explicitly test pd.array() behaviour (remove xfail)

Author: jorisvandenbossche

pandas/tests/arrays/test_array.py

@@ -5,8 +5,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 import pandas as pd
 import pandas._testing as tm
 from pandas.api.extensions import register_extension_dtype
@@ -215,21 +213,43 @@ def test_dt64_array(dtype_unit):
             .construct_array_type()
             ._from_sequence(["a", None], dtype=pd.StringDtype()),
         ),
+        (
+            ["a", None],
+            "str",
+            pd.StringDtype(na_value=np.nan)
+            .construct_array_type()
+            ._from_sequence(["a", None], dtype=pd.StringDtype(na_value=np.nan)),
+        ),
         (
             ["a", None],
             pd.StringDtype(),
             pd.StringDtype()
             .construct_array_type()
             ._from_sequence(["a", None], dtype=pd.StringDtype()),
         ),
+        (
+            ["a", None],
+            pd.StringDtype(na_value=np.nan),
+            pd.StringDtype(na_value=np.nan)
+            .construct_array_type()
+            ._from_sequence(["a", None], dtype=pd.StringDtype(na_value=np.nan)),
+        ),
         (
             # numpy array with string dtype
             np.array(["a", "b"], dtype=str),
-            None,
+            pd.StringDtype(),
             pd.StringDtype()
             .construct_array_type()
             ._from_sequence(["a", "b"], dtype=pd.StringDtype()),
         ),
+        (
+            # numpy array with string dtype
+            np.array(["a", "b"], dtype=str),
+            pd.StringDtype(na_value=np.nan),
+            pd.StringDtype(na_value=np.nan)
+            .construct_array_type()
+            ._from_sequence(["a", "b"], dtype=pd.StringDtype(na_value=np.nan)),
+        ),
         # Boolean
         (
             [True, None],
@@ -287,7 +307,6 @@ def test_array_copy():
     assert tm.shares_memory(a, b)
 
 
-@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
 @pytest.mark.parametrize(
     "data, expected",
     [
@@ -387,6 +406,13 @@ def test_array_copy():
             .construct_array_type()
             ._from_sequence(["a", None], dtype=pd.StringDtype()),
         ),
+        (
+            # numpy array with string dtype
+            np.array(["a", "b"], dtype=str),
+            pd.StringDtype()
+            .construct_array_type()
+            ._from_sequence(["a", "b"], dtype=pd.StringDtype()),
+        ),
         # Boolean
         ([True, False], BooleanArray._from_sequence([True, False], dtype="boolean")),
         ([True, None], BooleanArray._from_sequence([True, None], dtype="boolean")),