Backport PR #55670 on branch 2.1.x (REGR: merge_asof raising TypeErro…

…r for "by" with datelike dtypes) (#55676)

Backport PR #55670: REGR: merge_asof raising TypeError for "by" with datelike dtypes

Co-authored-by: Luke Manley <lukemanley@gmail.com>

doc/source/whatsnew/v2.1.2.rst

@@ -17,6 +17,7 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrame.resample` which was extrapolating back to ``origin`` when ``origin`` was outside its bounds (:issue:`55064`)
 - Fixed regression in :meth:`DataFrame.sort_index` which was not sorting correctly when the index was a sliced :class:`MultiIndex` (:issue:`55379`)
 - Fixed performance regression with wide DataFrames, typically involving methods where all columns were accessed individually (:issue:`55256`, :issue:`55245`)
+- Fixed regression in :func:`merge_asof` raising ``TypeError`` for ``by`` with datetime and timedelta dtypes (:issue:`55453`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_212.bug_fixes:

pandas/core/reshape/merge.py

@@ -2193,6 +2193,10 @@ def injection(obj: ArrayLike):
                 # TODO: conversions for EAs that can be no-copy.
                 lbv = np.asarray(lbv)
                 rbv = np.asarray(rbv)
+                if needs_i8_conversion(lbv.dtype):
+                    lbv = lbv.view("i8")
+                if needs_i8_conversion(rbv.dtype):
+                    rbv = rbv.view("i8")
             else:
                 # We get here with non-ndarrays in test_merge_by_col_tz_aware
                 #  and test_merge_groupby_multiple_column_with_categorical_column

pandas/tests/reshape/merge/test_merge_asof.py

@@ -1341,6 +1341,34 @@ def test_by_mixed_tz_aware(self):
         expected["value_y"] = np.array([np.nan], dtype=object)
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize("dtype", ["m8[ns]", "M8[us]"])
+    def test_by_datelike(self, dtype):
+        # GH 55453
+        left = pd.DataFrame(
+            {
+                "by_col": np.array([1], dtype=dtype),
+                "on_col": [2],
+                "value": ["a"],
+            }
+        )
+        right = pd.DataFrame(
+            {
+                "by_col": np.array([1], dtype=dtype),
+                "on_col": [1],
+                "value": ["b"],
+            }
+        )
+        result = merge_asof(left, right, by="by_col", on="on_col")
+        expected = pd.DataFrame(
+            {
+                "by_col": np.array([1], dtype=dtype),
+                "on_col": [2],
+                "value_x": ["a"],
+                "value_y": ["b"],
+            }
+        )
+        tm.assert_frame_equal(result, expected)
+
     def test_timedelta_tolerance_nearest(self, unit):
         # GH 27642
         if unit == "s":