Chore: Bump pre-commit and Github actions + py3.10 on CI

.github/workflows/ci.yml

@@ -11,11 +11,11 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        PYTHON_VERSION: ["3.7", "3.9"]
+        PYTHON_VERSION: ["3.7", "3.10"]
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
       - name: Setup conda cache
-        uses: actions/cache@v2
+        uses: actions/cache@v3
         with:
           path: ~/conda_pkgs_dir
           key:
@@ -30,7 +30,7 @@ jobs:
           use-only-tar-bz2: true
           use-mamba: true
       - name: Setup hypothesis DB cache
-        uses: actions/cache@v2
+        uses: actions/cache@v3
         with:
           path: ./.hypothesis
           key: hypothesisDB ${{ matrix.PYTHON_VERSION }}
@@ -39,7 +39,7 @@ jobs:
         run: ./.github/ci.sh ${{ matrix.PYTHON_VERSION }}
       - name: Publish a Python distribution to PyPI
         if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags') && matrix.PYTHON_VERSION == '3.7'
-        uses: pypa/gh-action-pypi-publish@v1.4.2
+        uses: pypa/gh-action-pypi-publish@v1.5.0
         with:
           user: __token__
           password: ${{ secrets.PYPI_API_TOKEN }}
@@ -49,12 +49,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout branch
-        uses: actions/[email protected]
-        with:
-          ref: ${{ github.head_ref }}
+        uses: actions/checkout@v3
       - name: Install Python 3.9
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: 3.9
       - name: Run pre-commit checks
-        uses: pre-commit/action@v2.0.0
+        uses: pre-commit/action@v3.0.0

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/psf/black
-    rev: 20.8b1
+    rev: 22.6.0
     hooks:
       - id: black
         language_version: python3

lleaves/lleaves.py

@@ -159,7 +159,7 @@ def predict(self, data, n_jobs=os.cpu_count()):
                 f"Data must be of dimension (N, {self.num_feature()}), is {data.shape}."
             )
         # protect against `ctypes.c_int32` silently overflowing and causing SIGSEGV
-        if n_predictions >= 2 ** 31 - 1:
+        if n_predictions >= 2**31 - 1:
             raise ValueError(
                 "Prediction is not supported for datasets with >=2^31-1 rows. "
                 "Split the dataset into smaller chunks first."

tests/test_categoricals.py

@@ -195,7 +195,7 @@ def test_categorical_prediction_llvm_real(data, categorical_model_txt):
 
     input = data.draw(
         st.lists(
-            st.integers(min_value=0, max_value=2 ** 31 - 2),
+            st.integers(min_value=0, max_value=2**31 - 2),
             max_size=llvm_model.num_feature(),
             min_size=llvm_model.num_feature(),
         )

tests/test_tree_output.py

@@ -104,7 +104,7 @@ def test_forest_llvm_mode_cat(data, llvm_lgbm_model_cat):
 
     input_cats = data.draw(
         st.lists(
-            st.integers(min_value=0, max_value=2 ** 31 - 2),
+            st.integers(min_value=0, max_value=2**31 - 2),
             min_size=sum(cat_bitvec),
             max_size=sum(cat_bitvec),
         )