# Command-Line Interface¶

Command Description
create-study Create a new study.
dashboard Launch web dashboard (beta).
studies Show a list of studies.
study optimize Start optimization of a study.
study set-user-attr Set a user attribute to a study.

Optuna provides command-line interface as shown in the above table.

Let us assume you are not in IPython shell and writing Python script files instead. It is totally fine to write scripts like the following:

import optuna

def objective(trial):
x = trial.suggest_uniform('x', -10, 10)
return (x - 2) ** 2

if __name__ == '__main__':
study = optuna.create_study()
study.optimize(objective, n_trials=100)
print('Best value: {} (params: {})\n'.format(study.best_value, study.best_params))


However, we can reduce boilerplate codes by using our optuna command. Let us assume that foo.py contains only the following code.

def objective(trial):
x = trial.suggest_uniform('x', -10, 10)
return (x - 2) ** 2


Even so, we can invoke the optimization as follows. (Don’t care about --storage sqlite:///example.db for now, which is described in Saving/Resuming Study with RDB Backend.)

$cat foo.py def objective(trial): x = trial.suggest_uniform('x', -10, 10) return (x - 2) ** 2$ STUDY_NAME=optuna create-study --storage sqlite:///example.db
$optuna study optimize foo.py objective --n-trials=100 --storage sqlite:///example.db --study$STUDY_NAME
[I 2018-05-09 10:40:25,196] Finished a trial resulted in value: 54.353767789264026. Current best value is 54.353767789264026 with parameters: {'x': -5.372500782588228}.
[I 2018-05-09 10:40:25,197] Finished a trial resulted in value: 15.784266965526376. Current best value is 15.784266965526376 with parameters: {'x': 5.972941852774387}.
...
[I 2018-05-09 10:40:26,204] Finished a trial resulted in value: 14.704254135013741. Current best value is 2.280758099793617e-06 with parameters: {'x': 1.9984897821018828}.


Please note that foo.py only contains the definition of the objective function. By giving the script file name and the method name of objective function to optuna study optimize command, we can invoke the optimization.