[backport 2.3.x] TST: remove expected warnings for new numexpr version (#62553) (#62557)

Author: Alvaro-Kothe

pandas/tests/frame/test_arithmetic.py

@@ -12,6 +12,7 @@
 import pytest
 
 from pandas.compat import HAS_PYARROW
+from pandas.compat._optional import import_optional_dependency
 import pandas.util._test_decorators as td
 
 import pandas as pd
@@ -27,6 +28,7 @@
     _check_mixed_float,
     _check_mixed_int,
 )
+from pandas.util.version import Version
 
 
 @pytest.fixture
@@ -1092,6 +1094,8 @@ def test_binop_other(self, op, value, dtype, switch_numexpr_min_elements):
             (operator.mod, "complex128"),
         }
 
+        ne = import_optional_dependency("numexpr", errors="ignore")
+        ne_warns_on_op = ne is not None and Version(ne.__version__) < Version("2.13.1")
         if (op, dtype) in invalid:
             warn = None
             if (dtype == "<M8[ns]" and op == operator.add) or (
@@ -1120,7 +1124,11 @@ def test_binop_other(self, op, value, dtype, switch_numexpr_min_elements):
 
         elif (op, dtype) in skip:
             if op in [operator.add, operator.mul]:
-                if expr.USE_NUMEXPR and switch_numexpr_min_elements == 0:
+                if (
+                    expr.USE_NUMEXPR
+                    and switch_numexpr_min_elements == 0
+                    and ne_warns_on_op
+                ):
                     # "evaluating in Python space because ..."
                     warn = UserWarning
                 else:

pandas/tests/series/test_arithmetic.py

@@ -11,6 +11,7 @@
 
 from pandas._libs import lib
 from pandas._libs.tslibs import IncompatibleFrequency
+from pandas.compat._optional import import_optional_dependency
 
 import pandas as pd
 from pandas import (
@@ -26,7 +27,7 @@
 import pandas._testing as tm
 from pandas.core import ops
 from pandas.core.computation import expressions as expr
-from pandas.core.computation.check import NUMEXPR_INSTALLED
+from pandas.util.version import Version
 
 
 @pytest.fixture(autouse=True, params=[0, 1000000], ids=["numexpr", "python"])
@@ -353,9 +354,12 @@ def test_add_list_to_masked_array(self, val, dtype):
 
     def test_add_list_to_masked_array_boolean(self, request):
         # GH#22962
+        ne = import_optional_dependency("numexpr", errors="ignore")
         warning = (
             UserWarning
-            if request.node.callspec.id == "numexpr" and NUMEXPR_INSTALLED
+            if request.node.callspec.id == "numexpr"
+            and ne
+            and Version(ne.__version__) < Version("2.13.1")
             else None
         )
         ser = Series([True, None, False], dtype="boolean")

pandas/tests/test_expressions.py

@@ -4,6 +4,8 @@
 import numpy as np
 import pytest
 
+from pandas.compat._optional import import_optional_dependency
+
 from pandas import option_context
 import pandas._testing as tm
 from pandas.core.api import (
@@ -12,6 +14,7 @@
     Series,
 )
 from pandas.core.computation import expressions as expr
+from pandas.util.version import Version
 
 
 @pytest.fixture
@@ -324,7 +327,7 @@ def test_bool_ops_raise_on_arithmetic(self, op_str, opname):
     @pytest.mark.parametrize(
         "op_str,opname", [("+", "add"), ("*", "mul"), ("-", "sub")]
     )
-    def test_bool_ops_warn_on_arithmetic(self, op_str, opname):
+    def test_bool_ops_warn_on_arithmetic(self, op_str, opname, monkeypatch):
         n = 10
         df = DataFrame(
             {
@@ -343,36 +346,47 @@ def test_bool_ops_warn_on_arithmetic(self, op_str, opname):
             # raises TypeError
             return
 
-        with tm.use_numexpr(True, min_elements=5):
-            with tm.assert_produces_warning():
-                r = f(df, df)
-                e = fe(df, df)
-                tm.assert_frame_equal(r, e)
-
-            with tm.assert_produces_warning():
-                r = f(df.a, df.b)
-                e = fe(df.a, df.b)
-                tm.assert_series_equal(r, e)
-
-            with tm.assert_produces_warning():
-                r = f(df.a, True)
-                e = fe(df.a, True)
-                tm.assert_series_equal(r, e)
-
-            with tm.assert_produces_warning():
-                r = f(False, df.a)
-                e = fe(False, df.a)
-                tm.assert_series_equal(r, e)
-
-            with tm.assert_produces_warning():
-                r = f(False, df)
-                e = fe(False, df)
-                tm.assert_frame_equal(r, e)
-
-            with tm.assert_produces_warning():
-                r = f(df, True)
-                e = fe(df, True)
-                tm.assert_frame_equal(r, e)
+        msg = "operator is not supported by numexpr"
+        ne = import_optional_dependency("numexpr", errors="ignore")
+        warning = (
+            UserWarning
+            if ne
+            and op_str in {"+", "*"}
+            and Version(ne.__version__) < Version("2.13.1")
+            else None
+        )
+        with monkeypatch.context() as m:
+            m.setattr(expr, "_MIN_ELEMENTS", 5)
+            with option_context("compute.use_numexpr", True):
+                with tm.assert_produces_warning(warning, match=msg):
+                    r = f(df, df)
+                    e = fe(df, df)
+                    tm.assert_frame_equal(r, e)
+
+                with tm.assert_produces_warning(warning, match=msg):
+                    r = f(df.a, df.b)
+                    e = fe(df.a, df.b)
+                    tm.assert_series_equal(r, e)
+
+                with tm.assert_produces_warning(warning, match=msg):
+                    r = f(df.a, True)
+                    e = fe(df.a, True)
+                    tm.assert_series_equal(r, e)
+
+                with tm.assert_produces_warning(warning, match=msg):
+                    r = f(False, df.a)
+                    e = fe(False, df.a)
+                    tm.assert_series_equal(r, e)
+
+                with tm.assert_produces_warning(warning, match=msg):
+                    r = f(False, df)
+                    e = fe(False, df)
+                    tm.assert_frame_equal(r, e)
+
+                with tm.assert_produces_warning(warning, match=msg):
+                    r = f(df, True)
+                    e = fe(df, True)
+                    tm.assert_frame_equal(r, e)
 
     @pytest.mark.parametrize(
         "test_input,expected",