abacusai.algorithm

Classes

CodeSource

Code source for python-based custom feature groups and models

AbstractApiClass

Algorithm

Customer created algorithm

Module Contents

class abacusai.algorithm.CodeSource(client, sourceType=None, sourceCode=None, applicationConnectorId=None, applicationConnectorInfo=None, packageRequirements=None, status=None, error=None, publishingMsg=None, moduleDependencies=None)

Bases: abacusai.return_class.AbstractApiClass

Code source for python-based custom feature groups and models

Parameters:
  • client (ApiClient) – An authenticated API Client instance

  • sourceType (str) – The type of the source, one of TEXT, PYTHON, FILE_UPLOAD, or APPLICATION_CONNECTOR

  • sourceCode (str) – If the type of the source is TEXT, the raw text of the function

  • applicationConnectorId (str) – The Application Connector to fetch the code from

  • applicationConnectorInfo (str) – Args passed to the application connector to fetch the code

  • packageRequirements (list) – The pip package dependencies required to run the code

  • status (str) – The status of the code and validations

  • error (str) – If the status is failed, an error message describing what went wrong

  • publishingMsg (dict) – Warnings in the source code

  • moduleDependencies (list) – The list of internal modules dependencies required to run the code

__repr__()

Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:

The dict value representation of the class parameters

Return type:

dict

import_as_cell()

Adds the source code as an unexecuted cell in the notebook.

class abacusai.algorithm.AbstractApiClass(client, id)
__eq__(other)

Return self==value.

_get_attribute_as_dict(attribute)
class abacusai.algorithm.Algorithm(client, name=None, problemType=None, createdAt=None, updatedAt=None, isDefaultEnabled=None, trainingInputMappings=None, trainFunctionName=None, predictFunctionName=None, predictManyFunctionName=None, initializeFunctionName=None, configOptions=None, algorithmId=None, useGpu=None, algorithmTrainingConfig=None, onlyOfflineDeployable=None, codeSource={})

Bases: abacusai.return_class.AbstractApiClass

Customer created algorithm

Parameters:
  • client (ApiClient) – An authenticated API Client instance

  • name (str) – The name of the algorithm

  • problemType (str) – The type of the problem this algorithm will work on

  • createdAt (str) – When the algorithm was created

  • updatedAt (str) – When the algorithm was last updated

  • isDefaultEnabled (bool) – Whether train with the algorithm by default

  • trainingInputMappings (dict) – The mappings for train function parameters’ names, e.g. names for training data, name for training config

  • trainFunctionName (str) – Name of the function found in the source code that will be executed to train the model. It is not executed when this function is run.

  • predictFunctionName (str) – Name of the function found in the source code that will be executed run predictions through model. It is not executed when this function is run.

  • predictManyFunctionName (str) – Name of the function found in the source code that will be executed for batch prediction of the model. It is not executed when this function is run.

  • initializeFunctionName (str) – Name of the function found in the source code to initialize the trained model before using it to make predictions using the model

  • configOptions (dict) – Map dataset types and configs to train function parameter names

  • algorithmId (str) – The unique identifier of the algorithm

  • useGpu (bool) – Whether to use gpu for model training

  • algorithmTrainingConfig (dict) – The algorithm specific training config

  • onlyOfflineDeployable (bool) – Whether or not the algorithm is only allowed to be deployed offline

  • codeSource (CodeSource) – Info about the source code of the algorithm

__repr__()

Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:

The dict value representation of the class parameters

Return type:

dict