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test_reader_dataframe_v1beta1.py
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test_reader_dataframe_v1beta1.py
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# -*- coding: utf-8 -*-
#
# Copyright 2018 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
#
# https://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.
"""System tests for reading rows with pandas connector."""
import numpy
import pyarrow.types
import pytest
from google.cloud import bigquery_storage_v1beta1
def test_read_rows_to_arrow(client, project_id):
table_ref = bigquery_storage_v1beta1.types.TableReference()
table_ref.project_id = "bigquery-public-data"
table_ref.dataset_id = "new_york_citibike"
table_ref.table_id = "citibike_stations"
read_options = bigquery_storage_v1beta1.types.TableReadOptions()
read_options.selected_fields.append("station_id")
read_options.selected_fields.append("latitude")
read_options.selected_fields.append("longitude")
read_options.selected_fields.append("name")
session = client.create_read_session(
table_ref,
"projects/{}".format(project_id),
format_=bigquery_storage_v1beta1.enums.DataFormat.ARROW,
read_options=read_options,
requested_streams=1,
)
stream_pos = bigquery_storage_v1beta1.types.StreamPosition(
stream=session.streams[0]
)
tbl = client.read_rows(stream_pos).to_arrow(session)
assert tbl.num_columns == 4
schema = tbl.schema
# Use field with a name specifier as there may be ordering differences
# when selected_fields is used
assert pyarrow.types.is_int64(schema.field("station_id").type)
assert pyarrow.types.is_float64(schema.field("latitude").type)
assert pyarrow.types.is_float64(schema.field("longitude").type)
assert pyarrow.types.is_string(schema.field("name").type)
@pytest.mark.parametrize(
"data_format,expected_schema_type",
(
(bigquery_storage_v1beta1.enums.DataFormat.AVRO, "avro_schema"),
(bigquery_storage_v1beta1.enums.DataFormat.ARROW, "arrow_schema"),
),
)
def test_read_rows_to_dataframe(client, project_id, data_format, expected_schema_type):
table_ref = bigquery_storage_v1beta1.types.TableReference()
table_ref.project_id = "bigquery-public-data"
table_ref.dataset_id = "new_york_citibike"
table_ref.table_id = "citibike_stations"
session = client.create_read_session(
table_ref,
"projects/{}".format(project_id),
format_=data_format,
requested_streams=1,
)
schema_type = session.WhichOneof("schema")
assert schema_type == expected_schema_type
stream_pos = bigquery_storage_v1beta1.types.StreamPosition(
stream=session.streams[0]
)
frame = client.read_rows(stream_pos).to_dataframe(
session, dtypes={"latitude": numpy.float16}
)
# Station ID is a required field (no nulls), so the datatype should always
# be integer.
assert frame.station_id.dtype.name == "int64"
assert frame.latitude.dtype.name == "float16"
assert frame.longitude.dtype.name == "float64"
assert frame["name"].str.startswith("Central Park").any()