initiate_job ¶

def initiate_job(
    self,
    account_id: "capo_glacier.types.string.string",
    vault_name: "capo_glacier.types.string.string",
    *,
    config_overrides: Optional[GlacierClientConfig] = None,
    job_parameters: Optional[
        "capo_glacier.types.job_parameters.JobParameters"
    ] = None,
) -> "capo_glacier.types.initiate_job_output.InitiateJobOutput":
    """<p>This operation initiates a job of the specified type, which can be a select, an archival retrieval, or a vault retrieval. For more information about using this operation, see the documentation for the underlying REST API <a href="https://docs.aws.amazon.com/amazonglacier/latest/dev/api-initiate-job-post.html">Initiate a Job</a>. </p>

    Args:
        account_id: <p>The <code>AccountId</code> value is the AWS account ID of the account that owns the vault. You can either specify an AWS account ID or optionally a single '<code>-</code>' (hyphen), in which case Amazon Glacier uses the AWS account ID associated with the credentials used to sign the request. If you use an account ID, do not include any hyphens ('-') in the ID.</p>
        vault_name: <p>The name of the vault.</p>
        job_parameters: <p>Provides options for specifying job information.</p>

    Raises:
        capo_glacier.errors.insufficient_capacity_exception.InsufficientCapacityException: <p>Returned if there is insufficient capacity to process this expedited request. This error only applies to expedited retrievals and not to standard or bulk retrievals.</p>
        capo_glacier.errors.invalid_parameter_value_exception.InvalidParameterValueException: <p>Returned if a parameter of the request is incorrectly specified.</p>
        capo_glacier.errors.missing_parameter_value_exception.MissingParameterValueException: <p>Returned if a required header or parameter is missing from the request.</p>
        capo_glacier.errors.no_longer_supported_exception.NoLongerSupportedException: <p>Returned if the request was made by a customer with no Amazon Glacier storage. The request is denied as the API is no longer supported for new customers. Please use Amazon S3 Glacier storage classes instead.</p>
        capo_glacier.errors.policy_enforced_exception.PolicyEnforcedException: <p>Returned if a retrieval job would exceed the current data policy's retrieval rate limit. For more information about data retrieval policies,</p>
        capo_glacier.errors.resource_not_found_exception.ResourceNotFoundException: <p>Returned if the specified resource (such as a vault, upload ID, or job ID) doesn't exist.</p>
        capo_glacier.errors.service_unavailable_exception.ServiceUnavailableException: <p>Returned if the service cannot complete the request.</p>
        capo_glacier.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        To initiate an inventory-retrieval job
        The example initiates an inventory-retrieval job for the vault named examplevault.

        >>> client.initiate_job(account_id='-', vault_name='examplevault', job_parameters={'Type': 'inventory-retrieval', 'Description': 'My inventory job', 'Format': 'CSV', 'SNSTopic': 'arn:aws:sns:us-west-2:111111111111:Glacier-InventoryRetrieval-topic-Example'})
    """

    def _handler(
        req: "OperationRequest[capo_glacier.types.initiate_job_input.InitiateJobInput]",
    ) -> OperationResponse[
        "capo_glacier.types.initiate_job_output.InitiateJobOutput"
    ]:
        import capo_glacier._operations.glacier.initiate_job

        output, http_response = (
            capo_glacier._operations.glacier.initiate_job.initiate_job(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("InitiateJob")
    )
    input_: capo_glacier.types.initiate_job_input.InitiateJobInput = {
        "account_id": account_id,
        "vault_name": vault_name,
    }
    if job_parameters is not None:
        input_["job_parameters"] = job_parameters

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