iter_list_inference_recommendations_jobs ¶

def iter_list_inference_recommendations_jobs(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    creation_time_after: Optional[
        "capo_sagemaker.types.creation_time.CreationTime"
    ] = None,
    creation_time_before: Optional[
        "capo_sagemaker.types.creation_time.CreationTime"
    ] = None,
    last_modified_time_after: Optional[
        "capo_sagemaker.types.last_modified_time.LastModifiedTime"
    ] = None,
    last_modified_time_before: Optional[
        "capo_sagemaker.types.last_modified_time.LastModifiedTime"
    ] = None,
    name_contains: Optional[
        "capo_sagemaker.types.name_contains.NameContains"
    ] = None,
    status_equals: Optional[
        "capo_sagemaker.types.recommendation_job_status.RecommendationJobStatus"
    ] = None,
    sort_by: Optional[
        "capo_sagemaker.types.list_inference_recommendations_jobs_sort_by.ListInferenceRecommendationsJobsSortBy"
    ] = None,
    sort_order: Optional["capo_sagemaker.types.sort_order.SortOrder"] = None,
    next_token: Optional["capo_sagemaker.types.next_token.NextToken"] = None,
    max_results: Optional["capo_sagemaker.types.max_results.MaxResults"] = None,
    model_name_equals: Optional["capo_sagemaker.types.model_name.ModelName"] = None,
    model_package_version_arn_equals: Optional[
        "capo_sagemaker.types.model_package_arn.ModelPackageArn"
    ] = None,
) -> "Iterator[capo_sagemaker.types.inference_recommendations_job.InferenceRecommendationsJob]":
    _token = next_token
    while True:
        _response = self.list_inference_recommendations_jobs(
            config_overrides=config_overrides,
            creation_time_after=creation_time_after,
            creation_time_before=creation_time_before,
            last_modified_time_after=last_modified_time_after,
            last_modified_time_before=last_modified_time_before,
            name_contains=name_contains,
            status_equals=status_equals,
            sort_by=sort_by,
            sort_order=sort_order,
            next_token=_token,
            max_results=max_results,
            model_name_equals=model_name_equals,
            model_package_version_arn_equals=model_package_version_arn_equals,
        )
        _page = _resolve_path(_response, ("inference_recommendations_jobs",))
        for _item in _page or []:
            yield _item
        _token = _resolve_path(_response, ("next_token",))
        if not _token:
            break