98 lines
No EOL
3.4 KiB
Python
98 lines
No EOL
3.4 KiB
Python
from DataBase import *
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from SpotifyWebAPI import find_song, update_access_token
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from fuzzywuzzy import fuzz
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def spotify_pattern_generator():
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update_access_token()
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local_library = get_data("local_library")
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spotify_library = get_data("tracks")
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def find_local_songs_on_spotify(local_lib):
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from tqdm import tqdm
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total = len(local_library)
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found_tracks_map = {}
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with tqdm(total=total, desc='Searching local songs on spotify') as pbar:
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for track_id, track in local_lib.items():
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search_pattern = f"{track['name']} {track['artist']} {track['album']}"
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found_tracks = find_song(search_pattern)
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found_tracks_map[track_id] = found_tracks[0:1]
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pbar.update(1)
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return found_tracks_map
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spotify_found_tracks = find_local_songs_on_spotify(local_library)
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spotify_user_track = {track['track']['id']: {"local_mappings": []} for track in spotify_library}
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spotify_pattern = {}
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for local_id, found_items in spotify_found_tracks.items():
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spotify_pattern[local_id] = {"score": 0.0, "items": []}
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if not len(found_items):
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continue
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for found_item in found_items:
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spotify_track_id = found_item['id']
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if spotify_track_id in spotify_user_track:
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spotify_pattern[local_id]['items'].append(spotify_track_id)
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spotify_user_track[spotify_track_id]['local_mappings'].append(local_id)
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for spotify_id, track_local_mappings in spotify_user_track.items():
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score = len(track_local_mappings['local_mappings'])
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for local_id in track_local_mappings['local_mappings']:
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spotify_pattern[local_id]['score'] = 1 / score
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save_data(spotify_pattern, "link_pattern_spotify")
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def fuzzy_pattern_generator():
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local_library = get_data("local_library")
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track_descriptions = get_data("tracks")
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def get_matched(src_pattern, patterns):
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result = {}
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for target_pattern in patterns:
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similarity_score = fuzz.token_set_ratio(src_pattern, target_pattern)
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result[target_pattern] = similarity_score / 100
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sorted_results = sorted(result.items(), key=lambda item: item[1], reverse=True)
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return sorted_results
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def resolve_tracks(s_patterns, t_patterns):
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from tqdm import tqdm
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pattern_map = {}
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total = len(s_patterns)
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with tqdm(total=total, desc='Progress') as pbar:
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for s_pattern in s_patterns:
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res = get_matched(s_pattern, t_patterns)
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matched = {"score": 0, "items": []}
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if len(res):
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matched['items'] = res[0:min(len(res), 4)]
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matched['score'] = res[0][1]
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pattern_map[s_pattern] = matched
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pbar.update(1)
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return pattern_map
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source_patterns = []
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for track in track_descriptions:
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artists = get_artists_str(track['track']['artists'])
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pattern = f"{track['track']['name']} {artists}"
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source_patterns.append(pattern)
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target_patterns = [local['path'] for _, local in local_library.items()]
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fuzzy_pattern = resolve_tracks(source_patterns, target_patterns)
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save_data(fuzzy_pattern, "link_pattern_fuzzy")
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def run_pattern_generators():
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#fuzzy_pattern_generator()
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spotify_pattern_generator()
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if __name__ == "__main__":
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run_pattern_generators() |