citrine.resources.branch module

class citrine.resources.branch.Branch(name: str, *, session: Session | None = None)

Bases: Resource[Branch]

A project branch.

A branch is a container for design workflows.

access_control_dict() → dict

Return an access control entity representation of this resource. Internal use only.

classmethod build(data: dict) → Self

Build an instance of this object from given data.

dump() → dict

Dump this instance.

archived = None

created_at = None

property design_workflows: DesignWorkflowCollection

Return a resource representing all workflows contained within this branch.

property experiment_datasource: ExperimentDataSource | None

Return this branch’s experiment data source, or None if one doesn’t exist.

name: str = None

project_id: UUID | None = None

root_id = None

uid = None

updated_at = None

version = None

class citrine.resources.branch.BranchCollection(project_id: UUID, session: Session)

Bases: Collection[Branch]

A collection of Branches.

archive(*, root_id: UUID | str, version: int | str | None = 'latest')

Archive a branch.

Parameters:

• root_id (Union[UUID, str]) – Unique ID of the branch root

• version (Union[int, str], optional) – The version of the branch. If provided, must either be a positive integer, or “latest”. Defaults to “latest”.

build(data: dict) → Branch

Build an individual branch from a dictionary.

Parameters:

data (dict) – A dictionary representing the branch.

Returns:

The branch created from data.

Return type:

Branch

data_updates(*, root_id: UUID | str, version: int | str | None = 'latest') → BranchDataUpdate

Get data updates for a branch.

Parameters:

• root_id (Union[UUID, str]) – Unique ID of the branch root

• version (Union[int, str], optional) – The version of the branch. If provided, must either be a positive integer, or “latest”. Defaults to “latest”.

Returns:

A list of data updates and compatible predictors

Return type:

BranchDataUpdate

delete(uid: UUID | str) → Response

Delete a particular element of the collection.

get(*, root_id: UUID | str, version: int | str | None = 'latest') → Branch

Retrieve a branch by its root ID and, optionally, its version number.

Omitting the version number will retrieve the latest version.

Parameters:

• root_id (Union[UUID, str]) – Unique identifier of the branch root

• version (Union[int, str], optional) – The version of the branch to retrieve. If provided, must either be a positive integer, or “latest”. Defaults to “latest”.

Returns:

The requested version of the branch.

Return type:

Branch

get_by_version_id(*, version_id: UUID | str) → Branch

Given a branch version ID, retrieve the branch.

Parameters:

version_id (Union[UUID, str]) – Unique ID of the branch version

Returns:

The requested branch.

Return type:

Branch

list(*, per_page: int = 20) → Iterator[Branch]

List all active branches using pagination.

Yields all active branches paginating over all available pages.

Parameters:

per_page (int, optional) – Max number of branches to return per page. Default is 20. This parameter is used when making requests to the backend service.

Returns:

All branches in this collection.

Return type:

Iterator[Branch]

list_all(*, per_page: int = 20) → Iterator[Branch]

List active branches using pagination.

Yields all active branches, paginating over all available pages.

Parameters:

per_page (int, optional) – Max number of branches to return per page. Default is 20. This parameter is used when making requests to the backend service.

Returns:

Active branches in this collection.

Return type:

Iterator[Branch]

list_archived(*, per_page: int = 20) → Iterator[Branch]

List archived branches using pagination.

Yields all archived branches, paginating over all available pages.

Parameters:

per_page (int, optional) – Max number of branches to return per page. Default is 20. This parameter is used when making requests to the backend service.

Returns:

Archived branches in this collection.

Return type:

Iterator[Branch]

next_version(root_id: UUID | str, *, branch_instructions: NextBranchVersionRequest, retrain_models: bool = True)

Move a branch to the next version.

Parameters:

• root_id (Union[UUID, str]) – Unique identifier of the branch root to advance to next version

• branch_instructions (NextBranchVersionRequest) – Instructions for how the next version of a branch should handle its predictors when the workflows are cloned. data_updates contains the list of data source versions to upgrade (current->latest), and use_predictors will either have a <predictor_id>:latest to indicate the workflow should use a new version of the predictor. Or <predictor_id>:<version #> to indicate that the workflow should use an existing predictor version.

• retrain_models (bool) – If true, when new versions of models are created, they are automatically scheduled for training

Returns:

The new branch record after version update

Return type:

Branch

register(model: CreationType) → CreationType

Create a new element of the collection by registering an existing resource.

restore(*, root_id: UUID | str, version: int | str | None = 'latest')

Restore an archived branch.

Parameters:

• root_id (Union[UUID, str]) – Unique ID of the branch root

• version (Union[int, str], optional) – The version of the branch. If provided, must either be a positive integer, or “latest”. Defaults to “latest”.

update(model: CreationType) → CreationType

Update a particular element of the collection.

update_data(*, root_id: UUID | str, version: int | str | None = 'latest', use_existing: bool = True, retrain_models: bool = False) → Branch | None

Automatically advance the branch to the next version.

If there are no newer versions of data sources used by this branch this method returns without doing anything

Parameters:

• root_id (Union[UUID, str]) – Unique ID of the branch root

• version (Union[int, str], optional) – The version of the branch. If provided, must either be a positive integer, or “latest”. Defaults to “latest”.

• use_existing (bool) – If true the workflows in this branch will use existing predictors that are using the latest versions of the data sources and are ready to use.

• retrain_models (bool) – If true, when new versions of models are created, they are automatically scheduled for training.

Returns:

The new branch record after version update or None if no update

Return type:

Branch