time-it-profiler 1.0.2

A lightweight Python decorator for measuring execution time and system resource usage.

Save the updated README.md file for PyPI as a downloadable markdown file

time-it-profiler - Python Function Profiler

🚀 Overview

time-it-profiler is a lightweight Python decorator that measures execution time, memory usage, and CPU time of any function. It is designed to be efficient, flexible, and easy to integrate into any Python project.

📌 Features

✅ Execution Time Measurement (High-precision timing with perf_counter)
✅ Memory Usage Tracking (Peak memory usage in MB)
✅ CPU Time Monitoring (User & System CPU time)
✅ Zero Overhead When Disabled (measure_time=False bypasses all profiling logic)
✅ Easy to Use as a Decorator (@time_it)
✅ Lightweight & No External Dependencies

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📥 Installation

Install directly from PyPI using:

pip install time-it-profiler

📂 GitHub Repository

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📖 Usage

✅ Basic Example

from time_it import time_it

@time_it(measure_time=True)  # Enable profiling
def sample_function():
    total = sum(range(1, 1000000))
    return total

sample_function()

Example Output:

Execution Time: 0.012345 seconds
Memory Usage: 1.23 MB
User CPU Time: 0.002345 seconds
System CPU Time: 0.000678 seconds

✅ Disable Profiling (Zero Overhead)

@time_it(measure_time=False)  # No profiling, function runs normally
def quick_function():
    return sum(range(1, 100))

quick_function()

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🔍 How It Works

time_it Function

import time
import resource
from functools import wraps

def time_it(measure_time=True):
    def decorator(func):
        if not measure_time:
            return func  # Return the function unmodified if profiling is disabled

        @wraps(func)
        def wrapper(*args, **kwargs):
            start_time = time.perf_counter()
            start_resources = resource.getrusage(resource.RUSAGE_SELF)
            
            result = func(*args, **kwargs)
            
            end_time = time.perf_counter()
            end_resources = resource.getrusage(resource.RUSAGE_SELF)

            memory = (end_resources.ru_maxrss - start_resources.ru_maxrss) / 1024  # Convert KB to MB
            user_time = end_resources.ru_utime - start_resources.ru_utime
            system_time = end_resources.ru_stime - start_resources.ru_stime

            print(
                f"Execution Time: {end_time - start_time:.6f} seconds\\n"
                f"Memory Usage: {memory:.2f} MB\\n"
                f"User CPU Time: {user_time:.6f} seconds\\n"
                f"System CPU Time: {system_time:.6f} seconds"
            )

            return result
        return wrapper
    return decorator

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🛠️ Contributing

Contributions are welcome! Fork the repository on GitHub and submit a pull request.

🔗 GitHub Repo: https://github.com/brianvess/time_it.git

1. Fork this repository.

2. Create a new branch:

   git checkout -b feature-branch
   

3. Commit your changes:

   git commit -m "Added new feature"
   

4. Push the changes:

   git push origin feature-branch
   

5. Submit a pull request! 🎉

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📜 License

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

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🌟 Credits

Developed by Brian Vess.
If you find this useful, please ⭐ star this repository and contribute! 🚀