CLN remove unnecessary trailing commas to get ready for new version of black: generic -> blocks (#35950)

* pandas/core/groupby/generic.py

* pandas/core/groupby/groupby.py

* pandas/core/groupby/ops.py

* pandas/core/indexes/datetimelike.py

* pandas/core/indexes/interval.py

* pandas/core/indexes/numeric.py

* pandas/core/indexes/range.py

* pandas/core/internals/blocks.py

Author: MarcoGorelli

pandas/core/groupby/generic.py

@@ -221,9 +221,7 @@ def _selection_name(self):
     def apply(self, func, *args, **kwargs):
         return super().apply(func, *args, **kwargs)
 
-    @doc(
-        _agg_template, examples=_agg_examples_doc, klass="Series",
-    )
+    @doc(_agg_template, examples=_agg_examples_doc, klass="Series")
     def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs):
 
         if maybe_use_numba(engine):
@@ -935,9 +933,7 @@ class DataFrameGroupBy(GroupBy[DataFrame]):
     See :ref:`groupby.aggregate.named` for more."""
     )
 
-    @doc(
-        _agg_template, examples=_agg_examples_doc, klass="DataFrame",
-    )
+    @doc(_agg_template, examples=_agg_examples_doc, klass="DataFrame")
     def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs):
 
         if maybe_use_numba(engine):

pandas/core/groupby/groupby.py

@@ -1077,7 +1077,7 @@ def _aggregate_with_numba(self, data, func, *args, engine_kwargs=None, **kwargs)
                 tuple(args), kwargs, func, engine_kwargs
             )
         result = numba_agg_func(
-            sorted_data, sorted_index, starts, ends, len(group_keys), len(data.columns),
+            sorted_data, sorted_index, starts, ends, len(group_keys), len(data.columns)
         )
         if cache_key not in NUMBA_FUNC_CACHE:
             NUMBA_FUNC_CACHE[cache_key] = numba_agg_func
@@ -1595,8 +1595,7 @@ def max(self, numeric_only: bool = False, min_count: int = -1):
     def first(self, numeric_only: bool = False, min_count: int = -1):
         def first_compat(obj: FrameOrSeries, axis: int = 0):
             def first(x: Series):
-                """Helper function for first item that isn't NA.
-                """
+                """Helper function for first item that isn't NA."""
                 x = x.array[notna(x.array)]
                 if len(x) == 0:
                     return np.nan
@@ -1620,8 +1619,7 @@ def first(x: Series):
     def last(self, numeric_only: bool = False, min_count: int = -1):
         def last_compat(obj: FrameOrSeries, axis: int = 0):
             def last(x: Series):
-                """Helper function for last item that isn't NA.
-                """
+                """Helper function for last item that isn't NA."""
                 x = x.array[notna(x.array)]
                 if len(x) == 0:
                     return np.nan

pandas/core/groupby/ops.py

@@ -583,7 +583,7 @@ def transform(self, values, how: str, axis: int = 0, **kwargs):
         return self._cython_operation("transform", values, how, axis, **kwargs)
 
     def _aggregate(
-        self, result, counts, values, comp_ids, agg_func, min_count: int = -1,
+        self, result, counts, values, comp_ids, agg_func, min_count: int = -1
     ):
         if agg_func is libgroupby.group_nth:
             # different signature from the others
@@ -603,9 +603,7 @@ def _transform(
 
         return result
 
-    def agg_series(
-        self, obj: Series, func: F, *args, **kwargs,
-    ):
+    def agg_series(self, obj: Series, func: F, *args, **kwargs):
         # Caller is responsible for checking ngroups != 0
         assert self.ngroups != 0
 
@@ -653,9 +651,7 @@ def _aggregate_series_fast(self, obj: Series, func: F):
         result, counts = grouper.get_result()
         return result, counts
 
-    def _aggregate_series_pure_python(
-        self, obj: Series, func: F, *args, **kwargs,
-    ):
+    def _aggregate_series_pure_python(self, obj: Series, func: F, *args, **kwargs):
         group_index, _, ngroups = self.group_info
 
         counts = np.zeros(ngroups, dtype=int)
@@ -841,9 +837,7 @@ def groupings(self) -> "List[grouper.Grouping]":
             for lvl, name in zip(self.levels, self.names)
         ]
 
-    def agg_series(
-        self, obj: Series, func: F, *args, **kwargs,
-    ):
+    def agg_series(self, obj: Series, func: F, *args, **kwargs):
         # Caller is responsible for checking ngroups != 0
         assert self.ngroups != 0
         assert len(self.bins) > 0  # otherwise we'd get IndexError in get_result

pandas/core/indexes/datetimelike.py

@@ -81,9 +81,7 @@ def wrapper(left, right):
     DatetimeLikeArrayMixin,
     cache=True,
 )
-@inherit_names(
-    ["mean", "asi8", "freq", "freqstr", "_box_func"], DatetimeLikeArrayMixin,
-)
+@inherit_names(["mean", "asi8", "freq", "freqstr", "_box_func"], DatetimeLikeArrayMixin)
 class DatetimeIndexOpsMixin(ExtensionIndex):
     """
     Common ops mixin to support a unified interface datetimelike Index.

pandas/core/indexes/interval.py

@@ -182,10 +182,10 @@ def func(intvidx_self, other, sort=False):
 )
 @inherit_names(["set_closed", "to_tuples"], IntervalArray, wrap=True)
 @inherit_names(
-    ["__array__", "overlaps", "contains", "left", "right", "length"], IntervalArray,
+    ["__array__", "overlaps", "contains", "left", "right", "length"], IntervalArray
 )
 @inherit_names(
-    ["is_non_overlapping_monotonic", "mid", "closed"], IntervalArray, cache=True,
+    ["is_non_overlapping_monotonic", "mid", "closed"], IntervalArray, cache=True
 )
 class IntervalIndex(IntervalMixin, ExtensionIndex):
     _typ = "intervalindex"

pandas/core/indexes/numeric.py

@@ -436,7 +436,7 @@ def isin(self, values, level=None):
     def _is_compatible_with_other(self, other) -> bool:
         return super()._is_compatible_with_other(other) or all(
             isinstance(
-                obj, (ABCInt64Index, ABCFloat64Index, ABCUInt64Index, ABCRangeIndex),
+                obj, (ABCInt64Index, ABCFloat64Index, ABCUInt64Index, ABCRangeIndex)
             )
             for obj in [self, other]
         )

pandas/core/indexes/range.py

@@ -82,7 +82,7 @@ class RangeIndex(Int64Index):
     # Constructors
 
     def __new__(
-        cls, start=None, stop=None, step=None, dtype=None, copy=False, name=None,
+        cls, start=None, stop=None, step=None, dtype=None, copy=False, name=None
     ):
 
         cls._validate_dtype(dtype)

pandas/core/internals/blocks.py

@@ -724,7 +724,7 @@ def replace(
                 # _can_hold_element checks have reduced this back to the
                 #  scalar case and we can avoid a costly object cast
                 return self.replace(
-                    to_replace[0], value, inplace=inplace, regex=regex, convert=convert,
+                    to_replace[0], value, inplace=inplace, regex=regex, convert=convert
                 )
 
             # GH 22083, TypeError or ValueError occurred within error handling
@@ -905,7 +905,7 @@ def setitem(self, indexer, value):
         return block
 
     def putmask(
-        self, mask, new, inplace: bool = False, axis: int = 0, transpose: bool = False,
+        self, mask, new, inplace: bool = False, axis: int = 0, transpose: bool = False
     ) -> List["Block"]:
         """
         putmask the data to the block; it is possible that we may create a
@@ -1292,7 +1292,7 @@ def shift(self, periods: int, axis: int = 0, fill_value=None):
         return [self.make_block(new_values)]
 
     def where(
-        self, other, cond, errors="raise", try_cast: bool = False, axis: int = 0,
+        self, other, cond, errors="raise", try_cast: bool = False, axis: int = 0
     ) -> List["Block"]:
         """
         evaluate the block; return result block(s) from the result
@@ -1366,7 +1366,7 @@ def where_func(cond, values, other):
                 # we are explicitly ignoring errors
                 block = self.coerce_to_target_dtype(other)
                 blocks = block.where(
-                    orig_other, cond, errors=errors, try_cast=try_cast, axis=axis,
+                    orig_other, cond, errors=errors, try_cast=try_cast, axis=axis
                 )
                 return self._maybe_downcast(blocks, "infer")
 
@@ -1605,7 +1605,7 @@ def set(self, locs, values):
         self.values = values
 
     def putmask(
-        self, mask, new, inplace: bool = False, axis: int = 0, transpose: bool = False,
+        self, mask, new, inplace: bool = False, axis: int = 0, transpose: bool = False
     ) -> List["Block"]:
         """
         See Block.putmask.__doc__
@@ -1816,7 +1816,7 @@ def diff(self, n: int, axis: int = 1) -> List["Block"]:
         return super().diff(n, axis)
 
     def shift(
-        self, periods: int, axis: int = 0, fill_value: Any = None,
+        self, periods: int, axis: int = 0, fill_value: Any = None
     ) -> List["ExtensionBlock"]:
         """
         Shift the block by `periods`.
@@ -1833,7 +1833,7 @@ def shift(
         ]
 
     def where(
-        self, other, cond, errors="raise", try_cast: bool = False, axis: int = 0,
+        self, other, cond, errors="raise", try_cast: bool = False, axis: int = 0
     ) -> List["Block"]:
 
         cond = _extract_bool_array(cond)
@@ -1945,7 +1945,7 @@ def _can_hold_element(self, element: Any) -> bool:
         )
 
     def to_native_types(
-        self, na_rep="", float_format=None, decimal=".", quoting=None, **kwargs,
+        self, na_rep="", float_format=None, decimal=".", quoting=None, **kwargs
     ):
         """ convert to our native types format """
         values = self.values
@@ -2369,7 +2369,7 @@ def replace(self, to_replace, value, inplace=False, regex=False, convert=True):
         if not np.can_cast(to_replace_values, bool):
             return self
         return super().replace(
-            to_replace, value, inplace=inplace, regex=regex, convert=convert,
+            to_replace, value, inplace=inplace, regex=regex, convert=convert
         )
 
 
@@ -2453,18 +2453,18 @@ def replace(self, to_replace, value, inplace=False, regex=False, convert=True):
 
         if not either_list and is_re(to_replace):
             return self._replace_single(
-                to_replace, value, inplace=inplace, regex=True, convert=convert,
+                to_replace, value, inplace=inplace, regex=True, convert=convert
             )
         elif not (either_list or regex):
             return super().replace(
-                to_replace, value, inplace=inplace, regex=regex, convert=convert,
+                to_replace, value, inplace=inplace, regex=regex, convert=convert
             )
         elif both_lists:
             for to_rep, v in zip(to_replace, value):
                 result_blocks = []
                 for b in blocks:
                     result = b._replace_single(
-                        to_rep, v, inplace=inplace, regex=regex, convert=convert,
+                        to_rep, v, inplace=inplace, regex=regex, convert=convert
                     )
                     result_blocks = _extend_blocks(result, result_blocks)
                 blocks = result_blocks
@@ -2475,18 +2475,18 @@ def replace(self, to_replace, value, inplace=False, regex=False, convert=True):
                 result_blocks = []
                 for b in blocks:
                     result = b._replace_single(
-                        to_rep, value, inplace=inplace, regex=regex, convert=convert,
+                        to_rep, value, inplace=inplace, regex=regex, convert=convert
                     )
                     result_blocks = _extend_blocks(result, result_blocks)
                 blocks = result_blocks
             return result_blocks
 
         return self._replace_single(
-            to_replace, value, inplace=inplace, convert=convert, regex=regex,
+            to_replace, value, inplace=inplace, convert=convert, regex=regex
         )
 
     def _replace_single(
-        self, to_replace, value, inplace=False, regex=False, convert=True, mask=None,
+        self, to_replace, value, inplace=False, regex=False, convert=True, mask=None
     ):
         """
         Replace elements by the given value.