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prepared first release
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.github/workflows/deploy_pypi.yml

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name: useful_layers release deployment on PyPI
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on:
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release:
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types: [published]
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jobs:
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deploy:
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name: Build and publish to PyPI
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runs-on: ubuntu-18.04
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python 3.7.6
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uses: actions/setup-python@v2
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with:
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python-version: 3.9.5
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- name: Install pypa/build
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run: pip install build
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- name: Build a binary wheel and a source tarball
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run: python -m build --sdist --wheel --outdir dist/ .
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- name: Publish distribution to Test PyPI
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uses: pypa/gh-action-pypi-publish@master
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with:
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user: __token__
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password: ${{ secrets.PYPI_API_TOKEN }}

setup.cfg

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[metadata]
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description-file = README.md

setup.py

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use_setuptools()
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from setuptools import setup, find_packages
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__version__ = '0.0.1'
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__version__ = '0.0a0.dev1'
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with open("README.md", "r", encoding="utf-8") as fh:
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long_description = fh.read()
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setup(
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name='useful_layers',
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packages=find_packages(),
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include_package_data=True,
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version=__version__,
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description="""
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Useful Layers
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Useful Layers is a torch based library containing some experimental,
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but useful layers
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""",
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long_description=long_description,
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long_description_content_type="text/markdown",
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author='Jan Ernsting',
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author_email='[email protected]',
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url='https://github.com/jernsting/useful_layers.git',
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url='https://jernsting.github.io/useful_layers/',
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download_url='https://github.com/jernsting/useful_layers/archive/' +
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__version__ + '.tar.gz',
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keywords=['machine learning', 'deep learning', 'experimental', 'science'],
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classifiers=[],
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classifiers=[
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'Development Status :: 2 - Pre-Alpha',
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'Intended Audience :: Developers',
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'Intended Audience :: Science/Research',
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'License :: OSI Approved :: MIT License',
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'Programming Language :: Python :: 3',
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'Topic :: Scientific/Engineering :: Artificial Intelligence',
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],
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project_urls={
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"Source Code": "https://github.com/jernsting/useful_layers",
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"Documentation": 'https://jernsting.github.io/useful_layers/',
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"Bug Tracker": "https://github.com/jernsting/useful_layers/issues"
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}
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)

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