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type-stubs / mypy-boto3-sagemaker-metrics
Install & Compatibility
Where this runs
tested against v1.43.0 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.910 runs
installs and imports cleanly · install 0.0s · import 0.000s · 18.2MB
glibcpy 3.10–3.910 runs
installs and imports cleanly · install 2.6s · import 0.000s · 19MB
71MB installed
● package 71MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
SageMakerMetricsClient
✓ from mypy_boto3_sagemaker_metrics import SageMakerMetricsClient
✗ from mypy_boto3_sagemaker_metrics import SageMakerMetricsClient
This quickstart demonstrates how to use the type-hinted SageMakerMetrics client to put batch metrics. It shows the correct way to instantiate a client with explicit type annotation and then call a service method, benefiting from IDE auto-completion and static type checks. Replace `my-trial-component-name` with an actual SageMaker Trial Component name for execution.
import boto3
from datetime import datetime
from mypy_boto3_sagemaker_metrics.client import SageMakerMetricsClient
def put_example_metrics(trial_component_name: str):
client: SageMakerMetricsClient = boto3.client("sagemaker-metrics")
response = client.batch_put_metrics(
TrialComponentName=trial_component_name,
MetricData=[
{
'MetricName': 'accuracy',
'Timestamp': datetime.now(),
'Step': 0,
'Value': 0.95
},
{
'MetricName': 'loss',
'Timestamp': datetime.now(),
'Step': 0,
'Value': 0.05
},
]
)
print(f"Successfully put metrics: {response}")
# Example usage (requires an existing SageMaker Trial Component)
# try:
# put_example_metrics("my-trial-component-name")
# except Exception as e:
# print(f"Error putting metrics: {e}")
# Note: Creating a Trial Component is outside the scope of this quickstart.
# You would typically get this name from a SageMaker training job or experiment.
Debug
Known issues
breakingAs of `mypy-boto3-builder` version 8.12.0 (which generated `mypy-boto3-sagemaker-metrics` 1.42.3), Python 3.8 support has been explicitly removed. Projects requiring type stubs for this service must use Python 3.9 or newer.fixUpgrade your project's Python version to 3.9 or later, or pin an older version of `mypy-boto3-sagemaker-metrics` that supported Python 3.8 if absolute compatibility is needed.
affects: >=1.42.3 (generated by builder >=8.12.0)
breakingIn `mypy-boto3-builder` 8.9.0, there were breaking changes to TypeDef naming conventions. Specifically, suffixes like `RequestRequestTypeDef` were shortened to `RequestTypeDef`, and `Extra` postfixes were moved. While this specific package's service might not be directly affected, other `mypy-boto3` packages used in conjunction could break.fixReview your code for direct imports of TypeDefs from `mypy-boto3` packages and adjust names according to the new conventions, often found in the `type_defs` submodule.
affects: >=1.42.3 (generated by builder >=8.9.0)
gotchaThis package provides *only* type annotations for `boto3`. It does not include the `boto3` library itself. You must install `boto3` separately for your code to run at runtime.fixEnsure `boto3` is included in your project's dependencies: `pip install boto3`.
affects: All versions
gotchaThe `mypy-boto3` libraries migrated to PEP 561 packages. While this generally improves compatibility with type checkers, older `mypy` configurations or non-standard `pip` usage might require explicit configuration or ensuring packages are installed in the environment where `mypy` runs.fixVerify your `mypy` configuration (e.g., `pyproject.toml`) is up-to-date and that `mypy-boto3-sagemaker-metrics` is installed in the Python environment used by your type checker. For best results, use `uv` or `pip` for installation.
affects: >=1.42.3 (generated by builder >=8.12.0)
Upgrade
Version history
1.43.0latest on PyPI · released Apr 29, 2026
Audit
Dependencies
boto3requiredProvides the actual runtime functionality for interacting with AWS services.
typing-extensionsoptionalMay be required for full type compatibility on Python versions older than 3.10, although recent builder versions aim to manage this automatically. Typically not needed for Python >=3.9.