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4 changes: 2 additions & 2 deletions bigframes/core/logging/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.

from bigframes.core.logging import log_adapter
from bigframes.core.logging import data_types, log_adapter

__all__ = ["log_adapter"]
__all__ = ["log_adapter", "data_types"]
65 changes: 65 additions & 0 deletions bigframes/core/logging/data_types.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,65 @@
# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# 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.


from bigframes import dtypes


def _add_data_type(existing_types: int, curr_type: dtypes.Dtype) -> int:
return existing_types | _get_dtype_mask(curr_type)


def _get_dtype_mask(dtype: dtypes.Dtype) -> int:
if dtype == dtypes.INT_DTYPE:
return 1 << 1
if dtype == dtypes.FLOAT_DTYPE:
return 1 << 2
if dtype == dtypes.BOOL_DTYPE:
return 1 << 3
if dtype == dtypes.STRING_DTYPE:
return 1 << 4
if dtype == dtypes.BYTES_DTYPE:
return 1 << 5
if dtype == dtypes.DATE_DTYPE:
return 1 << 6
if dtype == dtypes.TIME_DTYPE:
return 1 << 7
if dtype == dtypes.DATETIME_DTYPE:
return 1 << 8
if dtype == dtypes.TIMESTAMP_DTYPE:
return 1 << 9
if dtype == dtypes.TIMEDELTA_DTYPE:
return 1 << 10
if dtype == dtypes.NUMERIC_DTYPE:
return 1 << 11
if dtype == dtypes.BIGNUMERIC_DTYPE:
return 1 << 12
if dtype == dtypes.GEO_DTYPE:
return 1 << 13
if dtype == dtypes.JSON_DTYPE:
return 1 << 14

if dtypes.is_struct_like(dtype):
mask = 1 << 15
if dtype == dtypes.OBJ_REF_DTYPE:
# obj_ref is a special struct type for multi-modal data.
# It should be double counted as both "struct" and its own type.
mask = mask | (1 << 17)
return mask

if dtypes.is_array_like(dtype):
return 1 << 16

# If an unknown datat type is present, mark it with the least significant bit.
return 1 << 0
69 changes: 69 additions & 0 deletions tests/unit/core/logging/test_data_types.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,69 @@
# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# 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 pandas as pd
import pyarrow as pa
import pytest

from bigframes import dtypes
from bigframes.core.logging import data_types

UNKNOWN_TYPE = pd.ArrowDtype(pa.time64("ns"))

PA_STRUCT_TYPE = pa.struct([("city", pa.string()), ("pop", pa.int64())])

PA_LIST_TYPE = pa.list_(pa.int64())


@pytest.mark.parametrize(
("dtype", "expected_mask"),
[
(UNKNOWN_TYPE, 1 << 0),
(dtypes.INT_DTYPE, 1 << 1),
(dtypes.FLOAT_DTYPE, 1 << 2),
(dtypes.BOOL_DTYPE, 1 << 3),
(dtypes.STRING_DTYPE, 1 << 4),
(dtypes.BYTES_DTYPE, 1 << 5),
(dtypes.DATE_DTYPE, 1 << 6),
(dtypes.TIME_DTYPE, 1 << 7),
(dtypes.DATETIME_DTYPE, 1 << 8),
(dtypes.TIMESTAMP_DTYPE, 1 << 9),
(dtypes.TIMEDELTA_DTYPE, 1 << 10),
(dtypes.NUMERIC_DTYPE, 1 << 11),
(dtypes.BIGNUMERIC_DTYPE, 1 << 12),
(dtypes.GEO_DTYPE, 1 << 13),
(dtypes.JSON_DTYPE, 1 << 14),
(pd.ArrowDtype(PA_STRUCT_TYPE), 1 << 15),
(pd.ArrowDtype(PA_LIST_TYPE), 1 << 16),
(dtypes.OBJ_REF_DTYPE, (1 << 15) | (1 << 17)),
],
)
def test_get_dtype_mask(dtype, expected_mask):
assert data_types._get_dtype_mask(dtype) == expected_mask


def test_add_data_type__type_overlap_no_op():
curr_type = dtypes.STRING_DTYPE
existing_types = data_types._get_dtype_mask(curr_type)

assert data_types._add_data_type(existing_types, curr_type) == existing_types


def test_add_data_type__new_type_updated():
curr_type = dtypes.STRING_DTYPE
existing_types = data_types._get_dtype_mask(dtypes.INT_DTYPE)

assert data_types._add_data_type(
existing_types, curr_type
) == existing_types | data_types._get_dtype_mask(curr_type)
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