Package (microsoft#244)

* build and upload pypi package

* pandas in dependency

.github/workflows/CD.yml

@@ -0,0 +1,52 @@
+# This workflows will build and upload a Python Package using Twine when a release is published
+# Conda-forge bot will pick up new PyPI version and automatically create new version
+# For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries
+
+name: CD
+
+on:
+  release:
+    types: [published]
+
+jobs:
+  deploy:
+    strategy:
+      matrix:
+        os: ['ubuntu-latest']
+        python-version: [3.8]
+    runs-on: ${{ matrix.os }}
+    environment: package
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Cache conda
+        uses: actions/cache@v1
+        with:
+          path: ~/conda_pkgs_dir
+          key: conda-${{ matrix.os }}-python-${{ matrix.python-version }}-${{ hashFiles('environment.yml') }}
+      - name: Setup Miniconda
+        uses: conda-incubator/setup-miniconda@v2
+        with:
+          auto-update-conda: true
+          auto-activate-base: false
+          activate-environment: hcrystalball
+          python-version: ${{ matrix.python-version }}
+          use-only-tar-bz2: true
+      - name: Install from source
+        # This is required for the pre-commit tests
+        shell: pwsh
+        run: pip install .
+      - name: Conda list
+        shell: pwsh
+        run: conda list
+      - name: Build
+        shell: pwsh
+        run: |
+          pip install twine
+          python setup.py sdist bdist_wheel
+      - name: Publish to PyPI
+        env:
+          TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
+          TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+        shell: pwsh
+        run: twine upload dist/*

README.md

@@ -111,7 +111,7 @@ automl_settings = {
     "time_budget": 10,  # in seconds
     "metric": 'r2',
     "task": 'regression',
-    "log_file_name": "test/california.log",
+    "log_file_name": "test/boston.log",
 }
 X_train, y_train = fetch_california_housing(return_X_y=True)
 # Train with labeled input data

flaml/version.py

@@ -1 +1 @@
-__version__ = "0.6.6"
+__version__ = "0.6.7"

setup.py

@@ -18,7 +18,7 @@
     "lightgbm>=2.3.1",
     "xgboost>=0.90,<=1.3.3",
     "scipy>=1.4.1",
-    # "catboost>=0.23",  # making optional for conda
+    "pandas>=1.1.4",
     "scikit-learn>=0.24",
 ]
 

test/test_automl.py

@@ -503,7 +503,7 @@ def test_regression(self):
         automl_settings = {
             "time_budget": 2,
             "task": "regression",
-            "log_file_name": "test/california.log",
+            "log_file_name": "test/boston.log",
             "log_training_metric": True,
             "n_jobs": 1,
             "model_history": True,
@@ -625,7 +625,7 @@ def test_parallel(self, hpo_method=None):
         automl_settings = {
             "time_budget": 10,
             "task": "regression",
-            "log_file_name": "test/california.log",
+            "log_file_name": "test/boston.log",
             "log_type": "all",
             "n_jobs": 1,
             "n_concurrent_trials": 2,