BUG: Unable to open Stata 118 or 119 format files saved in big-endian…

doc/source/whatsnew/v3.0.0.rst

@@ -434,6 +434,7 @@ I/O
 - Bug in :meth:`DataFrame.to_excel` when writing empty :class:`DataFrame` with :class:`MultiIndex` on both axes (:issue:`57696`)
 - Bug in :meth:`DataFrame.to_string` that raised ``StopIteration`` with nested DataFrames. (:issue:`16098`)
 - Bug in :meth:`read_csv` raising ``TypeError`` when ``index_col`` is specified and ``na_values`` is a dict containing the key ``None``. (:issue:`57547`)
+- Bug in :meth:`read_stata` raising ``KeyError`` when input file is stored in big-endian format and contains strL data. (:issue:`58638`)
 
 Period
 ^^^^^^

pandas/io/stata.py

@@ -1599,14 +1599,13 @@ def _read_strls(self) -> None:
                 v_o = self._read_uint64()
             else:
                 buf = self._path_or_buf.read(12)
-                # Only tested on little endian file on little endian machine.
+                # Only tested on little endian machine.
                 v_size = 2 if self._format_version == 118 else 3
                 if self._byteorder == "<":
                     buf = buf[0:v_size] + buf[4 : (12 - v_size)]
                 else:
-                    # This path may not be correct, impossible to test
-                    buf = buf[0:v_size] + buf[(4 + v_size) :]
-                v_o = struct.unpack("Q", buf)[0]
+                    buf = buf[4 - v_size : 4] + buf[(4 + v_size) :]
+                v_o = struct.unpack(f"{self._byteorder}Q", buf)[0]
             typ = self._read_uint8()
             length = self._read_uint32()
             va = self._path_or_buf.read(length)

pandas/tests/io/test_stata.py

@@ -318,8 +318,19 @@ def test_readold_dta4(self, file, datapath):
         tm.assert_frame_equal(parsed, expected)
 
     # File containing strls
-    def test_read_dta12(self, datapath):
-        parsed_117 = self.read_dta(datapath("io", "data", "stata", "stata12_117.dta"))
+    @pytest.mark.parametrize(
+        "file",
+        [
+            "stata12_117",
+            "stata12_be_117",
+            "stata12_118",
+            "stata12_be_118",
+            "stata12_119",
+            "stata12_be_119",
+        ],
+    )
+    def test_read_dta12(self, file, datapath):
+        parsed_117 = self.read_dta(datapath("io", "data", "stata", f"{file}.dta"))
         expected = DataFrame.from_records(
             [
                 [1, "abc", "abcdefghi"],
@@ -331,8 +342,18 @@ def test_read_dta12(self, datapath):
 
         tm.assert_frame_equal(parsed_117, expected, check_dtype=False)
 
-    def test_read_dta18(self, datapath):
-        parsed_118 = self.read_dta(datapath("io", "data", "stata", "stata14_118.dta"))
+    # 117 is not included in this list as it uses ASCII strings
+    @pytest.mark.parametrize(
+        "file",
+        [
+            "stata14_118",
+            "stata14_be_118",
+            "stata14_119",
+            "stata14_be_119",
+        ],
+    )
+    def test_read_dta18(self, file, datapath):
+        parsed_118 = self.read_dta(datapath("io", "data", "stata", f"{file}.dta"))
         parsed_118["Bytes"] = parsed_118["Bytes"].astype("O")
         expected = DataFrame.from_records(
             [
@@ -356,7 +377,7 @@ def test_read_dta18(self, datapath):
         for col in parsed_118.columns:
             tm.assert_almost_equal(parsed_118[col], expected[col])
 
-        with StataReader(datapath("io", "data", "stata", "stata14_118.dta")) as rdr:
+        with StataReader(datapath("io", "data", "stata", f"{file}.dta")) as rdr:
             vl = rdr.variable_labels()
             vl_expected = {
                 "Unicode_Cities_Strl": "Here are some strls with Ünicode chars",
@@ -1800,8 +1821,18 @@ def test_gzip_writing(self, temp_file):
             reread = read_stata(gz, index_col="index")
         tm.assert_frame_equal(df, reread)
 
-    def test_unicode_dta_118(self, datapath):
-        unicode_df = self.read_dta(datapath("io", "data", "stata", "stata16_118.dta"))
+    # 117 is not included in this list as it uses ASCII strings
+    @pytest.mark.parametrize(
+        "file",
+        [
+            "stata16_118",
+            "stata16_be_118",
+            "stata16_119",
+            "stata16_be_119",
+        ],
+    )
+    def test_unicode_dta_118(self, file, datapath):
+        unicode_df = self.read_dta(datapath("io", "data", "stata", f"{file}.dta"))
 
         columns = ["utf8", "latin1", "ascii", "utf8_strl", "ascii_strl"]
         values = [