from DataBase import *
from SpotifyWebAPI import find_song, update_access_token

from fuzzywuzzy import fuzz


def spotify_pattern_generator():
    update_access_token()

    local_library = get_data("local_library")
    spotify_library = get_data("tracks")

    def find_local_songs_on_spotify(local_lib):
        from tqdm import tqdm
        total = len(local_library)
        found_tracks_map = {}
        with tqdm(total=total, desc='Searching local songs on spotify') as pbar:
            for track_id, track in local_lib.items():
                search_pattern = f"{track['name']} {track['artist']} {track['album']}"
                found_tracks = find_song(search_pattern)
                found_tracks_map[track_id] = found_tracks[0:1]
                pbar.update(1)
        return found_tracks_map

    spotify_found_tracks = find_local_songs_on_spotify(local_library)
    spotify_user_track = {track['track']['id']: {"local_mappings": []} for track in spotify_library}

    spotify_pattern = {}
    for local_id, found_items in spotify_found_tracks.items():
        spotify_pattern[local_id] = {"score": 0.0, "items": []}

        if not len(found_items):
            continue

        for found_item in found_items:
            spotify_track_id = found_item['id']
            if spotify_track_id in spotify_user_track:
                spotify_pattern[local_id]['items'].append(spotify_track_id)
                spotify_user_track[spotify_track_id]['local_mappings'].append(local_id)

    for spotify_id, track_local_mappings in spotify_user_track.items():
        score = len(track_local_mappings['local_mappings'])
        for local_id in track_local_mappings['local_mappings']:
            spotify_pattern[local_id]['score'] = 1 / score

    save_data(spotify_pattern, "link_pattern_spotify")


def fuzzy_pattern_generator():
    local_library = get_data("local_library")
    track_descriptions = get_data("tracks")

    def get_matched(src_pattern, patterns):
        result = {}
        for target_pattern in patterns:
            similarity_score = fuzz.token_set_ratio(src_pattern, target_pattern)
            result[target_pattern] = similarity_score / 100

        sorted_results = sorted(result.items(), key=lambda item: item[1], reverse=True)
        return sorted_results

    def resolve_tracks(s_patterns, t_patterns):
        from tqdm import tqdm

        pattern_map = {}

        total = len(s_patterns)
        with tqdm(total=total, desc='Progress') as pbar:
            for s_pattern in s_patterns:
                res = get_matched(s_pattern, t_patterns)
                matched = {"score": 0, "items": []}
                if len(res):
                    matched['items'] = res[0:min(len(res), 4)]
                    matched['score'] = res[0][1]
                pattern_map[s_pattern] = matched
                pbar.update(1)

        return pattern_map

    source_patterns = []
    for track in track_descriptions:
        artists = get_artists_str(track['track']['artists'])
        pattern = f"{track['track']['name']} {artists}"
        source_patterns.append(pattern)

    target_patterns = [local['path'] for _, local in local_library.items()]

    fuzzy_pattern = resolve_tracks(source_patterns, target_patterns)
    save_data(fuzzy_pattern, "link_pattern_fuzzy")


def run_pattern_generators():
    #fuzzy_pattern_generator()
    spotify_pattern_generator()


if __name__ == "__main__":
    run_pattern_generators()