Backport PR #49771 on branch 1.5.x (PERF: Use fastpath for accessing …

…option value in internals) (#50128)

Co-authored-by: Joris Van den Bossche <jorisvandenbossche@gmail.com>
Co-authored-by: Patrick Hoefler <61934744+phofl@users.noreply.github.com>

pandas/core/internals/managers.py

@@ -15,7 +15,7 @@
 
 import numpy as np
 
-from pandas._config import get_option
+from pandas._config.config import _global_config
 
 from pandas._libs import (
     algos as libalgos,
@@ -2427,5 +2427,8 @@ def _preprocess_slice_or_indexer(
         return "fancy", indexer, len(indexer)
 
 
+_mode_options = _global_config["mode"]
+
+
 def _using_copy_on_write():
-    return get_option("mode.copy_on_write")
+    return _mode_options["copy_on_write"]

pandas/tests/copy_view/test_internals.py

@@ -3,6 +3,7 @@
 
 import pandas.util._test_decorators as td
 
+import pandas as pd
 from pandas import DataFrame
 from pandas.tests.copy_view.util import get_array
 
@@ -62,3 +63,33 @@ def test_clear_parent(using_copy_on_write):
     # when losing the last reference, also the parent should be reset
     subset["b"] = 0
     assert subset._mgr.parent is None
+
+
+@pytest.mark.single_cpu
+@td.skip_array_manager_invalid_test
+def test_switch_options():
+    # ensure we can switch the value of the option within one session
+    # (assuming data is constructed after switching)
+
+    # using the option_context to ensure we set back to global option value
+    # after running the test
+    with pd.option_context("mode.copy_on_write", False):
+        df = DataFrame({"a": [1, 2, 3], "b": [0.1, 0.2, 0.3]})
+        subset = df[:]
+        subset.iloc[0, 0] = 0
+        # df updated with CoW disabled
+        assert df.iloc[0, 0] == 0
+
+        pd.options.mode.copy_on_write = True
+        df = DataFrame({"a": [1, 2, 3], "b": [0.1, 0.2, 0.3]})
+        subset = df[:]
+        subset.iloc[0, 0] = 0
+        # df not updated with CoW enabled
+        assert df.iloc[0, 0] == 1
+
+        pd.options.mode.copy_on_write = False
+        df = DataFrame({"a": [1, 2, 3], "b": [0.1, 0.2, 0.3]})
+        subset = df[:]
+        subset.iloc[0, 0] = 0
+        # df updated with CoW disabled
+        assert df.iloc[0, 0] == 0