ''],
+        'quetiapine': [0, 0, 0],
+        'quetiapine_doses': ['', '', ''],
+        'note': ['Test note 1', 'Test note 2', 'Test note 3']
+    })

tests/test_constants.py

@@ -2,7 +2,6 @@
 Tests for constants module.
 """
 import os
-import pytest
 from unittest.mock import patch
 
 import sys

tests/test_data_manager.py

@@ -3,10 +3,7 @@ Tests for the DataManager class.
 """
 import os
 import csv
-import pytest
-import pandas as pd
-from unittest.mock import Mock, patch
-import tempfile
+from unittest.mock import patch
 
 import sys
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
@@ -17,20 +14,21 @@ from src.data_manager import DataManager
 class TestDataManager:
     """Test cases for the DataManager class."""
 
-    def test_init(self, temp_csv_file, mock_logger):
+    def test_init(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager):
         """Test DataManager initialization."""
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
         assert dm.filename == temp_csv_file
         assert dm.logger == mock_logger
+        assert dm.medicine_manager == mock_medicine_manager
         assert os.path.exists(temp_csv_file)
 
-    def test_initialize_csv_creates_file_with_headers(self, temp_csv_file, mock_logger):
+    def test_initialize_csv_creates_file_with_headers(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager):
         """Test that initialize_csv creates a file with proper headers."""
         # Remove the file if it exists
         if os.path.exists(temp_csv_file):
             os.unlink(temp_csv_file)
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
 
         # Check file exists and has correct headers
         assert os.path.exists(temp_csv_file)
@@ -45,33 +43,33 @@ class TestDataManager:
             ]
             assert headers == expected_headers
 
-    def test_initialize_csv_does_not_overwrite_existing_file(self, temp_csv_file, mock_logger):
+    def test_initialize_csv_does_not_overwrite_existing_file(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager):
         """Test that initialize_csv does not overwrite existing file."""
         # Write some data to the file first
         with open(temp_csv_file, 'w') as f:
             f.write("existing,data\n1,2\n")
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
 
         # Check that existing data is preserved
         with open(temp_csv_file, 'r') as f:
             content = f.read()
             assert "existing,data" in content
 
-    def test_load_data_empty_file(self, temp_csv_file, mock_logger):
+    def test_load_data_empty_file(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager):
         """Test loading data from an empty file."""
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
         df = dm.load_data()
         assert df.empty
 
-    def test_load_data_nonexistent_file(self, mock_logger):
+    def test_load_data_nonexistent_file(self, mock_logger, mock_medicine_manager, mock_pathology_manager):
         """Test loading data from a nonexistent file."""
-        dm = DataManager("nonexistent.csv", mock_logger)
+        dm = DataManager("nonexistent.csv", mock_logger, mock_medicine_manager, mock_pathology_manager)
         df = dm.load_data()
         assert df.empty
         mock_logger.warning.assert_called()
 
-    def test_load_data_with_valid_data(self, temp_csv_file, mock_logger, sample_data):
+    def test_load_data_with_valid_data(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager, sample_data):
         """Test loading valid data from CSV file."""
         # Write sample data to file
         with open(temp_csv_file, 'w', newline='') as f:
@@ -86,7 +84,7 @@ class TestDataManager:
             # Write sample data
             writer.writerows(sample_data)
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
         df = dm.load_data()
 
         assert not df.empty
@@ -102,7 +100,7 @@ class TestDataManager:
         assert df["anxiety"].dtype == int
         assert df["note"].dtype == object
 
-    def test_load_data_sorted_by_date(self, temp_csv_file, mock_logger):
+    def test_load_data_sorted_by_date(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager):
         """Test that loaded data is sorted by date."""
         # Write data in random order
         unsorted_data = [
@@ -121,7 +119,7 @@ class TestDataManager:
             ])
             writer.writerows(unsorted_data)
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
         df = dm.load_data()
 
         # Check that data is sorted by date
@@ -129,10 +127,10 @@ class TestDataManager:
         assert df.iloc[1]["note"] == "second"
         assert df.iloc[2]["note"] == "third"
 
-    def test_add_entry_success(self, temp_csv_file, mock_logger):
+    def test_add_entry_success(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager):
         """Test successfully adding an entry."""
-        dm = DataManager(temp_csv_file, mock_logger)
-        entry = ["2024-01-01", 3, 2, 4, 3, 1, 0, 2, 1, "Test note"]
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
+        entry = ["2024-01-01", 3, 2, 4, 3, 1, "", 0, "", 2, "", 1, "", 0, "", "Test note"]
 
         result = dm.add_entry(entry)
         assert result is True
@@ -143,7 +141,7 @@ class TestDataManager:
         assert df.iloc[0]["date"] == "2024-01-01"
         assert df.iloc[0]["note"] == "Test note"
 
-    def test_add_entry_duplicate_date(self, temp_csv_file, mock_logger, sample_data):
+    def test_add_entry_duplicate_date(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager, sample_data):
         """Test adding entry with duplicate date."""
         # Add initial data
         with open(temp_csv_file, 'w', newline='') as f:
@@ -156,7 +154,7 @@ class TestDataManager:
             ])
             writer.writerows(sample_data)
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
         # Try to add entry with existing date
         duplicate_entry = ["2024-01-01", 5, 5, 5, 5, 1, "", 1, "", 1, "", 1, "", 0, "", "Duplicate"]
 
@@ -164,7 +162,7 @@ class TestDataManager:
         assert result is False
         mock_logger.warning.assert_called_with("Entry with date 2024-01-01 already exists.")
 
-    def test_update_entry_success(self, temp_csv_file, mock_logger, sample_data):
+    def test_update_entry_success(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager, sample_data):
         """Test successfully updating an entry."""
         # Add initial data
         with open(temp_csv_file, 'w', newline='') as f:
@@ -177,7 +175,7 @@ class TestDataManager:
             ])
             writer.writerows(sample_data)
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
         updated_values = ["2024-01-01", 5, 5, 5, 5, 2, "", 2, "", 2, "", 2, "", 1, "", "Updated note"]
 
         result = dm.update_entry("2024-01-01", updated_values)
@@ -189,7 +187,7 @@ class TestDataManager:
         assert updated_row["depression"] == 5
         assert updated_row["note"] == "Updated note"
 
-    def test_update_entry_change_date(self, temp_csv_file, mock_logger, sample_data):
+    def test_update_entry_change_date(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager, sample_data):
         """Test updating an entry with a date change."""
         # Add initial data
         with open(temp_csv_file, 'w', newline='') as f:
@@ -202,7 +200,7 @@ class TestDataManager:
             ])
             writer.writerows(sample_data)
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
         updated_values = ["2024-01-05", 5, 5, 5, 5, 2, "", 2, "", 2, "", 2, "", 1, "", "Updated note"]
 
         result = dm.update_entry("2024-01-01", updated_values)
@@ -213,7 +211,7 @@ class TestDataManager:
         assert not any(df["date"] == "2024-01-01")
         assert any(df["date"] == "2024-01-05")
 
-    def test_update_entry_duplicate_date(self, temp_csv_file, mock_logger, sample_data):
+    def test_update_entry_duplicate_date(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager, sample_data):
         """Test updating entry to a date that already exists."""
         # Add initial data
         with open(temp_csv_file, 'w', newline='') as f:
@@ -226,7 +224,7 @@ class TestDataManager:
             ])
             writer.writerows(sample_data)
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
         # Try to change date to one that already exists
         updated_values = ["2024-01-02", 5, 5, 5, 5, 2, "", 2, "", 2, "", 2, "", 1, "", "Updated note"]
 
@@ -236,7 +234,7 @@ class TestDataManager:
             "Cannot update: entry with date 2024-01-02 already exists."
         )
 
-    def test_delete_entry_success(self, temp_csv_file, mock_logger, sample_data):
+    def test_delete_entry_success(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager, sample_data):
         """Test successfully deleting an entry."""
         # Add initial data
         with open(temp_csv_file, 'w', newline='') as f:
@@ -249,7 +247,7 @@ class TestDataManager:
             ])
             writer.writerows(sample_data)
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
 
         result = dm.delete_entry("2024-01-02")
         assert result is True
@@ -259,7 +257,7 @@ class TestDataManager:
         assert len(df) == 2
         assert not any(df["date"] == "2024-01-02")
 
-    def test_delete_entry_nonexistent(self, temp_csv_file, mock_logger, sample_data):
+    def test_delete_entry_nonexistent(self, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager, sample_data):
         """Test deleting a nonexistent entry."""
         # Add initial data
         with open(temp_csv_file, 'w', newline='') as f:
@@ -272,7 +270,7 @@ class TestDataManager:
             ])
             writer.writerows(sample_data)
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
 
         result = dm.delete_entry("2024-01-10")
         assert result is True  # Should return True even if no matching entry
@@ -282,22 +280,22 @@ class TestDataManager:
         assert len(df) == 3
 
     @patch('pandas.read_csv')
-    def test_load_data_exception_handling(self, mock_read_csv, temp_csv_file, mock_logger):
+    def test_load_data_exception_handling(self, mock_read_csv, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager):
         """Test exception handling in load_data."""
         mock_read_csv.side_effect = Exception("Test error")
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
         df = dm.load_data()
 
         assert df.empty
         mock_logger.error.assert_called_with("Error loading data: Test error")
 
     @patch('builtins.open')
-    def test_add_entry_exception_handling(self, mock_open, temp_csv_file, mock_logger):
+    def test_add_entry_exception_handling(self, mock_open, temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager):
         """Test exception handling in add_entry."""
         mock_open.side_effect = Exception("Test error")
 
-        dm = DataManager(temp_csv_file, mock_logger)
+        dm = DataManager(temp_csv_file, mock_logger, mock_medicine_manager, mock_pathology_manager)
         entry = ["2024-01-01", 3, 2, 4, 3, 1, 0, 2, 1, "Test note"]
 
         result = dm.add_entry(entry)

tests/test_dose_parsing.py

@@ -1,5 +1,4 @@
 import pytest
-from datetime import datetime
 import tkinter as tk
 from src.ui_manager import UIManager
 

tests/test_graph_manager.py

@@ -6,8 +6,7 @@ import pytest
 import pandas as pd
 import tkinter as tk
 from tkinter import ttk
-from unittest.mock import Mock, patch, MagicMock
-import matplotlib.pyplot as plt
+from unittest.mock import Mock, patch
 
 import sys
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
@@ -433,6 +432,329 @@ class TestGraphManager:
                 assert mock_ax.clear.call_count >= 2
                 assert mock_canvas.draw.call_count >= 2
 
+    def test_enhanced_legend_functionality(self, parent_frame):
+        """Test that the enhanced legend displays correctly with medicine data."""
+        df_with_doses = pd.DataFrame({
+            'date': ['2024-01-01', '2024-01-02'],
+            'depression': [3, 2],
+            'anxiety': [2, 3],
+            'sleep': [4, 3],
+            'appetite': [3, 4],
+            'bupropion': [1, 1],
+            'bupropion_doses': ['2024-01-01 08:00:00:150mg', '2024-01-02 08:00:00:200mg'],
+            'hydroxyzine': [0, 0],
+            'hydroxyzine_doses': ['', ''],
+            'gabapentin': [0, 0],
+            'gabapentin_doses': ['', ''],
+            'propranolol': [1, 1],
+            'propranolol_doses': ['2024-01-01 12:00:00:10mg', '2024-01-02 12:00:00:15mg'],
+            'quetiapine': [0, 0],
+            'quetiapine_doses': ['', ''],
+        })
+
+        with patch('matplotlib.pyplot.subplots') as mock_subplots:
+            mock_fig = Mock()
+            mock_ax = Mock()
+            mock_ax.get_legend_handles_labels.return_value = ([], [])
+            mock_subplots.return_value = (mock_fig, mock_ax)
+
+            with patch('graph_manager.FigureCanvasTkAgg') as mock_canvas_class:
+                mock_canvas = Mock()
+                mock_canvas_class.return_value = mock_canvas
+
+                gm = GraphManager(parent_frame)
+
+                # Enable some medicine toggles
+                gm.toggle_vars["bupropion"].set(True)
+                gm.toggle_vars["propranolol"].set(True)
+                gm.toggle_vars["hydroxyzine"].set(True)  # No dose data
+
+                gm.update_graph(df_with_doses)
+
+                # Verify that legend is called with enhanced parameters
+                mock_ax.legend.assert_called()
+                legend_call = mock_ax.legend.call_args
+
+                # Check that enhanced legend parameters are used
+                assert 'ncol' in legend_call.kwargs
+                assert legend_call.kwargs['ncol'] == 2
+                assert 'fontsize' in legend_call.kwargs
+                assert legend_call.kwargs['fontsize'] == 'small'
+                assert 'frameon' in legend_call.kwargs
+                assert legend_call.kwargs['frameon'] is True
+
+    def test_legend_with_medicines_without_data(self, parent_frame):
+        """Test that medicines without dose data are properly tracked in legend."""
+        df_with_partial_doses = pd.DataFrame({
+            'date': ['2024-01-01'],
+            'depression': [3],
+            'anxiety': [2],
+            'sleep': [4],
+            'appetite': [3],
+            'bupropion': [1],
+            'bupropion_doses': ['2024-01-01 08:00:00:150mg'],
+            'hydroxyzine': [0],
+            'hydroxyzine_doses': [''],  # No dose data
+            'gabapentin': [0],
+            'gabapentin_doses': [''],  # No dose data
+            'propranolol': [0],
+            'propranolol_doses': [''],
+            'quetiapine': [0],
+            'quetiapine_doses': [''],
+        })
+
+        with patch('matplotlib.pyplot.subplots') as mock_subplots:
+            mock_fig = Mock()
+            mock_ax = Mock()
+
+            # Mock the legend handles and labels
+            original_handles = [Mock()]
+            original_labels = ['Bupropion (avg: 150.0mg)']
+            mock_ax.get_legend_handles_labels.return_value = (original_handles, original_labels)
+
+            mock_subplots.return_value = (mock_fig, mock_ax)
+
+            with patch('graph_manager.FigureCanvasTkAgg') as mock_canvas_class:
+                mock_canvas = Mock()
+                mock_canvas_class.return_value = mock_canvas
+
+                gm = GraphManager(parent_frame)
+
+                # Enable medicines with and without data
+                gm.toggle_vars["bupropion"].set(True)  # Has data
+                gm.toggle_vars["hydroxyzine"].set(True)  # No data
+                gm.toggle_vars["gabapentin"].set(True)  # No data
+
+                gm.update_graph(df_with_partial_doses)
+
+                # Verify legend was called
+                mock_ax.legend.assert_called()
+
+                # Check that the legend call includes additional handles/labels
+                legend_call = mock_ax.legend.call_args
+                handles, labels = legend_call.args[:2]
+
+                # Should have more labels than just the original ones
+                assert len(labels) > len(original_labels)
+
+    def test_average_dose_calculation_in_legend(self, parent_frame):
+        """Test that average doses are correctly calculated and displayed in legend."""
+        df_with_varying_doses = pd.DataFrame({
+            'date': ['2024-01-01', '2024-01-02', '2024-01-03'],
+            'depression': [3, 2, 4],
+            'anxiety': [2, 3, 1],
+            'sleep': [4, 3, 5],
+            'appetite': [3, 4, 2],
+            'bupropion': [1, 1, 1],
+            'bupropion_doses': ['2024-01-01 08:00:00:100mg',
+                               '2024-01-02 08:00:00:200mg',
+                               '2024-01-03 08:00:00:150mg'],  # Average should be 150mg
+            'propranolol': [1, 1, 0],
+            'propranolol_doses': ['2024-01-01 12:00:00:10mg',
+                                 '2024-01-02 12:00:00:20mg',
+                                 ''],  # Average should be 15mg
+            'hydroxyzine': [0, 0, 0],
+            'hydroxyzine_doses': ['', '', ''],
+            'gabapentin': [0, 0, 0],
+            'gabapentin_doses': ['', '', ''],
+            'quetiapine': [0, 0, 0],
+            'quetiapine_doses': ['', '', ''],
+        })
+
+        with patch('matplotlib.pyplot.subplots') as mock_subplots:
+            mock_fig = Mock()
+            mock_ax = Mock()
+            mock_subplots.return_value = (mock_fig, mock_ax)
+
+            with patch('graph_manager.FigureCanvasTkAgg') as mock_canvas_class:
+                mock_canvas = Mock()
+                mock_canvas_class.return_value = mock_canvas
+
+                gm = GraphManager(parent_frame)
+
+                # Test the average calculation directly
+                bup_avg = gm._calculate_daily_dose('2024-01-01 08:00:00:100mg')
+                assert bup_avg == 100.0
+
+                prop_avg = gm._calculate_daily_dose('2024-01-01 12:00:00:10mg')
+                assert prop_avg == 10.0
+
+                # Test with full data
+                gm.toggle_vars["bupropion"].set(True)
+                gm.toggle_vars["propranolol"].set(True)
+                gm.update_graph(df_with_varying_doses)
+
+                # Verify that bars were plotted (indicating dose data was processed)
+                mock_ax.bar.assert_called()
+
+    def test_legend_positioning_and_styling(self, parent_frame):
+        """Test that legend positioning and styling parameters are correctly applied."""
+        df_simple = pd.DataFrame({
+            'date': ['2024-01-01'],
+            'depression': [3],
+            'anxiety': [2],
+            'sleep': [4],
+            'appetite': [3],
+            'bupropion': [1],
+            'bupropion_doses': ['2024-01-01 08:00:00:150mg'],
+            'hydroxyzine': [0],
+            'hydroxyzine_doses': [''],
+            'gabapentin': [0],
+            'gabapentin_doses': [''],
+            'propranolol': [0],
+            'propranolol_doses': [''],
+            'quetiapine': [0],
+            'quetiapine_doses': [''],
+        })
+
+        with patch('matplotlib.pyplot.subplots') as mock_subplots:
+            mock_fig = Mock()
+            mock_ax = Mock()
+            mock_ax.get_legend_handles_labels.return_value = ([Mock()], ['Test Label'])
+            mock_subplots.return_value = (mock_fig, mock_ax)
+
+            with patch('graph_manager.FigureCanvasTkAgg') as mock_canvas_class:
+                mock_canvas = Mock()
+                mock_canvas_class.return_value = mock_canvas
+
+                gm = GraphManager(parent_frame)
+                gm.update_graph(df_simple)
+
+                # Verify legend styling parameters
+                mock_ax.legend.assert_called()
+                legend_call = mock_ax.legend.call_args
+
+                expected_params = {
+                    'loc': 'upper left',
+                    'bbox_to_anchor': (0, 1),
+                    'ncol': 2,
+                    'fontsize': 'small',
+                    'frameon': True,
+                    'fancybox': True,
+                    'shadow': True,
+                    'framealpha': 0.9
+                }
+
+                for param, expected_value in expected_params.items():
+                    assert param in legend_call.kwargs
+                    assert legend_call.kwargs[param] == expected_value
+
+    def test_medicine_tracking_lists(self, parent_frame):
+        """Test that medicines are correctly categorized into with_data and without_data lists."""
+        df_mixed_data = pd.DataFrame({
+            'date': ['2024-01-01', '2024-01-02'],
+            'depression': [3, 2],
+            'anxiety': [2, 3],
+            'sleep': [4, 3],
+            'appetite': [3, 4],
+            # Medicines with data
+            'bupropion': [1, 1],
+            'bupropion_doses': ['2024-01-01 08:00:00:150mg', '2024-01-02 08:00:00:200mg'],
+            'propranolol': [1, 1],
+            'propranolol_doses': ['2024-01-01 12:00:00:10mg', '2024-01-02 12:00:00:15mg'],
+            # Medicines without data (but toggled on)
+            'hydroxyzine': [0, 0],
+            'hydroxyzine_doses': ['', ''],
+            'gabapentin': [0, 0],
+            'gabapentin_doses': ['', ''],
+            'quetiapine': [0, 0],
+            'quetiapine_doses': ['', ''],
+        })
+
+        with patch('matplotlib.pyplot.subplots') as mock_subplots:
+            mock_fig = Mock()
+            mock_ax = Mock()
+            mock_ax.get_legend_handles_labels.return_value = ([], [])
+            mock_subplots.return_value = (mock_fig, mock_ax)
+
+            with patch('graph_manager.FigureCanvasTkAgg') as mock_canvas_class:
+                mock_canvas = Mock()
+                mock_canvas_class.return_value = mock_canvas
+
+                gm = GraphManager(parent_frame)
+
+                # Enable all medicines
+                gm.toggle_vars["bupropion"].set(True)      # Has data
+                gm.toggle_vars["propranolol"].set(True)    # Has data
+                gm.toggle_vars["hydroxyzine"].set(True)    # No data
+                gm.toggle_vars["gabapentin"].set(True)     # No data
+                gm.toggle_vars["quetiapine"].set(False)    # Disabled
+
+                gm.update_graph(df_mixed_data)
+
+                # Verify that the method was called and plotting occurred
+                mock_ax.bar.assert_called()  # Should be called for medicines with data
+                mock_ax.legend.assert_called()  # Legend should be created
+
+    def test_legend_dummy_handle_creation(self, parent_frame):
+        """Test that dummy handles are created for medicines without data."""
+        df_no_dose_data = pd.DataFrame({
+            'date': ['2024-01-01'],
+            'depression': [3],
+            'anxiety': [2],
+            'sleep': [4],
+            'appetite': [3],
+            'bupropion': [0],
+            'bupropion_doses': [''],
+            'hydroxyzine': [0],
+            'hydroxyzine_doses': [''],
+            'gabapentin': [0],
+            'gabapentin_doses': [''],
+            'propranolol': [0],
+            'propranolol_doses': [''],
+            'quetiapine': [0],
+            'quetiapine_doses': [''],
+        })
+
+        with patch('matplotlib.pyplot.subplots') as mock_subplots:
+            mock_fig = Mock()
+            mock_ax = Mock()
+            mock_ax.get_legend_handles_labels.return_value = ([Mock()], ['Depression'])
+            mock_subplots.return_value = (mock_fig, mock_ax)
+
+            with patch('graph_manager.FigureCanvasTkAgg') as mock_canvas_class:
+                mock_canvas = Mock()
+                mock_canvas_class.return_value = mock_canvas
+
+                # Mock Rectangle import for dummy handle creation
+                with patch('matplotlib.patches.Rectangle') as mock_rectangle:
+                    mock_dummy_handle = Mock()
+                    mock_rectangle.return_value = mock_dummy_handle
+
+                    gm = GraphManager(parent_frame)
+
+                    # Enable some medicines without data
+                    gm.toggle_vars["hydroxyzine"].set(True)
+                    gm.toggle_vars["gabapentin"].set(True)
+
+                    gm.update_graph(df_no_dose_data)
+
+                    # If there are medicines without data, Rectangle should be called
+                    # to create dummy handles
+                    if gm.toggle_vars["hydroxyzine"].get() or gm.toggle_vars["gabapentin"].get():
+                        mock_rectangle.assert_called()
+
+    def test_empty_dataframe_legend_handling(self, parent_frame):
+        """Test that legend is handled correctly with empty DataFrame."""
+        empty_df = pd.DataFrame()
+
+        with patch('matplotlib.pyplot.subplots') as mock_subplots:
+            mock_fig = Mock()
+            mock_ax = Mock()
+            mock_subplots.return_value = (mock_fig, mock_ax)
+
+            with patch('graph_manager.FigureCanvasTkAgg') as mock_canvas_class:
+                mock_canvas = Mock()
+                mock_canvas_class.return_value = mock_canvas
+
+                gm = GraphManager(parent_frame)
+                gm.update_graph(empty_df)
+
+                # With empty data, legend should not be called
+                mock_ax.legend.assert_not_called()
+                mock_ax.clear.assert_called()
+                mock_canvas.draw.assert_called()
+
     def test_dose_calculation_comprehensive(self, parent_frame, sample_dose_data):
         """Test dose calculation with comprehensive test cases."""
         gm = GraphManager(parent_frame)

tests/test_init.py

@@ -2,7 +2,6 @@
 Tests for init module.
 """
 import os
-import tempfile
 import pytest
 from unittest.mock import patch, Mock
 

tests/test_logger.py

@@ -3,9 +3,8 @@ Tests for logger module.
 """
 import os
 import logging
-import tempfile
 import pytest
-from unittest.mock import patch, Mock
+from unittest.mock import patch
 
 import sys
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))

tests/test_main.py

@@ -4,7 +4,7 @@ Tests for the main application and MedTrackerApp class.
 import os
 import pytest
 import tkinter as tk
-from unittest.mock import Mock, patch, MagicMock
+from unittest.mock import Mock, patch
 import pandas as pd
 
 import sys

tests/test_ui_manager.py

@@ -5,8 +5,7 @@ import os
 import pytest
 import tkinter as tk
 from tkinter import ttk
-from unittest.mock import Mock, patch, MagicMock
-from datetime import datetime
+from unittest.mock import Mock, patch
 
 import sys
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))

uv.lock

@@ -20,6 +20,28 @@ wheels = [
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