Python库 | mypy-boto3-sagemaker-1.12.22.0.tar.gz

# mypy-boto3-sagemaker [](https://pypi.org/project/mypy-boto3-sagemaker) [](https://pypi.org/project/mypy-boto3-sagemaker) [](https://mypy-boto3-builder.readthedocs.io/) Type annotations for [boto3.SageMaker 1.12.22](https://boto3.amazonaws.com/v1/documentation/api/1.12.22/reference/services/sagemaker.html#SageMaker) service compatible with [mypy](https://github.com/python/mypy), [VSCode](https://code.visualstudio.com/), [PyCharm](https://www.jetbrains.com/pycharm/) and other tools. Generated by [mypy-boto3-buider 1.0.5](https://github.com/vemel/mypy_boto3_builder). More information can be found on [boto3-stubs](https://pypi.org/project/boto3-stubs/) page. - [mypy-boto3-sagemaker](#mypy-boto3-sagemaker) - [How to use](#how-to-use) - [Type checking](#type-checking) - [How it works](#how-it-works) ## How to use ### Type checking Make sure you have [mypy](https://github.com/python/mypy) installed and activated in your IDE. Install `boto3-stubs` for `SageMaker` service. ```bash python -m pip install boto3-stubs[mypy-boto3-sagemaker] ``` Use `boto3` with `mypy_boto3` in your project and enjoy type checking and auto-complete. ```python import boto3 from mypy_boto3 import sagemaker # alternative import if you do not want to install mypy_boto3 package # import mypy_boto3_sagemaker as sagemaker # Use this client as usual, now mypy can check if your code is valid. # Check if your IDE supports function overloads, # you probably do not need explicit type annotations # client = boto3.client("sagemaker") client: sagemaker.SageMakerClient = boto3.client("sagemaker") # works for session as well session = boto3.session.Session(region="us-west-1") session_client: sagemaker.SageMakerClient = session.client("sagemaker") # Waiters need type annotation on creation endpoint_deleted_waiter: sagemaker.EndpointDeletedWaiter = client.get_waiter("endpoint_deleted") endpoint_in_service_waiter: sagemaker.EndpointInServiceWaiter = client.get_waiter("endpoint_in_service") notebook_instance_deleted_waiter: sagemaker.NotebookInstanceDeletedWaiter = client.get_waiter("notebook_instance_deleted") notebook_instance_in_service_waiter: sagemaker.NotebookInstanceInServiceWaiter = client.get_waiter("notebook_instance_in_service") notebook_instance_stopped_waiter: sagemaker.NotebookInstanceStoppedWaiter = client.get_waiter("notebook_instance_stopped") processing_job_completed_or_stopped_waiter: sagemaker.ProcessingJobCompletedOrStoppedWaiter = client.get_waiter("processing_job_completed_or_stopped") training_job_completed_or_stopped_waiter: sagemaker.TrainingJobCompletedOrStoppedWaiter = client.get_waiter("training_job_completed_or_stopped") transform_job_completed_or_stopped_waiter: sagemaker.TransformJobCompletedOrStoppedWaiter = client.get_waiter("transform_job_completed_or_stopped") # Paginators need type annotation on creation list_algorithms_paginator: sagemaker.ListAlgorithmsPaginator = client.get_paginator("list_algorithms") list_apps_paginator: sagemaker.ListAppsPaginator = client.get_paginator("list_apps") list_auto_ml_jobs_paginator: sagemaker.ListAutoMLJobsPaginator = client.get_paginator("list_auto_ml_jobs") list_candidates_for_auto_ml_job_paginator: sagemaker.ListCandidatesForAutoMLJobPaginator = client.get_paginator("list_candidates_for_auto_ml_job") list_code_repositories_paginator: sagemaker.ListCodeRepositoriesPaginator = client.get_paginator("list_code_repositories") list_compilation_jobs_paginator: sagemaker.ListCompilationJobsPaginator = client.get_paginator("list_compilation_jobs") list_domains_paginator: sagemaker.ListDomainsPaginator = client.get_paginator("list_domains") list_endpoint_configs_paginator: sagemaker.ListEndpointConfigsPaginator = client.get_paginator("list_endpoint_configs") list_endpoints_paginator: sagemaker.ListEndpointsPaginator = client.get_paginator("list_endpoints") list_experiments_paginator: sagemaker.ListExperimentsPaginator = client.get_paginator("list_experiments") list_flow_definitions_paginator: sagemaker.ListFlowDefinitionsPaginator = client.get_paginator("list_flow_definitions") list_human_task_uis_paginator: sagemaker.ListHumanTaskUisPaginator = client.get_paginator("list_human_task_uis") list_hyper_parameter_tuning_jobs_paginator: sagemaker.ListHyperParameterTuningJobsPaginator = client.get_paginator("list_hyper_parameter_tuning_jobs") list_labeling_jobs_paginator: sagemaker.ListLabelingJobsPaginator = client.get_paginator("list_labeling_jobs") list_labeling_jobs_for_workteam_paginator: sagemaker.ListLabelingJobsForWorkteamPaginator = client.get_paginator("list_labeling_jobs_for_workteam") list_model_packages_paginator: sagemaker.ListModelPackagesPaginator = client.get_paginator("list_model_packages") list_models_paginator: sagemaker.ListModelsPaginator = client.get_paginator("list_models") list_monitoring_executions_paginator: sagemaker.ListMonitoringExecutionsPaginator = client.get_paginator("list_monitoring_executions") list_monitoring_schedules_paginator: sagemaker.ListMonitoringSchedulesPaginator = client.get_paginator("list_monitoring_schedules") list_notebook_instance_lifecycle_configs_paginator: sagemaker.ListNotebookInstanceLifecycleConfigsPaginator = client.get_paginator("list_notebook_instance_lifecycle_configs") list_notebook_instances_paginator: sagemaker.ListNotebookInstancesPaginator = client.get_paginator("list_notebook_instances") list_processing_jobs_paginator: sagemaker.ListProcessingJobsPaginator = client.get_paginator("list_processing_jobs") list_subscribed_workteams_paginator: sagemaker.ListSubscribedWorkteamsPaginator = client.get_paginator("list_subscribed_workteams") list_tags_paginator: sagemaker.ListTagsPaginator = client.get_paginator("list_tags") list_training_jobs_paginator: sagemaker.ListTrainingJobsPaginator = client.get_paginator("list_training_jobs") list_training_jobs_for_hyper_parameter_tuning_job_paginator: sagemaker.ListTrainingJobsForHyperParameterTuningJobPaginator = client.get_paginator("list_training_jobs_for_hyper_parameter_tuning_job") list_transform_jobs_paginator: sagemaker.ListTransformJobsPaginator = client.get_paginator("list_transform_jobs") list_trial_components_paginator: sagemaker.ListTrialComponentsPaginator = client.get_paginator("list_trial_components") list_trials_paginator: sagemaker.ListTrialsPaginator = client.get_paginator("list_trials") list_user_profiles_paginator: sagemaker.ListUserProfilesPaginator = client.get_paginator("list_user_profiles") list_workteams_paginator: sagemaker.ListWorkteamsPaginator = client.get_paginator("list_workteams") search_paginator: sagemaker.SearchPaginator = client.get_paginator("search") ``` ## How it works Fully automated [builder](https://github.com/vemel/mypy_boto3_builder) carefully generates type annotations for each service, patiently waiting for `boto3` updates. It delivers a drop-in type annotations for you and makes sure that: - All available `boto3` services are covered. - Each public class and method of every `boto3` service gets valid type annotations extracted from the documentation (blame `botocore` docs if types are incorrect). - Type annotations include up-to-date documentation. - Link to documentation is provided for every method. - Code is processed by [black](https://github.com/psf/black) for readability.