update_resolver ¶

def update_resolver(
    self,
    api_id: "capo_appsync.types.string.String",
    type_name: "capo_appsync.types.resource_name.ResourceName",
    field_name: "capo_appsync.types.resource_name.ResourceName",
    *,
    config_overrides: Optional[AppSyncClientConfig] = None,
    data_source_name: Optional[
        "capo_appsync.types.resource_name.ResourceName"
    ] = None,
    request_mapping_template: Optional[
        "capo_appsync.types.mapping_template.MappingTemplate"
    ] = None,
    response_mapping_template: Optional[
        "capo_appsync.types.mapping_template.MappingTemplate"
    ] = None,
    kind: Optional["capo_appsync.types.resolver_kind.ResolverKind"] = None,
    pipeline_config: Optional[
        "capo_appsync.types.pipeline_config.PipelineConfig"
    ] = None,
    sync_config: Optional["capo_appsync.types.sync_config.SyncConfig"] = None,
    caching_config: Optional[
        "capo_appsync.types.caching_config.CachingConfig"
    ] = None,
    max_batch_size: Optional[
        "capo_appsync.types.max_batch_size.MaxBatchSize"
    ] = None,
    runtime: Optional["capo_appsync.types.app_sync_runtime.AppSyncRuntime"] = None,
    code: Optional["capo_appsync.types.code.Code"] = None,
    metrics_config: Optional[
        "capo_appsync.types.resolver_level_metrics_config.ResolverLevelMetricsConfig"
    ] = None,
) -> "capo_appsync.types.update_resolver_response.UpdateResolverResponse":
    """<p>Updates a <code>Resolver</code> object.</p>

    Args:
        api_id: <p>The API ID.</p>
        type_name: <p>The new type name.</p>
        field_name: <p>The new field name.</p>
        data_source_name: <p>The new data source name.</p>
        request_mapping_template: <p>The new request mapping template.</p> <p>A resolver uses a request mapping template to convert a GraphQL expression into a format that a data source can understand. Mapping templates are written in Apache Velocity Template Language (VTL).</p> <p>VTL request mapping templates are optional when using an Lambda data source. For all other data sources, VTL request and response mapping templates are required.</p>
        response_mapping_template: <p>The new response mapping template.</p>
        kind: <p>The resolver type.</p> <ul> <li> <p> <b>UNIT</b>: A UNIT resolver type. A UNIT resolver is the default resolver type. You can use a UNIT resolver to run a GraphQL query against a single data source.</p> </li> <li> <p> <b>PIPELINE</b>: A PIPELINE resolver type. You can use a PIPELINE resolver to invoke a series of <code>Function</code> objects in a serial manner. You can use a pipeline resolver to run a GraphQL query against multiple data sources.</p> </li> </ul>
        pipeline_config: <p>The <code>PipelineConfig</code>.</p>
        sync_config: <p>The <code>SyncConfig</code> for a resolver attached to a versioned data source.</p>
        caching_config: <p>The caching configuration for the resolver.</p>
        max_batch_size: <p>The maximum batching size for a resolver.</p>
        code: <p>The <code>resolver</code> code that contains the request and response functions. When code is used, the <code>runtime</code> is required. The <code>runtime</code> value must be <code>APPSYNC_JS</code>.</p>
        metrics_config: <p>Enables or disables enhanced resolver metrics for specified resolvers. Note that <code>metricsConfig</code> won't be used unless the <code>resolverLevelMetricsBehavior</code> value is set to <code>PER_RESOLVER_METRICS</code>. If the <code>resolverLevelMetricsBehavior</code> is set to <code>FULL_REQUEST_RESOLVER_METRICS</code> instead, <code>metricsConfig</code> will be ignored. However, you can still set its value.</p> <p> <code>metricsConfig</code> can be <code>ENABLED</code> or <code>DISABLED</code>.</p>

    Raises:
        capo_appsync.errors.bad_request_exception.BadRequestException: <p>The request is not well formed. For example, a value is invalid or a required field is missing. Check the field values, and then try again.</p>
        capo_appsync.errors.concurrent_modification_exception.ConcurrentModificationException: <p>Another modification is in progress at this time and it must complete before you can make your change.</p>
        capo_appsync.errors.internal_failure_exception.InternalFailureException: <p>An internal AppSync error occurred. Try your request again.</p>
        capo_appsync.errors.not_found_exception.NotFoundException: <p>The resource specified in the request was not found. Check the resource, and then try again.</p>
        capo_appsync.errors.unauthorized_exception.UnauthorizedException: <p>You aren't authorized to perform this operation.</p>
        capo_appsync.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_appsync.types.update_resolver_request.UpdateResolverRequest]",
    ) -> OperationResponse[
        "capo_appsync.types.update_resolver_response.UpdateResolverResponse"
    ]:
        import capo_appsync._operations.aws_deepdish_control_plane_service.update_resolver

        output, http_response = (
            capo_appsync._operations.aws_deepdish_control_plane_service.update_resolver.update_resolver(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("UpdateResolver")
    )
    input_: capo_appsync.types.update_resolver_request.UpdateResolverRequest = {
        "api_id": api_id,
        "type_name": type_name,
        "field_name": field_name,
    }
    if data_source_name is not None:
        input_["data_source_name"] = data_source_name
    if request_mapping_template is not None:
        input_["request_mapping_template"] = request_mapping_template
    if response_mapping_template is not None:
        input_["response_mapping_template"] = response_mapping_template
    if kind is not None:
        input_["kind"] = kind
    if pipeline_config is not None:
        input_["pipeline_config"] = pipeline_config
    if sync_config is not None:
        input_["sync_config"] = sync_config
    if caching_config is not None:
        input_["caching_config"] = caching_config
    if max_batch_size is not None:
        input_["max_batch_size"] = max_batch_size
    if runtime is not None:
        input_["runtime"] = runtime
    if code is not None:
        input_["code"] = code
    if metrics_config is not None:
        input_["metrics_config"] = metrics_config

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