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SageMakerRuntime module#

Index > SageMakerRuntime

Auto-generated documentation for SageMakerRuntime type annotations stubs module types-aiobotocore-sagemaker-runtime.

How to install#

You can generate type annotations for aiobotocore package locally with mypy-boto3-builder. Use uv for build isolation.

  1. Run mypy-boto3-builder in your package root directory: uvx --with 'aiobotocore==2.23.0' mypy-boto3-builder
  2. Select aiobotocore AWS SDK.
  3. Add SageMakerRuntime service.
  4. Use provided commands to install generated packages.

From PyPI with pip#

Install types-aiobotocore for SageMakerRuntime service.

# install with aiobotocore type annotations
python -m pip install 'types-aiobotocore[sagemaker-runtime]'

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

# standalone installation
python -m pip install types-aiobotocore-sagemaker-runtime

How to uninstall#

python -m pip uninstall -y types-aiobotocore-sagemaker-runtime

Usage#

Code samples can be found in Examples.

SageMakerRuntimeClient#

Type annotations and code completion for session.create_client("sagemaker-runtime") as SageMakerRuntimeClient boto3 documentation

# SageMakerRuntimeClient usage example

from aiobotocore.session import get_session

from types_aiobotocore_sagemaker_runtime.client import SageMakerRuntimeClient


session = get_session()
async with session.create_client("sagemaker-runtime") as client:
    client: SageMakerRuntimeClient

Literals#

Type annotations for literals used in methods and schema.

# SageMakerRuntimeServiceName usage example

from types_aiobotocore_sagemaker_runtime.literals import SageMakerRuntimeServiceName

def get_value() -> SageMakerRuntimeServiceName:
    return "sagemaker-runtime"

Type definitions#

Type annotations for type definitions used in methods and schema.