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setup.py
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"""
Heavily inspired from https://github.com/huggingface/transformers
Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/master/setup.py
To create the package for pypi.
1. Change the version in __init__.py, setup.py as well as docs/source/conf.py.
2. Unpin specific versions from setup.py (like isort).
2. Commit these changes with the message: "Release: VERSION"
3. Add a tag in git to mark the release: "git tag VERSION -m'Adds tag VERSION for pypi' "
Push the tag to git: git push --tags origin master
4. Build both the sources and the wheel. Do not change anything in setup.py between
creating the wheel and the source distribution (obviously).
For the wheel, run: "python setup.py bdist_wheel" in the top level directory.
(this will build a wheel for the python version you use to build it).
For the sources, run: "python setup.py sdist"
You should now have a /dist directory with both .whl and .tar.gz source versions.
Usualy run: "python setup.py sdist bdist_wheel"
5. Check that everything looks correct by uploading the package to the pypi test server:
twine upload dist/* -r pypitest
(pypi suggest using twine as other methods upload files via plaintext.)
You may have to specify the repository url, use the following command then:
twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/
Check that you can install it in a virtualenv by running:
pip install -i https://testpypi.python.org/pypi transformers
6. Upload the final version to actual pypi:
twine upload dist/* -r pypi
7. Copy the release notes from RELEASE.md to the tag in github once everything is looking hunky-dory.
8. Add the release version to docs/source/_static/js/custom.js and .circleci/deploy.sh
9. Update README.md to redirect to correct documentation.
"""
from setuptools import setup, find_packages
extras = {}
setup(
name="ml_things",
version="0.0.1",
author="George Mihaila",
author_email="georgemihaila@my.unt.edu",
description="Useful functions when working with Machine Learning in Python",
long_description=open("README.md", "r", encoding="utf-8").read(),
long_description_content_type="text/markdown",
keywords="NLP deep learning pytorch tensorflow numpy",
license="Apache",
url="https://github.com/gmihaila/ml_things",
package_dir={"": "src"},
packages=find_packages("src"),
install_requires=[
"scikit-learn",
"numpy",
"requests",
"tqdm >= 4.27",
"ftfy >= 5.8",
"matplotlib>=3.4.0",
],
extras_require=extras,
python_requires=">=3.6.0",
classifiers=[
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
)