[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

openml/__init__.py

@@ -18,6 +18,8 @@
 # License: BSD 3-Clause
 from __future__ import annotations
 
+from openml._get import get
+
 from . import (
     _api_calls,
     config,
@@ -48,7 +50,6 @@
     OpenMLSupervisedTask,
     OpenMLTask,
 )
-from openml._get import get
 
 
 def populate_cache(

openml/_get.py

@@ -4,6 +4,8 @@
 # to discuss and possibly
 # todo: add global get utility here
 # in general, e.g., datasets will not have same name as models etc
+from __future__ import annotations
+
 from openml.models import get
 
 __all__ = ["get"]

openml/base/_base_pkg.py

@@ -1,16 +1,17 @@
 """Base Packager class."""
 
+from __future__ import annotations
+
 import inspect
-from pathlib import Path
 import sys
 import textwrap
+from pathlib import Path
 
 from skbase.base import BaseObject
 from skbase.utils.dependencies import _check_estimator_deps
 
 
 class _BasePkg(BaseObject):
-
     _tags = {
         "python_dependencies": None,
         "python_version": None,
@@ -50,15 +51,11 @@ def serialize(self):
 
         cls_str = cls_str.encode("utf-8")
         exec(f"import {compress_method}")
-        compressed_str = eval(f"{compress_method}.compress(cls_str)")
-
-        return compressed_str
+        return eval(f"{compress_method}.compress(cls_str)")
 
 
 def _has_source(obj) -> bool:
-    """
-    Return True if inspect.getsource(obj) should succeed.
-    """
+    """Return True if inspect.getsource(obj) should succeed."""
     module_name = getattr(obj, "__module__", None)
     if not module_name or module_name not in sys.modules:
         return False
@@ -82,7 +79,7 @@ def class_to_source(cls) -> str:
     -------
     str : complete definition of cls, as str.
         Imports are not contained or serialized.
-    """""
+    """ ""
 
     # Fast path: class has retrievable source
     if _has_source(cls):
@@ -111,7 +108,7 @@ def class_to_source(cls) -> str:
                 lines.append(f"    def {name}(self): ...")
             body_added = True
         else:
-            lines.append(f"    {name} = {repr(value)}")
+            lines.append(f"    {name} = {value!r}")
             body_added = True
 
     if not body_added:

openml/models/_get.py

@@ -1,6 +1,7 @@
-
 """Model retrieval utility."""
 
+from __future__ import annotations
+
 from functools import lru_cache
 
 
@@ -22,14 +23,10 @@ def get(id: str):
     ModuleNotFoundError
         if dependencies of object to retrieve are not satisfied
     """
-
     id_lookup = _id_lookup()
     obj = id_lookup.get(id)
     if obj is None:
-        raise ValueError(
-            f"Error in openml.get, object with package id {id} "
-            "does not exist."
-        )
+        raise ValueError(f"Error in openml.get, object with package id {id} " "does not exist.")
     return obj().materialize()
 
 
@@ -45,9 +42,7 @@ def _id_lookup_cached(obj_type=None):
     all_objs = _all_objects(obj_type=obj_type)
 
     # todo: generalize that pkg can contain more than one object
-    lookup_dict = {obj.get_class_tag("pkg_id"): obj for obj in all_objs}
-
-    return lookup_dict
+    return {obj.get_class_tag("pkg_id"): obj for obj in all_objs}
 
 
 @lru_cache
@@ -56,8 +51,4 @@ def _all_objects(obj_type=None):
 
     from openml.models.apis._classifier import _ModelPkgClassifier
 
-    clses = all_objects(
-        object_types=_ModelPkgClassifier, package_name="openml", return_names=False
-    )
-
-    return clses
+    return all_objects(object_types=_ModelPkgClassifier, package_name="openml", return_names=False)

openml/models/apis/_classifier.py

@@ -1,10 +1,11 @@
 """Base package for sklearn classifiers."""
 
+from __future__ import annotations
+
 from openml.models.base import _OpenmlModelPkg
 
 
 class _ModelPkgClassifier(_OpenmlModelPkg):
-
     _tags = {
         # tags specific to API type
         "pkg_obj_type": "classifier",

openml/models/base/_base.py

@@ -1,10 +1,11 @@
 """Base model package class."""
 
+from __future__ import annotations
+
 from openml.base import _BasePkg
 
 
 class _OpenmlModelPkg(_BasePkg):
-
     _obj = None
 
     def _materialize(self):
@@ -22,20 +23,18 @@ def _materialize(self):
         if pkg_obj == "reference":
             from skbase.utils.dependencies import _safe_import
 
-            obj = _safe_import(self._obj)
-            return obj
+            return _safe_import(self._obj)
 
-        elif pkg_obj == "code":
+        if pkg_obj == "code":
             exec(self._obj)
 
             return obj
 
         # elif pkg_obj == "craft":
         #    identify and call appropriate craft method
 
-        else:
-            raise ValueError(
-                'Error in package tag "pkg_obj", '
-                'must be one of "reference", "code", "craft", '
-                f'but found value {pkg_obj}, of type {type(pkg_obj)}'
-            )
+        raise ValueError(
+            'Error in package tag "pkg_obj", '
+            'must be one of "reference", "code", "craft", '
+            f"but found value {pkg_obj}, of type {type(pkg_obj)}"
+        )

openml/models/classification/auto_sklearn.py

@@ -1,11 +1,11 @@
 """Auto-sklearn classifier."""
 
+from __future__ import annotations
 
 from openml.models.apis import _ModelPkgClassifier
 
 
 class OpenmlPkg__AutoSklearnClassifier(_ModelPkgClassifier):
-
     _tags = {
         "pkg_id": "AutoSklearnClassifier",
         "python_dependencies": "auto-sklearn",

openml/models/classification/xgboost.py

@@ -1,11 +1,11 @@
 """Xgboost classifier."""
 
+from __future__ import annotations
 
 from openml.models.apis import _ModelPkgClassifier
 
 
 class OpenmlPkg__XGBClassifier(_ModelPkgClassifier):
-
     _tags = {
         "pkg_id": "XGBClassifier",
         "python_dependencies": "xgboost",