merge head

.github/workflows/python-app.yml

@@ -0,0 +1,39 @@
+# This workflow will install Python dependencies, run tests and lint with a single version of Python
+# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
+
+name: test_app
+
+on:
+  push:
+    branches: [ "master" ]
+  pull_request:
+    branches: [ "master" ]
+
+permissions:
+  contents: read
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v3
+    - name: Set up Python 3.8
+      uses: actions/setup-python@v3
+      with:
+        python-version: "3.8"
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install flake8 pytest
+        if [ -f starter/requirements.txt ]; then pip install -r starter/requirements.txt; fi
+    - name: Lint with flake8
+      run: |
+        # stop the build if there are Python syntax errors or undefined names
+        # flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    # - name: Test with pytest
+    #   run: |
+    #     pytest

starter/requirements.txt

@@ -1,4 +1,3 @@
-python==3.8
 numpy
 pandas
 scikit-learn

starter/starter/ml/data.py

@@ -64,7 +64,7 @@ def process_data(
             y = lb.transform(y.values).ravel()
         # Catch the case where y is None because we're doing inference.
         except AttributeError:
-            pass
+            y = None
 
     X = np.concatenate([X_continuous, X_categorical], axis=1)
     return X, y, encoder, lb

starter/starter/train_model.py

@@ -3,6 +3,7 @@
 from sklearn.model_selection import train_test_split
 
 # Add the necessary imports for the starter code.
+from ml.data import process_data
 
 # Add code to load in the data.