Move mock execution class to conftest

Author: datapythonista

pandas/tests/apply/common.py

@@ -1,64 +1,7 @@
-import numpy as np
-
-from pandas import (
-    DataFrame,
-    Series,
-)
-from pandas.api.executors import BaseExecutionEngine
 from pandas.core.groupby.base import transformation_kernels
 
 # There is no Series.cumcount or DataFrame.cumcount
 series_transform_kernels = [
     x for x in sorted(transformation_kernels) if x != "cumcount"
 ]
 frame_transform_kernels = [x for x in sorted(transformation_kernels) if x != "cumcount"]
-
-
-class MockExecutionEngine(BaseExecutionEngine):
-    """
-    Execution Engine to test if the execution engine interface receives and
-    uses all parameters provided by the user.
-
-    Making this engine work as the default Python engine by calling it, no extra
-    functionality is implemented here.
-
-    When testing, this will be called when this engine is provided, and then the
-    same pandas.map and pandas.apply function will be called, but without engine,
-    executing the default behavior from the python engine.
-    """
-
-    def map(data, func, args, kwargs, decorator, skip_na):
-        kwargs_to_pass = kwargs if isinstance(data, DataFrame) else {}
-        return data.map(func, na_action="ignore" if skip_na else None, **kwargs_to_pass)
-
-    def apply(data, func, args, kwargs, decorator, axis):
-        if isinstance(data, Series):
-            return data.apply(func, convert_dtype=True, args=args, by_row=False)
-        elif isinstance(data, DataFrame):
-            return data.apply(
-                func,
-                axis=axis,
-                raw=False,
-                result_type=None,
-                args=args,
-                by_row="compat",
-                **kwargs,
-            )
-        else:
-            assert isinstance(data, np.ndarray)
-
-            def wrap_function(func):
-                # https://github.com/numpy/numpy/issues/8352
-                def wrapper(*args, **kwargs):
-                    result = func(*args, **kwargs)
-                    if isinstance(result, str):
-                        result = np.array(result, dtype=object)
-                    return result
-
-                return wrapper
-
-            return np.apply_along_axis(wrap_function(func), axis, data, *args, **kwargs)
-
-
-class MockEngineDecorator:
-    __pandas_udf__ = MockExecutionEngine

pandas/tests/apply/conftest.py

@@ -1,6 +1,61 @@
+import numpy as np
 import pytest
 
-from pandas.tests.apply.common import MockEngineDecorator
+from pandas import (
+    DataFrame,
+    Series,
+)
+from pandas.api.executors import BaseExecutionEngine
+
+
+class MockExecutionEngine(BaseExecutionEngine):
+    """
+    Execution Engine to test if the execution engine interface receives and
+    uses all parameters provided by the user.
+
+    Making this engine work as the default Python engine by calling it, no extra
+    functionality is implemented here.
+
+    When testing, this will be called when this engine is provided, and then the
+    same pandas.map and pandas.apply function will be called, but without engine,
+    executing the default behavior from the python engine.
+    """
+
+    def map(data, func, args, kwargs, decorator, skip_na):
+        kwargs_to_pass = kwargs if isinstance(data, DataFrame) else {}
+        return data.map(func, na_action="ignore" if skip_na else None, **kwargs_to_pass)
+
+    def apply(data, func, args, kwargs, decorator, axis):
+        if isinstance(data, Series):
+            return data.apply(func, convert_dtype=True, args=args, by_row=False)
+        elif isinstance(data, DataFrame):
+            return data.apply(
+                func,
+                axis=axis,
+                raw=False,
+                result_type=None,
+                args=args,
+                by_row="compat",
+                **kwargs,
+            )
+        else:
+            assert isinstance(data, np.ndarray)
+
+            def wrap_function(func):
+                # https://github.com/numpy/numpy/issues/8352
+                def wrapper(*args, **kwargs):
+                    result = func(*args, **kwargs)
+                    if isinstance(result, str):
+                        result = np.array(result, dtype=object)
+                    return result
+
+                return wrapper
+
+            return np.apply_along_axis(wrap_function(func), axis, data, *args, **kwargs)
+
+
+class MockEngineDecorator:
+    __pandas_udf__ = MockExecutionEngine
 
 
 @pytest.fixture(params=[None, MockEngineDecorator])

pandas/tests/apply/test_frame_apply.py

@@ -17,7 +17,7 @@
     date_range,
 )
 import pandas._testing as tm
-from pandas.tests.apply.common import MockEngineDecorator
+from pandas.tests.apply.conftest import MockEngineDecorator
 from pandas.tests.frame.common import zip_frames
 from pandas.util.version import Version