Anchor Connector for Podcast Data
Project description
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
plays_by_geo_city
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()
# plays_by_geo_city = connector.plays_by_geo_city("Germany")
# ...
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:
- Install your locally checked out code in development mode, including its dependencies, and all dev dependencies into a virtual environment:
pipenv sync --dev
- Create an environment file and fill in the required values:
cp .env.sample .env
- 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
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