create_configured_audience_model ¶

def create_configured_audience_model(
    self,
    name: "capo_cleanroomsml.types.name_string.NameString",
    audience_model_arn: "capo_cleanroomsml.types.audience_model_arn.AudienceModelArn",
    output_config: "capo_cleanroomsml.types.configured_audience_model_output_config.ConfiguredAudienceModelOutputConfig",
    shared_audience_metrics: "capo_cleanroomsml.types.metrics_list.MetricsList",
    *,
    config_overrides: Optional[CleanRoomsMLClientConfig] = None,
    description: Optional[
        "capo_cleanroomsml.types.resource_description.ResourceDescription"
    ] = None,
    min_matching_seed_size: Optional[
        "capo_cleanroomsml.types.min_matching_seed_size.MinMatchingSeedSize"
    ] = None,
    audience_size_config: Optional[
        "capo_cleanroomsml.types.audience_size_config.AudienceSizeConfig"
    ] = None,
    tags: Optional["capo_cleanroomsml.types.tag_map.TagMap"] = None,
    child_resource_tag_on_create_policy: Optional[
        "capo_cleanroomsml.types.tag_on_create_policy.TagOnCreatePolicy"
    ] = None,
) -> "capo_cleanroomsml.types.create_configured_audience_model_response.CreateConfiguredAudienceModelResponse":
    """<p>Defines the information necessary to create a configured audience model.</p>

    Args:
        name: <p>The name of the configured audience model.</p>
        audience_model_arn: <p>The Amazon Resource Name (ARN) of the audience model to use for the configured audience model.</p>
        output_config: <p>Configure the Amazon S3 location and IAM Role for audiences created using this configured audience model. Each audience will have a unique location. The IAM Role must have <code>s3:PutObject</code> permission on the destination Amazon S3 location. If the destination is protected with Amazon S3 KMS-SSE, then the Role must also have the required KMS permissions.</p>
        description: <p>The description of the configured audience model.</p>
        shared_audience_metrics: <p>Whether audience metrics are shared.</p>
        min_matching_seed_size: <p>The minimum number of users from the seed audience that must match with users in the training data of the audience model. The default value is 500.</p>
        audience_size_config: <p>Configure the list of output sizes of audiences that can be created using this configured audience model. A request to <a>StartAudienceGenerationJob</a> that uses this configured audience model must have an <code>audienceSize</code> selected from this list. You can use the <code>ABSOLUTE</code> <a>AudienceSize</a> to configure out audience sizes using the count of identifiers in the output. You can use the <code>Percentage</code> <a>AudienceSize</a> to configure sizes in the range 1-100 percent.</p>
        tags: <p>The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.</p> <p>The following basic restrictions apply to tags:</p> <ul> <li> <p>Maximum number of tags per resource - 50.</p> </li> <li> <p>For each resource, each tag key must be unique, and each tag key can have only one value.</p> </li> <li> <p>Maximum key length - 128 Unicode characters in UTF-8.</p> </li> <li> <p>Maximum value length - 256 Unicode characters in UTF-8.</p> </li> <li> <p>If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.</p> </li> <li> <p>Tag keys and values are case sensitive.</p> </li> <li> <p>Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.</p> </li> </ul>
        child_resource_tag_on_create_policy: <p>Configure how the service tags audience generation jobs created using this configured audience model. If you specify <code>NONE</code>, the tags from the <a>StartAudienceGenerationJob</a> request determine the tags of the audience generation job. If you specify <code>FROM_PARENT_RESOURCE</code>, the audience generation job inherits the tags from the configured audience model, by default. Tags in the <a>StartAudienceGenerationJob</a> will override the default.</p> <p>When the client is in a different account than the configured audience model, the tags from the client are never applied to a resource in the caller's account.</p>

    Raises:
        capo_cleanroomsml.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_cleanroomsml.errors.conflict_exception.ConflictException: <p>You can't complete this action because another resource depends on this resource.</p>
        capo_cleanroomsml.errors.resource_not_found_exception.ResourceNotFoundException: <p>The resource you are requesting does not exist.</p>
        capo_cleanroomsml.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>You have exceeded your service quota.</p>
        capo_cleanroomsml.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_cleanroomsml.errors.validation_exception.ValidationException: <p>The request parameters for this request are incorrect.</p>
        capo_cleanroomsml.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_cleanroomsml.types.create_configured_audience_model_request.CreateConfiguredAudienceModelRequest]",
    ) -> OperationResponse[
        "capo_cleanroomsml.types.create_configured_audience_model_response.CreateConfiguredAudienceModelResponse"
    ]:
        import capo_cleanroomsml._operations.aws_stark_control_service.create_configured_audience_model

        output, http_response = (
            capo_cleanroomsml._operations.aws_stark_control_service.create_configured_audience_model.create_configured_audience_model(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CreateConfiguredAudienceModel")
    )
    input_: capo_cleanroomsml.types.create_configured_audience_model_request.CreateConfiguredAudienceModelRequest = {
        "name": name,
        "audience_model_arn": audience_model_arn,
        "output_config": output_config,
        "shared_audience_metrics": shared_audience_metrics,
    }
    if description is not None:
        input_["description"] = description
    if min_matching_seed_size is not None:
        input_["min_matching_seed_size"] = min_matching_seed_size
    if audience_size_config is not None:
        input_["audience_size_config"] = audience_size_config
    if tags is not None:
        input_["tags"] = tags
    if child_resource_tag_on_create_policy is not None:
        input_["child_resource_tag_on_create_policy"] = (
            child_resource_tag_on_create_policy
        )

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output