REF: de-duplicate cython funcs (pandas-dev#46735)

Author: jbrockmendel

pandas/_libs/algos.pxd

@@ -1,4 +1,7 @@
-from pandas._libs.dtypes cimport numeric_t
+from pandas._libs.dtypes cimport (
+    numeric_object_t,
+    numeric_t,
+)
 
 
 cdef numeric_t kth_smallest_c(numeric_t* arr, Py_ssize_t k, Py_ssize_t n) nogil
@@ -10,3 +13,10 @@ cdef enum TiebreakEnumType:
     TIEBREAK_FIRST
     TIEBREAK_FIRST_DESCENDING
     TIEBREAK_DENSE
+
+
+cdef numeric_object_t get_rank_nan_fill_val(
+    bint rank_nans_highest,
+    numeric_object_t val,
+    bint is_datetimelike=*,
+)

pandas/_libs/algos.pyx

@@ -822,13 +822,17 @@ def is_monotonic(ndarray[numeric_object_t, ndim=1] arr, bint timelike):
 
 cdef numeric_object_t get_rank_nan_fill_val(
     bint rank_nans_highest,
-    numeric_object_t[:] _=None
+    numeric_object_t val,
+    bint is_datetimelike=False,
 ):
     """
     Return the value we'll use to represent missing values when sorting depending
     on if we'd like missing values to end up at the top/bottom. (The second parameter
     is unused, but needed for fused type specialization)
     """
+    if numeric_object_t is int64_t and is_datetimelike and not rank_nans_highest:
+        return NPY_NAT + 1
+
     if rank_nans_highest:
         if numeric_object_t is object:
             return Infinity()
@@ -854,6 +858,9 @@ cdef numeric_object_t get_rank_nan_fill_val(
         if numeric_object_t is object:
             return NegInfinity()
         elif numeric_object_t is int64_t:
+            # Note(jbrockmendel) 2022-03-15 for reasons unknown, using util.INT64_MIN
+            #  instead of NPY_NAT here causes build warnings and failure in
+            #  test_cummax_i8_at_implementation_bound
             return NPY_NAT
         elif numeric_object_t is int32_t:
             return util.INT32_MIN
@@ -975,7 +982,7 @@ def rank_1d(
     # will flip the ordering to still end up with lowest rank.
     # Symmetric logic applies to `na_option == 'bottom'`
     nans_rank_highest = ascending ^ (na_option == 'top')
-    nan_fill_val = get_rank_nan_fill_val[numeric_object_t](nans_rank_highest)
+    nan_fill_val = get_rank_nan_fill_val(nans_rank_highest, <numeric_object_t>0)
     if nans_rank_highest:
         order = [masked_vals, mask]
     else:
@@ -1335,7 +1342,7 @@ def rank_2d(
 
     nans_rank_highest = ascending ^ (na_option == 'top')
     if check_mask:
-        nan_fill_val = get_rank_nan_fill_val[numeric_object_t](nans_rank_highest)
+        nan_fill_val = get_rank_nan_fill_val(nans_rank_highest, <numeric_object_t>0)
 
         if numeric_object_t is object:
             mask = missing.isnaobj2d(values).view(np.uint8)

pandas/_libs/groupby.pyx

@@ -31,7 +31,10 @@ from numpy.math cimport NAN
 cnp.import_array()
 
 from pandas._libs cimport util
-from pandas._libs.algos cimport kth_smallest_c
+from pandas._libs.algos cimport (
+    get_rank_nan_fill_val,
+    kth_smallest_c,
+)
 
 from pandas._libs.algos import (
     ensure_platform_int,
@@ -989,36 +992,16 @@ cdef inline bint _treat_as_na(numeric_object_t val, bint is_datetimelike) nogil:
         return False
 
 
-cdef numeric_t _get_min_or_max(numeric_t val, bint compute_max, bint is_datetimelike):
+cdef numeric_object_t _get_min_or_max(numeric_object_t val, bint compute_max, bint is_datetimelike):
     """
-    Find either the min or the max supported by numeric_t; 'val' is a placeholder
-    to effectively make numeric_t an argument.
+    Find either the min or the max supported by numeric_object_t; 'val' is a
+    placeholder to effectively make numeric_object_t an argument.
     """
-    if numeric_t is int64_t:
-        if compute_max and is_datetimelike:
-            return -_int64_max
-        # Note(jbrockmendel) 2022-03-15 for reasons unknown, using util.INT64_MIN
-        #  instead of NPY_NAT here causes build warnings and failure in
-        #  test_cummax_i8_at_implementation_bound
-        return NPY_NAT if compute_max else util.INT64_MAX
-    elif numeric_t is int32_t:
-        return util.INT32_MIN if compute_max else util.INT32_MAX
-    elif numeric_t is int16_t:
-        return util.INT16_MIN if compute_max else util.INT16_MAX
-    elif numeric_t is int8_t:
-        return util.INT8_MIN if compute_max else util.INT8_MAX
-
-    elif numeric_t is uint64_t:
-        return 0 if compute_max else util.UINT64_MAX
-    elif numeric_t is uint32_t:
-        return 0 if compute_max else util.UINT32_MAX
-    elif numeric_t is uint16_t:
-        return 0 if compute_max else util.UINT16_MAX
-    elif numeric_t is uint8_t:
-        return 0 if compute_max else util.UINT8_MAX
-
-    else:
-        return -np.inf if compute_max else np.inf
+    return get_rank_nan_fill_val(
+        not compute_max,
+        val=val,
+        is_datetimelike=is_datetimelike,
+    )
 
 
 cdef numeric_t _get_na_val(numeric_t val, bint is_datetimelike):