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Python code performace metrics calculation tool

Project description

Perfwatch

Perfwatch is a python package that allows you to monitor the performance of your code. It is designed to be used in a Jupyter notebook, but can also be used in a Python script.

Table of Contents

Installation

To install perfwatch, run the following command:

pip install perfwatch

Development

To install perfwatch for development, clone the repository and run the following command:

poetry install

To setup pre-commit hooks, run the following command:

poetry run pre-commit install

To run the tests, run the following command:

poetry run pytest

Usage

Available Profiler Types

The profiler supports the following profiler types:

  • cpu: Profiles CPU usage using the cProfile module.
  • memory: Profiles memory usage using the memory_profiler module.
  • thread: Profiles thread creation and usage.
  • io: Profiles I/O operations.
  • network: Profiles network traffic using the NetworkProfiler class.
  • gpu: Profiles GPU usage using the GPUProfiler class.
  • cache: Profiles cache performance (not implemented).
  • exception: Profiles exception handling (not implemented).
  • system: Profiles system performance (not implemented).
  • distributed: Profiles distributed system performance (not implemented).
  • line: Profiles line-by-line execution using the line_profiler module.
  • time: Profiles execution time.

Basic Usage

from perfwatch import watch

@watch(["line", "cpu", "time"])
def test():
    for _ in range(1000000):
        pass

if __name__ == "__main__":
    test()

Customizing Profiling

You can customize the profiling behavior by passing additional keyword arguments to the watch decorator. For example:

@watch(["network"], packet_src="localhost")
def my_function(x, y):
    # function implementation
    pass

Logging

You can log the profiling results to a file by assigning LOG_FILE_PATH envar to desired file location

License

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

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