ConMedPartApp: Automated Exam Room Distribution & Man- agement Desktop Application

ConMedPartApp is a professional-grade Desktop application engineered to automate the complex, time-consuming process of distributing candidates across exam rooms. Built entirely with Python and PyQt6, this robust system replaces manual administrative tasks with an intelligent, automated workflow tailored for educational institutions and exam centers.

The application ensures a seamless organizational process from importing candidate lists to generating ready-to-print official examination documents (PDFs). It features a completely offline architecture, guaranteeing absolute data privacy and security through local SQLite databases.

Core Features & Capabilities:

Intelligent Candidate Distribution: An automated allocation engine that assigns candidates to specific rooms based on capacity constraints and room classifications across multiple exam centers.

Dynamic Data Import: Seamless bulk import of candidate data via CSV or Excel formats, mapping critical fields such as ID, Name, Region, and Language preferences.

Comprehensive Room Configuration: Allows administrators to create exam centers, configure individual rooms, classify them by type (e.g., standard, accessible), and monitor total available capacity in real-time.

Automated Document Generation (PDF): Automatically generates professional, print-ready documents including candidate display lists per room and official attendance sheets using ReportLab.

Secure Local Storage: Utilizes three separate, locally-stored SQLite databases (Candidates, Rooms, Distribution History) ensuring zero external server dependencies and maximum data confidentiality.

Intuitive Graphical Interface: A highly responsive and user-friendly GUI built with PyQt6, featuring a streamlined 4-step workflow (Configure → Import → Distribute → Generate).

Technical Architecture & Full Tech Stack:

Core Language: Python 3.8+ (Designed with Object-Oriented Architecture principles).

Graphical User Interface (GUI): PyQt6 for building a modern, responsive, and cross-platform desktop interface.

Database Management: SQLite3 for lightweight, secure, and serverless local data persistence.

Data Processing & Analysis: Pandas for efficient parsing, manipulation, and validation of large CSV/Excel datasets.

Document Rendering: ReportLab for programmatic generation of complex, structured PDF documents.

Image Processing: Pillow (PIL) for handling application assets and institution logos within generated reports.

🔗 Live Links & References:

Source Code (GitHub): https://github.com/ABDELA...

Project Portfolio: https://elkholtyabde.verc...