Implement GLYVIA glucose analysis desktop application

[Copilot]

Builds a privacy-first desktop application for glucose data analysis and health report generation. All processing happens locally using Python standard library only—no external dependencies, no cloud services, no network calls.

Architecture

Modular design with separation of concerns:

• models/ - Data structures (GlucoseReading, GlucoseDataset)
• core/ - Analysis engines (TIR calculator, statistics, trends, pattern recognition)
• ui/ - Tkinter medical-grade interface
• utils/ - CSV import/export, report generation

Zero dependencies: Tkinter, csv, datetime, dataclasses, pathlib, typing—all standard library.

Core Features

Time-in-Range Analysis

• 5 glucose ranges (<54, 54-69, 70-180, 181-250, >250 mg/dL)
• Target-based calculations (≥70% in range goal)

Statistical Analysis

• Mean, median, std dev, CV%, percentiles (25th, 50th, 75th)
• Min/max values with validation (0-600 mg/dL)

Trend & Pattern Analysis

• Daily averages and hourly patterns
• Peak/lowest time identification
• 7-day rolling variability windows

Professional Reporting

• Text and HTML formatted reports
• Statistics, TIR visualization, pattern identification, personalized recommendations
• Medical disclaimers included

Data Management

CSV import with flexible column mapping:

DataLoader.load_from_csv(
    file_path='data.csv',
    timestamp_column='timestamp',  # YYYY-MM-DD HH:MM:SS
    value_column='glucose',         # mg/dL
    notes_column='notes'            # Optional
)

Sample data generator for testing (realistic glucose patterns with meal spikes).

UI Design

Medical-grade interface with real-time statistics dashboard:

• 4 metric cards (readings count, mean glucose, std dev, TIR%)
• Action buttons (load, analyze, export)
• Scrollable results panel
• Professional color scheme (#2c3e50, #3498db, #27ae60)

Cross-Platform Support

Platform-specific launchers:

• GLYVIA.bat - Windows
• GLYVIA.sh - Linux/Mac
• Direct: python src/main.py

Testing & Quality

Comprehensive test suite covering all analysis engines, data operations, and report generation. CodeQL scan clean (0 vulnerabilities).

Documentation

Complete user guide, quick start, changelog, configuration options, and EULA for one-time purchase model.

Original prompt

This repository contains GLYVIA, a Windows desktop application built with Python and Tkinter for analysing glucose data and generating professional health reports.

The project focuses on:

• Clean medical UI design
• Local data processing
• Glucose trend analysis
• Time-in-range and distribution reporting
• One-time purchase desktop software

No cloud services. No subscriptions. Privacy-first design.

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