Spotify Connector

This is a simple library for connecting to the unofficial Spotify podcast API.
It can be used to export data from your dashboard at https://podcasters.spotify.com/home.

Supported Data

• List of episodes
• Starts and streams
• Listeners
• Followers
• Gender
• Age
• Country
• Episode performance

Credentials

Before you can use the library, you must extract your Spotify credentials from the dashboard; they are not exposed through your Spotify settings.

You can use our web extension for that or take a look at the code to see how to do it manually.

You need three values:

• sp_dc: Can be found in the Spotify cookies once you're logged in. It's a long string with around 160 characters.
• sp_key: Can also be found in the Spotify cookies once you're logged in. It's a UUID (36 characters).
• client_id: This is a static value and stays the same for everyone. It is 05a1371ee5194c27860b3ff3ff3979d2. Spotify might change it in the future, so if you run into issues, please check your network requests while logged in to find the new value.

Installation

pip install spotifyconnector

Usage as a library

from spotifyconnector import SpotifyConnector

# Set up the connector
connector = SpotifyConnector(
    base_url="https://generic.wg.spotify.com/podcasters/v0123"
    client_id="05a1371ee5194c27860b3ff3ff3979d2", # login to spotify and monitor connection to get this id
    podcast_id="your_spotify_podcast_id",
    sp_dc="xxxxxxxxxxxxxxxxxx...xxx", # can be found in cookies after logged in (long string)
    sp_key="xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" # can be found in cookies after logged in
)

# Get podcast metadata
connector.metadata()

# Get the list of listeners of a podcast
listeners = connector.listeners()

# Get the aggregated listeners of a podcast (by age, country, gender)
aggregate = connector.aggregate()

# Iterate over all episodes (supports pagination)
for episode in connector.episodes():
    # Do something with episode
    pass

# Get the performance of an episode
performance = connector.performance("episode_id")

# ...

See __main.py__ for all endpoints.

Local Testing

You can run the script locally to test it:

make dev

To run the script with verbose logging:

export LOGURU_LEVEL=TRACE
make dev

Development

We use Pipenv for virtualenv and dev dependency management. With Pipenv installed:

1. Install your locally checked-out code in development mode, including its dependencies, and all dev dependencies into a virtual environment:

pipenv sync --dev

2. Create an environment file and fill in the required values:

cp .env.example .env

3. Run the script in the virtual environment, which will automatically load your .env:

pipenv run spotifyconnector

To add a new dependency for use during the development of this library:

pipenv install --dev $package

To add a new dependency necessary for the correct operation of this library, add the package to the install_requires section of ./setup.py, then:

pipenv install

To publish the package:

python setup.py sdist bdist_wheel
twine upload dist/*

or

make publish

Credits

This was inspired by the code at wdr-okr, extended and released to PyPi.