# import logging
# import pytest
#
# from app.api_client import ApiClient
# from ui_automation_framework.utils import AppConfig
# from ui_automation_framework.utils import logger as cl
# import pandas
# import  numpy as np
#
# # dates = [('2017-01-01', '2017-12-31')]
# # isrcs = [('USSM10803202',
# #           'USSM10804556',
# #           'USSM10804557',
# #           'USSM10804727',
# #           'USSM10804728',
# #           'USSM10804752',
# #           'USSM10803760',
# #           'USSM10804754',
# #           'USSM10804755',
# #           'USSM10804756',
# #           'USSM10804757'
# #           )]
# # markets = ["_gl"]
# # upc = 888880932099
#
# dates = [('2018-04-11', '2018-04-11')]
# isrcs = [('USSM10804556', 'USSM10804556')]
# markets = ["us"]
#
# log = cl.Logger(logging.DEBUG)
#
# api_client = ApiClient(AppConfig.get("api_auth_url"),
#                        AppConfig.get("qa_api_url"), 5000)
#
#
# # @pytest.mark.skip(reason="test run on a request with specific data")
# @pytest.mark.parametrize(("start_date", "end_date"), dates)
# @pytest.mark.parametrize("market", markets)
# @pytest.mark.parametrize("isrc", isrcs)
# def test_spotify_saves_and_skips(market,
#                                  start_date,
#                                  end_date, isrc):
#     token_mobile = api_client.authorize()
#
#     delphi_data = \
#         api_client.get_spotify_demographics_delphi_isrcs(isrc, start_date,
#                                                          end_date,
#                                                          market,
#                                                          token_mobile)[
#             'body'][0]
#
#     delphi_values = [delphi_data['saves']['total']/2, delphi_data['skips']/2]
#     sss = api_client.get_spotify_saves_and_skips(isrc, start_date,
#                                                          end_date,
#                                                          market, token_mobile)['body'][0]['data']
#
#     log.info('sss: {}'.format(sss))
#     sss_values = [0,0]
#     for m in sss:
#         if dict(m).get('market') == market:
#             sss_values = [m.get('data')[0], m.get('data')[1]]
#
#     df = pandas.DataFrame(
#         {'delphi': delphi_values, 'dsp-api': sss_values}, index=['save', 'skips']
#     )
#
#     conditions = [
#         df['dsp-api'] > df['delphi'],
#         df['dsp-api'] < df['delphi'],
#         df['dsp-api'] == df['delphi'],
#         df['dsp-api'].isnull()]
#     choices = [((df['dsp-api'] - df['delphi']) / df['dsp-api']) * 100, ((df['delphi'] - df['dsp-api']) / df['dsp-api']) * 100, 'no change', 'no DSP-API data for the field']
#
#     df['% diff'] = np.select(conditions, choices, default='NaN')
#
#     log.info('df: {}'.format(df))
#     df.to_excel(
#         'saves_and_skips_{}_{}_{}_{}.xlsx'.format(isrc, market,
#                                                          start_date,
#                                                          end_date))