reformat

Author: TomAugspurger

pandas/core/tools/datetimes.py

@@ -68,8 +68,9 @@ def _guess_datetime_format_for_array(arr, **kwargs):
  return _guess_datetime_format(arr[non_nan_elements[0]], **kwargs)
 
 
-def should_cache(arg: ArrayConvertible, unique_share: float = 0.7,
- check_count: Optional[int] = None) -> bool:
+def should_cache(
+ arg: ArrayConvertible, unique_share: float = 0.7, check_count: Optional[int] = None
+) -> bool:
  """
  Decides whether to do caching.
 
@@ -109,12 +110,13 @@ def should_cache(arg: ArrayConvertible, unique_share: float = 0.7,
  else:
  check_count = 500
  else:
- assert 0 <= check_count <= len(arg), \
- 'check_count must be in next bounds: [0; len(arg)]'
+ assert (
+ 0 <= check_count <= len(arg)
+ ), "check_count must be in next bounds: [0; len(arg)]"
  if check_count == 0:
  return False
 
- assert 0 < unique_share < 1, 'unique_share must be in next bounds: (0; 1)'
+ assert 0 < unique_share < 1, "unique_share must be in next bounds: (0; 1)"
 
  unique_elements = unique(arg[:check_count])
  if len(unique_elements) > check_count * unique_share:
@@ -554,11 +556,21 @@ def _adjust_to_origin(arg, origin, unit):
  return arg
 
 
-@deprecate_kwarg(old_arg_name='box', new_arg_name=None)
-def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
- utc=None, box=True, format=None, exact=True,
- unit=None, infer_datetime_format=False, origin='unix',
- cache=True):
+@deprecate_kwarg(old_arg_name="box", new_arg_name=None)
+def to_datetime(
+ arg,
+ errors="raise",
+ dayfirst=False,
+ yearfirst=False,
+ utc=None,
+ box=True,
+ format=None,
+ exact=True,
+ unit=None,
+ infer_datetime_format=False,
+ origin="unix",
+ cache=True,
+):
  """
  Convert argument to datetime.
 

pandas/tests/indexes/datetimes/test_tools.py

@@ -2243,19 +2243,24 @@ def test_arg_tz_ns_unit(self, offset, utc, exp):
  tm.assert_index_equal(result, expected)
 
 
-@pytest.mark.parametrize('listlike,do_caching', [
- ([1, 2, 3, 4, 5, 6, 7, 8, 9, 0], False),
- ([1, 1, 1, 1, 4, 5, 6, 7, 8, 9], True)
-])
+@pytest.mark.parametrize(
+ "listlike,do_caching",
+ [([1, 2, 3, 4, 5, 6, 7, 8, 9, 0], False), ([1, 1, 1, 1, 4, 5, 6, 7, 8, 9], True)],
+)
 def test_should_cache(listlike, do_caching):
- assert tools.should_cache(listlike, check_count=len(listlike),
- unique_share=0.7) == do_caching
+ assert (
+ tools.should_cache(listlike, check_count=len(listlike), unique_share=0.7)
+ == do_caching
+ )
 
 
-@pytest.mark.parametrize('unique_share,check_count, err_message', [
- (0.5, 11, r'check_count must be in next bounds: \[0; len\(arg\)\]'),
- (10, 2, r'unique_share must be in next bounds: \(0; 1\)')
-])
+@pytest.mark.parametrize(
+ "unique_share,check_count, err_message",
+ [
+ (0.5, 11, r"check_count must be in next bounds: \[0; len\(arg\)\]"),
+ (10, 2, r"unique_share must be in next bounds: \(0; 1\)"),
+ ],
+)
 def test_should_cache_errors(unique_share, check_count, err_message):
  arg = [5] * 10
 

pandas/tests/io/parser/test_parse_dates.py

@@ -1096,18 +1096,21 @@ def test_read_with_parse_dates_invalid_type(all_parsers, parse_dates):
 
 
 @pytest.mark.parametrize("cache_dates", [True, False])
-@pytest.mark.parametrize("value", [
- 'nan', '0', ''])
+@pytest.mark.parametrize("value", ["nan", "0", ""])
 def test_bad_date_parse(all_parsers, cache_dates, value):
  # if we have an invalid date make sure that we handle this with
  # and w/o the cache properly
  parser = all_parsers
- s = StringIO(('%s,\n' % value) * 50000)
+ s = StringIO(("%s,\n" % value) * 50000)
 
- parser.read_csv(s,
- header=None, names=['foo', 'bar'], parse_dates=['foo'],
- infer_datetime_format=False,
- cache_dates=cache_dates)
+ parser.read_csv(
+ s,
+ header=None,
+ names=["foo", "bar"],
+ parse_dates=["foo"],
+ infer_datetime_format=False,
+ cache_dates=cache_dates,
+ )
 
 
 def test_parse_dates_empty_string(all_parsers):