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Collection of Python utilities intended to be useful for machine learning research and experiments

Project description

jutility

Collection of Python utilities intended to be useful for machine learning research and experiments.

Contents

Install with pip

The jutility package is available as a Python package on PyPI, and can be installed with pip using the following commands:

python -m pip install -U pip
python -m pip install -U jutility

Usage examples

Coming soon

(in the meantime, see scripts/make_logo.py which made the logo above, and unit tests for util, plotting, and sweep)

Unit tests

To run unit all unit tests, install pytest (these tests have previously been run with pytest version 5.4.1), and run the following command (at the time of writing, this takes about 17 seconds to run 42 unit tests, because several unit tests involve saving images or GIFs to disk):

pytest

Build package locally

jutility can be built and installed locally using the following commands, replacing $WHEEL_NAME with the name of the wheel built by the python -m build command (for example, jutility-0.0.5-py3-none-any.whl):

python -m build
python -m pip install --force-reinstall --no-deps dist/$WHEEL_NAME

Updating package on PyPI

This package was uploaded to PyPI following the Packaging Python Projects tutorial in the official Python documentation.

To update PyPI with a newer version, update the version tag in pyproject.toml, and then use the following commands:

rm -rf dist/*
python -m build
python -m twine upload dist/*

When prompted by twine, enter __token__ as the username, and paste an API token from the PyPI account management webpage as the password (including the pypi- prefix).

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