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‎python/example_code/healthlake/README.md‎

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# HealthImaging code examples for the SDK for Python
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## Overview
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Shows how to use the AWS SDK for Python (Boto3) to work with AWS HealthImaging.
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<!--custom.overview.start-->
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<!--custom.overview.end-->
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_HealthImaging is a HIPAA-eligible service that helps health care providers and their medical imaging ISV partners store, transform, and apply machine learning to medical images._
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## ⚠ Important
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* Running this code might result in charges to your AWS account. For more details, see [AWS Pricing](https://aws.amazon.com/pricing/) and [Free Tier](https://aws.amazon.com/free/).
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* Running the tests might result in charges to your AWS account.
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* We recommend that you grant your code least privilege. At most, grant only the minimum permissions required to perform the task. For more information, see [Grant least privilege](https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html#grant-least-privilege).
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* This code is not tested in every AWS Region. For more information, see [AWS Regional Services](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services).
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<!--custom.important.start-->
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<!--custom.important.end-->
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## Code examples
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### Prerequisites
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For prerequisites, see the [README](../../README.md#Prerequisites) in the `python` folder.
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Install the packages required by these examples by running the following in a virtual environment:
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```
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python -m pip install -r requirements.txt
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```
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<!--custom.prerequisites.start-->
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<!--custom.prerequisites.end-->
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### Get started
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- [Hello HealthImaging](imaging_set_and_frames_workflow/hello.py#L4) (`ListDatastores`)
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### Single actions
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Code excerpts that show you how to call individual service functions.
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- [CopyImageSet](health_lake_wrapper.py#L417)
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- [CreateDatastore](health_lake_wrapper.py#L31)
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- [DeleteDatastore](health_lake_wrapper.py#L104)
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- [DeleteImageSet](health_lake_wrapper.py#L489)
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- [GetDICOMImportJob](health_lake_wrapper.py#L158)
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- [GetDatastore](health_lake_wrapper.py#L54)
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- [GetImageFrame](health_lake_wrapper.py#L318)
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- [GetImageSet](health_lake_wrapper.py#L241)
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- [GetImageSetMetadata](health_lake_wrapper.py#L274)
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- [ListDICOMImportJobs](health_lake_wrapper.py#L183)
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- [ListDatastores](health_lake_wrapper.py#L79)
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- [ListImageSetVersions](health_lake_wrapper.py#L350)
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- [ListTagsForResource](health_lake_wrapper.py#L556)
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- [SearchImageSets](health_lake_wrapper.py#L211)
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- [StartDICOMImportJob](health_lake_wrapper.py#L124)
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- [TagResource](health_lake_wrapper.py#L514)
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- [UntagResource](health_lake_wrapper.py#L534)
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- [UpdateImageSetMetadata](health_lake_wrapper.py#L381)
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### Scenarios
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Code examples that show you how to accomplish a specific task by calling multiple
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functions within the same service.
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- [Get started with image sets and image frames](imaging_set_and_frames_workflow/imaging_set_and_frames.py)
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- [Tagging a data store](tagging_data_stores.py)
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- [Tagging an image set](tagging_image_sets.py)
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<!--custom.examples.start-->
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<!--custom.examples.end-->
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## Run the examples
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### Instructions
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<!--custom.instructions.start-->
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<!--custom.instructions.end-->
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#### Hello HealthImaging
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This example shows you how to get started using HealthImaging.
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```
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python imaging_set_and_frames_workflow/hello.py
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```
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#### Get started with image sets and image frames
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This example shows you how to import DICOM files and download image frames in HealthImaging.</para>
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<para>The implementation is structured as a workflow command-line
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application.
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- Set up resources for a DICOM import.
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- Import DICOM files into a data store.
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- Retrieve the image set IDs for the import job.
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- Retrieve the image frame IDs for the image sets.
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- Download, decode and verify the image frames.
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- Clean up resources.
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<!--custom.scenario_prereqs.medical-imaging_Scenario_ImageSetsAndFrames.start-->
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<!--custom.scenario_prereqs.medical-imaging_Scenario_ImageSetsAndFrames.end-->
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Start the example by running the following at a command prompt:
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```
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python imaging_set_and_frames_workflow/imaging_set_and_frames.py
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```
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<!--custom.scenarios.medical-imaging_Scenario_ImageSetsAndFrames.start-->
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<!--custom.scenarios.medical-imaging_Scenario_ImageSetsAndFrames.end-->
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#### Tagging a data store
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This example shows you how to tag a HealthImaging data store.
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<!--custom.scenario_prereqs.medical-imaging_Scenario_TaggingDataStores.start-->
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<!--custom.scenario_prereqs.medical-imaging_Scenario_TaggingDataStores.end-->
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Start the example by running the following at a command prompt:
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```
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python tagging_data_stores.py
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```
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<!--custom.scenarios.medical-imaging_Scenario_TaggingDataStores.start-->
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<!--custom.scenarios.medical-imaging_Scenario_TaggingDataStores.end-->
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#### Tagging an image set
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This example shows you how to tag a HealthImaging image set.
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<!--custom.scenario_prereqs.medical-imaging_Scenario_TaggingImageSets.start-->
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<!--custom.scenario_prereqs.medical-imaging_Scenario_TaggingImageSets.end-->
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Start the example by running the following at a command prompt:
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```
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python tagging_image_sets.py
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```
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<!--custom.scenarios.medical-imaging_Scenario_TaggingImageSets.start-->
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<!--custom.scenarios.medical-imaging_Scenario_TaggingImageSets.end-->
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### Tests
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⚠ Running tests might result in charges to your AWS account.
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To find instructions for running these tests, see the [README](../../README.md#Tests)
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in the `python` folder.
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<!--custom.tests.start-->
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<!--custom.tests.end-->
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## Additional resources
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- [HealthImaging Developer Guide](https://docs.aws.amazon.com/healthimaging/latest/devguide/what-is.html)
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- [HealthImaging API Reference](https://docs.aws.amazon.com/healthimaging/latest/APIReference/Welcome.html)
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- [SDK for Python HealthImaging reference](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/medical-imaging.html)
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<!--custom.resources.start-->
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<!--custom.resources.end-->
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---
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Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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SPDX-License-Identifier: Apache-2.0

‎python/example_code/healthlake/health_lake_wrapper.py‎

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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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# SPDX-License-Identifier: Apache-2.0
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"""
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Purpose
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Shows how to use the AWS SDK for Python (Boto3) to manage and invoke AWS HealthImaging
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functions.
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"""
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from boto3 import client
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import logging
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import boto3
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from botocore.exceptions import ClientError
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import time
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logger = logging.getLogger(__name__)
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# snippet-start:[python.example_code.medical-imaging.HealthLakeWrapper]
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class HealthLakeWrapper:
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def __init__(self, health_lake_client):
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self.health_lake_client = health_lake_client
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# snippet-start:[python.example_code.medical-imaging.HealthLakeWrapper.decl]
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@classmethod
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def from_client(cls) -> "HealthLakeWrapper":
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"""
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Creates a HealthLakeWrapper instance with a default AWS HealthLake client.
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:return: An instance of HealthLakeWrapper initialized with the default HealthLake client.
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"""
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kms_client = boto3.client("healthlake")
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return cls(kms_client)
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# snippet-end:[python.example_code.medical-imaging.HealthLakeWrapper.decl]
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# snippet-start:[python.example_code.medical-imaging.CreateFHIRDatastore]
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def create_fihr_datastore(self, datastore_name: str, sse_configuration : dict[str, any] = None,
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identity_provider_configuration : dict[str, any] = None) -> str:
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"""
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Creates a new HealthLake datastore.
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When creating a SMART on FHIR datastore, the following parameters are required:
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- sse_configuration: The server-side encryption configuration for a SMART on FHIR-enabled data store.
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- identity_provider_configuration: The identity provider configuration for a SMART on FHIR-enabled data store.
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:param datastore_name: The name of the data store.
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:param sse_configuration: The server-side encryption configuration for a SMART on FHIR-enabled data store.
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:param identity_provider_configuration: The identity provider configuration for a SMART on FHIR-enabled data store.
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:return: The datastore ID.
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"""
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try:
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parameters = {
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'DatastoreName': datastore_name,
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'DatastoreTypeVersion' : 'R4'
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}
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if sse_configuration is not None and identity_provider_configuration is not None:
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# Creating a SMART on FHIR-enabled data store
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parameters['SseConfiguration'] = sse_configuration
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parameters['IdentityProviderConfiguration'] = identity_provider_configuration
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response = self.health_lake_client.create_fhir_datastore(**parameters)
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return response['datastoreId']
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except ClientError as err:
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logger.exception("Couldn't create datastore %s. Here's why",
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datastore_name, err.response["Error"]["Message"])
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raise
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# snippet-end:[python.example_code.medical-imaging.CreateFHIRDatastore]
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# snippet-start:[python.example_code.medical-imaging.DescribeFHIRDatastore]
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def describe_fhir_datastore(self, datastore_id: str) -> dict[str, any]:
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"""
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Describes a HealthLake datastore.
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:param datastore_id: The datastore ID.
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:return: The datastore description.
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"""
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try:
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response = self.health_lake_client.describe_fhir_datastore(
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DatastoreId=datastore_id)
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return response['DatastoreProperties']
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except ClientError as err:
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logger.exception("Couldn't describe datastore with ID %s. Here's why",
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datastore_id, err.response["Error"]["Message"])
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raise
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# snippet-end:[python.example_code.medical-imaging.HealthLakeWrapper]
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def wait_datastore_active(self, datastore_id: str) -> None:
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"""
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Waits for a HealthLake datastore to become active.
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:param datastore_id: The datastore ID.
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"""
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counter = 0
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max_count_minutes = 40 # It can take a while to create a datastore, so we'll wait up to 40 minutes.
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data_store_active = False
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while counter < max_count_minutes:
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datastore = self.health_lake_client.describe_fhir_datastore(
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DatastoreId=datastore_id)
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if datastore["DatastoreProperties"]["DatastoreStatus"] == "ACTIVE":
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data_store_active = True
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break
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else:
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counter += 1
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time.sleep(60)
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if data_store_active :
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logger.info("Datastore with ID %s is active after %d minutes.", datastore_id, counter)
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else:
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raise ClientError("Datastore with ID %s is not active after %d minutes.", datastore_id, counter)
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try:
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waiter = self.health_lake_client.get_waiter("datastore_active")
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waiter.wait(DatastoreId=datastore_id)
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except ClientError as err:
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logger.exception("Data store with ID %s failed to become active. Here's why",
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datastore_id, err.response["Error"]["Message"])
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raise
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def health_lake_demo(self) -> None:
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use_smart_data_store = False
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testing_code = True
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datastore_name = "health_imaging_datastore"
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if use_smart_data_store:
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pass
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else:
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data_store_id = self.health_imaging_client.list_datastores(
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maxResults=1
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)['datastoreResults'][0]['datastoreId']
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if __name__ == "__main__":
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health_lake_wrapper = HealthLakeWrapper.from_client()
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‎python/example_code/healthlake/requirements.txt‎

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boto3>=1.34.149
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pytest>=7.2.1
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botocore>=1.34.149

‎python/example_code/healthlake/test/conftest.py‎

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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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# SPDX-License-Identifier: Apache-2.0
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"""
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Contains common test fixtures used to run AWS HealthImaging
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tests.
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"""
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import sys
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# This is needed so Python can find test_tools on the path.
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sys.path.append("../..")
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from test_tools.fixtures.common import *

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