import os

from app.utils import generate_excel_file, get_friday, round_int

QUERY = 'NMFSongsByDate'
apollo_endpoint = "/gate-api/tracks/nmf/?date={}&distributors=sme%2Ctheorchard%2Cawal"

friday = os.environ.get('FRIDAY', 'last')

def test_nmf_by_date_query(graphql, api_apollo):
    total_fetched = 0
    def get_variables(num):
        return {
            "date": get_friday(friday),
            "limit": 200,
            "offset": num,
            "selectedMarket": ""
        }

    response_insights_first = graphql.fetch_data(QUERY, get_variables(total_fetched))
    insights_items = response_insights_first['newMusicFridayByDate']['entries']['entries']
    insights_total = int(response_insights_first['newMusicFridayByDate']['entries']['total'])
    while total_fetched < insights_total:
        total_fetched +=200
        response_insights_part = graphql.fetch_data(QUERY, get_variables(total_fetched))
        insights_items += response_insights_part['newMusicFridayByDate']['entries']['entries']

    isrc_insights = [item['isrc']['isrc'] for item in insights_items]
    response_apollo_all = api_apollo.get(apollo_endpoint.format(get_friday(friday)))
    response_apollo = response_apollo_all['items']
    total_apollo = response_apollo_all['count']
    isrc_apollo = [item['isrc'] for item in response_apollo]
    common_isrsc = list(set(isrc_apollo) & set(isrc_insights))
    response_apollo = sorted([item for item in response_apollo if item['isrc'] in common_isrsc], key=lambda item: item['isrc'])
    insights_items = sorted([item for item in insights_items if item['isrc']['isrc'] in common_isrsc],
                            key=lambda item: item['isrc']['isrc'])

    songs_insights = [item['trackName'] if item['trackName'] is not None
                      else item['isrc']['globalSoundRecording']['name']
                      for item in insights_items]
    artists_insights = [item['artistName'] if item['artistName'] is not None
                        else ', '.join(sorted(participant['name'] for participant in item['isrc']['globalSoundRecording']['globalParticipants']))
                        for item in insights_items]
    featuring_insights = [item['feature'] for item in insights_items]
    top10rank_insights = [item['top10Rank'] for item in insights_items]
    avg_position_insights = [item['averagePosition'] for item in insights_items]
    countries_insights_str = [', '.join(sorted(f"{placement['market']}-{placement['position']}" for placement in item['placements'])) for item in insights_items]

    songs_apollo = [item['trackName'] for item in response_apollo]
    artists_apollo = [', '.join(sorted(participant['name'] for participant in item['artists'])) for item in response_apollo]
    featuring_apollo = [sum(1 for playlist in item['playlists'] if playlist['position']) for item in response_apollo]
    top10rank_apollo = [item['topTenFeatureCount'] for item in response_apollo]
    avg_position_apollo = [round_int(sum(playlist['position'] for playlist in item['playlists'])/len(item['playlists'])) for item in response_apollo]
    countries_apollo_str = [', '.join(sorted(f"{playlist['countryCode'].upper()}-{playlist['position']}" for playlist in item['playlists'][:10])) for item in response_apollo]

    diff_songs = [0 if a.lower()[:4] == b.lower()[:4] else 1 for a, b in zip(songs_apollo, songs_insights)]
    diff_artists = [0 if a.lower()[:4] == b.lower()[:4] else 1 for a, b in zip(artists_apollo, artists_insights)]
    diff_featuring = [abs(int(b - a)) if a != 0 else None for a, b in zip(featuring_apollo, featuring_insights)]
    diff_top_rank = [abs(int(b - a)) if a != 0 else None for a, b in zip(top10rank_apollo, top10rank_insights)]
    diff_avg_position = [abs(int(b - a)) if a != 0 else None for a, b in zip(avg_position_apollo, avg_position_insights)]
    diff_countries = [0 if a == b else 1 for a, b in zip(countries_apollo_str, countries_insights_str)]
    diff_isrcs_list = list(set(isrc_apollo) - set(isrc_insights))
    diff_isrcs = f'missing isrcs {len(diff_isrcs_list)} : ' + ','.join(diff_isrcs_list)


    data_dict = {
        "song_insights": [diff_isrcs] + songs_insights,
        "songs_apollo": ['']+songs_apollo,
        "change_songs": ['']+diff_songs,

        "artist_insights": ['']+artists_insights,
        "artists_apollo": ['']+artists_apollo,
        "change_artists": ['']+diff_artists,

        "featuring_insights": ['']+featuring_insights,
        "featuring_apollo": ['']+featuring_apollo,
        "change_featuring": ['']+diff_featuring,

        "top 10 rank_insights": ['']+top10rank_insights,
        "top 10 rank apollo": ['']+top10rank_apollo,
        "change_top_10": ['']+diff_top_rank,

        "avg position_insights": ['']+avg_position_insights,
        "avg_position_apollo": ['']+avg_position_apollo,
        "change_avg_position": ['']+diff_avg_position,

        "countries_insights": ['']+countries_insights_str,
        "countries_apollo": ['']+countries_apollo_str,
        "change_countries": ['']+diff_countries,
    }
    generate_excel_file(data_dict, QUERY, [get_friday(friday)])