feat: Add support for array and float32 SQL query params

google/cloud/bigtable/data/_async/client.py

@@ -569,6 +569,8 @@ async def execute_query(
                 will be chained with a RetryExceptionGroup containing GoogleAPIError exceptions
                 from any retries that failed
             google.api_core.exceptions.GoogleAPIError: raised if the request encounters an unrecoverable error
+            google.cloud.bigtable.data.exceptions.ParameterTypeInferenceFailed: Raised if
+                a parameter is passed without an explicit type, and the type cannot be infered
         """
         warnings.warn(
             "ExecuteQuery is in preview and may change in the future.",

google/cloud/bigtable/data/execute_query/_async/execute_query_iterator.py

@@ -22,7 +22,6 @@
     Tuple,
     TYPE_CHECKING,
 )
-
 from google.api_core import retry as retries
 
 from google.cloud.bigtable.data.execute_query._byte_cursor import _ByteCursor
@@ -116,7 +115,6 @@ def __init__(
             exception_factory=_retry_exception_factory,
         )
         self._req_metadata = req_metadata
-
         try:
             self._register_instance_task = CrossSync.create_task(
                 self._client._register_instance,

google/cloud/bigtable/data/execute_query/_parameters_formatting.py

@@ -12,12 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from typing import Any, Dict, Optional
 import datetime
+from typing import Any, Dict, Optional
+
 from google.api_core.datetime_helpers import DatetimeWithNanoseconds
+
 from google.cloud.bigtable.data.exceptions import ParameterTypeInferenceFailed
-from google.cloud.bigtable.data.execute_query.values import ExecuteQueryValueType
 from google.cloud.bigtable.data.execute_query.metadata import SqlType
+from google.cloud.bigtable.data.execute_query.values import ExecuteQueryValueType
 
 
 def _format_execute_query_params(
@@ -48,7 +50,6 @@ def _format_execute_query_params(
     parameter_types = parameter_types or {}
 
     result_values = {}
-
     for key, value in params.items():
         user_provided_type = parameter_types.get(key)
         try:
@@ -109,6 +110,16 @@ def _detect_type(value: ExecuteQueryValueType) -> SqlType.Type:
             "Cannot infer type of None, please provide the type manually."
         )
 
+    if isinstance(value, list):
+        raise ParameterTypeInferenceFailed(
+            "Cannot infer type of ARRAY parameters, please provide the type manually."
+        )
+
+    if isinstance(value, float):
+        raise ParameterTypeInferenceFailed(
+            "Cannot infer type of float, must specify either FLOAT32 or FLOAT64 type manually."
+        )
+
     for field_type, type_dict in _TYPES_TO_TYPE_DICTS:
         if isinstance(value, field_type):
             return type_dict

google/cloud/bigtable/data/execute_query/_query_result_parsing_utils.py

@@ -22,6 +22,7 @@
     SqlType.Bytes: "bytes_value",
     SqlType.String: "string_value",
     SqlType.Int64: "int_value",
+    SqlType.Float32: "float_value",
     SqlType.Float64: "float_value",
     SqlType.Bool: "bool_value",
     SqlType.Timestamp: "timestamp_value",

google/cloud/bigtable/data/execute_query/metadata.py

@@ -21,23 +21,16 @@
 """
 
 from collections import defaultdict
-from typing import (
-    Optional,
-    List,
-    Dict,
-    Set,
-    Type,
-    Union,
-    Tuple,
-    Any,
-)
+import datetime
+from typing import Any, Dict, List, Optional, Set, Tuple, Type, Union
+
+from google.api_core.datetime_helpers import DatetimeWithNanoseconds
+from google.protobuf import timestamp_pb2  # type: ignore
+from google.type import date_pb2  # type: ignore
+
 from google.cloud.bigtable.data.execute_query.values import _NamedList
 from google.cloud.bigtable_v2 import ResultSetMetadata
 from google.cloud.bigtable_v2 import Type as PBType
-from google.type import date_pb2  # type: ignore
-from google.protobuf import timestamp_pb2  # type: ignore
-from google.api_core.datetime_helpers import DatetimeWithNanoseconds
-import datetime
 
 
 class SqlType:
@@ -127,6 +120,8 @@ class Array(Type):
         def __init__(self, element_type: "SqlType.Type"):
             if isinstance(element_type, SqlType.Array):
                 raise ValueError("Arrays of arrays are not supported.")
+            if isinstance(element_type, SqlType.Map):
+                raise ValueError("Arrays of Maps are not supported.")
             self._element_type = element_type
 
         @property
@@ -140,10 +135,21 @@ def from_pb_type(cls, type_pb: Optional[PBType] = None) -> "SqlType.Array":
             return cls(_pb_type_to_metadata_type(type_pb.array_type.element_type))
 
         def _to_value_pb_dict(self, value: Any):
-            raise NotImplementedError("Array is not supported as a query parameter")
+            if value is None:
+                return {}
+
+            return {
+                "array_value": {
+                    "values": [
+                        self.element_type._to_value_pb_dict(entry) for entry in value
+                    ]
+                }
+            }
 
         def _to_type_pb_dict(self) -> Dict[str, Any]:
-            raise NotImplementedError("Array is not supported as a query parameter")
+            return {
+                "array_type": {"element_type": self.element_type._to_type_pb_dict()}
+            }
 
         def __eq__(self, other):
             return super().__eq__(other) and self.element_type == other.element_type
@@ -222,6 +228,13 @@ class Float64(Type):
         value_pb_dict_field_name = "float_value"
         type_field_name = "float64_type"
 
+    class Float32(Type):
+        """Float32 SQL type."""
+
+        expected_type = float
+        value_pb_dict_field_name = "float_value"
+        type_field_name = "float32_type"
+
     class Bool(Type):
         """Bool SQL type."""
 
@@ -376,6 +389,7 @@ def _pb_metadata_to_metadata_types(
     "bytes_type": SqlType.Bytes,
     "string_type": SqlType.String,
     "int64_type": SqlType.Int64,
+    "float32_type": SqlType.Float32,
     "float64_type": SqlType.Float64,
     "bool_type": SqlType.Bool,
     "timestamp_type": SqlType.Timestamp,

tests/system/data/test_system_async.py

@@ -14,13 +14,16 @@
 
 import pytest
 import asyncio
+import datetime
 import uuid
 import os
 from google.api_core import retry
 from google.api_core.exceptions import ClientError
 
+from google.cloud.bigtable.data.execute_query.metadata import SqlType
 from google.cloud.bigtable.data.read_modify_write_rules import _MAX_INCREMENT_VALUE
 from google.cloud.environment_vars import BIGTABLE_EMULATOR
+from google.type import date_pb2
 
 from google.cloud.bigtable.data._cross_sync import CrossSync
 
@@ -1027,3 +1030,83 @@ async def test_execute_query_simple(self, client, table_id, instance_id):
         row = rows[0]
         assert row["a"] == 1
         assert row["b"] == "foo"
+
+    @CrossSync.pytest
+    @pytest.mark.usefixtures("client")
+    @CrossSync.Retry(
+        predicate=retry.if_exception_type(ClientError), initial=1, maximum=5
+    )
+    async def test_execute_query_params(self, client, table_id, instance_id):
+        query = (
+            "SELECT @stringParam AS strCol, @bytesParam as bytesCol, @int64Param AS intCol, "
+            "@float32Param AS float32Col, @float64Param AS float64Col, @boolParam AS boolCol, "
+            "@tsParam AS tsCol, @dateParam AS dateCol, @byteArrayParam AS byteArrayCol, "
+            "@stringArrayParam AS stringArrayCol, @intArrayParam AS intArrayCol, "
+            "@float32ArrayParam AS float32ArrayCol, @float64ArrayParam AS float64ArrayCol, "
+            "@boolArrayParam AS boolArrayCol, @tsArrayParam AS tsArrayCol, "
+            "@dateArrayParam AS dateArrayCol"
+        )
+        parameters = {
+            "stringParam": "foo",
+            "bytesParam": b"bar",
+            "int64Param": 12,
+            "float32Param": 1.1,
+            "float64Param": 1.2,
+            "boolParam": True,
+            "tsParam": datetime.datetime.fromtimestamp(1000, tz=datetime.timezone.utc),
+            "dateParam": datetime.date(2025, 1, 16),
+            "byteArrayParam": [b"foo", b"bar", None],
+            "stringArrayParam": ["foo", "bar", None],
+            "intArrayParam": [1, None, 2],
+            "float32ArrayParam": [1.2, None, 1.3],
+            "float64ArrayParam": [1.4, None, 1.5],
+            "boolArrayParam": [None, False, True],
+            "tsArrayParam": [
+                datetime.datetime.fromtimestamp(1000, tz=datetime.timezone.utc),
+                datetime.datetime.fromtimestamp(2000, tz=datetime.timezone.utc),
+                None,
+            ],
+            "dateArrayParam": [
+                datetime.date(2025, 1, 16),
+                datetime.date(2025, 1, 17),
+                None,
+            ],
+        }
+        param_types = {
+            "float32Param": SqlType.Float32(),
+            "float64Param": SqlType.Float64(),
+            "byteArrayParam": SqlType.Array(SqlType.Bytes()),
+            "stringArrayParam": SqlType.Array(SqlType.String()),
+            "intArrayParam": SqlType.Array(SqlType.Int64()),
+            "float32ArrayParam": SqlType.Array(SqlType.Float32()),
+            "float64ArrayParam": SqlType.Array(SqlType.Float64()),
+            "boolArrayParam": SqlType.Array(SqlType.Bool()),
+            "tsArrayParam": SqlType.Array(SqlType.Timestamp()),
+            "dateArrayParam": SqlType.Array(SqlType.Date()),
+        }
+        result = await client.execute_query(
+            query, instance_id, parameters=parameters, parameter_types=param_types
+        )
+        rows = [r async for r in result]
+        assert len(rows) == 1
+        row = rows[0]
+        assert row["strCol"] == parameters["stringParam"]
+        assert row["bytesCol"] == parameters["bytesParam"]
+        assert row["intCol"] == parameters["int64Param"]
+        assert row["float32Col"] == pytest.approx(parameters["float32Param"])
+        assert row["float64Col"] == pytest.approx(parameters["float64Param"])
+        assert row["boolCol"] == parameters["boolParam"]
+        assert row["tsCol"] == parameters["tsParam"]
+        assert row["dateCol"] == date_pb2.Date(year=2025, month=1, day=16)
+        assert row["stringArrayCol"] == parameters["stringArrayParam"]
+        assert row["byteArrayCol"] == parameters["byteArrayParam"]
+        assert row["intArrayCol"] == parameters["intArrayParam"]
+        assert row["float32ArrayCol"] == pytest.approx(parameters["float32ArrayParam"])
+        assert row["float64ArrayCol"] == pytest.approx(parameters["float64ArrayParam"])
+        assert row["boolArrayCol"] == parameters["boolArrayParam"]
+        assert row["tsArrayCol"] == parameters["tsArrayParam"]
+        assert row["dateArrayCol"] == [
+            date_pb2.Date(year=2025, month=1, day=16),
+            date_pb2.Date(year=2025, month=1, day=17),
+            None,
+        ]

tests/system/data/test_system_autogen.py

@@ -16,12 +16,15 @@
 # This file is automatically generated by CrossSync. Do not edit manually.
 
 import pytest
+import datetime
 import uuid
 import os
 from google.api_core import retry
 from google.api_core.exceptions import ClientError
+from google.cloud.bigtable.data.execute_query.metadata import SqlType
 from google.cloud.bigtable.data.read_modify_write_rules import _MAX_INCREMENT_VALUE
 from google.cloud.environment_vars import BIGTABLE_EMULATOR
+from google.type import date_pb2
 from google.cloud.bigtable.data._cross_sync import CrossSync
 from . import TEST_FAMILY, TEST_FAMILY_2
 
@@ -838,3 +841,74 @@ def test_execute_query_simple(self, client, table_id, instance_id):
         row = rows[0]
         assert row["a"] == 1
         assert row["b"] == "foo"
+
+    @pytest.mark.usefixtures("client")
+    @CrossSync._Sync_Impl.Retry(
+        predicate=retry.if_exception_type(ClientError), initial=1, maximum=5
+    )
+    def test_execute_query_params(self, client, table_id, instance_id):
+        query = "SELECT @stringParam AS strCol, @bytesParam as bytesCol, @int64Param AS intCol, @float32Param AS float32Col, @float64Param AS float64Col, @boolParam AS boolCol, @tsParam AS tsCol, @dateParam AS dateCol, @byteArrayParam AS byteArrayCol, @stringArrayParam AS stringArrayCol, @intArrayParam AS intArrayCol, @float32ArrayParam AS float32ArrayCol, @float64ArrayParam AS float64ArrayCol, @boolArrayParam AS boolArrayCol, @tsArrayParam AS tsArrayCol, @dateArrayParam AS dateArrayCol"
+        parameters = {
+            "stringParam": "foo",
+            "bytesParam": b"bar",
+            "int64Param": 12,
+            "float32Param": 1.1,
+            "float64Param": 1.2,
+            "boolParam": True,
+            "tsParam": datetime.datetime.fromtimestamp(1000, tz=datetime.timezone.utc),
+            "dateParam": datetime.date(2025, 1, 16),
+            "byteArrayParam": [b"foo", b"bar", None],
+            "stringArrayParam": ["foo", "bar", None],
+            "intArrayParam": [1, None, 2],
+            "float32ArrayParam": [1.2, None, 1.3],
+            "float64ArrayParam": [1.4, None, 1.5],
+            "boolArrayParam": [None, False, True],
+            "tsArrayParam": [
+                datetime.datetime.fromtimestamp(1000, tz=datetime.timezone.utc),
+                datetime.datetime.fromtimestamp(2000, tz=datetime.timezone.utc),
+                None,
+            ],
+            "dateArrayParam": [
+                datetime.date(2025, 1, 16),
+                datetime.date(2025, 1, 17),
+                None,
+            ],
+        }
+        param_types = {
+            "float32Param": SqlType.Float32(),
+            "float64Param": SqlType.Float64(),
+            "byteArrayParam": SqlType.Array(SqlType.Bytes()),
+            "stringArrayParam": SqlType.Array(SqlType.String()),
+            "intArrayParam": SqlType.Array(SqlType.Int64()),
+            "float32ArrayParam": SqlType.Array(SqlType.Float32()),
+            "float64ArrayParam": SqlType.Array(SqlType.Float64()),
+            "boolArrayParam": SqlType.Array(SqlType.Bool()),
+            "tsArrayParam": SqlType.Array(SqlType.Timestamp()),
+            "dateArrayParam": SqlType.Array(SqlType.Date()),
+        }
+        result = client.execute_query(
+            query, instance_id, parameters=parameters, parameter_types=param_types
+        )
+        rows = [r for r in result]
+        assert len(rows) == 1
+        row = rows[0]
+        assert row["strCol"] == parameters["stringParam"]
+        assert row["bytesCol"] == parameters["bytesParam"]
+        assert row["intCol"] == parameters["int64Param"]
+        assert row["float32Col"] == pytest.approx(parameters["float32Param"])
+        assert row["float64Col"] == pytest.approx(parameters["float64Param"])
+        assert row["boolCol"] == parameters["boolParam"]
+        assert row["tsCol"] == parameters["tsParam"]
+        assert row["dateCol"] == date_pb2.Date(year=2025, month=1, day=16)
+        assert row["stringArrayCol"] == parameters["stringArrayParam"]
+        assert row["byteArrayCol"] == parameters["byteArrayParam"]
+        assert row["intArrayCol"] == parameters["intArrayParam"]
+        assert row["float32ArrayCol"] == pytest.approx(parameters["float32ArrayParam"])
+        assert row["float64ArrayCol"] == pytest.approx(parameters["float64ArrayParam"])
+        assert row["boolArrayCol"] == parameters["boolArrayParam"]
+        assert row["tsArrayCol"] == parameters["tsArrayParam"]
+        assert row["dateArrayCol"] == [
+            date_pb2.Date(year=2025, month=1, day=16),
+            date_pb2.Date(year=2025, month=1, day=17),
+            None,
+        ]