feat: support float32 parameters in dbapi

dbapi should not add an explicit type code when a parameter of type
float is encountered. Instead, it should rely on Spanner to infer
the correct type. This way, both FLOAT32 and FLOAT64 can be used with
the Python float type.

Updates googleapis/python-spanner-sqlalchemy#409

google/cloud/spanner_dbapi/parse_utils.py

@@ -29,12 +29,19 @@
 from .types import DateStr, TimestampStr
 from .utils import sanitize_literals_for_upload
 
+# Note: This mapping deliberately does not contain a value for float.
+# The reason for that is that it is better to just let Spanner determine
+# the parameter type instead of specifying one explicitly. The reason for
+# this is that if the client specifies FLOAT64, and the actual column that
+# the parameter is used for is of type FLOAT32, then Spanner will return an
+# error. If however the client does not specify a type, then Spanner will
+# automatically choose the appropriate type based on the column where the
+# value will be inserted/updated or that it will be compared with.
 TYPES_MAP = {
     bool: spanner.param_types.BOOL,
     bytes: spanner.param_types.BYTES,
     str: spanner.param_types.STRING,
     int: spanner.param_types.INT64,
-    float: spanner.param_types.FLOAT64,
     datetime.datetime: spanner.param_types.TIMESTAMP,
     datetime.date: spanner.param_types.DATE,
     DateStr: spanner.param_types.DATE,

tests/system/test_dbapi.py

@@ -11,11 +11,13 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
+import base64
 import datetime
 from collections import defaultdict
+
 import pytest
 import time
+import decimal
 
 from google.cloud import spanner_v1
 from google.cloud._helpers import UTC
@@ -50,7 +52,22 @@
     SQL SECURITY INVOKER
     AS
     SELECT c.email
-    FROM contacts AS c;"""
+    FROM contacts AS c;
+    
+    CREATE TABLE all_types (
+        id int64,
+        col_bool bool,
+        col_bytes bytes(max),
+        col_date date,
+        col_float32 float32,
+        col_float64 float64,
+        col_int64 int64,
+        col_json json,
+        col_numeric numeric,
+        col_string string(max),
+        coL_timestamp timestamp,
+    ) primary key (col_int64);
+    """
 
 DDL_STATEMENTS = [stmt.strip() for stmt in DDL.split(";") if stmt.strip()]
 
@@ -1602,3 +1619,29 @@ def test_list_tables(self, include_views):
     def test_invalid_statement_error(self):
         with pytest.raises(ProgrammingError):
             self._cursor.execute("-- comment only")
+
+    def test_insert_all_types(self):
+        """Test inserting all supported data types"""
+
+        self._conn.autocommit = True
+        self._cursor.execute(
+            """
+    INSERT INTO all_types (id, col_bool, col_bytes, col_date, col_float32, col_float64,
+                           col_int64, col_json, col_numeric, col_string, col_timestamp)
+    VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
+        """,
+            (
+                1,
+                True,
+                base64.b64encode(b"test-bytes"),
+                datetime.date(2024, 12, 3),
+                3.14,
+                3.14,
+                123,
+                JsonObject({"key": "value"}),
+                decimal.Decimal("3.14"),
+                "test-string",
+                datetime.datetime(2024, 12, 3, 17, 30, 14),
+            ),
+        )
+        assert self._cursor.rowcount == 1

tests/unit/spanner_dbapi/test_parse_utils.py

@@ -218,6 +218,8 @@ def test_get_param_types(self):
         params = {
             "a1": 10,
             "b1": "string",
+            # Note: We only want a value and not a type for this.
+            # Instead, we let Spanner infer the correct type (FLOAT64 or FLOAT32)
             "c1": 10.39,
             "d1": TimestampStr("2005-08-30T01:01:01.000001Z"),
             "e1": DateStr("2019-12-05"),
@@ -232,7 +234,6 @@ def test_get_param_types(self):
         want_types = {
             "a1": param_types.INT64,
             "b1": param_types.STRING,
-            "c1": param_types.FLOAT64,
             "d1": param_types.TIMESTAMP,
             "e1": param_types.DATE,
             "f1": param_types.BOOL,