Optimizing API Calls to Avoid Rate Limits for Playlist Recommendations

[otya_no_mizu]

Hello everyone,

I am Japanese, so my English may be unnatural. I've been working on a project where I generate playlist recommendations based on specific playlists using the Spotify API. Recently, I've encountered an issue where my calls to `sp.playlist_items(playlist_id)` and `sp.recommendations(seed_tracks=original_tracks, limit=10)` are leading to an increase in rate limit errors. My playlists typically contain about 100-150 tracks, but I only need to select about 50 tracks for generating recommendations.

To address the issue, I've implemented a few optimizations, such as reducing the number of tracks fetched from each playlist to 50 and considering lowering the number of recommended tracks from 10 to 5. Here's a simplified version of my current approach:

def get_playlist_tracks(playlist_id):
    tracks = []
    results = sp.playlist_items(playlist_id)
    for item in results['items']:
        track = item['track']
        tracks.append(track['id'])
    tracks = tracks[:50]
    random.shuffle(tracks)
    return tracks

def create_similar_playlist():
    current_time = datetime.datetime.now().strftime("%Y%m%d")
    new_playlist_name = f"P {current_time}"
    similar_tracks = []

    for playlist in playlists_info:
        original_tracks = get_playlist_tracks(playlist['uri'])
        results = sp.recommendations(seed_tracks=original_tracks, limit=5)  # Considering reducing limit here
        similar_tracks.extend([track['id'] for track in results['tracks']])

I'm reaching out to the community for advice on further optimizing these API calls to avoid hitting rate limits. Specifically, I'm interested in any best practices for efficiently fetching tracks from playlists and generating recommendations without sacrificing the quality of the recommendations.

Has anyone else faced similar challenges? How did you manage to optimize your API usage? Any insights or suggestions would be greatly appreciated.

Thank you in advance for your help!