# 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
# import time
#
# # dates = [("2017-01-01", "2017-12-31"), ("2018-01-01", "2017-06-29")]
# # isrcs = ["USSM10804556"]
# # markets = ["us"]
#
# dates = [("2017-01-01", "2017-12-31"), ("2018-01-01", "2017-06-29")]
# isrcs = ["GBBKS1500214"]
# markets = ["us"]
# #
# # dates = [("2019-07-01", "2019-12-31"), ("2020-01-01", "2020-09-01")]
# # isrcs = ["QM6P41952433"]
# # markets = ["jp"]
# #
# # dates = [("2019-07-01", "2019-12-31"), ("2020-01-01", "2020-09-01")]
# # isrcs = ["QZES71982312"]
# # markets = [ "au"]
# #
# # dates = [("2019-07-01", "2019-12-31"), ("2020-01-01", "2020-09-01")]
# # isrcs = ["USSM11914962"]
# # markets = ["gl"]
# #
# # dates = [("2019-07-01", "2019-12-31"), ("2020-01-01", "2020-09-01")]
# # isrcs = ["USXDR1900703"]
# # markets = ["ar"]
#
# log = cl.Logger(logging.DEBUG)
# api_client = ApiClient(AppConfig.get("api_auth_url"), AppConfig.get("qa_api_url"), 5000)
# token_mobile = api_client.authorize()
#
# @pytest.mark.parametrize(("start_date", "end_date"), dates)
# @pytest.mark.parametrize("isrc", isrcs)
# @pytest.mark.parametrize("market", markets)
# def test_spotify_streams_sum(isrc, start_date, end_date, market):
#     delphi_data = api_client.get_spotify_demographics_delphi(isrc, start_date, end_date, market, token_mobile)[
#         'body'][0]
#
#     resp_total = [delphi_data['genders']['male'], delphi_data['genders']['neutral'], delphi_data['genders']['unknown'], delphi_data['genders']['female']]
#
#     male_total = 0
#     neutral_total = 0
#     female_total = 0
#     unknown_total = 0
#
#     for k, v in delphi_data['age_bands'].items():
#         if k.startswith('male'):
#             male_total += int(v)
#         elif k.startswith('female'):
#             female_total += int(v)
#         elif k.startswith('unknown'):
#             unknown_total += int(v)
#         elif k.startswith('neutral'):
#             neutral_total += int(v)
#
#     genders_values = [resp_total[0], resp_total[1], resp_total[2], resp_total[3]]
#     age_bands_values = [male_total, neutral_total, unknown_total, female_total]
#
#     df = pandas.DataFrame({'Genders': genders_values, 'Age Bands': age_bands_values}, index=['Male', 'Neutral', 'Unknown', 'Female'])
#     df['diff'] = (df.shift(axis=1)-df).dropna(axis=1).add_prefix('d')
#     df.to_excel('sum_spotify_result_{}_{}_{}_{}.xlsx'.format(isrc, market, start_date, end_date))
#
# @pytest.mark.parametrize(("start_date", "end_date"), dates)
# @pytest.mark.parametrize("isrc", isrcs)
# @pytest.mark.parametrize("market", markets)
# def test_apple_streams_sum(isrc, start_date, end_date, market):
#     delphi_data = api_client.get_apple_demographics_delphi(isrc, start_date, end_date, market, token_mobile)[
#         'body'][0]
#
#     resp_total = [delphi_data['genders']['male'], delphi_data['genders']['neutral'], delphi_data['genders']['unknown'],
#                   delphi_data['genders']['female']]
#
#     male_total = 0
#     neutral_total = 0
#     female_total = 0
#     unknown_total = 0
#
#     for k, v in delphi_data['age_bands'].items():
#         if k.startswith('male'):
#             male_total += int(v)
#         elif k.startswith('female'):
#             female_total += int(v)
#         elif k.startswith('unknown'):
#             unknown_total += int(v)
#         elif k.startswith('neutral'):
#             neutral_total += int(v)
#
#     genders_values = [resp_total[0], resp_total[1], resp_total[2], resp_total[3]]
#     age_bands_values = [male_total, neutral_total, unknown_total, female_total]
#
#     df = pandas.DataFrame({'Genders': genders_values, 'Age Bands': age_bands_values},
#                           index=['Male', 'Neutral', 'Unknown', 'Female'])
#     df['diff'] = (df.shift(axis=1) - df).dropna(axis=1).add_prefix('d')
#     df.to_excel('sum_apple_result_{}_{}_{}_{}.xlsx'.format(isrc, market, start_date, end_date))