Examples#
Index > SageMakerMetrics > Examples
Auto-generated documentation for SageMakerMetrics type annotations stubs module types-aiobotocore-sagemaker-metrics.
Client#
Implicit type annotations#
Can be used with types-aiobotocore[sagemaker-metrics]
package installed.
Write your SageMakerMetrics
code as usual,
type checking and code completion should work out of the box.
# SageMakerMetricsClient usage example
from aiobotocore.session import get_session
session = get_session()
async with session.create_client("sagemaker-metrics") as client: # (1)
result = await client.batch_put_metrics() # (2)
- client: SageMakerMetricsClient
- result: BatchPutMetricsResponseTypeDef
Explicit type annotations#
With types-aiobotocore-lite[sagemaker-metrics]
or a standalone types_aiobotocore_sagemaker_metrics
package, you have to explicitly specify
client: SageMakerMetricsClient
type annotation.
All other type annotations are optional, as types should be discovered automatically. However, these type annotations can be helpful in your functions and methods.
# SageMakerMetricsClient usage example with type annotations
from aiobotocore.session import get_session
from types_aiobotocore_sagemaker_metrics.client import SageMakerMetricsClient
from types_aiobotocore_sagemaker_metrics.type_defs import BatchPutMetricsResponseTypeDef
from types_aiobotocore_sagemaker_metrics.type_defs import BatchPutMetricsRequestRequestTypeDef
session = get_session()
async with session.create_client("sagemaker-metrics") as client:
client: SageMakerMetricsClient
kwargs: BatchPutMetricsRequestRequestTypeDef = {...}
result: BatchPutMetricsResponseTypeDef = await client.batch_put_metrics(**kwargs)