iops-profiler Documentation

iops-profiler is a Jupyter IPython magic extension for measuring I/O operations per second (IOPS) in your code. Profile file operations directly in your notebooks with simple magic commands.

Quick Start

Install iops-profiler:

>> pip install iops-profiler

Load it in your Jupyter notebook:

%load_ext iops_profiler

Profile your code:

%%iops
with open('test.txt', 'w') as f:
    f.write('Hello, World!' * 1000)

Get Started

API Reference

API Reference
- iops_profiler

Contributing

Dev Guide - Getting Started

Before installing any dependencies or writing code, it’s a great idea to create a virtual environment. LINCC-Frameworks engineers primarily use conda to manage virtual environments. If you have conda installed locally, you can run the following to create and activate a new environment.

>> conda create env -n <env_name> python=3.10
>> conda activate <env_name>

Once you have created a new environment, you can install this project for local development using the following commands:

>> pip install -e .'[dev]'
>> pre-commit install
>> conda install pandoc

Notes:

The single quotes around '[dev]' may not be required for your operating system.
pre-commit install will initialize pre-commit for this local repository, so that a set of tests will be run prior to completing a local commit. For more information, see the Python Project Template documentation on pre-commit.
Installing pandoc allows you to verify that automatic rendering of Jupyter notebooks into documentation for ReadTheDocs works as expected. For more information, see the Python Project Template documentation on Sphinx and Python Notebooks.