BUG: Ignore warning for duplicate columns in to_dict when orient='tight'

doc/source/whatsnew/v3.0.0.rst

@@ -456,6 +456,7 @@ Other
 - Bug in :func:`unique` on :class:`Index` not always returning :class:`Index` (:issue:`57043`)
 - Bug in :meth:`DataFrame.eval` and :meth:`DataFrame.query` which caused an exception when using NumPy attributes via ``@`` notation, e.g., ``df.eval("@np.floor(a)")``. (:issue:`58041`)
 - Bug in :meth:`DataFrame.sort_index` when passing ``axis="columns"`` and ``ignore_index=True`` and ``ascending=False`` not returning a :class:`RangeIndex` columns (:issue:`57293`)
+- Bug in :meth:`DataFrame.to_dict` when ``orieent='tight'`` raise unnecessary ``UserWarning``. (:issue:`58281`)
 - Bug in :meth:`DataFrame.transform` that was returning the wrong order unless the index was monotonically increasing. (:issue:`57069`)
 - Bug in :meth:`DataFrame.where` where using a non-bool type array in the function would return a ``ValueError`` instead of a ``TypeError`` (:issue:`56330`)
 - Bug in :meth:`Index.sort_values` when passing a key function that turns values into tuples, e.g. ``key=natsort.natsort_key``, would raise ``TypeError`` (:issue:`56081`)

pandas/core/methods/to_dict.py

@@ -148,7 +148,7 @@ def to_dict(
         Return a collections.abc.MutableMapping object representing the
         DataFrame. The resulting transformation depends on the `orient` parameter.
     """
-    if not df.columns.is_unique:
+    if orient != "tight" and not df.columns.is_unique:
         warnings.warn(
             "DataFrame columns are not unique, some columns will be omitted.",
             UserWarning,

pandas/tests/frame/methods/test_to_dict.py

@@ -513,6 +513,18 @@ def test_to_dict_masked_native_python(self):
         result = df.to_dict(orient="records")
         assert isinstance(result[0]["a"], int)
 
+    def test_to_dict_tight_no_warning_with_duplicate_column(self):
+        # GH#58281
+        df = DataFrame(
+            {
+                "A": [1, 2, 3],
+                "B": [4, 5, 6],
+            }
+        )
+        df.columns = ["A", "A"]
+        with tm.assert_produces_warning(None):
+            df.to_dict(orient="tight")
+
 
 @pytest.mark.parametrize(
     "val", [Timestamp(2020, 1, 1), Timedelta(1), Period("2020"), Interval(1, 2)]