85 lines
3.0 KiB
Python
85 lines
3.0 KiB
Python
import random
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import re
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import string
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from difflib import SequenceMatcher
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import spotipy
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from lingua_franca.parse import fuzzy_match
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from spotipy import SpotifyOAuth
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from jarvis.utils import config_utils
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scope = "user-read-playback-state, user-modify-playback-state, user-read-currently-playing"
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# TODO: Investigate the open_browser and automatic auth renewing without user interaction
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sp = spotipy.Spotify(auth_manager=SpotifyOAuth(scope=scope,
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client_id=config_utils.get_in_config("SPOTIFY_CLIENT_ID"),
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client_secret=config_utils.get_in_config("SPOTIFY_CLIENT_SECRET"),
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redirect_uri='http://localhost:8888/callback/',
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open_browser=False))
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def get_spotify():
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return sp
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def query_song(song=None, artist=None):
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if song is not None and artist is not None:
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query = '*{}* artist:{}'.format(song, artist)
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elif song is None and artist is not None:
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query = "artist:" + artist
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elif song is not None and artist is None:
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query = song
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else:
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song = "Back In Black AC/DC" # proof that jarvis has a heart :)
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query = song
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data = get_spotify().search(q=query, limit=6, type='track')['tracks']['items']
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if data and len(data) > 0:
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if song is not None:
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tracks = [(best_confidence(d['name'], song), d) for d in data]
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else:
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tracks = [(best_confidence(d['name'], 'None'), d) for d in data]
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tracks.sort(key=lambda x: x[0])
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tracks.reverse() # Place best matches first
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# Find pretty similar tracks to the best match
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tracks = [t for t in tracks if t[0] > tracks[0][0] - 0.1]
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# Sort remaining tracks by popularity
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tracks.sort(key=lambda x: x[1]['popularity'])
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# print([(t[0], t[1]['name'], t[1]['artists'][0]['name']) for t in tracks]) # DEBUG
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data = [tracks[-1][1]]
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# return tracks[-1][0], {'data': data, 'name': None, 'type': 'track'}
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return data
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def is_music_playing():
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return sp.current_user_playing_track()['is_playing']
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def best_confidence(title, query):
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"""Find best match for a title against a query.
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Some titles include ( Remastered 2016 ) and similar info. This method
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will test the raw title and a version that has been parsed to remove
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such information.
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Arguments:
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title: title name from spotify search
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query: query from user
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Returns:
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(float) best condidence
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"""
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if query == 'None':
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return SequenceMatcher(None, random_string_generator(5), random_string_generator(5)).ratio()
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best = title.lower()
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best_stripped = re.sub(r'(\(.+\)|-.+)$', '', best).strip()
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return max(fuzzy_match(best, query), fuzzy_match(best_stripped, query))
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def random_string_generator(str_size):
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return ''.join(random.choice(string.ascii_letters + string.punctuation) for x in range(str_size))
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