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FastBench
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FastBench is a high-performance Python package for benchmarking code execution time, CPU usage, and memory usage. It's implemented in Python for simplicity and provides a simple API for measuring the performance of your Python code.

✨ Features

  • ⏱️ Measure the execution time of a function or code block
  • 📊 Track CPU usage during code execution
  • 🖥️ Monitor memory usage during code execution
  • ⚡ Lightweight and fast
  • 🔄 Simple and easy-to-use API

Installation

You can install FastBench via pip:

pip install fastbench

Usage

Here's an example of how to use FastBench to benchmark Python code:

from fastbench import mt, mc, mm

# Define a sample function for testing
def sample_function(n):
  return sum(range(n))

# Test the mt function (measure execution time)
time_taken = mt(sample_function, n=1000000)
print("Time taken:", time_taken)

# Test the mc function (measure CPU usage)
cpu_usage = mc(sample_function, n=1000000)
print("CPU usage:", cpu_usage)

# Test the mm function (measure memory usage)
memory_usage = mm(sample_function, n=1000000)
print("Memory usage:", memory_usage)

Contributing

Contributions are welcome! Check out the Contribution Guidelines.

License

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

Release files for fastbench 0.1.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for fastbench 0.1.5
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Table of built distributions (wheels) for fastbench 0.1.5
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fastbench-0.1.5-py3-none-any.whl Python 3 none any Details

Total release size: 6.4 kB

Release files / fastbench-0.1.5.tar.gz

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