feat: support for py313, py314

Author: simonprovost

.github/workflows/build-and-test.yml

@@ -12,7 +12,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, windows-latest, macos-latest]
-        python-version: ["3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
     steps:
     - uses: actions/checkout@v4
     - name: Set up Python

.github/workflows/build-wheels.yml

@@ -34,6 +34,8 @@ jobs:
             cp310-manylinux_x86_64 cp310-manylinux_aarch64 cp310-macosx_x86_64 cp310-win_amd64
             cp311-manylinux_x86_64 cp311-manylinux_aarch64 cp311-macosx_x86_64 cp311-win_amd64
             cp312-manylinux_x86_64 cp312-manylinux_aarch64 cp312-macosx_x86_64 cp312-win_amd64
+            cp313-manylinux_x86_64 cp313-manylinux_aarch64 cp313-macosx_x86_64 cp313-win_amd64
+            cp314-manylinux_x86_64 cp314-manylinux_aarch64 cp314-macosx_x86_64 cp314-win_amd64
       - name: Store artifacts
         uses: actions/upload-artifact@v4
         with:

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
 -   repo: https://github.com/ambv/black
-    rev: 20.8b1
+    rev: 24.8.0
     hooks:
     - id: black
       language_version: python3

build_tools/requirements.txt

@@ -1,10 +1,10 @@
 -r ../requirements.txt
 pytest
 pre-commit
-black==20.8b1
+black==24.8.0
 click==8.0.3
 flake8==3.8.4
 pytest-cov
 lightgbm
 xgboost
-cython>=0.28.5
+cython>=3.0,<3.1

deepforest/_binner.py

@@ -5,7 +5,6 @@
     https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/ensemble/_hist_gradient_boosting/binning.py
 """
 
-
 __all__ = ["Binner"]
 
 import numpy as np

deepforest/_estimator.py

@@ -1,6 +1,5 @@
 """A wrapper on the base estimator for the naming consistency."""
 
-
 __all__ = ["Estimator"]
 
 import numpy as np

deepforest/_io.py

@@ -3,7 +3,6 @@
 class is designed to support the partial mode in deep forest.
 """
 
-
 __all__ = ["Buffer"]
 
 import os

deepforest/_layer.py

@@ -1,6 +1,5 @@
 """Implementation of the cascade layer in deep forest."""
 
-
 __all__ = [
     "BaseCascadeLayer",
     "ClassificationCascadeLayer",

deepforest/_utils.py

@@ -1,6 +1,5 @@
 """Implement utilities used in deep forest."""
 
-
 import numpy as np
 from datetime import datetime
 

deepforest/cascade.py

@@ -1,6 +1,5 @@
 """Implementation of Deep Forest."""
 
-
 __all__ = ["CascadeForestClassifier", "CascadeForestRegressor"]
 
 import numbers
@@ -770,10 +769,12 @@ def fit(self, X, y, sample_weight=None):
         X, y = check_X_y(
             X,
             y,
-            multi_output=True
-            if type_of_target(y)
-            in ("continuous-multioutput", "multiclass-multioutput")
-            else False,
+            multi_output=(
+                True
+                if type_of_target(y)
+                in ("continuous-multioutput", "multiclass-multioutput")
+                else False
+            ),
         )
 
         self._check_input(X, y)
@@ -1427,10 +1428,12 @@ def fit(self, X, y, sample_weight=None):
         X, y = check_X_y(
             X,
             y,
-            multi_output=True
-            if type_of_target(y)
-            in ("continuous-multioutput", "multiclass-multioutput")
-            else False,
+            multi_output=(
+                True
+                if type_of_target(y)
+                in ("continuous-multioutput", "multiclass-multioutput")
+                else False
+            ),
         )
         # Check the input for classification
         y = self._encode_class_labels(y)
@@ -1639,10 +1642,12 @@ def fit(self, X, y, sample_weight=None):
         X, y = check_X_y(
             X,
             y,
-            multi_output=True
-            if type_of_target(y)
-            in ("continuous-multioutput", "multiclass-multioutput")
-            else False,
+            multi_output=(
+                True
+                if type_of_target(y)
+                in ("continuous-multioutput", "multiclass-multioutput")
+                else False
+            ),
         )
 
         # Check the input for regression