File pandas-pr59353-np2eval.patch of Package python-pandas

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File pandas-pr59353-np2eval.patch of Package python-pandas

diff --git a/pandas/_testing/__init__.py b/pandas/_testing/__init__.py
index 361998db8e..87d419e2db 100644
--- a/pandas/_testing/__init__.py
+++ b/pandas/_testing/__init__.py
@@ -111,6 +111,7 @@ ALL_FLOAT_DTYPES: list[Dtype] = [*FLOAT_NUMPY_DTYPES, *FLOAT_EA_DTYPES]
 
 COMPLEX_DTYPES: list[Dtype] = [complex, "complex64", "complex128"]
 STRING_DTYPES: list[Dtype] = [str, "str", "U"]
+COMPLEX_FLOAT_DTYPES: list[Dtype] = [*COMPLEX_DTYPES, *FLOAT_NUMPY_DTYPES]
 
 DATETIME64_DTYPES: list[Dtype] = ["datetime64[ns]", "M8[ns]"]
 TIMEDELTA64_DTYPES: list[Dtype] = ["timedelta64[ns]", "m8[ns]"]
diff --git a/pandas/conftest.py b/pandas/conftest.py
index 7c35dfdde9..10134c90f8 100644
--- a/pandas/conftest.py
+++ b/pandas/conftest.py
@@ -1403,6 +1403,21 @@ def complex_dtype(request):
     return request.param
 
 
+@pytest.fixture(params=tm.COMPLEX_FLOAT_DTYPES)
+def complex_or_float_dtype(request):
+    """
+    Parameterized fixture for complex and numpy float dtypes.
+
+    * complex
+    * 'complex64'
+    * 'complex128'
+    * float
+    * 'float32'
+    * 'float64'
+    """
+    return request.param
+
+
 @pytest.fixture(params=tm.SIGNED_INT_NUMPY_DTYPES)
 def any_signed_int_numpy_dtype(request):
     """
diff --git a/pandas/core/computation/expr.py b/pandas/core/computation/expr.py
index b5861fbaeb..d642c37cea 100644
--- a/pandas/core/computation/expr.py
+++ b/pandas/core/computation/expr.py
@@ -31,7 +31,6 @@ from pandas.core.computation.ops import (
     UNARY_OPS_SYMS,
     BinOp,
     Constant,
-    Div,
     FuncNode,
     Op,
     Term,
@@ -370,7 +369,7 @@ class BaseExprVisitor(ast.NodeVisitor):
         "Add",
         "Sub",
         "Mult",
-        None,
+        "Div",
         "Pow",
         "FloorDiv",
         "Mod",
@@ -533,9 +532,6 @@ class BaseExprVisitor(ast.NodeVisitor):
         left, right = self._maybe_downcast_constants(left, right)
         return self._maybe_evaluate_binop(op, op_class, left, right)
 
-    def visit_Div(self, node, **kwargs):
-        return lambda lhs, rhs: Div(lhs, rhs)
-
     def visit_UnaryOp(self, node, **kwargs):
         op = self.visit(node.op)
         operand = self.visit(node.operand)
diff --git a/pandas/core/computation/ops.py b/pandas/core/computation/ops.py
index 95ac20ba39..ea8b1c0457 100644
--- a/pandas/core/computation/ops.py
+++ b/pandas/core/computation/ops.py
@@ -332,31 +332,6 @@ for d in (_cmp_ops_dict, _bool_ops_dict, _arith_ops_dict):
     _binary_ops_dict.update(d)
 
 
-def _cast_inplace(terms, acceptable_dtypes, dtype) -> None:
-    """
-    Cast an expression inplace.
-
-    Parameters
-    ----------
-    terms : Op
-        The expression that should cast.
-    acceptable_dtypes : list of acceptable numpy.dtype
-        Will not cast if term's dtype in this list.
-    dtype : str or numpy.dtype
-        The dtype to cast to.
-    """
-    dt = np.dtype(dtype)
-    for term in terms:
-        if term.type in acceptable_dtypes:
-            continue
-
-        try:
-            new_value = term.value.astype(dt)
-        except AttributeError:
-            new_value = dt.type(term.value)
-        term.update(new_value)
-
-
 def is_term(obj) -> bool:
     return isinstance(obj, Term)
 
@@ -516,31 +491,6 @@ class BinOp(Op):
 def isnumeric(dtype) -> bool:
     return issubclass(np.dtype(dtype).type, np.number)
 
-
-class Div(BinOp):
-    """
-    Div operator to special case casting.
-
-    Parameters
-    ----------
-    lhs, rhs : Term or Op
-        The Terms or Ops in the ``/`` expression.
-    """
-
-    def __init__(self, lhs, rhs) -> None:
-        super().__init__("/", lhs, rhs)
-
-        if not isnumeric(lhs.return_type) or not isnumeric(rhs.return_type):
-            raise TypeError(
-                f"unsupported operand type(s) for {self.op}: "
-                f"'{lhs.return_type}' and '{rhs.return_type}'"
-            )
-
-        # do not upcast float32s to float64 un-necessarily
-        acceptable_dtypes = [np.float32, np.float64]
-        _cast_inplace(com.flatten(self), acceptable_dtypes, np.float64)
-
-
 UNARY_OPS_SYMS = ("+", "-", "~", "not")
 _unary_ops_funcs = (operator.pos, operator.neg, operator.invert, operator.invert)
 _unary_ops_dict = dict(zip(UNARY_OPS_SYMS, _unary_ops_funcs))
diff --git a/pandas/tests/computation/test_eval.py b/pandas/tests/computation/test_eval.py
index 17630f14b0..e8fad6b8cb 100644
--- a/pandas/tests/computation/test_eval.py
+++ b/pandas/tests/computation/test_eval.py
@@ -747,16 +747,26 @@ class TestTypeCasting:
     @pytest.mark.parametrize("op", ["+", "-", "*", "**", "/"])
     # maybe someday... numexpr has too many upcasting rules now
     # chain(*(np.core.sctypes[x] for x in ['uint', 'int', 'float']))
-    @pytest.mark.parametrize("dt", [np.float32, np.float64])
     @pytest.mark.parametrize("left_right", [("df", "3"), ("3", "df")])
-    def test_binop_typecasting(self, engine, parser, op, dt, left_right):
-        df = DataFrame(np.random.default_rng(2).standard_normal((5, 3)), dtype=dt)
+    def test_binop_typecasting(
+        self, engine, parser, op, complex_or_float_dtype, left_right, request
+    ):
+        # GH#21374
+        dtype = complex_or_float_dtype
+        df = DataFrame(np.random.default_rng(2).standard_normal((5, 3)), dtype=dtype)
         left, right = left_right
         s = f"{left} {op} {right}"
         res = pd.eval(s, engine=engine, parser=parser)
-        assert df.values.dtype == dt
-        assert res.values.dtype == dt
-        tm.assert_frame_equal(res, eval(s))
+        if dtype == "complex64" and engine == "numexpr":
+            mark = pytest.mark.xfail(
+                reason="numexpr issue with complex that are upcast "
+                "to complex 128 "
+                "https://github.com/pydata/numexpr/issues/492"
+            )
+            request.applymarker(mark)
+        assert df.values.dtype == dtype
+        assert res.values.dtype == dtype
+        tm.assert_frame_equal(res, eval(s), check_exact=False)
 
 
 # -------------------------------------

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