chore(python): use black==22.3.0 (#96)

Source-Link: googleapis/synthtool@6fab84a
Post-Processor: gcr.io/cloud-devrel-public-resources/owlbot-python:latest@sha256:7cffbc10910c3ab1b852c05114a08d374c195a81cdec1d4a67a1d129331d0bfe

Author: gcf-owl-bot[bot]

.github/.OwlBot.lock.yaml

@@ -13,4 +13,4 @@
 # limitations under the License.
 docker:
   image: gcr.io/cloud-devrel-public-resources/owlbot-python:latest
-  digest: sha256:4e1991042fe54b991db9ca17c8fb386e61b22fe4d1472a568bf0fcac85dcf5d3
+  digest: sha256:7cffbc10910c3ab1b852c05114a08d374c195a81cdec1d4a67a1d129331d0bfe

db_dtypes/__init__.py

@@ -197,7 +197,8 @@ def __arrow_array__(self, type=None):
         # since the datetime epoch (midnight 1970-01-01).
         array = array.view(pyarrow.time64("ns"))
         return pyarrow.compute.cast(
-            array, type if type is not None else pyarrow.time64("ns"),
+            array,
+            type if type is not None else pyarrow.time64("ns"),
         )
 
 
@@ -297,7 +298,8 @@ def __arrow_array__(self, type=None):
         """
         array = pyarrow.array(self._ndarray, type=pyarrow.timestamp("ns"))
         return pyarrow.compute.cast(
-            array, type if type is not None else pyarrow.date32(),
+            array,
+            type if type is not None else pyarrow.date32(),
         )
 
     def __add__(self, other):

db_dtypes/core.py

@@ -64,7 +64,10 @@ def __init__(self, values, dtype=None, copy: bool = False):
 
     @classmethod
     def __ndarray(cls, scalars):
-        return numpy.array([cls._datetime(scalar) for scalar in scalars], "M8[ns]",)
+        return numpy.array(
+            [cls._datetime(scalar) for scalar in scalars],
+            "M8[ns]",
+        )
 
     @classmethod
     def _from_sequence(cls, scalars, *, dtype=None, copy=False):
@@ -186,7 +189,8 @@ def median(
             raise NotImplementedError("Need pandas 1.3 or later to calculate median.")
 
         pandas_backports.numpy_validate_median(
-            (), {"out": out, "overwrite_input": overwrite_input, "keepdims": keepdims},
+            (),
+            {"out": out, "overwrite_input": overwrite_input, "keepdims": keepdims},
         )
         result = pandas_backports.nanmedian(self._ndarray, axis=axis, skipna=skipna)
         if axis is None or self.ndim == 1:

docs/conf.py

@@ -279,7 +279,13 @@
 # (source start file, target name, title,
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [
-    (root_doc, "db-dtypes.tex", "db-dtypes Documentation", author, "manual",)
+    (
+        root_doc,
+        "db-dtypes.tex",
+        "db-dtypes Documentation",
+        author,
+        "manual",
+    )
 ]
 
 # The name of an image file (relative to this directory) to place at the top of
@@ -307,7 +313,15 @@
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [(root_doc, "db-dtypes", "db-dtypes Documentation", [author], 1,)]
+man_pages = [
+    (
+        root_doc,
+        "db-dtypes",
+        "db-dtypes Documentation",
+        [author],
+        1,
+    )
+]
 
 # If true, show URL addresses after external links.
 # man_show_urls = False
@@ -347,7 +361,10 @@
 intersphinx_mapping = {
     "python": ("https://python.readthedocs.org/en/latest/", None),
     "google-auth": ("https://googleapis.dev/python/google-auth/latest/", None),
-    "google.api_core": ("https://googleapis.dev/python/google-api-core/latest/", None,),
+    "google.api_core": (
+        "https://googleapis.dev/python/google-api-core/latest/",
+        None,
+    ),
     "grpc": ("https://grpc.github.io/grpc/python/", None),
     "proto-plus": ("https://proto-plus-python.readthedocs.io/en/latest/", None),
     "protobuf": ("https://googleapis.dev/python/protobuf/latest/", None),

noxfile.py

@@ -25,7 +25,7 @@
 import nox
 
 
-BLACK_VERSION = "black==19.10b0"
+BLACK_VERSION = "black==22.3.0"
 BLACK_PATHS = ["docs", "db_dtypes", "tests", "noxfile.py", "setup.py"]
 
 DEFAULT_PYTHON_VERSION = "3.8"
@@ -60,7 +60,9 @@ def lint(session):
     """
     session.install("flake8", BLACK_VERSION)
     session.run(
-        "black", "--check", *BLACK_PATHS,
+        "black",
+        "--check",
+        *BLACK_PATHS,
     )
     session.run("flake8", "db_dtypes", "tests")
 
@@ -70,7 +72,8 @@ def blacken(session):
     """Run black. Format code to uniform standard."""
     session.install(BLACK_VERSION)
     session.run(
-        "black", *BLACK_PATHS,
+        "black",
+        *BLACK_PATHS,
     )
 
 

samples/snippets/noxfile.py

@@ -29,7 +29,7 @@
 # WARNING - WARNING - WARNING - WARNING - WARNING
 # WARNING - WARNING - WARNING - WARNING - WARNING
 
-BLACK_VERSION = "black==19.10b0"
+BLACK_VERSION = "black==22.3.0"
 
 # Copy `noxfile_config.py` to your directory and modify it instead.
 
@@ -253,7 +253,7 @@ def py(session: nox.sessions.Session) -> None:
 
 
 def _get_repo_root() -> Optional[str]:
-    """ Returns the root folder of the project. """
+    """Returns the root folder of the project."""
     # Get root of this repository. Assume we don't have directories nested deeper than 10 items.
     p = Path(os.getcwd())
     for i in range(10):

samples/snippets/pandas_date_and_time_test.py

@@ -39,7 +39,8 @@ def test_pandas_date_and_time():
     assert list(dates) == [datetime.date(2021, 9, 17), datetime.date(2021, 9, 18)]
 
     assert np.array_equal(
-        diffs, dates.astype("datetime64") - dates2.astype("datetime64"),
+        diffs,
+        dates.astype("datetime64") - dates2.astype("datetime64"),
     )
 
     assert np.array_equal(after, dates.astype("object") + do)

tests/unit/test_arrow.py

@@ -54,7 +54,8 @@ def types_mapper(
             [dt.date(2021, 9, 27), None, dt.date(2011, 9, 27)], dtype="dbdate"
         ),
         pyarrow.array(
-            [dt.date(2021, 9, 27), None, dt.date(2011, 9, 27)], type=pyarrow.date32(),
+            [dt.date(2021, 9, 27), None, dt.date(2011, 9, 27)],
+            type=pyarrow.date32(),
         ),
     ),
     (
@@ -67,14 +68,18 @@ def types_mapper(
             type=pyarrow.date32(),
         ),
     ),
-    (pandas.Series([], dtype="dbtime"), pyarrow.array([], type=pyarrow.time64("ns")),),
+    (
+        pandas.Series([], dtype="dbtime"),
+        pyarrow.array([], type=pyarrow.time64("ns")),
+    ),
     (
         pandas.Series([None, None, None], dtype="dbtime"),
         pyarrow.array([None, None, None], type=pyarrow.time64("ns")),
     ),
     (
         pandas.Series(
-            [dt.time(0, 0, 0, 0), None, dt.time(23, 59, 59, 999_999)], dtype="dbtime",
+            [dt.time(0, 0, 0, 0), None, dt.time(23, 59, 59, 999_999)],
+            dtype="dbtime",
         ),
         pyarrow.array(
             [dt.time(0, 0, 0, 0), None, dt.time(23, 59, 59, 999_999)],
@@ -111,7 +116,8 @@ def types_mapper(
             [dt.date(2021, 9, 27), None, dt.date(2011, 9, 27)], dtype="dbdate"
         ),
         pyarrow.array(
-            [dt.date(2021, 9, 27), None, dt.date(2011, 9, 27)], type=pyarrow.date64(),
+            [dt.date(2021, 9, 27), None, dt.date(2011, 9, 27)],
+            type=pyarrow.date64(),
         ),
     ),
     (
@@ -124,14 +130,18 @@ def types_mapper(
             type=pyarrow.date64(),
         ),
     ),
-    (pandas.Series([], dtype="dbtime"), pyarrow.array([], type=pyarrow.time32("ms")),),
+    (
+        pandas.Series([], dtype="dbtime"),
+        pyarrow.array([], type=pyarrow.time32("ms")),
+    ),
     (
         pandas.Series([None, None, None], dtype="dbtime"),
         pyarrow.array([None, None, None], type=pyarrow.time32("ms")),
     ),
     (
         pandas.Series(
-            [dt.time(0, 0, 0, 0), None, dt.time(23, 59, 59, 999_000)], dtype="dbtime",
+            [dt.time(0, 0, 0, 0), None, dt.time(23, 59, 59, 999_000)],
+            dtype="dbtime",
         ),
         pyarrow.array(
             [dt.time(0, 0, 0, 0), None, dt.time(23, 59, 59, 999_000)],
@@ -158,7 +168,8 @@ def types_mapper(
     ),
     (
         pandas.Series(
-            [dt.time(0, 0, 0, 0), None, dt.time(23, 59, 59, 999_999)], dtype="dbtime",
+            [dt.time(0, 0, 0, 0), None, dt.time(23, 59, 59, 999_999)],
+            dtype="dbtime",
         ),
         pyarrow.array(
             [dt.time(0, 0, 0, 0), None, dt.time(23, 59, 59, 999_999)],
@@ -220,7 +231,8 @@ def types_mapper(
     ),
     pytest.param(
         pandas.Series(
-            ["0:0:0", "12:30:15.123456789", "23:59:59.999999999"], dtype="dbtime",
+            ["0:0:0", "12:30:15.123456789", "23:59:59.999999999"],
+            dtype="dbtime",
         ),
         pyarrow.array(
             [

tests/unit/test_dtypes.py

@@ -201,7 +201,8 @@ def test___getitem___arrayindex(dtype):
     cls = _cls(dtype)
     sample_values = SAMPLE_VALUES[dtype]
     np.testing.assert_array_equal(
-        cls(sample_values)[[1, 3]], cls([sample_values[1], sample_values[3]]),
+        cls(sample_values)[[1, 3]],
+        cls([sample_values[1], sample_values[3]]),
     )
 
 
@@ -410,7 +411,8 @@ def test_unique(dtype):
     cls = _cls(dtype)
     sample_values = SAMPLE_VALUES[dtype]
     np.testing.assert_array_equal(
-        cls(sample_values * 3).unique(), cls(sample_values),
+        cls(sample_values * 3).unique(),
+        cls(sample_values),
     )