optuna.storages.RedisStorage

class optuna.storages.RedisStorage(url, *, heartbeat_interval=None, grace_period=None, failed_trial_callback=None)[source]

Storage class for Redis backend.

Note that library users can instantiate this class, but the attributes provided by this class are not supposed to be directly accessed by them.

Example

We create an RedisStorage instance using the given redis database URL.

import optuna


def objective(trial):
    ...


storage = optuna.storages.RedisStorage(
    url="redis://passwd@localhost:port/db",
)

study = optuna.create_study(storage=storage)
study.optimize(objective)
Parameters
  • url (str) – URL of the redis storage, password and db are optional. (ie: redis://localhost:6379)

  • heartbeat_interval (Optional[int]) –

    Interval to record the heartbeat. It is recorded every interval seconds. heartbeat_interval must be None or a positive integer.

    Note

    The heartbeat is supposed to be used with optimize(). If you use ask() and tell() instead, it will not work.

  • grace_period (Optional[int]) – Grace period before a running trial is failed from the last heartbeat. grace_period must be None or a positive integer. If it is None, the grace period will be 2 * heartbeat_interval.

  • failed_trial_callback (Optional[Callable[[optuna.Study, FrozenTrial], None]]) –

    A callback function that is invoked after failing each stale trial. The function must accept two parameters with the following types in this order: Study and FrozenTrial.

    Note

    The procedure to fail existing stale trials is called just before asking the study for a new trial.

Note

If you use plan to use Redis as a storage mechanism for optuna, make sure Redis in installed and running. Please execute $ pip install -U redis to install redis python library.

Note

Added in v1.4.0 as an experimental feature. The interface may change in newer versions without prior notice. See https://github.com/optuna/optuna/releases/tag/v1.4.0.

Methods

check_trial_is_updatable(trial_id, trial_state)

Check whether a trial state is updatable.

create_new_study([study_name])

Create a new study from a name.

create_new_trial(study_id[, template_trial])

Create and add a new trial to a study.

delete_study(study_id)

Delete a study.

get_all_studies()

Read a list of FrozenStudy objects.

get_all_trials(study_id[, deepcopy, states])

Read all trials in a study.

get_best_trial(study_id)

Return the trial with the best value in a study.

get_failed_trial_callback()

Get the failed trial callback function.

get_heartbeat_interval()

Get the heartbeat interval if it is set.

get_n_trials(study_id[, state])

Count the number of trials in a study.

get_study_directions(study_id)

Read whether a study maximizes or minimizes an objective.

get_study_id_from_name(study_name)

Read the ID of a study.

get_study_name_from_id(study_id)

Read the study name of a study.

get_study_system_attrs(study_id)

Read the optuna-internal attributes of a study.

get_study_user_attrs(study_id)

Read the user-defined attributes of a study.

get_trial(trial_id)

Read a trial.

get_trial_id_from_study_id_trial_number(...)

Read the trial ID of a trial.

get_trial_number_from_id(trial_id)

Read the trial number of a trial.

get_trial_param(trial_id, param_name)

Read the parameter of a trial.

get_trial_params(trial_id)

Read the parameter dictionary of a trial.

get_trial_system_attrs(trial_id)

Read the optuna-internal attributes of a trial.

get_trial_user_attrs(trial_id)

Read the user-defined attributes of a trial.

record_heartbeat(trial_id)

Record the heartbeat of the trial.

remove_session()

Clean up all connections to a database.

set_study_directions(study_id, directions)

Register optimization problem directions to a study.

set_study_system_attr(study_id, key, value)

Register an optuna-internal attribute to a study.

set_study_user_attr(study_id, key, value)

Register a user-defined attribute to a study.

set_trial_intermediate_value(trial_id, step, ...)

Report an intermediate value of an objective function.

set_trial_param(trial_id, param_name, ...)

Set a parameter to a trial.

set_trial_state_values(trial_id, state[, values])

Update the state and values of a trial.

set_trial_system_attr(trial_id, key, value)

Set an optuna-internal attribute to a trial.

set_trial_user_attr(trial_id, key, value)

Set a user-defined attribute to a trial.

check_trial_is_updatable(trial_id, trial_state)

Check whether a trial state is updatable.

Parameters
  • trial_id (int) – ID of the trial. Only used for an error message.

  • trial_state (TrialState) – Trial state to check.

Raises

RuntimeError – If the trial is already finished.

Return type

None

create_new_study(study_name=None)[source]

Create a new study from a name.

If no name is specified, the storage class generates a name. The returned study ID is unique among all current and deleted studies.

Parameters

study_name (Optional[str]) – Name of the new study to create.

Returns

ID of the created study.

Raises

optuna.exceptions.DuplicatedStudyError – If a study with the same study_name already exists.

Return type

int

create_new_trial(study_id, template_trial=None)[source]

Create and add a new trial to a study.

The returned trial ID is unique among all current and deleted trials.

Parameters
  • study_id (int) – ID of the study.

  • template_trial (Optional[FrozenTrial]) – Template FronzenTrial with default user-attributes, system-attributes, intermediate-values, and a state.

Returns

ID of the created trial.

Raises

KeyError – If no study with the matching study_id exists.

Return type

int

delete_study(study_id)[source]

Delete a study.

Parameters

study_id (int) – ID of the study.

Raises

KeyError – If no study with the matching study_id exists.

Return type

None

get_all_studies()[source]

Read a list of FrozenStudy objects.

Returns

A list of FrozenStudy objects.

Return type

List[FrozenStudy]

get_all_trials(study_id, deepcopy=True, states=None)[source]

Read all trials in a study.

Parameters
  • study_id (int) – ID of the study.

  • deepcopy (bool) – Whether to copy the list of trials before returning. Set to True if you intend to update the list or elements of the list.

  • states (Optional[Container[TrialState]]) – Trial states to filter on. If None, include all states.

Returns

List of trials in the study.

Raises

KeyError – If no study with the matching study_id exists.

Return type

List[FrozenTrial]

get_best_trial(study_id)[source]

Return the trial with the best value in a study.

This method is valid only during single-objective optimization.

Parameters

study_id (int) – ID of the study.

Returns

The trial with the best objective value among all finished trials in the study.

Raises
  • KeyError – If no study with the matching study_id exists.

  • RuntimeError – If the study has more than one direction.

  • ValueError – If no trials have been completed.

Return type

FrozenTrial

get_failed_trial_callback()[source]

Get the failed trial callback function.

Returns

The failed trial callback function if it is set, otherwise None.

Return type

Optional[Callable[[Study, FrozenTrial], None]]

get_heartbeat_interval()[source]

Get the heartbeat interval if it is set.

Returns

The heartbeat interval if it is set, otherwise None.

Return type

Optional[int]

get_n_trials(study_id, state=None)

Count the number of trials in a study.

Parameters
Returns

Number of trials in the study.

Raises

KeyError – If no study with the matching study_id exists.

Return type

int

get_study_directions(study_id)[source]

Read whether a study maximizes or minimizes an objective.

Parameters

study_id (int) – ID of a study.

Returns

Optimization directions list of the study.

Raises

KeyError – If no study with the matching study_id exists.

Return type

List[StudyDirection]

get_study_id_from_name(study_name)[source]

Read the ID of a study.

Parameters

study_name (str) – Name of the study.

Returns

ID of the study.

Raises

KeyError – If no study with the matching study_name exists.

Return type

int

get_study_name_from_id(study_id)[source]

Read the study name of a study.

Parameters

study_id (int) – ID of the study.

Returns

Name of the study.

Raises

KeyError – If no study with the matching study_id exists.

Return type

str

get_study_system_attrs(study_id)[source]

Read the optuna-internal attributes of a study.

Parameters

study_id (int) – ID of the study.

Returns

Dictionary with the optuna-internal attributes of the study.

Raises

KeyError – If no study with the matching study_id exists.

Return type

Dict[str, Any]

get_study_user_attrs(study_id)[source]

Read the user-defined attributes of a study.

Parameters

study_id (int) – ID of the study.

Returns

Dictionary with the user attributes of the study.

Raises

KeyError – If no study with the matching study_id exists.

Return type

Dict[str, Any]

get_trial(trial_id)[source]

Read a trial.

Parameters

trial_id (int) – ID of the trial.

Returns

Trial with a matching trial ID.

Raises

KeyError – If no trial with the matching trial_id exists.

Return type

FrozenTrial

get_trial_id_from_study_id_trial_number(study_id, trial_number)[source]

Read the trial ID of a trial.

Parameters
  • study_id (int) – ID of the study.

  • trial_number (int) – Number of the trial.

Returns

ID of the trial.

Raises

KeyError – If no trial with the matching study_id and trial_number exists.

Return type

int

get_trial_number_from_id(trial_id)

Read the trial number of a trial.

Note

The trial number is only unique within a study, and is sequential.

Parameters

trial_id (int) – ID of the trial.

Returns

Number of the trial.

Raises

KeyError – If no trial with the matching trial_id exists.

Return type

int

get_trial_param(trial_id, param_name)

Read the parameter of a trial.

Parameters
  • trial_id (int) – ID of the trial.

  • param_name (str) – Name of the parameter.

Returns

Internal representation of the parameter.

Raises

KeyError – If no trial with the matching trial_id exists. If no such parameter exists.

Return type

float

get_trial_params(trial_id)

Read the parameter dictionary of a trial.

Parameters

trial_id (int) – ID of the trial.

Returns

Dictionary of a parameters. Keys are parameter names and values are internal representations of the parameter values.

Raises

KeyError – If no trial with the matching trial_id exists.

Return type

Dict[str, Any]

get_trial_system_attrs(trial_id)

Read the optuna-internal attributes of a trial.

Parameters

trial_id (int) – ID of the trial.

Returns

Dictionary with the optuna-internal attributes of the trial.

Raises

KeyError – If no trial with the matching trial_id exists.

Return type

Dict[str, Any]

get_trial_user_attrs(trial_id)

Read the user-defined attributes of a trial.

Parameters

trial_id (int) – ID of the trial.

Returns

Dictionary with the user-defined attributes of the trial.

Raises

KeyError – If no trial with the matching trial_id exists.

Return type

Dict[str, Any]

record_heartbeat(trial_id)[source]

Record the heartbeat of the trial.

Parameters

trial_id (int) – ID of the trial.

Return type

None

remove_session()

Clean up all connections to a database.

Return type

None

set_study_directions(study_id, directions)[source]

Register optimization problem directions to a study.

Parameters
Raises
  • KeyError – If no study with the matching study_id exists.

  • ValueError – If the directions are already set and the each coordinate of passed directions is the opposite direction or NOT_SET.

Return type

None

set_study_system_attr(study_id, key, value)[source]

Register an optuna-internal attribute to a study.

This method overwrites any existing attribute.

Parameters
  • study_id (int) – ID of the study.

  • key (str) – Attribute key.

  • value (Any) – Attribute value. It should be JSON serializable.

Raises

KeyError – If no study with the matching study_id exists.

Return type

None

set_study_user_attr(study_id, key, value)[source]

Register a user-defined attribute to a study.

This method overwrites any existing attribute.

Parameters
  • study_id (int) – ID of the study.

  • key (str) – Attribute key.

  • value (Any) – Attribute value. It should be JSON serializable.

Raises

KeyError – If no study with the matching study_id exists.

Return type

None

set_trial_intermediate_value(trial_id, step, intermediate_value)[source]

Report an intermediate value of an objective function.

This method overwrites any existing intermediate value associated with the given step.

Parameters
  • trial_id (int) – ID of the trial.

  • step (int) – Step of the trial (e.g., the epoch when training a neural network).

  • intermediate_value (float) – Intermediate value corresponding to the step.

Raises
  • KeyError – If no trial with the matching trial_id exists.

  • RuntimeError – If the trial is already finished.

Return type

None

set_trial_param(trial_id, param_name, param_value_internal, distribution)[source]

Set a parameter to a trial.

Parameters
  • trial_id (int) – ID of the trial.

  • param_name (str) – Name of the parameter.

  • param_value_internal (float) – Internal representation of the parameter value.

  • distribution (BaseDistribution) – Sampled distribution of the parameter.

Raises
  • KeyError – If no trial with the matching trial_id exists.

  • RuntimeError – If the trial is already finished.

Return type

None

set_trial_state_values(trial_id, state, values=None)[source]

Update the state and values of a trial.

Set return values of an objective function to values argument. If values argument is not None, this method overwrites any existing trial values.

Parameters
Returns

True if the state is successfully updated. False if the state is kept the same. The latter happens when this method tries to update the state of RUNNING trial to RUNNING.

Raises
  • KeyError – If no trial with the matching trial_id exists.

  • RuntimeError – If the trial is already finished.

Return type

bool

set_trial_system_attr(trial_id, key, value)[source]

Set an optuna-internal attribute to a trial.

This method overwrites any existing attribute.

Parameters
  • trial_id (int) – ID of the trial.

  • key (str) – Attribute key.

  • value (Any) – Attribute value. It should be JSON serializable.

Raises
  • KeyError – If no trial with the matching trial_id exists.

  • RuntimeError – If the trial is already finished.

Return type

None

set_trial_user_attr(trial_id, key, value)[source]

Set a user-defined attribute to a trial.

This method overwrites any existing attribute.

Parameters
  • trial_id (int) – ID of the trial.

  • key (str) – Attribute key.

  • value (Any) – Attribute value. It should be JSON serializable.

Raises
  • KeyError – If no trial with the matching trial_id exists.

  • RuntimeError – If the trial is already finished.

Return type

None