Data-science

ETL pipeline + Recommender API

Please note: A toggle to enable/disable the radar chart may arrive soon.

Usage (Production)

The Flask app returns 10 recommended songs based on one song's features.

Send a POST request to https://spotify-flow-ds.herokuapp.com/input passing in a JSON object of this structure:

{
    "track_id": "track id",
    "acousticness": (float),
    "danceability": (float),
    "duration_ms": (int),
    "energy": (float),
    "instrumentalness": (float),
    "key": (int),
    "liveness": (float),
    "loudness": (float),
    "mode": (int),
    "speechiness": (float),
    "tempo": (float),
    "time_signature": (int),
    "valence": (float),
    "popularity": (int)
}

If configured properly, returns:

{
    "radar_chart": "radar chart of inputted song^",
    "recommended_song_ids": [array of 10 song IDs]
}

^ A base64-encoded image. The radar chart uses the following features:

• danceability
• energy
• instrumentalness
• speechiness
• valence

Usage (Development)

Clone the repo, then run the following terminal commands within the repo directory.

pipenv install
pipenv shell
FLASK_APP=SPOTIFY-FLOW:APP flask run

To test the endpoint, create and run the following python code, replacing example JSON values accordingly.

import requests
import json
localURL = 'http://127.0.0.1:5000/input'
herokuURL = 'https://spotify-flow-ds.herokuapp.com/input'
dictToSend = {
    "track_id": "2RM4jf1Xa9zPgMGRDiht8O",
    "acousticness": 0.00582,
    "danceability": 0.743,
    "duration_ms": 238373,
    "energy": 0.339,
    "instrumentalness": 0,
    "key": 1,
    "liveness": 0.0812,
    "loudness": -7.678,
    "mode": 1,
    "speechiness": 0.409,
    "tempo": 203.927,
    "time_signature": 4,
    "valence": 0.118,
    "popularity": 15
}
res = requests.post(localURL, data=json.dumps(dictToSend))
print ('RESPONSE FROM SERVER\n' + res.text)