abacusai.prediction_operator

Classes

PredictionOperator

A prediction operator.

Module Contents

class abacusai.prediction_operator.PredictionOperator(client, name=None, predictionOperatorId=None, createdAt=None, updatedAt=None, projectId=None, predictFunctionName=None, sourceCode=None, initializeFunctionName=None, notebookId=None, memory=None, useGpu=None, featureGroupIds=None, featureGroupTableNames=None, codeSource={}, refreshSchedules={}, latestPredictionOperatorVersion={})

Bases: abacusai.return_class.AbstractApiClass

A prediction operator.

Parameters:

  • client (ApiClient) – An authenticated API Client instance

  • name (str) – The name for the prediction operator.

  • predictionOperatorId (str) – The unique identifier of the prediction operator.

  • createdAt (str) – Date and time at which the prediction operator was created.

  • updatedAt (str) – Date and time at which the prediction operator was updated.

  • projectId (str) – The project this prediction operator belongs to.

  • predictFunctionName (str) – Name of the function found in the source code that will be executed to run predictions.

  • sourceCode (str) – Python code used to make the prediction operator.

  • initializeFunctionName (str) – Name of the optional initialize function found in the source code. This function will generate anything used by predictions, based on input feature groups.

  • notebookId (str) – The unique string identifier of the notebook used to create or edit the prediction operator.

  • memory (int) – Memory in GB specified for the prediction operator.

  • useGpu (bool) – Whether this prediction operator is using gpu.

  • featureGroupIds (list) – A list of Feature Group IDs used for initializing.

  • featureGroupTableNames (list) – A list of Feature Group table names used for initializing.

  • codeSource (CodeSource) – If a python model, information on the source code.

  • latestPredictionOperatorVersion (PredictionOperatorVersion) – The unique string identifier of the latest version.

  • refreshSchedules (RefreshSchedule) – List of refresh schedules that indicate when the next prediction operator version will be processed

name
prediction_operator_id
created_at
updated_at
project_id
predict_function_name
source_code
initialize_function_name
notebook_id
memory
use_gpu
feature_group_ids
feature_group_table_names
code_source
refresh_schedules
latest_prediction_operator_version
deprecated_keys
__repr__()
to_dict()

Get a dict representation of the parameters in this class

Returns:

The dict value representation of the class parameters

Return type:

dict

refresh()

Calls describe and refreshes the current object’s fields

Returns:

The current object

Return type:

PredictionOperator

describe()

Describe an existing prediction operator.

Parameters:

prediction_operator_id (str) – The unique ID of the prediction operator.

Returns:

The requested prediction operator object.

Return type:

PredictionOperator

update(name=None, feature_group_ids=None, source_code=None, initialize_function_name=None, predict_function_name=None, cpu_size=None, memory=None, package_requirements=None, use_gpu=None)

Update an existing prediction operator. This does not create a new version.

Parameters:

  • name (str) – Name of the prediction operator.

  • feature_group_ids (List) – List of feature groups that are supplied to the initialize function as parameters. Each of the parameters are materialized Dataframes. The order should match the initialize function’s parameters.

  • source_code (str) – Contents of a valid Python source code file. The source code should contain the function predictFunctionName, and the function ‘initializeFunctionName’ if defined.

  • initialize_function_name (str) – Name of the optional initialize function found in the source code. This function will generate anything used by predictions, based on input feature groups.

  • predict_function_name (str) – Name of the function found in the source code that will be executed to run predictions.

  • cpu_size (str) – Size of the CPU for the prediction operator.

  • memory (int) – Memory (in GB) for the prediction operator.

  • package_requirements (list) – List of package requirement strings. For example: [‘numpy==1.2.3’, ‘pandas>=1.4.0’]

  • use_gpu (bool) – Whether this prediction operator needs gpu.

Returns:

The updated prediction operator object.

Return type:

PredictionOperator

delete()

Delete an existing prediction operator.

Parameters:

prediction_operator_id (str) – The unique ID of the prediction operator.

deploy(auto_deploy=True)

Deploy the prediction operator.

Parameters:

auto_deploy (bool) – Flag to enable the automatic deployment when a new prediction operator version is created.

Returns:

The created deployment object.

Return type:

Deployment

create_version()

Create a new version of the prediction operator.

Parameters:

prediction_operator_id (str) – The unique ID of the prediction operator.

Returns:

The created prediction operator version object.

Return type:

PredictionOperatorVersion

list_versions()

List all the prediction operator versions for a prediction operator.

Parameters:

prediction_operator_id (str) – The unique ID of the prediction operator.

Returns:

A list of prediction operator version objects.

Return type:

list[PredictionOperatorVersion]