Startpakket Processing Tool

A Python tool for processing and comparing student data from predeliberation and dashboard Excel files. The tool identifies students with FAIL status and compares SP (study points) values between different data sources.

Project Structure

The codebase has been organized into focused modules:

Core Scripts

script.py - Main orchestration script, handles command-line interface and coordinates all processing
data_processor.py - Core data processing functions for Excel file handling
cli_args.py - Command-line argument parsing and validation
config.py - Configuration management and logging setup
file_utils.py - File I/O utilities and output formatting

Processing Modules

checkheaders.py - Excel file header processing and normalization
process_predelib_file.py - Predeliberation file analysis and FAIL status detection
compare_sp.py - SP value comparison between predeliberation and dashboard files

Usage

Basic Usage

python script.py --predelib db.xlsx --dashboard dashboard_inschrijvingen.xlsx

Advanced Usage

# Save results to JSON file
python script.py -p db.xlsx -d dashboard_inschrijvingen.xlsx --output results.json

# Enable verbose logging
python script.py --predelib db.xlsx --dashboard dashboard_inschrijvingen.xlsx --verbose

# Custom log file
python script.py --predelib db.xlsx --dashboard dashboard_inschrijvingen.xlsx --log-file custom.log

Command-line Options

--predelib, -p: Path to predeliberation Excel file (required)
--dashboard, -d: Path to dashboard Excel file (required)
--output, -o: Output file path for JSON results (optional)
--verbose, -v: Enable verbose logging
--log-file: Custom log file path (default: startpakket_processing.log)

Features

File Validation: Automatically validates that input files exist and are Excel format
Header Processing: Intelligently detects and normalizes Excel headers
FAIL Detection: Identifies students with FAIL status in adviesrapport code
SP Comparison: Compares study points between predeliberation and dashboard data
Comprehensive Logging: Detailed logging with configurable verbosity
Flexible Output: Console summary with optional JSON export
Error Handling: Robust error handling with appropriate exit codes

Installation

Ensure Python 3.12+ is installed
Install required dependencies:
```
pip install pandas openpyxl
```

Input File Requirements

Predeliberation File (db.xlsx)

Must contain columns:

ID, Achternaam, Voornaam, E-mail
Totaal aantal SP, Aantal SP vereist
Adviesrapport code, Waarschuwing

Dashboard File (dashboard_inschrijvingen.xlsx)