Merge pull request #1241 from mindsdb/staging

Release 24.12.1.0

Author: MinuraPunchihewa

.github/workflows/lightwood.yml

@@ -7,64 +7,63 @@ on:
       - stable
       - staging
   release:
-    types: [ published ]
-
+    types: [published]
 
 jobs:
   test:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: ["3.8","3.9","3.10","3.11"]
+        python-version: ["3.9", "3.10", "3.11"]
     steps:
-    - uses: actions/checkout@v2
-    - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
-      with:
-        python-version: ${{ matrix.python-version }}
-    - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        python -m pip install setuptools poetry
-        poetry install -E dev -E image
-    - name: Install dependencies OSX
-      run: |
-        if [ "$RUNNER_OS" == "macOS" ]; then
-          brew install libomp;
-        fi
-      shell: bash
-      env:
-        CHECK_FOR_UPDATES: False
-    - name: Lint with flake8
-      run: |
-        poetry run python -m flake8 .
-    - name: Test with unittest
-      run: |
-        # Run all the "standard" tests
-        poetry run python -m unittest discover tests
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install setuptools poetry
+          poetry install -E dev -E image
+      - name: Install dependencies OSX
+        run: |
+          if [ "$RUNNER_OS" == "macOS" ]; then
+            brew install libomp;
+          fi
+        shell: bash
+        env:
+          CHECK_FOR_UPDATES: False
+      - name: Lint with flake8
+        run: |
+          poetry run python -m flake8 .
+      - name: Test with unittest
+        run: |
+          # Run all the "standard" tests
+          poetry run python -m unittest discover tests
 
   deploy:
     runs-on: ubuntu-latest
     environment: PublishCI
     needs: test
     if: github.ref == 'refs/heads/stable' || github.event_name == 'release'
     steps:
-    - uses: actions/checkout@v2
-    - name: Set up Python
-      uses: actions/setup-python@v2
-      with:
-        python-version: '3.8'
-    - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        pip install poetry
-    - name: Build
-      run: poetry build
-    - name: Publish
-      env:
-        POETRY_HTTP_BASIC_PYPI_USERNAME: __token__
-        POETRY_HTTP_BASIC_PYPI_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
-      run: |
-        poetry publish --dry-run
-        poetry publish
+      - uses: actions/checkout@v2
+      - name: Set up Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: "3.10"
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install poetry
+      - name: Build
+        run: poetry build
+      - name: Publish
+        env:
+          POETRY_HTTP_BASIC_PYPI_USERNAME: __token__
+          POETRY_HTTP_BASIC_PYPI_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+        run: |
+          poetry publish --dry-run
+          poetry publish

lightwood/analysis/nc/calibrate.py

@@ -59,7 +59,7 @@ def analyze(self, info: Dict[str, object], **kwargs) -> Dict[str, object]:
                 all_classes = np.array([ns.encoded_val_data.encoders[ns.target].rev_map[idx] for idx in class_keys])
 
             if data_type != dtype.tags:
-                enc = OneHotEncoder(sparse=False, handle_unknown='ignore')
+                enc = OneHotEncoder(sparse_output=False, handle_unknown='ignore')
                 enc.fit(all_classes.reshape(-1, 1))
                 output['label_encoders'] = enc  # needed to repr cat labels inside nonconformist
             else:

lightwood/encoder/helpers.py

@@ -45,7 +45,7 @@ class CatNormalizer:
     def __init__(self, encoder_class='one_hot'):
         self.encoder_class = encoder_class
         if encoder_class == 'one_hot':
-            self.scaler = OneHotEncoder(sparse=False, handle_unknown='ignore')
+            self.scaler = OneHotEncoder(sparse_output=False, handle_unknown='ignore')
         else:
             self.scaler = OrdinalEncoder()