Fixed bug when deciding Arrow datatype for numeric expressions (#510).

Author: anthony-tuininga

doc/src/release_notes.rst

@@ -53,6 +53,8 @@ Common Changes
     - Ensure that the GIL is held when releasing references to ``ArrowArray``
       objects when exported Arrow buffers are released by the consumer. In
       some circumstances this could cause a segfault.
+    - Fixed bug when deciding Arrow datatype for numeric expressions
+      (`issue 510 <https://github.com/oracle/python-oracledb/issues/510>`__)
 
     Note the data frame support in python-oracledb 3.3 is a pre-release, and
     may change in a future version

src/oracledb/impl/base/metadata.pyx

@@ -67,7 +67,7 @@ cdef class OracleMetadata:
             elif py_type_num == PY_TYPE_NUM_STR:
                 self._arrow_type = NANOARROW_TYPE_STRING
             elif py_type_num == PY_TYPE_NUM_INT and self.scale == 0 \
-                    and self.precision <= 18:
+                    and 0 < self.precision <= 18:
                 self._arrow_type = NANOARROW_TYPE_INT64
             else:
                 self._arrow_type = NANOARROW_TYPE_DOUBLE

tests/test_8000_dataframe.py

@@ -894,6 +894,26 @@ def test_8033(self):
                 """
             )
 
+    def test_8034(self):
+        "8034 - test expressions on numeric columns"
+        # fill only the numeric column - credit score
+        dataset = [
+            (1, None, None, None, None, None, None, 225, None),
+            (2, None, None, None, None, None, None, 365, None),
+        ]
+        data = [
+            (56.25,),
+            (91.25,),
+        ]
+        self.__check_interop()
+        self.__populate_table(dataset)
+
+        # Use numeric expression involving a column
+        statement = "select CreditScore/4 from TestDataFrame order by Id"
+        ora_df = self.conn.fetch_df_all(statement)
+        fetched_df = pyarrow.table(ora_df).to_pandas()
+        self.assertEqual(data, self.__get_data_from_df(fetched_df))
+
 
 if __name__ == "__main__":
     test_env.run_test_cases()