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fix: load_table_from_dataframe for higher scale decimal #1703

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Dec 18, 2023
Merged

fix: load_table_from_dataframe for higher scale decimal #1703

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969b13b
fix: load_table_from_dataframe for higher scale decimal
Gaurang033 Oct 25, 2023
47f5096
Update test_client.py
Linchin Dec 1, 2023
a662beb
fix test_load_table_from_dataframe_w_higher_scale_decimal128_datatype
Gaurang033 Dec 14, 2023
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4 changes: 3 additions & 1 deletion google/cloud/bigquery/_pandas_helpers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@
import warnings
from typing import Any, Union


from google.cloud.bigquery import _pyarrow_helpers
from google.cloud.bigquery import _versions_helpers
from google.cloud.bigquery import schema
Expand Down Expand Up @@ -485,7 +486,6 @@ def augment_schema(dataframe, current_bq_schema):
# pytype: disable=attribute-error
augmented_schema = []
unknown_type_fields = []

for field in current_bq_schema:
if field.field_type is not None:
augmented_schema.append(field)
Expand Down Expand Up @@ -515,6 +515,8 @@ def augment_schema(dataframe, current_bq_schema):
else:
detected_mode = field.mode
detected_type = _pyarrow_helpers.arrow_scalar_ids_to_bq(arrow_table.type.id)
if detected_type == "NUMERIC" and arrow_table.type.scale > 9:
detected_type = "BIGNUMERIC"

if detected_type is None:
unknown_type_fields.append(field)
Expand Down
43 changes: 43 additions & 0 deletions tests/unit/test_client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8891,6 +8891,49 @@ def test_load_table_from_dataframe_with_csv_source_format(self):
sent_config = load_table_from_file.mock_calls[0][2]["job_config"]
assert sent_config.source_format == job.SourceFormat.CSV

@unittest.skipIf(pandas is None, "Requires `pandas`")
@unittest.skipIf(pyarrow is None, "Requires `pyarrow`")
def test_load_table_from_dataframe_w_higher_scale_decimal128_datatype(self):
from google.cloud.bigquery.client import _DEFAULT_NUM_RETRIES
from google.cloud.bigquery import job
from google.cloud.bigquery.schema import SchemaField
from decimal import Decimal

client = self._make_client()
dataframe = pandas.DataFrame({"x": [Decimal("0.1234567891")]})
load_patch = mock.patch(
"google.cloud.bigquery.client.Client.load_table_from_file", autospec=True
)

get_table_patch = mock.patch(
"google.cloud.bigquery.client.Client.get_table", autospec=True
)
with load_patch as load_table_from_file, get_table_patch:
client.load_table_from_dataframe(
dataframe, self.TABLE_REF, location=self.LOCATION
)

load_table_from_file.assert_called_once_with(
client,
mock.ANY,
self.TABLE_REF,
num_retries=_DEFAULT_NUM_RETRIES,
rewind=True,
size=mock.ANY,
job_id=mock.ANY,
job_id_prefix=None,
location=self.LOCATION,
project=None,
job_config=mock.ANY,
timeout=DEFAULT_TIMEOUT,
)

sent_config = load_table_from_file.mock_calls[0][2]["job_config"]
assert sent_config.source_format == job.SourceFormat.PARQUET
assert tuple(sent_config.schema) == (
SchemaField("x", "BIGNUMERIC", "NULLABLE", None),
)

def test_load_table_from_json_basic_use(self):
from google.cloud.bigquery.client import _DEFAULT_NUM_RETRIES
from google.cloud.bigquery import job
Expand Down