compatible with python3.11

.github/workflows/test.yml

@@ -34,7 +34,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ "ubuntu-latest", "windows-latest" ] # todo support macos test
-        python-version: [ "3.8", "3.9", "3.10" ]
+        python-version: [ "3.8", "3.9", "3.10", "3.11" ]
     steps:
     - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}

openbox/surrogate/base/rf_with_instances_sklearn.py

@@ -6,7 +6,7 @@
 from sklearn.ensemble import RandomForestRegressor
 import threading
 from joblib import Parallel, delayed
-from sklearn.utils.fixes import _joblib_parallel_args
+# from sklearn.utils.fixes import _joblib_parallel_args
 from sklearn.utils.validation import check_is_fitted
 try:
     from sklearn.ensemble.base import _partition_estimators
@@ -20,6 +20,58 @@
 from openbox.utils.constants import N_TREES
 
 
+def _joblib_parallel_args(**kwargs):
+    """Set joblib.Parallel arguments in a compatible way for 0.11 and 0.12+
+
+    For joblib 0.11 this maps both ``prefer`` and ``require`` parameters to
+    a specific ``backend``.
+
+    Parameters
+    ----------
+
+    prefer : str in {'processes', 'threads'} or None
+        Soft hint to choose the default backend if no specific backend
+        was selected with the parallel_backend context manager.
+
+    require : 'sharedmem' or None
+        Hard condstraint to select the backend. If set to 'sharedmem',
+        the selected backend will be single-host and thread-based even
+        if the user asked for a non-thread based backend with
+        parallel_backend.
+
+    See joblib.Parallel documentation for more details
+    """
+    import joblib
+
+    if joblib.__version__ >= "0.12":
+        return kwargs
+
+    extra_args = set(kwargs.keys()).difference({"prefer", "require"})
+    if extra_args:
+        raise NotImplementedError(
+            "unhandled arguments %s with joblib %s"
+            % (list(extra_args), joblib.__version__)
+        )
+    args = {}
+    if "prefer" in kwargs:
+        prefer = kwargs["prefer"]
+        if prefer not in ["threads", "processes", None]:
+            raise ValueError("prefer=%s is not supported" % prefer)
+        args["backend"] = {
+            "threads": "threading",
+            "processes": "multiprocessing",
+            None: None,
+        }[prefer]
+
+    if "require" in kwargs:
+        require = kwargs["require"]
+        if require not in [None, "sharedmem"]:
+            raise ValueError("require=%s is not supported" % require)
+        if require == "sharedmem":
+            args["backend"] = "threading"
+    return args
+
+
 def _collect_prediction(predict, X, out, lock):
     """
     This is a utility function for joblib's Parallel.

requirements/main.txt

@@ -9,9 +9,9 @@ matplotlib
 pandas
 numpy>=1.7.1
 scipy>=0.18.1,<=1.10.1
-scikit-learn>=0.21.3,<=1.0.2
+scikit-learn>=0.21.3,<=1.1.3
 scikit-optimize>=0.9
-ConfigSpace>=0.4.20,<=0.6
+ConfigSpace>=0.4.20,<=0.6.1
 emcee
 statsmodels
 platypus-opt==1.0.4