Used kwargs to call Cython groupby funcs

Author: WillAyd

pandas/_libs/groupby_helper.pxi.in

@@ -907,14 +907,16 @@ def group_cumsum(numeric[:, :] out,
 @cython.boundscheck(False)
 @cython.wraparound(False)
 def group_shift_indexer(ndarray[int64_t] out, ndarray[int64_t] labels,
-                        int ngroups, int periods):
+                        int64_t ngroups, **kwargs):
     cdef:
         Py_ssize_t N, i, j, ii
-        int offset, sign
+        int offset, sign, periods
         int64_t lab, idxer, idxer_slot
         int64_t[:] label_seen = np.zeros(ngroups, dtype=np.int64)
         int64_t[:, :] label_indexer
 
+    periods = kwargs['periods']
+
     N, = (<object> labels).shape
 
     if periods < 0:
@@ -958,8 +960,7 @@ def group_shift_indexer(ndarray[int64_t] out, ndarray[int64_t] labels,
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def group_fillna_indexer(ndarray[int64_t] out, ndarray[int64_t] labels,
-                         ndarray[uint8_t] mask, object direction,
-                         int64_t limit):
+                         ndarray[uint8_t] mask, **kwargs):
     """Indexes how to fill values forwards or backwards within a group
 
     Parameters
@@ -980,9 +981,10 @@ def group_fillna_indexer(ndarray[int64_t] out, ndarray[int64_t] labels,
     cdef:
         Py_ssize_t i, N
         ndarray[int64_t] sorted_labels
-        int64_t curr_fill_idx=-1
-        int64_t idx, filled_vals=0
+        int64_t limit, idx, curr_fill_idx=-1, filled_vals=0
 
+    direction = kwargs['direction']
+    limit = kwargs['limit']
     N = len(out)
 
     # Make sure all arrays are the same size

pandas/core/groupby.py

@@ -1865,17 +1865,12 @@ def _get_cythonized_result(self, how, grouper, needs_mask=False,
         needs_ngroups : bool, default False
             Whether number of groups part of the Cython call signature
         **kwargs : dict
-            Extra arguments required for the given function. This method
-            internally stores an OrderedDict that maps those keywords to
-            positional arguments before calling the Cython layer
+            Extra arguments to be passed back to Cython funcs
 
         Returns
         -------
         GroupBy object populated with appropriate result(s)
         """
-        exp_kwds = collections.OrderedDict([
-            (('group_fillna_indexer'), ('direction', 'limit')),
-            (('group_shift_indexer'), ('nperiods',))])
 
         labels, _, ngroups = grouper.group_info
         output = collections.OrderedDict()
@@ -1891,9 +1886,7 @@ def _get_cythonized_result(self, how, grouper, needs_mask=False,
             if needs_ngroups:
                 func = partial(func, ngroups)
 
-            # Convert any keywords into positional arguments
-            func = partial(func, *(kwargs[x] for x in exp_kwds[how]))
-            func()  # Call func to modify indexer values in place
+            func(**kwargs)  # Call func to modify indexer values in place
             output[name] = algorithms.take_nd(obj.values, indexer)
 
         return self._wrap_transformed_output(output)
@@ -1917,7 +1910,7 @@ def shift(self, periods=1, freq=None, axis=0):
 
         return self._get_cythonized_result('group_shift_indexer',
                                            self.grouper, needs_ngroups=True,
-                                           nperiods=periods)
+                                           periods=periods)
 
     @Substitution(name='groupby')
     @Appender(_doc_template)