fix: avoid TypeError when using sorted search (#84)

* fix: address failing compliance tests in DateArray and TimeArray

test: add a test session with prerelease versions of dependencies

* fix min/max/median for 2D arrays

* fixes except for null contains

* actually use NaT as 'advertised'

* fix!: use `pandas.NaT` for missing values in dbdate and dbtime dtypes

This makes them consistent with other date/time dtypes, as well as internally
consistent with the advertised `dtype.na_value`.

BREAKING-CHANGE: dbdate and dbtime dtypes return NaT instead of None for missing values

Release-As: 0.4.0

* more progress towards compliance

* address errors in TestMethods

* move tests

* add prerelease deps

* fix: address failing tests with pandas 1.5.0

test: add a test session with prerelease versions of dependencies

* fix owlbot config

* 🦉 Updates from OwlBot post-processor

See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md

* 🦉 Updates from OwlBot post-processor

See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md

* document why microsecond precision is used

* use correct units

* add box_func tests

* typo

* fix: avoid TypeError when using sorted search

* add unit tests

* fix: dbdate and dbtime support set item

* add TestMethods

* add unit test for search sorted

Co-authored-by: Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>

db_dtypes/core.py

@@ -113,6 +113,14 @@ def _validate_scalar(self, value):
         """
         return self._datetime(value)
 
+    def _validate_searchsorted_value(self, value):
+        """
+        Convert a value for use in searching for a value in the backing numpy array.
+
+        TODO: With pandas 2.0, this may be unnecessary. https://github.com/pandas-dev/pandas/pull/45544#issuecomment-1052809232
+        """
+        return self._validate_setitem_value(value)
+
     def _validate_setitem_value(self, value):
         """
         Convert a value for use in setting a value in the backing numpy array.

tests/compliance/conftest.py

@@ -16,6 +16,28 @@
 import pytest
 
 
+@pytest.fixture(params=[True, False])
+def as_frame(request):
+    """
+    Boolean fixture to support Series and Series.to_frame() comparison testing.
+
+    See:
+    https://github.com/pandas-dev/pandas/blob/main/pandas/tests/extension/conftest.py
+    """
+    return request.param
+
+
+@pytest.fixture(params=[True, False])
+def as_series(request):
+    """
+    Boolean fixture to support arr and Series(arr) comparison testing.
+
+    See:
+    https://github.com/pandas-dev/pandas/blob/main/pandas/tests/extension/conftest.py
+    """
+    return request.param
+
+
 @pytest.fixture(params=["ffill", "bfill"])
 def fillna_method(request):
     """
@@ -28,6 +50,21 @@ def fillna_method(request):
     return request.param
 
 
+@pytest.fixture
+def invalid_scalar(data):
+    """
+    A scalar that *cannot* be held by this ExtensionArray.
+
+    The default should work for most subclasses, but is not guaranteed.
+
+    If the array can hold any item (i.e. object dtype), then use pytest.skip.
+
+    See:
+    https://github.com/pandas-dev/pandas/blob/main/pandas/tests/extension/conftest.py
+    """
+    return object.__new__(object)
+
+
 @pytest.fixture
 def na_value():
     return pandas.NaT
@@ -51,3 +88,26 @@ def cmp(a, b):
         return a is pandas.NaT and a is b
 
     return cmp
+
+
+@pytest.fixture(params=[None, lambda x: x])
+def sort_by_key(request):
+    """
+    Simple fixture for testing keys in sorting methods.
+    Tests None (no key) and the identity key.
+
+    See: https://github.com/pandas-dev/pandas/blob/main/pandas/conftest.py
+    """
+    return request.param
+
+
+@pytest.fixture(params=[True, False])
+def use_numpy(request):
+    """
+    Boolean fixture to support comparison testing of ExtensionDtype array
+    and numpy array.
+
+    See:
+    https://github.com/pandas-dev/pandas/blob/main/pandas/tests/extension/conftest.py
+    """
+    return request.param

tests/compliance/date/conftest.py

@@ -20,6 +20,15 @@
 from db_dtypes import DateArray, DateDtype
 
 
+@pytest.fixture(params=["data", "data_missing"])
+def all_data(request, data, data_missing):
+    """Parametrized fixture giving 'data' and 'data_missing'"""
+    if request.param == "data":
+        return data
+    elif request.param == "data_missing":
+        return data_missing
+
+
 @pytest.fixture
 def data():
     return DateArray(
@@ -32,6 +41,52 @@ def data():
     )
 
 
+@pytest.fixture
+def data_for_grouping():
+    """
+    Data for factorization, grouping, and unique tests.
+
+    Expected to be like [B, B, NA, NA, A, A, B, C]
+
+    Where A < B < C and NA is missing
+
+    See:
+    https://github.com/pandas-dev/pandas/blob/main/pandas/tests/extension/conftest.py
+    """
+    return DateArray(
+        [
+            datetime.date(1980, 1, 27),
+            datetime.date(1980, 1, 27),
+            None,
+            None,
+            datetime.date(1969, 12, 30),
+            datetime.date(1969, 12, 30),
+            datetime.date(1980, 1, 27),
+            datetime.date(2022, 3, 18),
+        ]
+    )
+
+
+@pytest.fixture
+def data_for_sorting():
+    """
+    Length-3 array with a known sort order.
+
+    This should be three items [B, C, A] with
+    A < B < C
+
+    See:
+    https://github.com/pandas-dev/pandas/blob/main/pandas/tests/extension/conftest.py
+    """
+    return DateArray(
+        [
+            datetime.date(1980, 1, 27),
+            datetime.date(2022, 3, 18),
+            datetime.date(1969, 12, 30),
+        ]
+    )
+
+
 @pytest.fixture
 def data_missing():
     """Length-2 array with [NA, Valid]
@@ -42,6 +97,36 @@ def data_missing():
     return DateArray([None, datetime.date(2022, 1, 27)])
 
 
+@pytest.fixture
+def data_missing_for_sorting():
+    """
+    Length-3 array with a known sort order.
+
+    This should be three items [B, NA, A] with
+    A < B and NA missing.
+
+    See:
+    https://github.com/pandas-dev/pandas/blob/main/pandas/tests/extension/conftest.py
+    """
+    return DateArray([datetime.date(1980, 1, 27), None, datetime.date(1969, 12, 30)])
+
+
+@pytest.fixture
+def data_repeated(data):
+    """
+    Generate many datasets.
+
+    See:
+    https://github.com/pandas-dev/pandas/blob/main/pandas/tests/extension/conftest.py
+    """
+
+    def gen(count):
+        for _ in range(count):
+            yield data
+
+    return gen
+
+
 @pytest.fixture
 def dtype():
     return DateDtype()

tests/compliance/date/test_date_compliance.py

@@ -20,7 +20,11 @@
 https://github.com/pandas-dev/pandas/blob/main/pandas/tests/extension/test_period.py
 """
 
+import pandas
 from pandas.tests.extension import base
+import pytest
+
+import db_dtypes
 
 
 class TestDtype(base.BaseDtypeTests):
@@ -45,3 +49,28 @@ class TestGetitem(base.BaseGetitemTests):
 
 class TestMissing(base.BaseMissingTests):
     pass
+
+
+# TODO(https://github.com/googleapis/python-db-dtypes-pandas/issues/78): Add
+# compliance tests for reduction operations.
+
+
+class TestMethods(base.BaseMethodsTests):
+    def test_combine_add(self):
+        pytest.skip("Cannot add dates.")
+
+    @pytest.mark.parametrize("dropna", [True, False])
+    def test_value_counts(self, all_data, dropna):
+        all_data = all_data[:10]
+        if dropna:
+            # Overridden from
+            # https://github.com/pandas-dev/pandas/blob/main/pandas/tests/extension/base/methods.py
+            # to avoid difference in dtypes.
+            other = db_dtypes.DateArray(all_data[~all_data.isna()])
+        else:
+            other = all_data
+
+        result = pandas.Series(all_data).value_counts(dropna=dropna).sort_index()
+        expected = pandas.Series(other).value_counts(dropna=dropna).sort_index()
+
+        self.assert_series_equal(result, expected)

tests/unit/test_date.py

@@ -328,3 +328,30 @@ def test_date_median_2d():
             )
         ),
     )
+
+
+@pytest.mark.parametrize(
+    ("search_term", "expected_index"),
+    (
+        (datetime.date(1899, 12, 31), 0),
+        (datetime.date(1900, 1, 1), 0),
+        (datetime.date(1920, 2, 2), 1),
+        (datetime.date(1930, 3, 3), 1),
+        (datetime.date(1950, 5, 5), 2),
+        (datetime.date(1990, 9, 9), 3),
+        (datetime.date(2012, 12, 12), 3),
+        (datetime.date(2022, 3, 24), 4),
+    ),
+)
+def test_date_searchsorted(search_term, expected_index):
+    test_series = pandas.Series(
+        [
+            datetime.date(1900, 1, 1),
+            datetime.date(1930, 3, 3),
+            datetime.date(1980, 8, 8),
+            datetime.date(2012, 12, 12),
+        ],
+        dtype="dbdate",
+    )
+    got = test_series.searchsorted(search_term)
+    assert got == expected_index