delete_vocabulary ¶

delete_vocabulary(
    instance_id: InstanceId,
    vocabulary_id: VocabularyId,
    *,
    config_overrides: Optional[ConnectClientConfig] = None,
) -> DeleteVocabularyResponse

Deletes the vocabulary that has the given identifier.

Parameters:

instance_id (InstanceId) –

The identifier of the Connect Customer instance. You can find the instance ID in the Amazon Resource Name (ARN) of the instance.
vocabulary_id (VocabularyId) –

The identifier of the custom vocabulary.

Raises:

AccessDeniedException –

You do not have sufficient permissions to perform this action.
InternalServiceException –

Request processing failed because of an error or failure with the service.
InvalidRequestException –

The request is not valid.
ResourceInUseException –

That resource is already in use (for example, you're trying to add a record with the same name as an existing record). If you are trying to delete a resource (for example, DeleteHoursOfOperation or DeletePredefinedAttribute), remove its reference from related resources and then try again.
ResourceNotFoundException –

The specified resource was not found.
ThrottlingException –

The throttling limit has been exceeded.
UnknownServiceError –

The service returned an error code this client does not model.

Source code in docs_src/capo_connect/_services/connect.py

def delete_vocabulary(
    self,
    instance_id: "capo_connect.types.instance_id.InstanceId",
    vocabulary_id: "capo_connect.types.vocabulary_id.VocabularyId",
    *,
    config_overrides: Optional[ConnectClientConfig] = None,
) -> "capo_connect.types.delete_vocabulary_response.DeleteVocabularyResponse":
    """<p>Deletes the vocabulary that has the given identifier.</p>

    Args:
        instance_id: <p>The identifier of the Connect Customer instance. You can <a href="https://docs.aws.amazon.com/connect/latest/adminguide/find-instance-arn.html">find the instance ID</a> in the Amazon Resource Name (ARN) of the instance.</p>
        vocabulary_id: <p>The identifier of the custom vocabulary.</p>

    Raises:
        capo_connect.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient permissions to perform this action.</p>
        capo_connect.errors.internal_service_exception.InternalServiceException: <p>Request processing failed because of an error or failure with the service.</p>
        capo_connect.errors.invalid_request_exception.InvalidRequestException: <p>The request is not valid.</p>
        capo_connect.errors.resource_in_use_exception.ResourceInUseException: <p>That resource is already in use (for example, you're trying to add a record with the same name as an existing record). If you are trying to delete a resource (for example, DeleteHoursOfOperation or DeletePredefinedAttribute), remove its reference from related resources and then try again.</p>
        capo_connect.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource was not found.</p>
        capo_connect.errors.throttling_exception.ThrottlingException: <p>The throttling limit has been exceeded.</p>
        capo_connect.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_connect.types.delete_vocabulary_request.DeleteVocabularyRequest]",
    ) -> OperationResponse[
        "capo_connect.types.delete_vocabulary_response.DeleteVocabularyResponse"
    ]:
        import capo_connect._operations.amazon_connect_service.delete_vocabulary

        output, http_response = (
            capo_connect._operations.amazon_connect_service.delete_vocabulary.delete_vocabulary(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DeleteVocabulary")
    )
    input_: capo_connect.types.delete_vocabulary_request.DeleteVocabularyRequest = {
        "instance_id": instance_id,
        "vocabulary_id": vocabulary_id,
    }

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