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 unit tests for util
, plotting
, and sweep
)
Unit tests
To run unit all unit tests, install pytest
, 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, using pytest
version 5.4.1):
pytest
Build package locally
jutility
can be built and installed locally using the following commands, replacing $WHEEL_NAME
with the name of the wheel built by the python -m build
command (for example, jutility-0.0.3-py3-none-any.whl
):
python -m build
python -m pip install --force-reinstall dist/$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).
Project details
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