CLN: some code cleanups

pandas/_libs/hashtable.pyx

@@ -86,7 +86,10 @@ cdef class Factorizer:
         self, ndarray[object] values, sort=False, na_sentinel=-1, na_value=None
     ):
         """
+        Examples
+        --------
         Factorize values with nans replaced by na_sentinel
+
         >>> factorize(np.array([1,2,np.nan], dtype='O'), na_sentinel=20)
         array([ 0,  1, 20])
         """
@@ -131,7 +134,10 @@ cdef class Int64Factorizer:
     def factorize(self, const int64_t[:] values, sort=False,
                   na_sentinel=-1, na_value=None):
         """
+        Examples
+        --------
         Factorize values with nans replaced by na_sentinel
+
         >>> factorize(np.array([1,2,np.nan], dtype='O'), na_sentinel=20)
         array([ 0,  1, 20])
         """

pandas/_libs/internals.pyx

@@ -105,8 +105,7 @@ cdef class BlockPlacement:
             Py_ssize_t start, stop, end, _
         if not self._has_array:
             start, stop, step, _ = slice_get_indices_ex(self._as_slice)
-            self._as_array = np.arange(start, stop, step,
-                                       dtype=np.int64)
+            self._as_array = np.arange(start, stop, step, dtype=np.int64)
             self._has_array = True
         return self._as_array
 
@@ -283,8 +282,7 @@ cdef slice_getitem(slice slc, ind):
     s_start, s_stop, s_step, s_len = slice_get_indices_ex(slc)
 
     if isinstance(ind, slice):
-        ind_start, ind_stop, ind_step, ind_len = slice_get_indices_ex(ind,
-                                                                      s_len)
+        ind_start, ind_stop, ind_step, ind_len = slice_get_indices_ex(ind, s_len)
 
         if ind_step > 0 and ind_len == s_len:
             # short-cut for no-op slice

pandas/_libs/interval.pyx

@@ -481,8 +481,7 @@ cdef class Interval(IntervalMixin):
 
 @cython.wraparound(False)
 @cython.boundscheck(False)
-def intervals_to_interval_bounds(ndarray intervals,
-                                 bint validate_closed=True):
+def intervals_to_interval_bounds(ndarray intervals, bint validate_closed=True):
     """
     Parameters
     ----------

pandas/_libs/join.pyx

@@ -817,18 +817,22 @@ def asof_join_nearest_on_X_by_Y(asof_t[:] left_values,
     right_indexer = np.empty(left_size, dtype=np.int64)
 
     # search both forward and backward
-    bli, bri = asof_join_backward_on_X_by_Y(left_values,
-                                            right_values,
-                                            left_by_values,
-                                            right_by_values,
-                                            allow_exact_matches,
-                                            tolerance)
-    fli, fri = asof_join_forward_on_X_by_Y(left_values,
-                                           right_values,
-                                           left_by_values,
-                                           right_by_values,
-                                           allow_exact_matches,
-                                           tolerance)
+    bli, bri = asof_join_backward_on_X_by_Y(
+        left_values,
+        right_values,
+        left_by_values,
+        right_by_values,
+        allow_exact_matches,
+        tolerance,
+    )
+    fli, fri = asof_join_forward_on_X_by_Y(
+        left_values,
+        right_values,
+        left_by_values,
+        right_by_values,
+        allow_exact_matches,
+        tolerance,
+    )
 
     for i in range(len(bri)):
         # choose timestamp from right with smaller difference