ows-master/startpakketten

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

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

Installation

1. Ensure Python 3.12+ is installed
2. 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)

Must contain columns:

• ID, Naam, Voornaam
• Ingeschr. SP (intern)

Output

The tool provides:

1. Console Summary: Overview of processing results
2. Failed Students Report: Detailed list of students with FAIL status
3. SP Mismatch Report: Any discrepancies between predeliberation and dashboard SP values
4. Optional JSON Export: Machine-readable results for further processing

Exit Codes

• 0: Success (no mismatches found)
• 1: Processing completed but mismatches found
• 130: Process interrupted by user
• Other: Fatal error occurred

Logging

All processing activities are logged to startpakket_processing.log by default. Use --verbose for detailed debug information.