text: """
  Copyright 2018 Goldman Sachs.
  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 datetime as dt
  from unittest import mock
  
  import pandas as pd
  import pytest
  
  from gs_quant.api.gs.data import GsDataApi
  from gs_quant.data import Dataset
  from gs_quant.data.utils import construct_dataframe_with_types
  
  test_types = {
      'date': 'date',
      'assetId': 'string',
      'askPrice': 'number',
      'adjustedAskPrice': 'number',
      'bidPrice': 'number',
      'adjustedBidPrice': 'number',
      'tradePrice': 'number',
      'adjustedTradePrice': 'number',
      'openPrice': 'number',
      'adjustedOpenPrice': 'number',
      'highPrice': 'number',
      'lowPrice': 'number',
      'adjustedHighPrice': 'number',
      'adjustedLowPrice': 'number',
      'updateTime': 'date-time'
  }
  test_data = [
      {
          'date': dt.date(2019, 1, 2),
          'assetId': 'MA4B66MW5E27U8P32SB',
          'askPrice': 2529,
          'adjustedAskPrice': 2529,
          'bidPrice': 2442.55,
          'adjustedBidPrice': 2442.55,
          'tradePrice': 2510.03,
          'adjustedTradePrice': 2510.03,
          'openPrice': 2476.96,
          'adjustedOpenPrice': 2476.96,
          'highPrice': 2519.49,
          'lowPrice': 2467.47,
          'adjustedHighPrice': 2519.49,
          'adjustedLowPrice': 2467.47,
          'updateTime': dt.datetime.strptime('2019-01-03T00:53:00Z', '%Y-%m-%dT%H:%M:%SZ')
      },
      {
          'date': dt.date(2019, 1, 3),
          'assetId': 'MA4B66MW5E27U8P32SB',
          'askPrice': 2502.34,
          'adjustedAskPrice': 2502.34,
          'bidPrice': 2418.09,
          'adjustedBidPrice': 2418.09,
          'tradePrice': 2447.89,
          'adjustedTradePrice': 2447.89,
          'openPrice': 2491.92,
          'adjustedOpenPrice': 2491.92,
          'highPrice': 2493.14,
          'lowPrice': 2443.96,
          'adjustedHighPrice': 2493.14,
          'adjustedLowPrice': 2443.96,
          'updateTime': dt.datetime.strptime('2019-01-04T00:14:00Z', '%Y-%m-%dT%H:%M:%SZ')
      },
      {
          'date': dt.date(2019, 1, 4),
          'assetId': 'MA4B66MW5E27U8P32SB',
          'askPrice': 2566.52,
          'adjustedAskPrice': 2566.52,
          'bidPrice': 2487.8,
          'adjustedBidPrice': 2487.8,
          'tradePrice': 2531.94,
          'adjustedTradePrice': 2531.94,
          'openPrice': 2474.33,
          'adjustedOpenPrice': 2474.33,
          'highPrice': 2538.07,
          'lowPrice': 2474.33,
          'adjustedHighPrice': 2538.07,
          'adjustedLowPrice': 2474.33,
          'updateTime': dt.datetime.strptime('2019-01-08T00:31:00Z', '%Y-%m-%dT%H:%M:%SZ')
      },
      {
          'date': dt.date(2019, 1, 7),
          'assetId': 'MA4B66MW5E27U8P32SB',
          'askPrice': 2591.75,
          'adjustedAskPrice': 2591.75,
          'bidPrice': 2509.77,
          'adjustedBidPrice': 2509.77,
          'tradePrice': 2549.69,
          'adjustedTradePrice': 2549.69,
          'openPrice': 2535.61,
          'adjustedOpenPrice': 2535.61,
          'highPrice': 2566.16,
          'lowPrice': 2524.56,
          'adjustedHighPrice': 2566.16,
          'adjustedLowPrice': 2524.56,
          'updateTime': dt.datetime.strptime('2019-01-08T00:31:00Z', '%Y-%m-%dT%H:%M:%SZ')
      },
      {
          'date': dt.date(2019, 1, 8),
          'assetId': 'MA4B66MW5E27U8P32SB',
          'askPrice': 2610.52,
          'adjustedAskPrice': 2610.52,
          'bidPrice': 2531.15,
          'adjustedBidPrice': 2531.15,
          'tradePrice': 2574.41,
          'adjustedTradePrice': 2574.41,
          'openPrice': 2568.11,
          'adjustedOpenPrice': 2568.11,
          'highPrice': 2579.82,
          'lowPrice': 2547.56,
          'adjustedHighPrice': 2579.82,
          'adjustedLowPrice': 2547.56,
          'updateTime': dt.datetime.strptime('2019-01-09T00:50:00Z', '%Y-%m-%dT%H:%M:%SZ')
      },
      {
          'date': dt.date(2019, 1, 9),
          'assetId': 'MA4B66MW5E27U8P32SB',
          'askPrice': 2623.09,
          'adjustedAskPrice': 2623.09,
          'bidPrice': 2537.19,
          'adjustedBidPrice': 2537.19,
          'tradePrice': 2584.96,
          'adjustedTradePrice': 2584.96,
          'openPrice': 2580,
          'adjustedOpenPrice': 2580,
          'highPrice': 2595.32,
          'lowPrice': 2568.89,
          'adjustedHighPrice': 2595.32,
          'adjustedLowPrice': 2568.89,
          'updateTime': dt.datetime.strptime('2019-01-10T00:44:00Z', '%Y-%m-%dT%H:%M:%SZ')
      }
  ]
  
  test_coverage_data = {'results': [{'gsid': 'gsid1'}]}
  
  
  @mock.patch("gs_quant.data.utils.get_types")
  @mock.patch.object(GsDataApi, 'query_data')
  def test_query_data(query_data, get_types):
      query_data.return_value = test_data
      get_types.return_value = test_types
      dataset = Dataset(Dataset.TR.TREOD)
      data = dataset.get_data(dt.date(2019, 1, 2), dt.date(2019, 1, 9), assetId='MA4B66MW5E27U8P32SB')
      assert data.equals(construct_dataframe_with_types(str(Dataset.TR.TREOD), test_data))
  
  
  @mock.patch("gs_quant.data.utils.get_types")
  @mock.patch.object(GsDataApi, 'query_data')
  def test_query_data_types(query_data, get_types):
      query_data.return_value = test_data
      get_types.return_value = test_types
      dataset = Dataset(Dataset.TR.TREOD)
      data = dataset.get_data(dt.date(2019, 1, 2), dt.date(2019, 1, 9), assetId='MA4B66MW5E27U8P32SB')
      assert data.equals(construct_dataframe_with_types(str(Dataset.TR.TREOD), test_data))
  
  
  @mock.patch("gs_quant.data.utils.get_types")
  @mock.patch.object(GsDataApi, 'last_data')
  def test_last_data(query_data, get_types):
      query_data.return_value = [test_data[-1]]
      get_types.return_value = test_types
      dataset = Dataset(Dataset.TR.TREOD)
      data = dataset.get_data_last(dt.date(2019, 1, 9), assetId='MA4B66MW5E27U8P32SB')
      assert data.equals(construct_dataframe_with_types(str(Dataset.TR.TREOD), ([test_data[-1]])))
  
  
  def test_get_data_series(mocker):
      field_value_maps = test_data
      mocker.patch("gs_quant.data.utils.get_types", return_value=test_types)
      mocker.patch.object(GsDataApi, 'query_data', return_value=field_value_maps)
      mocker.patch.object(GsDataApi, 'symbol_dimensions', return_value=('assetId',))
  
      dataset = Dataset(Dataset.TR.TREOD)
      series = dataset.get_data_series('tradePrice', dt.date(2019, 1, 2), dt.date(2019, 1, 9),
                                       assetId='MA4B66MW5E27U8P32SB')
  
      df = pd.DataFrame(test_data)
      index = pd.to_datetime(df.loc[:, 'date'].values)
      expected = pd.Series(index=index, data=df.loc[:, 'tradePrice'].values)
      expected = expected.rename_axis('date')
  
      pd.testing.assert_series_equal(series, expected)
  
  
  @mock.patch("gs_quant.data.utils.get_types")
  @mock.patch.object(GsDataApi, 'get_coverage')
  def test_get_coverage(get_coverage, get_types):
      get_coverage.return_value = test_coverage_data
      get_types.return_value = {'gsid': 'string'}
      data = Dataset(Dataset.TR.TREOD).get_coverage()
  
      assert data.equals(construct_dataframe_with_types(str(Dataset.TR.TREOD), test_coverage_data))
  
  
  if __name__ == "__main__":
      pytest.main(args=["test_dataset.py"])
  