feat: Bump version to 1.6.1 in Makefile, pyproject.toml, and CHANGELOG.md

feat: Remove outdated testing documentation and add comprehensive development and feature guides
- Deleted `TESTING_SETUP.md` and `TEST_UPDATES_SUMMARY.md` as they were outdated. - Introduced `CHANGELOG.md` to document notable changes and version history. - Added `DEVELOPMENT.md` for detailed development setup, testing framework, and debugging guidance. - Created `FEATURES.md` to outline core features and functionalities of TheChart. - Established `README.md` as a centralized documentation index for users and developers.
2025-07-31 11:42:13 -07:00 · 2025-07-31 11:39:12 -07:00 · 2025-07-31 11:20:18 -07:00 · 2025-07-31 11:11:21 -07:00 · 2025-07-31 10:18:09 -07:00 · 2025-07-31 10:06:25 -07:00
59 changed files with 4156 additions and 4140 deletions
@@ -1,5 +1,5 @@
 # Data files (except example data)
-*.csv
+thechart_data.csv
 ### !thechart_data.csv
 # Environment files
@@ -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": []
 		}
 	]
 }
@@ -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
@@ -1,5 +1,5 @@
 TARGET=thechart
-VERSION=1.0.0
+VERSION=1.6.1
 ROOT=/home/will
 ICON=chart-671.png
 SHELL=fish
@@ -147,7 +147,7 @@ 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
@@ -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.
@@ -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.
@@ -1,15 +1,34 @@
-# Thechart
+# TheChart
-App to manage medication and see the evolution of its effects.
+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
 - **[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 +198,85 @@ 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
 For complete feature documentation, see **[docs/FEATURES.md](docs/FEATURES.md)**.
 ## Development
-### Code Quality Tools
+### Testing Framework
-The project includes several code quality tools that are automatically set up:
+TheChart includes a comprehensive testing suite with **93% code coverage**:
-#### Formatting and Linting
+```bash
-```shell
+# Run all tests
-make format  # Format code with ruff
+make test
-make lint    # Run linter checks
+
 # 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:**
+**Testing Statistics:**
-```shell
+- **112 total tests** across 6 test modules
-uv run ruff format .  # Format code
+- **93% overall coverage** (482 statements, 33 missed)
-uv run ruff check .   # Check for issues
+- **Pre-commit testing** prevents broken commits
 ```
-#### Running Tests
+### Code Quality
-```shell
+```bash
-make test    # Run unit tests
+# Format code
-```
+make format
-**With uv directly:**
+# Check code quality
-```shell
+make lint
-uv run pytest  # Run tests with pytest
+
 # Run pre-commit checks
 pre-commit run --all-files
 ```
 ### Package Management with uv
-
+```bash
-#### Adding Dependencies
+# Add dependencies
 ```shell
 # Add a runtime dependency
 uv add package-name
-# Add a development dependency
+# Add development dependencies
 uv add --dev package-name
-# Add specific version
+# Update dependencies
-uv add "package-name>=1.0.0"
+uv sync --upgrade
 ```
-#### Removing Dependencies
+# Remove dependencies
 ```shell
 uv remove package-name
 ```
-#### Updating Dependencies
+For detailed development information, see **[docs/DEVELOPMENT.md](docs/DEVELOPMENT.md)**.
 ```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
 ## Deployment
@@ -312,43 +341,33 @@ python src/main.py
 ## Docker Usage
-## Docker Usage
+### Quick Start with Docker
-
+```bash
-### Building the Container Image
+# Build and start the application
 Build a multi-platform Docker image:
 ```shell
 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:**
+# Stop the application
 ```shell
 make stop
 ```
-3. **Access container shell:**
+# Access container shell
 ```shell
 make attach
 ```
 ### Manual Docker Commands
-If you prefer using Docker directly:
+```bash
 ```shell
 # Build image
 docker build -t thechart .
-# Run container
+# Run container with X11 forwarding (Linux)
-docker run -it --rm thechart
+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 +426,10 @@ 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.
+### Essential Commands
-
+```bash
 ### 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
 # Development workflow
 make install    # One-time setup
 make run        # Run application
@@ -451,6 +446,35 @@ 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 +495,3 @@ 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
@@ -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.
@@ -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()
@@ -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).
@@ -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).
@@ -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).
@@ -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).
@@ -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
    }
  ]
 }
@@ -0,0 +1 @@
 date,depression,anxiety,sleep,appetite,bupropion,bupropion_doses,hydroxyzine,hydroxyzine_doses,gabapentin,gabapentin_doses,propranolol,propranolol_doses,quetiapine,quetiapine_doses,note
@@ -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"
        }
    ]
 }
@@ -1,6 +1,6 @@
 [project]
 name = "thechart"
-version = "1.2.1"
+version = "1.6.1"
 description = "Chart to monitor your medication intake over time."
 readme = "README.md"
 requires-python = ">=3.13"
@@ -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")
@@ -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()
@@ -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()
@@ -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())
@@ -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!")
@@ -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()
@@ -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()
@@ -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")
@@ -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()
@@ -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()
@@ -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)
@@ -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()
@@ -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()
@@ -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)
@@ -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")
@@ -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()
@@ -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)
@@ -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!")
@@ -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!")
@@ -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()
@@ -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)
@@ -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()
@@ -4,40 +4,47 @@ 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."""
-    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
        self._initialize_csv_file()
    def _get_csv_headers(self) -> list[str]:
        """Get CSV headers based on current pathology and medicine configuration."""
        # 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"])
        return headers + ["note"]
    def _initialize_csv_file(self) -> None:
-        """Create CSV file with headers if it doesn't exist."""
+        """Create CSV file with headers if it doesn't exist or is empty."""
-        if not os.path.exists(self.filename):
+        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(
+                writer.writerow(self._get_csv_headers())
                    [
                        "date",
                        "depression",
                        "anxiety",
                        "sleep",
                        "appetite",
                        "bupropion",
                        "bupropion_doses",
                        "hydroxyzine",
                        "hydroxyzine_doses",
                        "gabapentin",
                        "gabapentin_doses",
                        "propranolol",
                        "propranolol_doses",
                        "quetiapine",
                        "quetiapine_doses",
                        "note",
                    ]
                )
    def load_data(self) -> pd.DataFrame:
        """Load data from CSV file."""
@@ -46,27 +53,19 @@ class DataManager:
            return pd.DataFrame()
        try:
-            df: pd.DataFrame = pd.read_csv(
+            # Build dtype dictionary dynamically
-                self.filename,
+            dtype_dict = {"date": str, "note": str}
-                dtype={
+
-                    "depression": int,
+            # Add pathology types
-                    "anxiety": int,
+            for pathology_key in self.pathology_manager.get_pathology_keys():
-                    "sleep": int,
+                dtype_dict[pathology_key] = int
-                    "appetite": int,
+
-                    "bupropion": int,
+            # Add medicine types
-                    "bupropion_doses": str,
+            for medicine_key in self.medicine_manager.get_medicine_keys():
-                    "hydroxyzine": int,
+                dtype_dict[medicine_key] = int
-                    "hydroxyzine_doses": str,
+                dtype_dict[f"{medicine_key}_doses"] = str
-                    "gabapentin": int,
+
-                    "gabapentin_doses": str,
+            df: pd.DataFrame = pd.read_csv(self.filename, dtype=dtype_dict).fillna("")
                    "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)
        except pd.errors.EmptyDataError:
            self.logger.warning("CSV file is empty. No data to load.")
@@ -107,69 +106,24 @@ class DataManager:
                )
                return False
-            # Find the row to update using original_date as a unique identifier
+            # Get current CSV headers to match with values
-            # Handle both old format (10 columns) and new format (16 columns)
+            headers = self._get_csv_headers()
-            if len(values) == 16:
+
-                # New format with all dose columns including quetiapine
+            # Ensure we have the right number of values
-                df.loc[
+            if len(values) != len(headers):
-                    df["date"] == original_date,
+                self.logger.warning(
-                    [
+                    f"Value count mismatch: expected {len(headers)}, got {len(values)}"
-                        "date",
+                )
-                        "depression",
+                # Pad with defaults if too few values
-                        "anxiety",
+                while len(values) < len(headers):
-                        "sleep",
+                    header = headers[len(values)]
-                        "appetite",
+                    if header == "note" or header.endswith("_doses"):
-                        "bupropion",
+                        values.append("")
-                        "bupropion_doses",
+                    else:
-                        "hydroxyzine",
+                        values.append(0)
-                        "hydroxyzine_doses",
+
-                        "gabapentin",
+            # Update the row using column names
-                        "gabapentin_doses",
+            df.loc[df["date"] == original_date, headers] = values
                        "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:
@@ -189,57 +143,6 @@ class DataManager:
            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]]:
@@ -7,25 +7,48 @@ 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."""
-    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 toggle variables for chart elements
+        self._initialize_toggle_vars()
-        self.toggle_vars: dict[str, tk.BooleanVar] = {
+        self._setup_ui()
            "depression": tk.BooleanVar(value=True),
            "anxiety": tk.BooleanVar(value=True),
            "sleep": tk.BooleanVar(value=True),
            "appetite": tk.BooleanVar(value=True),
        }
    def _initialize_toggle_vars(self) -> None:
        """Initialize toggle variables for chart elements."""
        self.toggle_vars: dict[str, tk.BooleanVar] = {}
        # Initialize pathology toggles dynamically
        for pathology_key in self.pathology_manager.get_pathology_keys():
            pathology = self.pathology_manager.get_pathology(pathology_key)
            default_value = pathology.default_enabled if pathology else True
            self.toggle_vars[pathology_key] = tk.BooleanVar(value=default_value)
        # Add medicine toggles dynamically
        for medicine_key in self.medicine_manager.get_medicine_keys():
            medicine = self.medicine_manager.get_medicine(medicine_key)
            default_value = medicine.default_enabled if medicine else False
            self.toggle_vars[medicine_key] = tk.BooleanVar(value=default_value)
    def _setup_ui(self) -> None:
        """Set up the UI components."""
        # Create control frame for toggles
        self.control_frame: ttk.Frame = ttk.Frame(self.parent_frame)
        self.control_frame.grid(row=0, column=0, sticky="ew", padx=5, pady=5)
@@ -59,21 +82,35 @@ class GraphManager:
            side="left", padx=5
        )
-        toggle_configs = [
+        # Pathologies toggles - dynamic based on pathology manager
-            ("depression", "Depression"),
+        pathologies_frame = ttk.LabelFrame(self.control_frame, text="Pathologies")
-            ("anxiety", "Anxiety"),
+        pathologies_frame.pack(side="left", padx=5, pady=2)
            ("sleep", "Sleep"),
            ("appetite", "Appetite"),
        ]
-        for key, label in toggle_configs:
+        for pathology_key in self.pathology_manager.get_pathology_keys():
-            checkbox = ttk.Checkbutton(
+            pathology = self.pathology_manager.get_pathology(pathology_key)
-                self.control_frame,
+            if pathology:
-                text=label,
+                checkbox = ttk.Checkbutton(
-                variable=self.toggle_vars[key],
+                    pathologies_frame,
-                command=self._handle_toggle_changed,
+                    text=pathology.display_name,
-            )
+                    variable=self.toggle_vars[pathology_key],
-            checkbox.pack(side="left", padx=5)
+                    command=self._handle_toggle_changed,
                )
                checkbox.pack(side="left", padx=3)
        # Medicines toggles - dynamic based on medicine manager
        medicines_frame = ttk.LabelFrame(self.control_frame, text="Medicines")
        medicines_frame.pack(side="left", padx=5, pady=2)
        for medicine_key in self.medicine_manager.get_medicine_keys():
            medicine = self.medicine_manager.get_medicine(medicine_key)
            if medicine:
                checkbox = ttk.Checkbutton(
                    medicines_frame,
                    text=medicine.display_name,
                    variable=self.toggle_vars[medicine_key],
                    command=self._handle_toggle_changed,
                )
                checkbox.pack(side="left", padx=3)
    def _handle_toggle_changed(self) -> None:
        """Handle toggle changes by replotting the graph."""
@@ -98,30 +135,110 @@ class GraphManager:
            # Track if any series are plotted
            has_plotted_series = False
-            # Plot data series based on toggle states
+            # Plot pathology data series based on toggle states
-            if self.toggle_vars["depression"].get():
+            for pathology_key in self.pathology_manager.get_pathology_keys():
-                self._plot_series(
+                if self.toggle_vars[pathology_key].get():
-                    df, "depression", "Depression (0:good, 10:bad)", "o", "-"
+                    pathology = self.pathology_manager.get_pathology(pathology_key)
-                )
+                    if pathology and pathology_key in df.columns:
-                has_plotted_series = True
+                        label = f"{pathology.display_name} ({pathology.scale_info})"
-            if self.toggle_vars["anxiety"].get():
+                        linestyle = (
-                self._plot_series(df, "anxiety", "Anxiety (0:good, 10:bad)", "o", "-")
+                            "dashed"
-                has_plotted_series = True
+                            if pathology.scale_orientation == "inverted"
-            if self.toggle_vars["sleep"].get():
+                            else "-"
-                self._plot_series(df, "sleep", "Sleep (0:bad, 10:good)", "o", "dashed")
+                        )
-                has_plotted_series = True
+                        self._plot_series(df, pathology_key, label, "o", linestyle)
-            if self.toggle_vars["appetite"].get():
+                        has_plotted_series = True
-                self._plot_series(
+
-                    df, "appetite", "Appetite (0:bad, 10:good)", "o", "dashed"
+            # Plot medicine dose data
-                )
+            # Get medicine colors from medicine manager
-                has_plotted_series = True
+            medicine_colors = self.medicine_manager.get_graph_colors()
            # Get medicines dynamically from medicine manager
            medicines = self.medicine_manager.get_medicine_keys()
            # Track medicines with and without data for legend
            medicines_with_data = []
            medicines_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)
                    # Only plot if there are non-zero doses
                    if any(dose > 0 for dose in daily_doses):
                        medicines_with_data.append(medicine)
                        # Scale doses for better visibility
                        # (divide by 10 to fit with 0-10 scale)
                        scaled_doses = [dose / 10 for dose in daily_doses]
                        # Calculate total dosage for this medicine across all days
                        total_medicine_dose = sum(daily_doses)
                        non_zero_doses = [d for d in daily_doses if d > 0]
                        avg_dose = total_medicine_dose / len(non_zero_doses)
                        # Create more informative label
                        label = f"{medicine.capitalize()} (avg: {avg_dose:.1f}mg)"
                        self.ax.bar(
                            df.index,
                            scaled_doses,
                            alpha=0.6,
                            color=medicine_colors.get(medicine, "#DDA0DD"),
                            label=label,
                            width=0.6,
                            bottom=-max(scaled_doses) * 1.1 if scaled_doses else -1,
                        )
                        has_plotted_series = True
                    else:
                        # Medicine is toggled on but has no dose data
                        if self.toggle_vars[medicine].get():
                            medicines_without_data.append(medicine)
            # Configure graph appearance
            if has_plotted_series:
-                self.ax.legend()
+                # Get current legend handles and labels
                handles, labels = self.ax.get_legend_handles_labels()
                # Add information about medicines without data if any are toggled on
                if medicines_without_data:
                    # Add a text note about medicines without dose data
                    med_list = ", ".join(medicines_without_data)
                    info_text = f"Tracked (no doses): {med_list}"
                    labels.append(info_text)
                    # Create a dummy handle for the info text (invisible)
                    from matplotlib.patches import Rectangle
                    dummy_handle = Rectangle(
                        (0, 0), 1, 1, fc="w", fill=False, edgecolor="none", linewidth=0
                    )
                    handles.append(dummy_handle)
                # Create an expanded legend with better formatting
                self.ax.legend(
                    handles,
                    labels,
                    loc="upper left",
                    bbox_to_anchor=(0, 1),
                    ncol=2,  # Display in 2 columns for better space usage
                    fontsize="small",
                    frameon=True,
                    fancybox=True,
                    shadow=True,
                    framealpha=0.9,
                )
            self.ax.set_title("Medication Effects Over Time")
            self.ax.set_xlabel("Date")
-            self.ax.set_ylabel("Rating (0-10)")
+            self.ax.set_ylabel("Rating (0-10) / Dose (mg)")
            # 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]))
            self.fig.autofmt_xdate()
        # Redraw the canvas
@@ -144,6 +261,42 @@ class GraphManager:
            label=label,
        )
    def _calculate_daily_dose(self, dose_str: str) -> float:
        """Calculate total daily dose from dose string format."""
        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
        dose_str = str(dose_str).replace("•", "").strip()
        # Split by | or by spaces if no | present
        dose_entries = dose_str.split("|") if "|" in dose_str else [dose_str]
        for entry in dose_entries:
            entry = entry.strip()
            if not entry:
                continue
            try:
                # Extract dose part after the last colon (timestamp:dose format)
                dose_part = entry.split(":")[-1] if ":" in entry else entry
                # Extract numeric part from dose (e.g., "150mg" -> 150)
                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
                        break
                if dose_value:
                    total_dose += float(dose_value)
            except (ValueError, IndexError):
                continue
        return total_dose
    def close(self) -> None:
        """Clean up resources."""
        plt.close(self.fig)
@@ -2,7 +2,7 @@ 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
@@ -11,6 +11,10 @@ from constants import LOG_LEVEL, LOG_PATH
 from data_manager import DataManager
 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
@@ -42,8 +46,14 @@ class MedTrackerApp:
            logger.debug(f"First argument: {first_argument}")
        # Initialize managers
-        self.ui_manager: UIManager = UIManager(root, logger)
+        self.medicine_manager: MedicineManager = MedicineManager(logger=logger)
-        self.data_manager: DataManager = DataManager(self.filename, 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 +64,9 @@ class MedTrackerApp:
        # Set up the main application UI
        self._setup_main_ui()
        # Add menu bar
        self._setup_menu()
    def _setup_main_ui(self) -> None:
        """Set up the main UI components."""
        import tkinter.ttk as ttk
@@ -74,12 +87,14 @@ 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
        )
        # --- 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 +121,69 @@ 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)
        # 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_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."""
        # 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 +202,25 @@ 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_values = [full_row["date"]]
-                full_row["date"],
+
-                full_row["depression"],
+            # Add pathology data dynamically
-                full_row["anxiety"],
+            for pathology_key in self.pathology_manager.get_pathology_keys():
-                full_row["sleep"],
+                if pathology_key in full_row:
-                full_row["appetite"],
+                    full_values.append(full_row[pathology_key])
-                full_row["bupropion"],
+                else:
-                full_row["bupropion_doses"],
+                    full_values.append(0)
-                full_row["hydroxyzine"],
+
-                full_row["hydroxyzine_doses"],
+            # Add medicine data dynamically
-                full_row["gabapentin"],
+            for medicine_key in self.medicine_manager.get_medicine_keys():
-                full_row["gabapentin_doses"],
+                if medicine_key in full_row:
-                full_row["propranolol"],
+                    full_values.append(full_row[medicine_key])
-                full_row["propranolol_doses"],
+                    full_values.append(full_row.get(f"{medicine_key}_doses", ""))
-                full_row["quetiapine"],
+                else:
-                full_row["quetiapine_doses"],
+                    full_values.extend([0, ""])
-                full_row["note"],
+
-            )
+            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 +238,60 @@ class MedTrackerApp:
        self,
        edit_win: tk.Toplevel,
        original_date: str,
-        date: str,
+        *args,
        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],
    ) -> None:
-        """Save the edited data to the CSV file."""
+        """Save edited data to CSV file with dynamic pathology/medicine support."""
-        values: list[str | int] = [
+        # Parse dynamic arguments
-            date,
+        # Format: date, pathology1, pathology2, ..., medicine1, medicine2,
-            dep,
+        # ..., note, dose_data
-            anx,
+
-            slp,
+        if len(args) < 2:  # At minimum need date and note
-            app,
+            messagebox.showerror("Error", "Invalid save data format", parent=edit_win)
-            bup,
+            return
-            dose_data.get("bupropion", ""),
+
-            hydro,
+        # Extract arguments
-            dose_data.get("hydroxyzine", ""),
+        date = args[0]
-            gaba,
+
-            dose_data.get("gabapentin", ""),
+        # Get pathology count to extract values
-            prop,
+        pathology_keys = self.pathology_manager.get_pathology_keys()
-            dose_data.get("propranolol", ""),
+        medicine_keys = self.medicine_manager.get_medicine_keys()
-            quet,
+
-            dose_data.get("quetiapine", ""),
+        # Expected format: date, pathology_values..., medicine_values...,
-            note,
+        # 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 +324,33 @@ class MedTrackerApp:
        """Add a new entry to the CSV file."""
        # Get current doses for today
        today = self.date_var.get()
-        bupropion_doses = ""
+        dose_values = {}
        hydroxyzine_doses = ""
        gabapentin_doses = ""
        propranolol_doses = ""
        quetiapine_doses = ""
        if today:
-            bup_doses = self.data_manager.get_today_medicine_doses(today, "bupropion")
+            # Get doses for all medicines dynamically
-            hydroxyzine_doses_list = self.data_manager.get_today_medicine_doses(
+            for medicine_key in self.medicine_manager.get_medicine_keys():
-                today, "hydroxyzine"
+                doses = self.data_manager.get_today_medicine_doses(today, medicine_key)
-            )
+                dose_values[f"{medicine_key}_doses"] = "|".join(
-            gaba_doses = self.data_manager.get_today_medicine_doses(today, "gabapentin")
+                    [f"{ts}:{dose}" for ts, dose in doses]
-            prop_doses = self.data_manager.get_today_medicine_doses(
+                )
-                today, "propranolol"
+        else:
-            )
+            # Set empty doses for all medicines
-            quet_doses = self.data_manager.get_today_medicine_doses(today, "quetiapine")
+            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])
+        # Build entry dynamically
-            hydroxyzine_doses = "|".join(
+        entry: list[str | int] = [self.date_var.get()]
                [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])
-        entry: list[str | int] = [
+        # Add pathology data dynamically
-            self.date_var.get(),
+        for pathology_key in self.pathology_manager.get_pathology_keys():
-            self.symptom_vars["depression"].get(),
+            entry.append(self.pathology_vars[pathology_key].get())
-            self.symptom_vars["anxiety"].get(),
+
-            self.symptom_vars["sleep"].get(),
+        # Add medicine data
-            self.symptom_vars["appetite"].get(),
+        for medicine_key in self.medicine_manager.get_medicine_keys():
-            self.medicine_vars["bupropion"][0].get(),
+            entry.append(self.medicine_vars[medicine_key][0].get())
-            bupropion_doses,
+            entry.append(dose_values[f"{medicine_key}_doses"])
-            self.medicine_vars["hydroxyzine"][0].get(),
+
-            hydroxyzine_doses,
+        entry.append(self.note_var.get())
            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(),
        ]
        logger.debug(f"Adding entry: {entry}")
        # Check if date is empty
@@ -317,8 +402,8 @@ class MedTrackerApp:
        """Clear all input fields."""
        logger.debug("Clearing input fields.")
        self.date_var.set("")
-        for key in self.symptom_vars:
+        for key in self.pathology_vars:
-            self.symptom_vars[key].set(0)
+            self.pathology_vars[key].set(0)
        for key in self.medicine_vars:
            self.medicine_vars[key][0].set(0)
        self.note_var.set("")
@@ -336,26 +421,20 @@ class MedTrackerApp:
        # Update the treeview with the data
        if not df.empty:
-            # Only show user-friendly columns in the table (not the dose columns)
+            # Build display columns dynamically (exclude dose columns for table view)
-            display_columns = [
+            display_columns = ["date", "depression", "anxiety", "sleep", "appetite"]
-                "date",
+
-                "depression",
+            # Add medicine columns (without dose columns)
-                "anxiety",
+            for medicine_key in self.medicine_manager.get_medicine_keys():
-                "sleep",
+                display_columns.append(medicine_key)
-                "appetite",
+
-                "bupropion",
+            display_columns.append("note")
                "hydroxyzine",
                "gabapentin",
                "propranolol",
                "quetiapine",
                "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
            for _index, row in display_df.iterrows():
@@ -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.")
@@ -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()
        }
@@ -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.")
@@ -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")
@@ -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()
@@ -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()
@@ -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."""
@@ -40,15 +115,17 @@ def sample_dataframe():
        'sleep': [4, 3, 5],
        'appetite': [3, 4, 2],
        'bupropion': [1, 1, 0],
-        'bupropion_doses': ['', '', ''],
+        'bupropion_doses': ['2024-01-01 08:00:00:150mg', '2024-01-02 08:00:00:300mg', ''],
        'hydroxyzine': [0, 1, 0],
-        'hydroxyzine_doses': ['', '', ''],
+        'hydroxyzine_doses': ['', '2024-01-02 20:00:00:25mg', ''],
        'gabapentin': [2, 2, 1],
-        'gabapentin_doses': ['', '', ''],
+        'gabapentin_doses': ['2024-01-01 12:00:00:100mg|2024-01-01 20:00:00:100mg',
                            '2024-01-02 12:00:00:100mg|2024-01-02 20:00:00:100mg',
                            '2024-01-03 12:00:00:100mg'],
        'propranolol': [1, 0, 1],
-        'propranolol_doses': ['', '', ''],
+        'propranolol_doses': ['2024-01-01 12:00:00:10mg', '', '2024-01-03 12:00:00:20mg'],
        'quetiapine': [0, 1, 0],
-        'quetiapine_doses': ['', '', ''],
+        'quetiapine_doses': ['', '2024-01-02 22:00:00:50mg', ''],
        'note': ['Test note 1', 'Test note 2', '']
    })
@@ -72,3 +149,48 @@ def mock_env_vars(monkeypatch):
    monkeypatch.setenv("LOG_LEVEL", "DEBUG")
    monkeypatch.setenv("LOG_PATH", "/tmp/test_logs")
    monkeypatch.setenv("LOG_CLEAR", "False")
@pytest.fixture
 def sample_dose_data():
    """Sample dose data for testing dose calculation."""
    return {
        'standard_format': '2025-07-28 18:59:45:150mg|2025-07-28 19:34:19:75mg',  # Should sum to 225
        'with_bullets': '• • • • 2025-07-30 07:50:00:300',  # Should be 300
        'decimal_doses': '2025-07-28 18:59:45:12.5mg|2025-07-28 19:34:19:7.5mg',  # Should sum to 20
        'no_timestamp': '100mg|50mg',  # Should sum to 150
        'mixed_format': '• 2025-07-30 22:50:00:10|75mg',  # Should sum to 85
        'empty_string': '',  # Should be 0
        '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']
    })
@@ -2,7 +2,6 @@
 Tests for constants module.
 """
 import os
 import pytest
 from unittest.mock import patch
 import sys
@@ -3,10 +3,7 @@ Tests for the DataManager class.
 """
 import os
 import csv
-import pytest
+from unittest.mock import patch
 import pandas as pd
 from unittest.mock import Mock, patch
 import tempfile
 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)
+        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"]
+        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)
@@ -1,5 +1,4 @@
 import pytest
 from datetime import datetime
 import tkinter as tk
 from src.ui_manager import UIManager
@@ -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
+from unittest.mock import Mock, patch
 import matplotlib.pyplot as plt
 import sys
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
@@ -38,14 +37,32 @@ class TestGraphManager:
        assert gm.parent_frame == parent_frame
        assert isinstance(gm.toggle_vars, dict)
        # Check symptom toggles
        assert "depression" in gm.toggle_vars
        assert "anxiety" in gm.toggle_vars
        assert "sleep" in gm.toggle_vars
        assert "appetite" in gm.toggle_vars
-        # Check that all toggles are initially True
+        # Check medicine toggles
-        for var in gm.toggle_vars.values():
+        assert "bupropion" in gm.toggle_vars
-            assert var.get() is True
+        assert "hydroxyzine" in gm.toggle_vars
        assert "gabapentin" in gm.toggle_vars
        assert "propranolol" in gm.toggle_vars
        assert "quetiapine" in gm.toggle_vars
        # Check that symptom toggles are initially True
        for symptom in ["depression", "anxiety", "sleep", "appetite"]:
            assert gm.toggle_vars[symptom].get() is True
        # Check that some medicine toggles are True by default
        assert gm.toggle_vars["bupropion"].get() is True
        assert gm.toggle_vars["propranolol"].get() is True
        # Check that some medicine toggles are False by default
        assert gm.toggle_vars["hydroxyzine"].get() is False
        assert gm.toggle_vars["gabapentin"].get() is False
        assert gm.toggle_vars["quetiapine"].get() is False
    def test_toggle_controls_creation(self, parent_frame):
        """Test that toggle controls are created properly."""
@@ -55,8 +72,9 @@ class TestGraphManager:
        assert hasattr(gm, 'control_frame')
        assert isinstance(gm.control_frame, ttk.Frame)
-        # Check that toggle variables exist
+        # Check that all toggle variables exist
-        expected_toggles = ["depression", "anxiety", "sleep", "appetite"]
+        expected_toggles = ["depression", "anxiety", "sleep", "appetite",
                           "bupropion", "hydroxyzine", "gabapentin", "propranolol", "quetiapine"]
        for toggle in expected_toggles:
            assert toggle in gm.toggle_vars
            assert isinstance(gm.toggle_vars[toggle], tk.BooleanVar)
@@ -265,3 +283,506 @@ class TestGraphManager:
                # Verify the graph was updated in each case
                assert mock_ax.clear.call_count >= 2
                assert mock_canvas.draw.call_count >= 2
    def test_calculate_daily_dose_empty_input(self, parent_frame):
        """Test dose calculation with empty/invalid input."""
        gm = GraphManager(parent_frame)
        # Test empty string
        assert gm._calculate_daily_dose("") == 0.0
        # Test NaN values
        assert gm._calculate_daily_dose("nan") == 0.0
        assert gm._calculate_daily_dose("NaN") == 0.0
        # Test None (will be converted to string)
        assert gm._calculate_daily_dose(None) == 0.0
    def test_calculate_daily_dose_standard_format(self, parent_frame):
        """Test dose calculation with standard timestamp:dose format."""
        gm = GraphManager(parent_frame)
        # Single dose
        dose_str = "2025-07-28 18:59:45:150mg"
        assert gm._calculate_daily_dose(dose_str) == 150.0
        # Multiple doses
        dose_str = "2025-07-28 18:59:45:150mg|2025-07-28 19:34:19:75mg"
        assert gm._calculate_daily_dose(dose_str) == 225.0
        # Doses without units
        dose_str = "2025-07-28 18:59:45:10|2025-07-28 19:34:19:5"
        assert gm._calculate_daily_dose(dose_str) == 15.0
    def test_calculate_daily_dose_with_symbols(self, parent_frame):
        """Test dose calculation with bullet symbols."""
        gm = GraphManager(parent_frame)
        # With bullet symbols
        dose_str = "• • • • 2025-07-30 07:50:00:300"
        assert gm._calculate_daily_dose(dose_str) == 300.0
        # Multiple bullets
        dose_str = "• 2025-07-30 22:50:00:10|• 2025-07-30 23:50:00:5"
        assert gm._calculate_daily_dose(dose_str) == 15.0
    def test_calculate_daily_dose_no_timestamp(self, parent_frame):
        """Test dose calculation without timestamp."""
        gm = GraphManager(parent_frame)
        # Just dose value
        dose_str = "150mg"
        assert gm._calculate_daily_dose(dose_str) == 150.0
        # Multiple values without timestamp
        dose_str = "100|50"
        assert gm._calculate_daily_dose(dose_str) == 150.0
    def test_calculate_daily_dose_decimal_values(self, parent_frame):
        """Test dose calculation with decimal values."""
        gm = GraphManager(parent_frame)
        # Decimal dose
        dose_str = "2025-07-28 18:59:45:12.5mg"
        assert gm._calculate_daily_dose(dose_str) == 12.5
        # Multiple decimal doses
        dose_str = "2025-07-28 18:59:45:12.5mg|2025-07-28 19:34:19:7.5mg"
        assert gm._calculate_daily_dose(dose_str) == 20.0
    def test_medicine_dose_plotting(self, parent_frame):
        """Test that medicine doses are plotted correctly."""
        # Create a DataFrame with dose data
        df_with_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, 0],
            'bupropion_doses': ['2024-01-01 08:00:00:150mg', '2024-01-02 08:00:00:300mg', ''],
            'hydroxyzine': [0, 1, 0],
            'hydroxyzine_doses': ['', '2024-01-02 20:00:00:25mg', ''],
            'gabapentin': [0, 0, 0],
            'gabapentin_doses': ['', '', ''],
            'propranolol': [1, 0, 1],
            'propranolol_doses': ['2024-01-01 12:00:00:10mg', '', '2024-01-03 12:00:00:20mg'],
            '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)
                gm.update_graph(df_with_doses)
                # Verify that bar plots were called (for medicines with doses)
                mock_ax.bar.assert_called()
                # Verify canvas was redrawn
                mock_canvas.draw.assert_called()
    def test_medicine_toggle_functionality(self, parent_frame):
        """Test that medicine toggles affect dose display."""
        df_with_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': [''],
            'gabapentin': [0],
            'gabapentin_doses': [''],
            'propranolol': [1],
            'propranolol_doses': ['2024-01-01 12:00:00:10mg'],
            'quetiapine': [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)
                # Turn off bupropion toggle
                gm.toggle_vars["bupropion"].set(False)
                gm.update_graph(df_with_doses)
                # Turn on hydroxyzine toggle (though it has no doses)
                gm.toggle_vars["hydroxyzine"].set(True)
                gm.update_graph(df_with_doses)
                # Verify the graph was updated
                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)
        # Test all sample dose data cases
        assert gm._calculate_daily_dose(sample_dose_data['standard_format']) == 225.0
        assert gm._calculate_daily_dose(sample_dose_data['with_bullets']) == 300.0
        assert gm._calculate_daily_dose(sample_dose_data['decimal_doses']) == 20.0
        assert gm._calculate_daily_dose(sample_dose_data['no_timestamp']) == 150.0
        assert gm._calculate_daily_dose(sample_dose_data['mixed_format']) == 85.0
        assert gm._calculate_daily_dose(sample_dose_data['empty_string']) == 0.0
        assert gm._calculate_daily_dose(sample_dose_data['nan_value']) == 0.0
        assert gm._calculate_daily_dose(sample_dose_data['no_units']) == 15.0
    def test_dose_calculation_edge_cases(self, parent_frame):
        """Test dose calculation with edge cases."""
        gm = GraphManager(parent_frame)
        # Test with malformed data
        assert gm._calculate_daily_dose("malformed:data") == 0.0
        assert gm._calculate_daily_dose("::::") == 0.0
        assert gm._calculate_daily_dose("2025-07-28:") == 0.0
        assert gm._calculate_daily_dose("2025-07-28::mg") == 0.0
        # Test with partial data
        assert gm._calculate_daily_dose("2025-07-28 18:59:45:150") == 150.0  # no units
        assert gm._calculate_daily_dose("150mg") == 150.0  # no timestamp
        # Test with spaces and special characters
        assert gm._calculate_daily_dose("  2025-07-28 18:59:45:150mg  ") == 150.0
        assert gm._calculate_daily_dose("••• 2025-07-28 18:59:45:150mg •••") == 150.0
@@ -2,7 +2,6 @@
 Tests for init module.
 """
 import os
 import tempfile
 import pytest
 from unittest.mock import patch, Mock
@@ -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'))
@@ -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
@@ -5,8 +5,7 @@ import os
 import pytest
 import tkinter as tk
 from tkinter import ttk
-from unittest.mock import Mock, patch, MagicMock
+from unittest.mock import Mock, patch
 from datetime import datetime
 import sys
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
@@ -698,7 +698,7 @@ wheels = [
 [[package]]
 name = "thechart"
-version = "1.2.1"
+version = "1.6.1"
 source = { virtual = "." }
 dependencies = [
    { name = "colorlog" },
Author	SHA1	Message	Date
William Valentin	949e43ac6c	feat: Bump version to 1.6.1 in Makefile, pyproject.toml, and CHANGELOG.md Build and Push Docker Image / build-and-push (push) Has been cancelled Details	2025-07-31 11:42:13 -07:00
William Valentin	33d7ae8d9f	feat: Remove outdated testing documentation and add comprehensive development and feature guides - Deleted `TESTING_SETUP.md` and `TEST_UPDATES_SUMMARY.md` as they were outdated. - Introduced `CHANGELOG.md` to document notable changes and version history. - Added `DEVELOPMENT.md` for detailed development setup, testing framework, and debugging guidance. - Created `FEATURES.md` to outline core features and functionalities of TheChart. - Established `README.md` as a centralized documentation index for users and developers.	2025-07-31 11:39:12 -07:00
William Valentin	e5e654a0b3	fix: Correct shell activation command in Makefile for proper environment setup Build and Push Docker Image / build-and-push (push) Has been cancelled Details	2025-07-31 11:20:18 -07:00
William Valentin	00443a540f	chore: Remove obsolete test scripts and unused methods from the data manager - Deleted test scripts for dose tracking, UI functionality, dynamic data, edit functionality, and final workflow. - Removed the `add_medicine_dose` method from the DataManager class as it is no longer needed.	2025-07-31 11:11:21 -07:00
William Valentin	59251ced31	chore: moved tests scripts	2025-07-31 10:18:09 -07:00
William Valentin	9471b91f4c	feat: Update default_enabled states for bupropion and propranolol to false	2025-07-31 10:06:25 -07:00
William Valentin	c755f0affc	Add comprehensive tests for dose tracking functionality - Implemented `test_dose_parsing_simple.py` to validate the dose parsing workflow. - Created `test_dose_save.py` to verify the saving functionality of dose tracking. - Added `test_dose_save_simple.py` for programmatic testing of dose saving without UI interaction. - Developed `test_final_workflow.py` to test the complete dose tracking workflow, ensuring doses are preserved during edits. - Enhanced `conftest.py` with a mock pathology manager for testing. - Updated `test_data_manager.py` to include pathology manager in DataManager tests and ensure compatibility with new features.	2025-07-31 09:50:45 -07:00
William Valentin	b8600ae57a	feat: Remove unused imports from test files for cleaner code	2025-07-30 16:02:26 -07:00
William Valentin	d7d4b332d4	Add medicine management functionality with UI and data handling - Implemented MedicineManagementWindow for adding, editing, and removing medicines. - Created MedicineManager to handle medicine configurations, including loading and saving to JSON. - Updated UIManager to dynamically generate medicine-related UI components based on the MedicineManager. - Enhanced test suite with mock objects for MedicineManager to ensure proper functionality in DataManager tests. - Added validation for medicine input fields in the UI. - Introduced default medicine configurations for initial setup.	2025-07-30 16:01:02 -07:00
William Valentin	ea30cb88c9	feat: Update default toggle states for bupropion and propranolol to false	2025-07-30 14:46:25 -07:00
William Valentin	b76191d66d	feat: Implement dose calculation fix and enhance legend feature Build and Push Docker Image / build-and-push (push) Has been cancelled Details - Fixed dose calculation logic in `_calculate_daily_dose` to correctly parse timestamps with multiple colons. - Added comprehensive test cases for various dose formats and edge cases in `test_dose_calculation.py`. - Enhanced graph legend to display individual medicines with average dosages and track medicines without dose data. - Updated legend styling and positioning for better readability and organization. - Created new tests for enhanced legend functionality, including handling of medicines with and without data. - Improved mocking for matplotlib components in tests to prevent TypeErrors.	2025-07-30 14:22:07 -07:00
William Valentin	d14d19e7d9	feat: add medicine dose graph plotting and toggle functionality with comprehensive tests Build and Push Docker Image / build-and-push (push) Has been cancelled Details	2025-07-30 13:18:25 -07:00
William Valentin	0a8d27957f	feat: enhance symptom scale creation with improved layout and dynamic value display	2025-07-30 12:41:25 -07:00
William Valentin	7e04aebd5d	feat: update version to 1.3.4 in pyproject.toml and uv.lock	2025-07-30 12:35:07 -07:00
		`@@ -0,0 +1 @@`
							`date,depression,anxiety,sleep,appetite,bupropion,bupropion_doses,hydroxyzine,hydroxyzine_doses,gabapentin,gabapentin_doses,propranolol,propranolol_doses,quetiapine,quetiapine_doses,note`