abacusai.pipeline_version — AbacusAI documentation

# 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