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SageMaker module#

Index > SageMaker

Auto-generated documentation for SageMaker type annotations stubs module mypy-boto3-sagemaker.

How to install#

You can generate type annotations for boto3 package locally with mypy_boto3_builder. Use uv for build isolation.

  1. Run mypy-boto3-builder in your package root directory: uvx --with 'boto3==1.36.2' mypy_boto3_builder
  2. Select boto3-stubs AWS SDK.
  3. Add SageMaker service.
  4. Use provided commands to install generated packages.

VSCode extension#

Add AWS Boto3 extension to your VSCode and run AWS boto3: Quick Start command.

Click Modify and select boto3 common and SageMaker.

From PyPI with pip#

Install boto3-stubs for SageMaker service.

# install with boto3 type annotations
python -m pip install 'boto3-stubs[sagemaker]'

# Lite version does not provide session.client/resource overloads
# it is more RAM-friendly, but requires explicit type annotations
python -m pip install 'boto3-stubs-lite[sagemaker]'

# standalone installation
python -m pip install mypy-boto3-sagemaker

How to uninstall#

python -m pip uninstall -y mypy-boto3-sagemaker

Usage#

Code samples can be found in Examples.

SageMakerClient#

Type annotations and code completion for boto3.client("sagemaker") as SageMakerClient boto3 documentation

# SageMakerClient usage example

from boto3.session import Session

from mypy_boto3_sagemaker.client import SageMakerClient

def get_client() -> SageMakerClient:
    return Session().client("sagemaker")

Paginators#

Type annotations and code completion for paginators from boto3.client("sagemaker").get_paginator("...").

# ListActionsPaginator usage example

from boto3.session import Session

from mypy_boto3_sagemaker.paginator import ListActionsPaginator

def get_list_actions_paginator() -> ListActionsPaginator:
    return Session().client("sagemaker").get_paginator("list_actions"))