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list_environment_outputs

list_environment_outputs(
    environment_name: ResourceName,
    *,
    config_overrides: Optional[ProtonClientConfig] = None,
    next_token: Optional[EmptyNextToken] = None,
    deployment_id: Optional[DeploymentId] = None,
) -> ListEnvironmentOutputsOutput

List the infrastructure as code outputs for your environment.

Parameters:

  • environment_name (ResourceName) –

    The environment name.

  • next_token (Optional[EmptyNextToken], default: None ) –

    A token that indicates the location of the next environment output in the array of environment outputs, after the list of environment outputs that was previously requested.

  • deployment_id (Optional[DeploymentId], default: None ) –

    The ID of the deployment whose outputs you want.

Raises:

Source code in docs_src/capo_proton/_services/proton.py
def list_environment_outputs(
    self,
    environment_name: "capo_proton.types.resource_name.ResourceName",
    *,
    config_overrides: Optional[ProtonClientConfig] = None,
    next_token: Optional[
        "capo_proton.types.empty_next_token.EmptyNextToken"
    ] = None,
    deployment_id: Optional["capo_proton.types.deployment_id.DeploymentId"] = None,
) -> (
    "capo_proton.types.list_environment_outputs_output.ListEnvironmentOutputsOutput"
):
    """<p>List the infrastructure as code outputs for your environment.</p>

    Args:
        environment_name: <p>The environment name.</p>
        next_token: <p>A token that indicates the location of the next environment output in the array of environment outputs, after the list of environment outputs that was previously requested.</p>
        deployment_id: <p>The ID of the deployment whose outputs you want.</p>

    Raises:
        capo_proton.errors.access_denied_exception.AccessDeniedException: <p>There <i>isn't</i> sufficient access for performing this action.</p>
        capo_proton.errors.internal_server_exception.InternalServerException: <p>The request failed to register with the service.</p>
        capo_proton.errors.resource_not_found_exception.ResourceNotFoundException: <p>The requested resource <i>wasn't</i> found.</p>
        capo_proton.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_proton.errors.validation_exception.ValidationException: <p>The input is invalid or an out-of-range value was supplied for the input parameter.</p>
        capo_proton.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_proton.types.list_environment_outputs_input.ListEnvironmentOutputsInput]",
    ) -> OperationResponse[
        "capo_proton.types.list_environment_outputs_output.ListEnvironmentOutputsOutput"
    ]:
        import capo_proton._operations.aws_proton20200720.list_environment_outputs

        output, http_response = (
            capo_proton._operations.aws_proton20200720.list_environment_outputs.list_environment_outputs(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_output(
        output: "capo_proton.types.list_environment_outputs_output.ListEnvironmentOutputsOutput",
    ) -> dict[str, Any]:
        import capo_proton.types.list_environment_outputs_output

        return capo_proton.types.list_environment_outputs_output.redact_sensitive(
            output
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("ListEnvironmentOutputs", redact_output=_redact_output),
    )
    input_: capo_proton.types.list_environment_outputs_input.ListEnvironmentOutputsInput = {
        "environment_name": environment_name
    }
    if next_token is not None:
        input_["next_token"] = next_token
    if deployment_id is not None:
        input_["deployment_id"] = deployment_id

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