CODEWITHSUNDEEP
pythonmultiprocessingspotify
Game Code
Game Code

Reputation: 11

How to speed up Spotify API calls?

I am retrieving track data from spotify api for a total of 10 tracks, but it takes around 2-3 seconds to run. Is there any way to speed it up by using some python libraries like multiprocessing or something else.

track_url = []
track_name = []
album_image = []
for i in range(len(tracks_recommend)):
    track_id = tracks_recommend.at[i, 'id']
    # call to spotify api
    res = spotify.track(track_id=track_id)
    track_url.append(res['external_urls'])
    track_name.append(res['name'])
    album_image.append(res['album']['images'][0]['url'])

Upvotes: 0

Views: 287

Answers (2)

Zorgoth
Zorgoth

Reputation: 671

Depends on whether Spotify tracks you and limits you to one request. If they don't, this would be what you could start with:

    def process_track(track_id)
        # call to spotify api
        res = spotify.track(track_id=track_id)
        return (res['external_urls'], res['name'], res['album']['images'][0]['url'])

    with Pool(4) as p: # replace 4 with whatever number you want
        track_ids = [tracks_recommend.at[i, 'id'] for i in range(len(tracks_recommend))]
        output = p.map(process_track, track_ids)
    
    track_url, track_name, album_image = zip(*output)

This won't help you with latency, but it might increase throughput.

Upvotes: 0

Raymond Hettinger
Raymond Hettinger

Reputation: 226486

Is there any way to speed it up by using some python libraries like multiprocessing

Yes, multiprocess works great running API requests in parallel. This will get you started:

from multiprocessing.pool import ThreadPool as Pool

def recommend(track_id):
    return spotify.track(track_id=track_id)

track_ids = [tracks_recommend.at[i, 'id']
             for i in range(len(tracks_recommend))]

with Pool(5) as pool:
   for res in pool.map(recommend, track_ids):
      ...

Upvotes: 1

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