create_worker_configuration ¶

create_worker_configuration(
    name: __stringMin1Max128,
    properties_file_content: __sensitiveString,
    *,
    config_overrides: Optional[KafkaConnectClientConfig] = None,
    description: Optional[__stringMax1024] = None,
    tags: Optional[Tags] = None,
) -> CreateWorkerConfigurationResponse

Creates a worker configuration using the specified properties.

Parameters:

description (Optional[__stringMax1024], default: None ) –

A summary description of the worker configuration.
name (__stringMin1Max128) –

The name of the worker configuration.
properties_file_content (__sensitiveString) –

Base64 encoded contents of connect-distributed.properties file.
tags (Optional[Tags], default: None ) –

The tags you want to attach to the worker configuration.

Raises:

BadRequestException –

HTTP Status Code 400: Bad request due to incorrect input. Correct your request and then retry it.
ConflictException –

HTTP Status Code 409: Conflict. A resource with this name already exists. Retry your request with another name.
ForbiddenException –

HTTP Status Code 403: Access forbidden. Correct your credentials and then retry your request.
InternalServerErrorException –

HTTP Status Code 500: Unexpected internal server error. Retrying your request might resolve the issue.
NotFoundException –

HTTP Status Code 404: Resource not found due to incorrect input. Correct your request and then retry it.
ServiceUnavailableException –

HTTP Status Code 503: Service Unavailable. Retrying your request in some time might resolve the issue.
TooManyRequestsException –

HTTP Status Code 429: Limit exceeded. Resource limit reached.
UnauthorizedException –

HTTP Status Code 401: Unauthorized request. The provided credentials couldn't be validated.
UnknownServiceError –

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

Source code in docs_src/capo_kafkaconnect/_services/kafka_connect.py

def create_worker_configuration(
    self,
    name: "capo_kafkaconnect.types.__string_min1_max128.__stringMin1Max128",
    properties_file_content: "capo_kafkaconnect.types.__sensitive_string.__sensitiveString",
    *,
    config_overrides: Optional[KafkaConnectClientConfig] = None,
    description: Optional[
        "capo_kafkaconnect.types.__string_max1024.__stringMax1024"
    ] = None,
    tags: Optional["capo_kafkaconnect.types.tags.Tags"] = None,
) -> "capo_kafkaconnect.types.create_worker_configuration_response.CreateWorkerConfigurationResponse":
    """<p>Creates a worker configuration using the specified properties.</p>

    Args:
        description: <p>A summary description of the worker configuration.</p>
        name: <p>The name of the worker configuration.</p>
        properties_file_content: <p>Base64 encoded contents of connect-distributed.properties file.</p>
        tags: <p>The tags you want to attach to the worker configuration.</p>

    Raises:
        capo_kafkaconnect.errors.bad_request_exception.BadRequestException: <p>HTTP Status Code 400: Bad request due to incorrect input. Correct your request and then retry it.</p>
        capo_kafkaconnect.errors.conflict_exception.ConflictException: <p>HTTP Status Code 409: Conflict. A resource with this name already exists. Retry your request with another name.</p>
        capo_kafkaconnect.errors.forbidden_exception.ForbiddenException: <p>HTTP Status Code 403: Access forbidden. Correct your credentials and then retry your request.</p>
        capo_kafkaconnect.errors.internal_server_error_exception.InternalServerErrorException: <p>HTTP Status Code 500: Unexpected internal server error. Retrying your request might resolve the issue.</p>
        capo_kafkaconnect.errors.not_found_exception.NotFoundException: <p>HTTP Status Code 404: Resource not found due to incorrect input. Correct your request and then retry it.</p>
        capo_kafkaconnect.errors.service_unavailable_exception.ServiceUnavailableException: <p>HTTP Status Code 503: Service Unavailable. Retrying your request in some time might resolve the issue.</p>
        capo_kafkaconnect.errors.too_many_requests_exception.TooManyRequestsException: <p>HTTP Status Code 429: Limit exceeded. Resource limit reached.</p>
        capo_kafkaconnect.errors.unauthorized_exception.UnauthorizedException: <p>HTTP Status Code 401: Unauthorized request. The provided credentials couldn't be validated.</p>
        capo_kafkaconnect.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_kafkaconnect.types.create_worker_configuration_request.CreateWorkerConfigurationRequest]",
    ) -> OperationResponse[
        "capo_kafkaconnect.types.create_worker_configuration_response.CreateWorkerConfigurationResponse"
    ]:
        import capo_kafkaconnect._operations.kafka_connect.create_worker_configuration

        output, http_response = (
            capo_kafkaconnect._operations.kafka_connect.create_worker_configuration.create_worker_configuration(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_kafkaconnect.types.create_worker_configuration_request.CreateWorkerConfigurationRequest",
    ) -> dict[str, Any]:
        import capo_kafkaconnect.types.create_worker_configuration_request

        return capo_kafkaconnect.types.create_worker_configuration_request.redact_sensitive(
            input_
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("CreateWorkerConfiguration", redact_input=_redact_input),
    )
    input_: capo_kafkaconnect.types.create_worker_configuration_request.CreateWorkerConfigurationRequest = {
        "name": name,
        "properties_file_content": properties_file_content,
    }
    if description is not None:
        input_["description"] = description
    if tags is not None:
        input_["tags"] = tags

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