BUG: fix skiprows callable infinite loop

doc/source/whatsnew/v1.5.0.rst

@@ -194,6 +194,7 @@ Conversion
 - Bug in constructing a :class:`Series` from a float-containing list or a floating-dtype ndarray-like (e.g. ``dask.Array``) and an integer dtype raising instead of casting like we would with an ``np.ndarray`` (:issue:`40110`)
 - Bug in :meth:`Float64Index.astype` to unsigned integer dtype incorrectly casting to ``np.int64`` dtype (:issue:`45309`)
 - Bug in :meth:`Series.astype` and :meth:`DataFrame.astype` from floating dtype to unsigned integer dtype failing to raise in the presence of negative values (:issue:`45151`)
+- Bug in :meth:`python_parser._next_line` causing an infinite loop with certain `skiprows` callables (:issue:`45585`)
 -
 
 Strings

pandas/io/parsers/python_parser.py

@@ -667,6 +667,8 @@ def _is_line_empty(self, line: list[Scalar]) -> bool:
     def _next_line(self) -> list[Scalar]:
         if isinstance(self.data, list):
             while self.skipfunc(self.pos):
+                if self.pos >= len(self.data):
+                    break
                 self.pos += 1
 
             while True:

pandas/tests/io/excel/test_readers.py

@@ -1165,6 +1165,24 @@ def test_read_excel_skiprows(self, request, read_ext):
         )
         tm.assert_frame_equal(actual, expected)
 
+    def test_read_excel_skiprows_callable_not_in(self, request, read_ext):
+        actual = pd.read_excel(
+            "testskiprows" + read_ext,
+            sheet_name="skiprows_list",
+            skiprows=lambda x: x not in [1, 3, 5],
+        )
+        expected = DataFrame(
+            [
+                [1, 2.5, pd.Timestamp("2015-01-01"), True],
+                # [2, 3.5, pd.Timestamp("2015-01-02"), False],
+                [3, 4.5, pd.Timestamp("2015-01-03"), False],
+                # [4, 5.5, pd.Timestamp("2015-01-04"), True],
+            ],
+            columns=["a", "b", "c", "d"],
+        )
+        tm.assert_frame_equal(actual, expected)
+
+
     def test_read_excel_nrows(self, read_ext):
         # GH 16645
         num_rows_to_pull = 5