capo-sagemakertrainingsessionruntime: typed, async Python SDK for AWS Sagemakertrainingsessionruntime

capo-sagemakertrainingsessionruntime is a typed Python SDK for AWS Sagemakertrainingsessionruntime. It has an async client, AsyncSageMakerTrainingSessionRuntimeClient, for asyncio and trio, and a sync client, SageMakerTrainingSessionRuntimeClient, with the same methods. Requests and responses are typed with TypedDicts, so your editor and type checker know every field.

It is part of capo, a community-driven alternative to boto3 and aioboto3, built on its own HTTP stack instead of botocore and generated from the official AWS Smithy models. Documentation: https://capo-sdk.dev/services/sagemakertrainingsessionruntime/

Installation

pip install capo-sagemakertrainingsessionruntime

Usage

from capo_sagemakertrainingsessionruntime import AsyncSageMakerTrainingSessionRuntimeClient


async def main():
    async with AsyncSageMakerTrainingSessionRuntimeClient() as sage_maker_training_session_runtime:
        # Example: call the execute_sampling_operation operation
        response = await sage_maker_training_session_runtime.execute_sampling_operation()
        print(response["operation_id"])

Streaming Response

Some operations return a streaming response body. Use the operation as an async context manager and iterate over the response field to read chunks.

from capo_sagemakertrainingsessionruntime import AsyncSageMakerTrainingSessionRuntimeClient


async def main():
    async with AsyncSageMakerTrainingSessionRuntimeClient() as sage_maker_training_session_runtime:
        # Example: call sample_training_session_with_response_stream and read the streaming response
        async with sage_maker_training_session_runtime.sample_training_session_with_response_stream() as response:
            async for chunk in response["body"]:
                print(chunk)

Error Handling

The SDK raises exceptions for errors returned by the API. Catch them to handle failures gracefully.

from capo_sagemakertrainingsessionruntime import AsyncSageMakerTrainingSessionRuntimeClient
from capo_sagemakertrainingsessionruntime.error import ConflictException


async def main():
    async with AsyncSageMakerTrainingSessionRuntimeClient() as sage_maker_training_session_runtime:
        try:
            await sage_maker_training_session_runtime.execute_sampling_operation()
        except ConflictException as e:
            print(f"Error: {e}")
            print(e.data)  # additional error data

Retrying

The SDK retries failed operations automatically. Retry behaviour follows the Smithy specification: errors are retried based on their is_retryable and is_throttling_error attributes. Throttling errors use a longer base delay. Network-level failures (connection errors and timeouts) are also retried. Non-retryable errors, such as client errors without the @retryable trait, are raised immediately without further attempts.

The number of attempts defaults to 3 and can be changed at the client level via retry_max_attempts, or per call via config_overrides.

from capo_sagemakertrainingsessionruntime import AsyncSageMakerTrainingSessionRuntimeClient


async def main():
    async with AsyncSageMakerTrainingSessionRuntimeClient() as sage_maker_training_session_runtime:
        # Default: 3 attempts for every operation
        response = await sage_maker_training_session_runtime.execute_sampling_operation()

        # Override per operation
        response = await sage_maker_training_session_runtime.execute_sampling_operation(config_overrides={"retry_max_attempts": 5})

        # Disable retries for this call
        response = await sage_maker_training_session_runtime.execute_sampling_operation(config_overrides={"retry_max_attempts": 1})