TST[string]: update expecteds for using_string_dtype to fix xfails (#61727)

* TST: update expecteds for using_string_dtype to fix xfails * Update to_dict_of_blocks test to hardcode object dtype * Comment * Split test, update expected, targeted xfails * Update json test * revert commented-out

Author: jbrockmendel

pandas/tests/arrays/categorical/test_constructors.py

@@ -6,10 +6,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
-from pandas.compat import HAS_PYARROW
-
 from pandas.core.dtypes.common import (
  is_float_dtype,
  is_integer_dtype,
@@ -444,13 +440,12 @@ def test_constructor_str_unknown(self):
  with pytest.raises(ValueError, match="Unknown dtype"):
  Categorical([1, 2], dtype="foo")
 
- @pytest.mark.xfail(
- using_string_dtype() and HAS_PYARROW, reason="Can't be NumPy strings"
- )
  def test_constructor_np_strs(self):
  # GH#31499 Hashtable.map_locations needs to work on np.str_ objects
- cat = Categorical(["1", "0", "1"], [np.str_("0"), np.str_("1")])
- assert all(isinstance(x, np.str_) for x in cat.categories)
+ # We can't pass all-strings because the constructor would cast
+ # those to StringDtype post-PDEP14
+ cat = Categorical(["1", "0", "1", 2], [np.str_("0"), np.str_("1"), 2])
+ assert all(isinstance(x, (np.str_, int)) for x in cat.categories)
 
  def test_constructor_from_categorical_with_dtype(self):
  dtype = CategoricalDtype(["a", "b", "c"], ordered=True)

pandas/tests/arrays/categorical/test_repr.py

@@ -1,7 +1,4 @@
 import numpy as np
-import pytest
-
-from pandas._config import using_string_dtype
 
 from pandas import (
  Categorical,
@@ -77,17 +74,19 @@ def test_print_none_width(self):
  with option_context("display.width", None):
  assert exp == repr(a)
 
- @pytest.mark.skipif(
- using_string_dtype(),
- reason="Change once infer_string is set to True by default",
- )
- def test_unicode_print(self):
+ def test_unicode_print(self, using_infer_string):
  c = Categorical(["aaaaa", "bb", "cccc"] * 20)
  expected = """\
 ['aaaaa', 'bb', 'cccc', 'aaaaa', 'bb', ..., 'bb', 'cccc', 'aaaaa', 'bb', 'cccc']
 Length: 60
 Categories (3, object): ['aaaaa', 'bb', 'cccc']"""
 
+ if using_infer_string:
+ expected = expected.replace(
+ "(3, object): ['aaaaa', 'bb', 'cccc']",
+ "(3, str): [aaaaa, bb, cccc]",
+ )
+
  assert repr(c) == expected
 
  c = Categorical(["ああああ", "いいいいい", "ううううううう"] * 20)
@@ -96,6 +95,12 @@ def test_unicode_print(self):
 Length: 60
 Categories (3, object): ['ああああ', 'いいいいい', 'ううううううう']""" # noqa: E501
 
+ if using_infer_string:
+ expected = expected.replace(
+ "(3, object): ['ああああ', 'いいいいい', 'ううううううう']",
+ "(3, str): [ああああ, いいいいい, ううううううう]",
+ )
+
  assert repr(c) == expected
 
  # unicode option should not affect to Categorical, as it doesn't care
@@ -106,6 +111,12 @@ def test_unicode_print(self):
 Length: 60
 Categories (3, object): ['ああああ', 'いいいいい', 'ううううううう']""" # noqa: E501
 
+ if using_infer_string:
+ expected = expected.replace(
+ "(3, object): ['ああああ', 'いいいいい', 'ううううううう']",
+ "(3, str): [ああああ, いいいいい, ううううううう]",
+ )
+
  assert repr(c) == expected
 
  def test_categorical_repr(self):

pandas/tests/frame/methods/test_astype.py

@@ -3,8 +3,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 import pandas.util._test_decorators as td
 
 import pandas as pd
@@ -745,10 +743,7 @@ def test_astype_tz_object_conversion(self, tz):
  result = result.astype({"tz": "datetime64[ns, Europe/London]"})
  tm.assert_frame_equal(result, expected)
 
- @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string) GH#60639")
- def test_astype_dt64_to_string(
- self, frame_or_series, tz_naive_fixture, using_infer_string
- ):
+ def test_astype_dt64_to_string(self, frame_or_series, tz_naive_fixture):
  # GH#41409
  tz = tz_naive_fixture
 
@@ -766,10 +761,7 @@ def test_astype_dt64_to_string(
  item = result.iloc[0]
  if frame_or_series is DataFrame:
  item = item.iloc[0]
- if using_infer_string:
- assert item is np.nan
- else:
- assert item is pd.NA
+ assert item is pd.NA
 
  # For non-NA values, we should match what we get for non-EA str
  alt = obj.astype(str)

pandas/tests/groupby/test_timegrouper.py

@@ -11,8 +11,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 import pandas as pd
 from pandas import (
  DataFrame,
@@ -76,10 +74,7 @@ def groupby_with_truncated_bingrouper(frame_for_truncated_bingrouper):
 
 
 class TestGroupBy:
- # TODO(infer_string) resample sum introduces 0's
- # https://github.com/pandas-dev/pandas/issues/60229
- @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
- def test_groupby_with_timegrouper(self):
+ def test_groupby_with_timegrouper(self, using_infer_string):
  # GH 4161
  # TimeGrouper requires a sorted index
  # also verifies that the resultant index has the correct name
@@ -116,8 +111,11 @@ def test_groupby_with_timegrouper(self):
  {"Buyer": 0, "Quantity": 0},
  index=exp_dti,
  )
- # Cast to object to avoid implicit cast when setting entry to "CarlCarlCarl"
+ # Cast to object/str to avoid implicit cast when setting
+ # entry to "CarlCarlCarl"
  expected = expected.astype({"Buyer": object})
+ if using_infer_string:
+ expected = expected.astype({"Buyer": "str"})
  expected.iloc[0, 0] = "CarlCarlCarl"
  expected.iloc[6, 0] = "CarlCarl"
  expected.iloc[18, 0] = "Joe"

pandas/tests/indexes/base_class/test_formats.py

@@ -1,7 +1,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
 import pandas._config.config as cf
 
 from pandas import Index
@@ -16,7 +15,6 @@ def test_repr_is_valid_construction_code(self):
  res = eval(repr(idx))
  tm.assert_index_equal(res, idx)
 
- @pytest.mark.xfail(using_string_dtype(), reason="repr different")
  @pytest.mark.parametrize(
  "index,expected",
  [
@@ -77,11 +75,13 @@ def test_repr_is_valid_construction_code(self):
  ),
  ],
  )
- def test_string_index_repr(self, index, expected):
+ def test_string_index_repr(self, index, expected, using_infer_string):
  result = repr(index)
+ if using_infer_string:
+ expected = expected.replace("dtype='object'", "dtype='str'")
+
  assert result == expected
 
- @pytest.mark.xfail(using_string_dtype(), reason="repr different")
  @pytest.mark.parametrize(
  "index,expected",
  [
@@ -121,11 +121,16 @@ def test_string_index_repr(self, index, expected):
  ),
  ],
  )
- def test_string_index_repr_with_unicode_option(self, index, expected):
+ def test_string_index_repr_with_unicode_option(
+ self, index, expected, using_infer_string
+ ):
  # Enable Unicode option -----------------------------------------
  with cf.option_context("display.unicode.east_asian_width", True):
  result = repr(index)
- assert result == expected
+
+ if using_infer_string:
+ expected = expected.replace("dtype='object'", "dtype='str'")
+ assert result == expected
 
  def test_repr_summary(self):
  with cf.option_context("display.max_seq_items", 10):

pandas/tests/indexes/categorical/test_category.py

@@ -199,6 +199,7 @@ def test_unique(self, data, categories, expected_data, ordered):
  expected = CategoricalIndex(expected_data, dtype=dtype)
  tm.assert_index_equal(idx.unique(), expected)
 
+ # TODO(3.0): remove this test once using_string_dtype() is always True
  @pytest.mark.xfail(using_string_dtype(), reason="repr doesn't roundtrip")
  def test_repr_roundtrip(self):
  ci = CategoricalIndex(["a", "b"], categories=["a", "b"], ordered=True)