CLN: run black pandas & flake8

Author: AlexKirko

pandas/core/tools/datetimes.py

@@ -320,13 +320,17 @@ def _convert_listlike_datetimes(
         # GH 30050 pass an ndarray to tslib.array_with_unit_to_datetime
         # because it expects an ndarray argument
         if isinstance(arg, IntegerArray):
-            arg_np = np.array(arg[np.logical_not(arg._mask)],dtype=type(arg[0]))
-            result_np, tz_parsed = tslib.array_with_unit_to_datetime(arg_np, unit, errors=errors)
-            result = np.empty(arg.shape[0],dtype='datetime64[' + unit + ']')
-            result[arg._mask] = np.datetime64('nat')
+            arg_np = np.array(arg[np.logical_not(arg._mask)], dtype=type(arg[0]))
+            result_np, tz_parsed = tslib.array_with_unit_to_datetime(
+                arg_np, unit, errors=errors
+            )
+            result = np.empty(arg.shape[0], dtype="datetime64[" + unit + "]")
+            result[arg._mask] = np.datetime64("nat")
             result[np.logical_not(arg._mask)] = result_np
         else:
-            result, tz_parsed = tslib.array_with_unit_to_datetime(arg, unit, errors=errors)
+            result, tz_parsed = tslib.array_with_unit_to_datetime(
+                arg, unit, errors=errors
+            )
         if errors == "ignore":
             from pandas import Index
 

pandas/tests/tools/test_datetime.py

@@ -1,21 +1,23 @@
 import pandas as pd
 import numpy as np
 
-import pytest
 import pandas.util.testing as tm
 
+
 def test_to_datetime():
     # Test for #30050
-    ser = pd.Series([1,2,None, 2**61, None])
+    ser = pd.Series([1, 2, None, 2 ** 61, None])
     ser = ser.astype("Int64")
 
-    res = pd.to_datetime(ser, unit='ns')
-    
-    expected = pd.Series([
-        np.datetime64('1970-01-01 00:00:00.000000001'),
-        np.datetime64('1970-01-01 00:00:00.000000002'),
-        np.datetime64('NaT'),
-        np.datetime64('2043-01-25 23:56:49.213693952'),
-        np.datetime64('NaT'),
-    ])
-    tm.assert_series_equal(res, expected)
+    res = pd.to_datetime(ser, unit="ns")
+
+    expected = pd.Series(
+        [
+            np.datetime64("1970-01-01 00:00:00.000000001"),
+            np.datetime64("1970-01-01 00:00:00.000000002"),
+            np.datetime64("NaT"),
+            np.datetime64("2043-01-25 23:56:49.213693952"),
+            np.datetime64("NaT"),
+        ]
+    )
+    tm.assert_series_equal(res, expected)