Projects

Projects are a selection of training data used to train a model.

Directory

class ProjectDirectory

Provides a collection of methods related to projects.

This class is accessed through client.projects.

Example

List all projects:

import ansys.simai.core

simai = ansys.simai.core.from_config()
simai.projects.list()

create(name: str) → Project

Create a project.

delete(project: Project | str) → None

Delete a project.

Parameters:

project (Project | str) – ID or model of the project.

get(id: str | None = None, name: str | None = None)

Get a project by either ID or name.

You can specify either the ID or the name, not both.

Parameters:

• id (str | None) – ID of the project.

• name (str | None) – Name of the project.

list() → List[Project]

List all projects available on the server.

Model

class Project

Provides the local representation of a project object.

delete() → None

Delete the project.

get_variables() → dict[str, list[str]] | None

Get the available variables for the model’s input/output.

is_trainable() → bool

Check if the project meets the prerequisites to be trained.

reload() → None

Refresh the object with its representation from the server.

property data: List[TrainingData]

List of all TrainingData instances in the project.

property fields: dict

Dictionary containing the raw object representation.

property id: str

ID of the object on the server.

property last_model_configuration: ModelConfiguration

The last configuration that was used for training a model in this project.

property name: str

Name of project.

property sample: TrainingData | None

Sample of the project. The sample determines what variable and settings are available during model configuration.

IsTrainableInfo

class IsTrainableInfo

Properties for project’s trainability.

The objects of this class can be used as booleans in condition statements as in the example:

Example

Verify the project is trainable

pt = my_project.is_trainable()

if pt:
    print(pt)

It prints:

<is_trainable: False, reason(s): Not enough data to train a model: we need at least 3 data points to train a model.>

is_trainable

True if the project is trainable, False if it is not.

Type:

bool

reason

If not_trainable is False, the reason why the project is not trainable. None otherwise.

Type:

str

Create new instance of IsTrainableInfo(is_trainable, reason)