Examples

Index > SageMakerMetrics > Examples

Auto-generated documentation for SageMakerMetrics type annotations stubs module types-boto3-sagemaker-metrics.

Client

Implicit type annotations

Can be used with types-boto3[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 boto3.session import Session


session = Session()

client = session.client("sagemaker-metrics")  # (1)
result = client.batch_get_metrics()  # (2)

1. client: SageMakerMetricsClient
2. result: BatchGetMetricsResponseTypeDef

Explicit type annotations

With types-boto3-lite[sagemaker-metrics] or a standalone types_boto3_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 boto3.session import Session

from types_boto3_sagemaker_metrics.client import SageMakerMetricsClient
from types_boto3_sagemaker_metrics.type_defs import BatchGetMetricsResponseTypeDef
from types_boto3_sagemaker_metrics.type_defs import BatchGetMetricsRequestRequestTypeDef


session = Session()

client: SageMakerMetricsClient = session.client("sagemaker-metrics")

kwargs: BatchGetMetricsRequestRequestTypeDef = {...}
result: BatchGetMetricsResponseTypeDef = client.batch_get_metrics(**kwargs)