REF: avoid getattr pattern for groupby-rank functions (#29166)

Author: jbrockmendel

pandas/_libs/groupby.pyx

@@ -923,12 +923,6 @@ def group_last(rank_t[:, :] out,
         raise RuntimeError("empty group with uint64_t")
 
 
-group_last_float64 = group_last["float64_t"]
-group_last_float32 = group_last["float32_t"]
-group_last_int64 = group_last["int64_t"]
-group_last_object = group_last["object"]
-
-
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def group_nth(rank_t[:, :] out,
@@ -1020,12 +1014,6 @@ def group_nth(rank_t[:, :] out,
         raise RuntimeError("empty group with uint64_t")
 
 
-group_nth_float64 = group_nth["float64_t"]
-group_nth_float32 = group_nth["float32_t"]
-group_nth_int64 = group_nth["int64_t"]
-group_nth_object = group_nth["object"]
-
-
 @cython.boundscheck(False)
 @cython.wraparound(False)
 def group_rank(float64_t[:, :] out,
@@ -1213,14 +1201,6 @@ def group_rank(float64_t[:, :] out,
                     out[i, 0] = out[i, 0] / grp_sizes[i, 0]
 
 
-group_rank_float64 = group_rank["float64_t"]
-group_rank_float32 = group_rank["float32_t"]
-group_rank_int64 = group_rank["int64_t"]
-group_rank_uint64 = group_rank["uint64_t"]
-# Note: we do not have a group_rank_object because that would require a
-#  not-nogil implementation, see GH#19560
-
-
 # ----------------------------------------------------------------------
 # group_min, group_max
 # ----------------------------------------------------------------------

pandas/core/groupby/ops.py

@@ -419,13 +419,21 @@ def get_func(fname):
 
             # otherwise find dtype-specific version, falling back to object
             for dt in [dtype_str, "object"]:
-                f = getattr(
+                f2 = getattr(
                     libgroupby,
                     "{fname}_{dtype_str}".format(fname=fname, dtype_str=dt),
                     None,
                 )
-                if f is not None:
-                    return f
+                if f2 is not None:
+                    return f2
+
+            if hasattr(f, "__signatures__"):
+                # inspect what fused types are implemented
+                if dtype_str == "object" and "object" not in f.__signatures__:
+                    # return None so we get a NotImplementedError below
+                    #  instead of a TypeError at runtime
+                    return None
+            return f
 
         ftype = self._cython_functions[kind][how]
 

pandas/tests/groupby/test_rank.py

@@ -3,6 +3,7 @@
 
 import pandas as pd
 from pandas import DataFrame, Series, concat
+from pandas.core.base import DataError
 from pandas.util import testing as tm
 
 
@@ -384,7 +385,7 @@ def test_rank_avg_even_vals():
 def test_rank_object_raises(ties_method, ascending, na_option, pct, vals):
     df = DataFrame({"key": ["foo"] * 5, "val": vals})
 
-    with pytest.raises(TypeError, match="not callable"):
+    with pytest.raises(DataError, match="No numeric types to aggregate"):
         df.groupby("key").rank(
             method=ties_method, ascending=ascending, na_option=na_option, pct=pct
         )