TST: remove expected warnings for new numexpr version (pandas-dev#62553)

Author: Alvaro-Kothe

pandas/tests/frame/test_arithmetic.py

@@ -11,6 +11,8 @@
 import numpy as np
 import pytest
 
+from pandas.compat._optional import import_optional_dependency
+
 import pandas as pd
 from pandas import (
  DataFrame,
@@ -24,6 +26,7 @@
  _check_mixed_float,
  _check_mixed_int,
 )
+from pandas.util.version import Version
 
 
 @pytest.fixture
@@ -1114,6 +1117,8 @@ 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 (
@@ -1142,7 +1147,11 @@ 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
+ ):
  warn = UserWarning
  else:
  warn = None

pandas/tests/series/test_arithmetic.py

@@ -10,6 +10,7 @@
 import pytest
 
 from pandas._libs import lib
+from pandas.compat._optional import import_optional_dependency
 
 import pandas as pd
 from pandas import (
@@ -25,7 +26,7 @@
 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"])
@@ -348,9 +349,12 @@ 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

@@ -4,10 +4,13 @@
 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 DataFrame
 from pandas.core.computation import expressions as expr
+from pandas.util.version import Version
 
 
 @pytest.fixture
@@ -340,35 +343,43 @@ def test_bool_ops_warn_on_arithmetic(self, op_str, opname, monkeypatch):
  return
 
  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(UserWarning, match=msg):
+ 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(UserWarning, match=msg):
+ 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(UserWarning, match=msg):
+ 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(UserWarning, match=msg):
+ 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(UserWarning, match=msg):
+ 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(UserWarning, match=msg):
+ with tm.assert_produces_warning(warning, match=msg):
  r = f(df, True)
  e = fe(df, True)
  tm.assert_frame_equal(r, e)