ENH: Map pandas integer to optimal SQLAlchemy integer type (GH35076)

doc/source/whatsnew/v1.3.0.rst

@@ -44,6 +44,7 @@ Other enhancements
 - Improve error message when ``usecols`` and ``names`` do not match for :func:`read_csv` and ``engine="c"`` (:issue:`29042`)
 - Improved consistency of error message when passing an invalid ``win_type`` argument in :class:`Window` (:issue:`15969`)
 - :func:`pandas.read_sql_query` now accepts a ``dtype`` argument to cast the columnar data from the SQL database based on user input (:issue:`10285`)
+- Improved integer type mapping from pandas to SQLAlchemy when using :meth:`DataFrame.to_sql` (:issue:`35076`)
 
 .. ---------------------------------------------------------------------------
 

pandas/io/sql.py

@@ -1124,6 +1124,7 @@ def _sqlalchemy_type(self, col):
             DateTime,
             Float,
             Integer,
+            SmallInteger,
             Text,
             Time,
         )
@@ -1154,8 +1155,13 @@ def _sqlalchemy_type(self, col):
             else:
                 return Float(precision=53)
         elif col_type == "integer":
-            if col.dtype == "int32":
+            # GH35076 Map pandas integer to optimal SQLAlchemy integer type
+            if col.dtype.name.lower() in ("int8", "uint8", "int16"):
+                return SmallInteger
+            elif col.dtype.name.lower() in ("uint16", "int32"):
                 return Integer
+            elif col.dtype.name.lower() == "uint64":
+                raise ValueError("Unsigned 64 bit integer datatype is not supported")
             else:
                 return BigInteger
         elif col_type == "boolean":

pandas/tests/io/test_sql.py

@@ -1160,6 +1160,45 @@ def test_sqlalchemy_type_mapping(self):
         # GH 9086: TIMESTAMP is the suggested type for datetimes with timezones
         assert isinstance(table.table.c["time"].type, sqltypes.TIMESTAMP)
 
+    @pytest.mark.parametrize(
+        "integer, expected",
+        [
+            ("int8", "SMALLINT"),
+            ("Int8", "SMALLINT"),
+            ("uint8", "SMALLINT"),
+            ("UInt8", "SMALLINT"),
+            ("int16", "SMALLINT"),
+            ("Int16", "SMALLINT"),
+            ("uint16", "INTEGER"),
+            ("UInt16", "INTEGER"),
+            ("int32", "INTEGER"),
+            ("Int32", "INTEGER"),
+            ("uint32", "BIGINT"),
+            ("UInt32", "BIGINT"),
+            ("int64", "BIGINT"),
+            ("Int64", "BIGINT"),
+            (int, "BIGINT" if np.dtype(int).name == "int64" else "INTEGER"),
+        ],
+    )
+    def test_sqlalchemy_integer_mapping(self, integer, expected):
+        # GH35076 Map pandas integer to optimal SQLAlchemy integer type
+        df = DataFrame([0, 1], columns=["a"], dtype=integer)
+        db = sql.SQLDatabase(self.conn)
+        table = sql.SQLTable("test_type", db, frame=df)
+
+        result = str(table.table.c.a.type)
+        assert result == expected
+
+    @pytest.mark.parametrize("integer", ["uint64", "UInt64"])
+    def test_sqlalchemy_integer_overload_mapping(self, integer):
+        # GH35076 Map pandas integer to optimal SQLAlchemy integer type
+        df = DataFrame([0, 1], columns=["a"], dtype=integer)
+        db = sql.SQLDatabase(self.conn)
+        with pytest.raises(
+            ValueError, match="Unsigned 64 bit integer datatype is not supported"
+        ):
+            sql.SQLTable("test_type", db, frame=df)
+
     def test_database_uri_string(self):
 
         # Test read_sql and .to_sql method with a database URI (GH10654)