Features

• Implement a new decorator ‘command_with_config’ which enables to pass default values for click options in a config file

• Performs the same checks as click regarding values passed in config file (ex: check if path exists)

• Seamless integration with click, just replace click.command with dclick.command_with_config

With click you would have to pass a default value directly in the code

from click import command
from click import option

@command()
@option('-n', '--n-epochs', type=int, default=5, help='Number of epochs to train the model')
def train(n_epochs):
    run_training_for(n_epochs)

if __name__ == '__main__':
    train()

However, if you want to run this code with different parameters you would have to edit the code each time or pass them in the command line. Both these solutions are not satisfying for automation and versioning. Imagine that you want to run your code inside a docker without the possibility to use the command line, like you are working with a managed platform on the cloud. With dclick you just have to change one line:

from dclick import command_with_config
from click import option

@command_with_config('path_to_config.json')
@option('-n', '--n-epochs', type=int)
def train(n_epochs):
    run_training_for(n_epochs):

if __name__ == '__main__':
    train()

Just be careful that the name in the config matches the name of the option. dclick takes care of the rest. You can pass a config as json, yaml or txt. Json and yaml are preferred.

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

0.1.0 (2020-06-23)

• First release on PyPI.