import logging

import pandas
from jsonbender import S as GetField
from parameterized import parameterized
from ui_automation_framework.utils import logger as cl

import app.src.tests.decomission.api_init as api_init
from app.src.tests.decomission.compare_helper import format_color, generate_provider, get_field_with_diff_the_same, merge_arrays, transform_json

API = api_init.APIOverride()
log = cl.Logger(logging.DEBUG)

delphi_to_delphi_curr_keys = {
    # playlist object
    "playlist_id": GetField("playlist_id"),
    "name": GetField("playlist", "name"),
    "track_count": GetField("playlist", "num_tracks"),
    "is_personalized": GetField("playlist", "is_personalised"),
    "country_code": GetField("playlist", "country_code"),
}

delphi_limit = 10000
delphi_current_playlist = "/v3/public/track-positions/playlists?dsp=spotify&isrc={0}&limit={1}&include=playlists"
delphi_prev_playlist = "/v3/public/track-positions/previous/playlists?isrc={0}&dsp=spotify&include=playlists&limit={1}"


@parameterized.expand([("USRC12204647"), ("USSM12200612"), ("USSM12209777"), ("USJI10800160"), ("GBARL1300107"), ("GBARL1300522"), ("USSM12300722"), ("USSM10804556"), ("USSM12210918")])  # as it was  # floawers
def test_current_vs_prev_playlists_spotify(isrc):
    delphi_current_response = API.get_delphi_response(delphi_current_playlist.format(isrc, delphi_limit))
    delphi_current_transformed_response = transform_json(delphi_to_delphi_curr_keys, delphi_current_response["items"])

    delphi_prev_response = API.get_delphi_response(delphi_prev_playlist.format(isrc, delphi_limit))
    delphi_prev_transformed_response = transform_json(delphi_to_delphi_curr_keys, delphi_prev_response["items"])

    aggregated_matrix = merge_arrays(delphi_current_transformed_response, delphi_prev_transformed_response, "playlist_id")
    aggregated_matrix_new = list(aggregated_matrix)

    for item in aggregated_matrix:
        if not aggregated_matrix[item][0] or not aggregated_matrix[item][1]:
            aggregated_matrix_new.pop(aggregated_matrix_new.index(item))

    index_for_all_fields = list(range(1, len(generate_provider(aggregated_matrix_new)) + 1))

    subset_to_mark = range(3, len(aggregated_matrix_new) * 5, 5)

    pandas.DataFrame(
        {"provider": generate_provider(aggregated_matrix_new), "playlist_id": get_field_with_diff_the_same("playlist_id", aggregated_matrix_new)},
        index=index_for_all_fields,
    ).style.apply(
        format_color, subset=(subset_to_mark, slice(None))
    ).to_excel(f"decomission/spotify_track_current_playlists/{isrc}_spotify_cur_vs_prev_playlist_total_apollo.xlsx")