anchorconnector 0.1.0

Anchor Connector for Podcast Data

Anchor Connector

This is a simple library for connecting to the unofficial Anchor API.
It can be used to export data from your dashboard at https://anchor.fm/dashboard.

Supported Endpoints

• total_plays
• plays_by_age_range
• plays_by_app
• plays_by_device
• plays_by_episode
• plays_by_gender
• plays_by_geo
• episodes

For each episode, the following endpoints are supported:

• episode_plays
• episode_performance
• episode_aggregated_performance
• episode_all_time_video_data

See __main.py__ for all endpoints.

Credentials

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

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

Installation

pip install anchorconnector

Usage as a library

from anchorconnector import AnchorConnector

connector = AnchorConnector(
   base_url=BASE_URL,
   webstation_id=WEBSTATION_ID,
   anchorpw_s=ANCHOR_PW_S,
)

end = datetime.now()
start = end - timedelta(days=30)

total_plays = connector.total_plays(True)
logger.info("Podcast Total Plays = {}", json.dumps(total_plays, indent=4))

plays_by_age_range = connector.plays_by_age_range(start, end)
logger.info(
   "Plays by Age Range = {}",
   json.dumps(plays_by_age_range, indent=4),
)

# plays_by_app = connector.plays_by_app(start, end)
# plays_by_device = connector.plays_by_device(start, end)
# plays_by_episode = connector.plays_by_episode(start, end)
# plays_by_gender = connector.plays_by_gender(start, end)
# plays_by_geo = connector.plays_by_geo(start, end)
# ...


for episode in connector.episodes():
   logger.info("Episode = {}", json.dumps(episode, indent=4))

   web_episode_id = episode["webEpisodeId"]

   episode_meta = connector.episode_plays(web_episode_id)
   logger.info("Episode Metadata = {}", json.dumps(episode_meta, indent=4))

   # ...

See __main.py__ for all endpoints.

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.sample .env

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

pipenv run anchorconnector

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