iter_list_inference_recommendations_job_steps ¶

iter_list_inference_recommendations_job_steps(
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    job_name: Optional[RecommendationJobName] = None,
    status: Optional[RecommendationJobStatus] = None,
    step_type: Optional[RecommendationStepType] = None,
    max_results: Optional[MaxResults] = None,
    next_token: Optional[NextToken] = None,
) -> Iterator[InferenceRecommendationsJobStep]

Source code in docs_src/capo_sagemaker/_services/sage_maker.py

def iter_list_inference_recommendations_job_steps(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    job_name: Optional[
        "capo_sagemaker.types.recommendation_job_name.RecommendationJobName"
    ] = None,
    status: Optional[
        "capo_sagemaker.types.recommendation_job_status.RecommendationJobStatus"
    ] = None,
    step_type: Optional[
        "capo_sagemaker.types.recommendation_step_type.RecommendationStepType"
    ] = None,
    max_results: Optional["capo_sagemaker.types.max_results.MaxResults"] = None,
    next_token: Optional["capo_sagemaker.types.next_token.NextToken"] = None,
) -> "Iterator[capo_sagemaker.types.inference_recommendations_job_step.InferenceRecommendationsJobStep]":
    _token = next_token
    while True:
        _response = self.list_inference_recommendations_job_steps(
            config_overrides=config_overrides,
            job_name=job_name,
            status=status,
            step_type=step_type,
            max_results=max_results,
            next_token=_token,
        )
        _page = _resolve_path(_response, ("steps",))
        for _item in _page or []:
            yield _item
        _token = _resolve_path(_response, ("next_token",))
        if not _token:
            break