abacusai.pipeline_version

Classes

`PythonFunctionArgument`	A config class for python function arguments
`CodeSource`	Code source for python-based custom feature groups and models
`PipelineStepVersion`	A version of a pipeline step.
`AbstractApiClass`
`PipelineVersion`	A version of a pipeline.

Module Contents

class abacusai.pipeline_version.PythonFunctionArgument

Bases: abacusai.api_class.abstract.ApiClass

A config class for python function arguments

Parameters:

variable_type (PythonFunctionArgumentType) – The type of the python function argument
name (str) – The name of the python function variable
is_required (bool) – Whether the argument is required
value (Any) – The value of the argument
pipeline_variable (str) – The name of the pipeline variable to use as the value

variable_type: abacusai.api_class.enums.PythonFunctionArgumentType

name: str

is_required: bool

value: Any

pipeline_variable: str

class abacusai.pipeline_version.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.pipeline_version.PipelineStepVersion(client, stepName=None, pipelineStepVersion=None, pipelineStepId=None, pipelineId=None, pipelineVersion=None, createdAt=None, updatedAt=None, status=None, error=None, outputErrors=None, pythonFunctionId=None, functionVariableMappings=None, stepDependencies=None, outputVariableMappings=None, cpuSize=None, memory=None, timeout=None, pipelineStepVersionReferences={}, codeSource={})

Bases: abacusai.return_class.AbstractApiClass

A version of a pipeline step.

Parameters:

client (ApiClient) – An authenticated API Client instance
stepName (str) – The name of the step.
pipelineStepVersion (str) – The reference to the pipeline step version.
pipelineStepId (str) – The reference to this step.
pipelineId (str) – The reference to the pipeline this step belongs to.
pipelineVersion (str) – The reference to the pipeline version.
createdAt (str) – The date and time which this step was created.
updatedAt (str) – The date and time when this step was last updated.
status (str) – The status of the pipeline version.
error (str) – The error message if the pipeline step failed.
outputErrors (str) – The error message of a pipeline step’s output.
pythonFunctionId (str) – The reference to the python function
functionVariableMappings (dict) – The mappings for function parameters’ names.
stepDependencies (list[str]) – List of steps this step depends on.
outputVariableMappings (dict) – The mappings for the output variables to the step.
cpuSize (str) – CPU size specified for the step function.
memory (int) – Memory in GB specified for the step function.
timeout (int) – The timeout in minutes for the pipeline step.
pipelineStepVersionReferences (PipelineStepVersionReference) – A list to the output instances of the pipeline step version.
codeSource (CodeSource) – Information about the source code of the pipeline step version.

__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

refresh()

Calls describe and refreshes the current object’s fields

Returns:: The current object
Return type:: PipelineStepVersion

describe()

Describes a pipeline step version.

Parameters:: pipeline_step_version (str) – The ID of the pipeline step version.
Returns:: An object describing the pipeline step version.
Return type:: PipelineStepVersion

get_step_version_logs()

Gets the logs for a given step version.

Parameters:: pipeline_step_version (str) – The id of the pipeline step version.
Returns:: Object describing the pipeline step logs.
Return type:: PipelineStepVersionLogs

class abacusai.pipeline_version.AbstractApiClass(client, id)

__eq__(other): Return self==value.

_get_attribute_as_dict(attribute)

class abacusai.pipeline_version.PipelineVersion(client, pipelineName=None, pipelineId=None, pipelineVersion=None, createdAt=None, updatedAt=None, completedAt=None, status=None, error=None, stepVersions={}, codeSource={}, pipelineVariableMappings={})

Bases: abacusai.return_class.AbstractApiClass

A version of a pipeline.

Parameters:

client (ApiClient) – An authenticated API Client instance
pipelineName (str) – The name of the pipeline this step is a part of.
pipelineId (str) – The reference to the pipeline this step belongs to.
pipelineVersion (str) – The reference to this pipeline version.
createdAt (str) – The date and time which this pipeline version was created.
updatedAt (str) – The date and time which this pipeline version was updated.
completedAt (str) – The date and time which this pipeline version was updated.
status (str) – The status of the pipeline version.
error (str) – The relevant error, if the status is FAILED.
stepVersions (PipelineStepVersion) – A list of the pipeline step versions.
codeSource (CodeSource) – information on the source code
pipelineVariableMappings (PythonFunctionArgument) – A description of the function variables into the pipeline.

__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

refresh()

Calls describe and refreshes the current object’s fields

Returns:: The current object
Return type:: PipelineVersion

describe()

Describes a specified pipeline version

Parameters:: pipeline_version (str) – Unique string identifier for the pipeline version
Returns:: Object describing the pipeline version
Return type:: PipelineVersion

reset(steps=None, include_downstream_steps=True)

Reruns a pipeline version for the given steps and downstream steps if specified.

Parameters:

steps (list) – List of pipeline step names to rerun.
include_downstream_steps (bool) – Whether to rerun downstream steps from the steps you have passed

Returns:

Object describing the pipeline version

Return type:

PipelineVersion

list_logs()

Gets the logs for the steps in a given pipeline version.

Parameters:: pipeline_version (str) – The id of the pipeline version.
Returns:: Object describing the logs for the steps in the pipeline.
Return type:: PipelineVersionLogs

skip_pending_steps()

Skips pending steps in a pipeline version.

Parameters:: pipeline_version (str) – The id of the pipeline version.
Returns:: Object describing the pipeline version
Return type:: PipelineVersion

wait_for_pipeline(timeout=1200)

A waiting call until all the stages in a pipeline version have completed.

Parameters:: timeout (int) – The waiting time given to the call to finish, if it doesn’t finish by the allocated time, the call is said to be timed out.

get_status()

Gets the status of the pipeline version.

Returns:: A string describing the status of a pipeline version (pending, running, complete, etc.).
Return type:: str