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Index > SageMakerMetrics > Examples

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


Implicit type annotations#

Can be used with boto3-stubs[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_put_metrics()  # (2)
  1. client: SageMakerMetricsClient
  2. result: BatchPutMetricsResponseTypeDef

Explicit type annotations#

With boto3-stubs-lite[sagemaker-metrics] or a standalone mypy_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 mypy_boto3_sagemaker_metrics.client import SageMakerMetricsClient
from mypy_boto3_sagemaker_metrics.type_defs import BatchPutMetricsResponseTypeDef
from mypy_boto3_sagemaker_metrics.type_defs import BatchPutMetricsRequestRequestTypeDef

session = Session()

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

kwargs: BatchPutMetricsRequestRequestTypeDef = {...}
result: BatchPutMetricsResponseTypeDef = client.batch_put_metrics(**kwargs)