Mini OS CPU Scheduler

A comprehensive CPU scheduling simulator implemented in Python that demonstrates core operating systems concepts. This package simulates and compares multiple CPU scheduling algorithms with detailed metrics and analysis.

🎯 Features

This simulator implements four fundamental CPU scheduling algorithms:

1. First-Come, First-Serve (FCFS) - Non-preemptive, executes processes in arrival order
2. Shortest Job First (SJF) - Non-preemptive, selects shortest available job
3. Priority Scheduling - Non-preemptive, executes highest priority process first
4. Round Robin (RR) - Preemptive, uses time quantum for fair scheduling

For each algorithm, the simulator calculates:

• Start time
• Finish time
• Waiting time
• Turnaround time
• Average waiting time
• Average turnaround time

🚀 Installation

Install from PyPI:

pip install mini-os-scheduler

For web dashboard support:

pip install "mini-os-scheduler[web]"

📖 Quick Start

Command Line Interface

After installation, use the mini-scheduler command:

# Run all algorithms with sample data
mini-scheduler --sample --algorithm all

# Run specific algorithm
mini-scheduler --sample --algorithm fcfs
mini-scheduler --sample --algorithm sjf
mini-scheduler --sample --algorithm priority
mini-scheduler --sample --algorithm rr --quantum 3

# Load from JSON file
mini-scheduler --file processes.json --algorithm all

# Load from CSV file
mini-scheduler --file processes.csv --algorithm sjf

Python API

from mini_os_scheduler import Process, compare_algorithms

# Create processes
processes = [
    Process(pid=1, arrival_time=0, burst_time=5, priority=2),
    Process(pid=2, arrival_time=1, burst_time=3, priority=1),
    Process(pid=3, arrival_time=2, burst_time=8, priority=3),
]

# Compare all algorithms
results = compare_algorithms(processes, time_quantum=2)

# Access results
for name, result in results.items():
    print(f"{name}:")
    print(f"  Avg Waiting Time: {result.avg_waiting_time:.2f}")
    print(f"  Avg Turnaround Time: {result.avg_turnaround_time:.2f}")
    for r in result.results:
        print(f"    PID {r.pid}: Start={r.start_time}, Finish={r.finish_time}")

Input File Formats

JSON Format (processes.json):

[
  {"pid": 1, "arrival_time": 0, "burst_time": 5, "priority": 2},
  {"pid": 2, "arrival_time": 1, "burst_time": 3, "priority": 1},
  {"pid": 3, "arrival_time": 2, "burst_time": 8, "priority": 3}
]

CSV Format (processes.csv):

pid,arrival_time,burst_time,priority
1,0,5,2
2,1,3,1
3,2,8,3

📊 Example Output

================================================================================
Algorithm: FCFS
================================================================================
PID    Arrival  Burst    Priority   Start    Finish   Waiting  Turnaround
--------------------------------------------------------------------------------
1      0        5        2          0        5        0        5
2      1        3        1          5        8        4        7
3      2        8        3          8        16       6        14
4      3        6        2          16       22       13       19
5      4        4        1          22       26       18       22
--------------------------------------------------------------------------------
Average                                                8.20     13.40
================================================================================

🌐 Web Dashboard

Start the interactive web dashboard:

python -m mini_os_scheduler.web.app

Then open your browser to http://localhost:5000

Note: Requires mini-os-scheduler[web] installation.

🧪 Testing

Run the test suite:

# Install development dependencies
pip install "mini-os-scheduler[dev]"

# Run tests
pytest tests/ -v

🏗️ Architecture

The package follows clean software engineering principles:

mini_os_scheduler/
├── models.py          # Process data models (Process, ProcessResult)
├── algorithms.py      # Core scheduling algorithm implementations
├── simulator.py       # Simulation runner and metrics calculation
├── main.py            # CLI entry point
└── web/               # Optional Flask web dashboard
    ├── app.py
    └── templates/

Design Principles

• Type Hints: Full type annotations for better code clarity and IDE support
• Docstrings: Comprehensive documentation for all functions
• Modularity: Each component has a single, well-defined responsibility
• Testability: Comprehensive test suite validating algorithm correctness

📈 Use Cases

• Education: Teaching operating systems concepts
• Research: Comparing scheduling algorithm performance
• Development: Understanding CPU scheduling behavior
• Portfolio: Demonstrating systems programming knowledge

🔧 Technical Details

Algorithm Implementations

• FCFS: Simple queue-based execution in arrival order
• SJF: Greedy selection of shortest available job at each decision point
• Priority: Selection based on priority value (lower = higher priority)
• Round Robin: Preemptive scheduling with circular queue and time slicing

Requirements

• Python 3.7 or higher
• No external dependencies (core package)
• Flask 2.0+ (for web dashboard, optional)

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

🔗 Links

• PyPI: https://pypi.org/project/mini-os-scheduler/
• GitHub: https://github.com/Karkibinod/mini-os-scheduler
• Issues: https://github.com/Karkibinod/mini-os-scheduler/issues

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A CPU scheduling simulator demonstrating systems programming concepts and software engineering best practices.