Altar Server Scheduling Algorithm

A Python-based automatic scheduling system that fairly distributes 40 altar servers across church services over a 6-week period.

🚀 Features

• Fair Distribution: Ensures every altar server gets equal assignments
• Sibling Pairing: Automatically assigns siblings together
• Availability Management: Respects individual availability preferences
• Absence Handling: Loads and processes absence data from file
• 8:30 AM Requirement: Ensures everyone serves at least once at the unpopular early service
• Three-Phase Algorithm: Optimizes assignments through multiple phases
• Comprehensive Reporting: Detailed statistics and validation reports

📋 Algorithm Rules

Core Constraints

1. Fairness: Equal number of assignments for all servers
2. Sibling Rule: Siblings always assigned together
3. No Consecutive Days: No server works consecutive days
4. 8:30 AM Requirement: Everyone must serve early service at least once
5. Availability: Only assigns servers when they're available
6. Group Leader Distribution: Proper distribution across services

🏗️ Project Structure

├── AltarServer.py      # Main English implementation
├── Ministrant.py       # Original German implementation
├── absences.txt        # English absence data
├── abmeldungen.txt     # German absence data
├── PROJECT_README.md   # Detailed technical documentation
└── README.md          # This file

🎯 Quick Start

1. Clone the repository

   git clone <repository-url>
   cd altar-server-scheduling

2. Run the algorithm

   python AltarServer.py

3. View results The program outputs:

   • Mass assignments for each service
   • Assignment statistics per server
   • Absence validation
   • 8:30 AM requirement compliance

📊 Sample Output

=== MASS OVERVIEW ===

1.04.25 at 8:30 (needs 4 servers):
  Assigned: 4 servers
    - Max (was absent)
    - Tom
    - Paul
    - Emma

=== ASSIGNMENT STATISTICS ===
Max: 2 assignments | 8:30 AM: OK
Lisa: 2 assignments | 8:30 AM: OK | Absences: 1
Tom: 3 assignments | 8:30 AM: OK
...

=== 8:30 AM REQUIREMENT CHECK ===
Everyone has at least one 8:30 service!

🗂️ Data Management

Absence File Format (absences.txt)

# Comments start with #
Name|Date
Max|1.04.25
Lisa|8.04.25

Adding New Servers

Modify the server list in AltarServer.py:

new_server = AltarServer(
    is_group_leader=False,
    name="NewName",
    assignment_counter=0,
    siblings="SiblingName",  # Empty string if no siblings
    available=["Sunday 8:30", "Sunday 10:30"]
)

🔧 Algorithm Details

Three-Phase System

1. Phase 0: 8:30 AM Priority

   • Prioritizes servers who haven't served early service
   • Ensures compliance with early service requirement

2. Phase 1: Fair Distribution

   • Sorts by assignment counter (least assignments first)
   • Maintains sibling pairing throughout

3. Phase 2: Preference Optimization

   • Attempts swaps to match server preferences
   • Improves satisfaction while preserving fairness

📈 Technical Specifications

• Language: Python 3.x
• Servers: 40 altar servers
• Schedule: 6 weeks (12 Sundays × 2 services = 24 masses)
• Dependencies: None (pure Python)
• Encoding: UTF-8 (supports international characters)

🌍 Multilingual Support

This project includes both German and English implementations:

• German: Ministrant.py (original)
• English: AltarServer.py (translation)

Both versions are functionally identical and can be used interchangeably.

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/improvement)
3. Commit your changes (git commit -am 'Add improvement')
4. Push to the branch (git push origin feature/improvement)
5. Create a Pull Request

📝 License

This project is open source and available under the MIT License.

🎯 Use Cases

Perfect for:

• Churches managing altar server schedules
• Youth group coordinators
• Educational purposes (algorithm learning)
• Scheduling system examples
• Python programming practice

📚 Educational Value

This project demonstrates:

• Object-oriented programming in Python
• Algorithm design and optimization
• File I/O operations
• Data structure manipulation
• Constraint satisfaction problems
• Fair distribution algorithms

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Created with ❤️ for church communities and Python learners