Python vs Rust: Performance Comparison

This project demonstrates a performance comparison between Python and Rust for two common operations:

Calculating Fibonacci numbers.
Multiplying two numbers.

The goal is to highlight the advantages of using Rust for computationally intensive tasks while showcasing Python's ease of use for quick prototyping.

Features

Rust Implementation: Optimized algorithms for Fibonacci calculation and multiplication, compiled as a Python module using PyO3.
Python Implementation: Equivalent algorithms written purely in Python.
Performance Metrics: Measures execution time, CPU usage, and memory usage for each implementation.
Real-time Results: Outputs whichever implementation finishes first.

Usage

Setup

Install Rust and Python.

Add the PyO3 dependency to your Cargo.toml:

[dependencies]
pyo3 = { version = "0.18", features = ["extension-module"] }

Build the Rust module:
```
maturin develop
```
Install the required Python packages:
```
pip install psutil
```

Run the Program

Execute the Python script:
```
python main.py
```
Follow the menu prompts to:
- Calculate Fibonacci numbers.
- Multiply two numbers.

Example Output

welcome to the Math Application

Menu:
1. Calculate Fibonacci
2. Multiply Two Numbers
3. Exit
Choose an option: 1
Enter the Fibonacci index: 20
Fibonacci(20) [Rust] = 6765 (time: 0.000077 seconds, CPU: 0.00%, Memory: 16.91 MB)
Fibonacci(20) [Python] = 6765 (time: 0.002380 seconds, CPU: 0.00%, Memory: 17.09 MB)

Performance Insights

Speed: Rust significantly outperforms Python for computationally intensive tasks, such as calculating Fibonacci numbers for larger indices.
Resource Efficiency: Rust uses less memory and takes advantage of multiple threads for improved CPU usage.
Scalability: Rust remains efficient for large inputs, whereas Python's performance degrades rapidly.

Why Use Python + Rust?

This hybrid approach allows you to:

Utilize Rust for performance-critical components.
Leverage Python's simplicity for scripting and prototyping.

Contributing

Contributions are welcome! Feel free to submit issues or pull requests to improve the project.

License

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

mwaijega/python_ft_rust