Automate PyPi Releases

.github/workflows/publish-to-pypi.yml

@@ -0,0 +1,34 @@
+name: Publish Python 🐍 distributions 📦 to PyPI
+
+on:
+  push:
+    tags:
+     - '*'
+
+jobs:
+  build-n-publish:
+    name: Build and publish Python 🐍 distributions 📦 to PyPI
+    runs-on: ubuntu-18.04
+    steps:
+    - uses: actions/checkout@master
+    - name: Set up Python 3.10
+      uses: actions/setup-python@v3
+      with:
+        python-version: '3.10'
+    - name: Install pypa/setuptools
+      run: >-
+        python -m
+        pip install wheel
+    - name: Extract tag name
+      id: tag
+      run: echo ::set-output name=TAG_NAME::$(echo $GITHUB_REF | cut -d / -f 3)
+    - name: Update version in setup.py
+      run: >-
+        sed -i "s/{{VERSION_PLACEHOLDER}}/${{ steps.tag.outputs.TAG_NAME }}/g" setup.py
+    - name: Build a binary wheel
+      run: >-
+        python setup.py sdist bdist_wheel
+    - name: Publish distribution 📦 to PyPI
+      uses: pypa/gh-action-pypi-publish@master
+      with:
+        password: ${{ secrets.PYPI_API_TOKEN }}

setup.py

@@ -1,7 +1,7 @@
 from setuptools import setup
 
 setup(name='Boruta',
-      version='0.1.5',
+      version='{{VERSION_PLACEHOLDER}}',
       description='Python Implementation of Boruta Feature Selection',
       url='https://github.com/danielhomola/boruta_py',
       download_url='https://github.com/danielhomola/boruta_py/tarball/0.1.5',
@@ -11,7 +11,7 @@
       packages=['boruta'],
       package_dir={'boruta': 'boruta'},
       package_data={'boruta/examples/*csv': ['boruta/examples/*.csv']},
-      include_package_data = True,
+      include_package_data=True,
       keywords=['feature selection', 'machine learning', 'random forest'],
       install_requires=['numpy>=1.10.4',
                         'scikit-learn>=0.17.1',