Backport PR #48995 on branch 1.5.x (REGR: to_parquet raising with bytes filename)

doc/source/whatsnew/v1.5.1.rst

@@ -85,6 +85,7 @@ Fixed regressions
 - Fixed Regression in :meth:`DataFrameGroupBy.apply` when user defined function is called on an empty dataframe (:issue:`47985`)
 - Fixed regression in :meth:`DataFrame.apply` when passing non-zero ``axis`` via keyword argument (:issue:`48656`)
 - Fixed regression in :meth:`Series.groupby` and :meth:`DataFrame.groupby` when the grouper is a nullable data type (e.g. :class:`Int64`) or a PyArrow-backed string array, contains null values, and ``dropna=False`` (:issue:`48794`)
+- Fixed regression in :meth:`DataFrame.to_parquet` raising when file name was specified as ``bytes`` (:issue:`48944`)
 - Fixed regression in :class:`ExcelWriter` where the ``book`` attribute could no longer be set; however setting this attribute is now deprecated and this ability will be removed in a future version of pandas (:issue:`48780`)
 
 .. ---------------------------------------------------------------------------

pandas/io/parquet.py

@@ -186,6 +186,8 @@ def write(
             and isinstance(path_or_handle.name, (str, bytes))
         ):
             path_or_handle = path_or_handle.name
+            if isinstance(path_or_handle, bytes):
+                path_or_handle = path_or_handle.decode()
 
         try:
             if partition_cols is not None:

pandas/tests/io/test_parquet.py

@@ -1182,3 +1182,13 @@ def test_close_file_handle_on_read_error(self):
                 read_parquet(path, engine="fastparquet")
             # The next line raises an error on Windows if the file is still open
             pathlib.Path(path).unlink(missing_ok=False)
+
+    def test_bytes_file_name(self, engine):
+        # GH#48944
+        df = pd.DataFrame(data={"A": [0, 1], "B": [1, 0]})
+        with tm.ensure_clean("test.parquet") as path:
+            with open(path.encode(), "wb") as f:
+                df.to_parquet(f)
+
+            result = read_parquet(path, engine=engine)
+        tm.assert_frame_equal(result, df)