text: # -*- 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.bigquery_storage import types
  
  
  def test_read_v1(client, project_id):
      read_session = types.ReadSession()
      read_session.table = "projects/{}/datasets/{}/tables/{}".format(
          "bigquery-public-data", "new_york_citibike", "citibike_stations"
      )
  
      read_session.read_options.selected_fields.append("station_id")
      read_session.read_options.selected_fields.append("latitude")
      read_session.read_options.selected_fields.append("longitude")
      read_session.read_options.selected_fields.append("name")
      read_session.data_format = types.DataFormat.ARROW
  
      session = client.create_read_session(
          request={
              "parent": "projects/{}".format(project_id),
              "read_session": read_session,
              "max_stream_count": 1,
          }
      )
  
      assert len(session.streams) == 1
  
      streamname = session.streams[0].name
  
      tbl = client.read_rows(streamname, offset=0).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",
      ((types.DataFormat.AVRO, "avro_schema"), (types.DataFormat.ARROW, "arrow_schema")),
  )
  def test_read_rows_to_dataframe(client, project_id, data_format, expected_schema_type):
      read_session = types.ReadSession()
      read_session.table = "projects/{}/datasets/{}/tables/{}".format(
          "bigquery-public-data", "new_york_citibike", "citibike_stations"
      )
      read_session.data_format = data_format
  
      session = client.create_read_session(
          request={
              "parent": "projects/{}".format(project_id),
              "read_session": read_session,
              "max_stream_count": 1,
          }
      )
      schema_type = session._pb.WhichOneof("schema")
      assert schema_type == expected_schema_type
  
      stream = session.streams[0].name
  
      frame = client.read_rows(stream).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()
  