reupdated str[python] catch after git shenanigans

Author: eicchen

pandas/tests/arrays/string_/test_string.py

@@ -61,6 +61,14 @@ def string_dtype_highest_priority(dtype1, dtype2):
     return DTYPE_HIERARCHY[max(h1, h2)]
 
 
+def test_dtype_constructor():
+    pytest.importorskip("pyarrow")
+
+    with tm.assert_produces_warning(FutureWarning):
+        dtype = pd.StringDtype("pyarrow_numpy")
+    assert dtype == pd.StringDtype("pyarrow", na_value=np.nan)
+
+
 def test_dtype_equality():
     pytest.importorskip("pyarrow")
 
@@ -531,8 +539,7 @@ def test_astype_float(dtype, any_float_dtype):
     # Don't compare arrays (37974)
     ser = pd.Series(["1.1", pd.NA, "3.3"], dtype=dtype)
     result = ser.astype(any_float_dtype)
-    item = np.nan if isinstance(result.dtype, np.dtype) else pd.NA
-    expected = pd.Series([1.1, item, 3.3], dtype=any_float_dtype)
+    expected = pd.Series([1.1, np.nan, 3.3], dtype=any_float_dtype)
     tm.assert_series_equal(result, expected)
 
 
@@ -846,30 +853,3 @@ def test_string_array_view_type_error():
     arr = pd.array(["a", "b", "c"], dtype="string")
     with pytest.raises(TypeError, match="Cannot change data-type for string array."):
         arr.view("i8")
-
-
-@pytest.mark.parametrize("box", [pd.Series, pd.array])
-def test_numpy_array_ufunc(dtype, box):
-    arr = box(["a", "bb", "ccc"], dtype=dtype)
-
-    # custom ufunc that works with string (object) input -> returning numeric
-    str_len_ufunc = np.frompyfunc(lambda x: len(x), 1, 1)
-    result = str_len_ufunc(arr)
-    expected_cls = pd.Series if box is pd.Series else np.array
-    # TODO we should infer int64 dtype here?
-    expected = expected_cls([1, 2, 3], dtype=object)
-    tm.assert_equal(result, expected)
-
-    # custom ufunc returning strings
-    str_multiply_ufunc = np.frompyfunc(lambda x: x * 2, 1, 1)
-    result = str_multiply_ufunc(arr)
-    expected = box(["aa", "bbbb", "cccccc"], dtype=dtype)
-    if dtype.storage == "pyarrow":
-        # TODO ArrowStringArray should also preserve the class / dtype
-        if box is pd.array:
-            expected = np.array(["aa", "bbbb", "cccccc"], dtype=object)
-        else:
-            # not specifying the dtype because the exact dtype is not yet preserved
-            expected = pd.Series(["aa", "bbbb", "cccccc"])
-
-    tm.assert_equal(result, expected)