Tips

Monitor Trial Related Information

You may want to log trial related information such as user who performs the trial, etc. The easiest way is to include these information in parameters.

>>> ex.parameter('user_name')
>>> ex.set_parameters(..., user_name='my_name')

Track Data Version

Most of experiments relies on external data source such as CSV, relational DB, etc. Sometimes experiment result is unexpectedly changed because of external data changes. In such cases, even though daskperiment checks function purity and issues a warning, users may not determine the exact reason.

It is recommended that data loading function is defined as a separate step, because if you receive a warning from that loading function, you can understand that the external data has changed.

>>> @ex
>>> def load_user_data(filename):
>>>     return pd.read_csv(filename)

Check Trial ID During Execution

You may want to know the current trial id during the trial. Then use Experiment.current_trial_id to check current trial id.

>>> @ex
>>> def experiment_step(a, b):
>>>     print('debug_information', ex.current_trial_id)
>>>     ...

You cannnot refer to current_trial_id outside of the experiment step because the id is generated when the trial is performed.

>>> ex.current_trial_id
daskperiment.core.errors.TrialIDNotFoundError: Current Trial ID only exists during a trial execution

To check the last trial id of the experiment outside of the experiment step, use .trial_id property.

>>> ex.trial_id
3

The next trial should be numbered as .trial_id + 1, if no other trial is triggered until your execution. Note that .trial_id cannot be referred during a trial execution to avoid confusion between .trial_id and .current_trial_id.