start_text_translation_job async ¶

async def start_text_translation_job(
    self,
    input_data_config: "capo_translate.types.input_data_config.InputDataConfig",
    output_data_config: "capo_translate.types.output_data_config.OutputDataConfig",
    data_access_role_arn: "capo_translate.types.iam_role_arn.IamRoleArn",
    source_language_code: "capo_translate.types.language_code_string.LanguageCodeString",
    target_language_codes: "capo_translate.types.target_language_code_string_list.TargetLanguageCodeStringList",
    client_token: "capo_translate.types.client_token_string.ClientTokenString",
    *,
    config_overrides: Optional[AsyncTranslateClientConfig] = None,
    job_name: Optional["capo_translate.types.job_name.JobName"] = None,
    terminology_names: Optional[
        "capo_translate.types.resource_name_list.ResourceNameList"
    ] = None,
    parallel_data_names: Optional[
        "capo_translate.types.resource_name_list.ResourceNameList"
    ] = None,
    settings: Optional[
        "capo_translate.types.translation_settings.TranslationSettings"
    ] = None,
) -> "capo_translate.types.start_text_translation_job_response.StartTextTranslationJobResponse":
    """<p>Starts an asynchronous batch translation job. Use batch translation jobs to translate large volumes of text across multiple documents at once. For batch translation, you can input documents with different source languages (specify <code>auto</code> as the source language). You can specify one or more target languages. Batch translation translates each input document into each of the target languages. For more information, see <a href="https://docs.aws.amazon.com/translate/latest/dg/async.html">Asynchronous batch processing</a>.</p> <p>Batch translation jobs can be described with the <a>DescribeTextTranslationJob</a> operation, listed with the <a>ListTextTranslationJobs</a> operation, and stopped with the <a>StopTextTranslationJob</a> operation.</p>

    Args:
        job_name: <p>The name of the batch translation job to be performed.</p>
        input_data_config: <p>Specifies the format and location of the input documents for the translation job.</p>
        output_data_config: <p>Specifies the S3 folder to which your job output will be saved. </p>
        data_access_role_arn: <p>The Amazon Resource Name (ARN) of an AWS Identity Access and Management (IAM) role that grants Amazon Translate read access to your input data. For more information, see <a href="https://docs.aws.amazon.com/translate/latest/dg/identity-and-access-management.html">Identity and access management </a>.</p>
        source_language_code: <p>The language code of the input language. Specify the language if all input documents share the same language. If you don't know the language of the source files, or your input documents contains different source languages, select <code>auto</code>. Amazon Translate auto detects the source language for each input document. For a list of supported language codes, see <a href="https://docs.aws.amazon.com/translate/latest/dg/what-is-languages.html">Supported languages</a>.</p>
        target_language_codes: <p>The target languages of the translation job. Enter up to 10 language codes. Each input file is translated into each target language.</p> <p>Each language code is 2 or 5 characters long. For a list of language codes, see <a href="https://docs.aws.amazon.com/translate/latest/dg/what-is-languages.html">Supported languages</a>.</p>
        terminology_names: <p>The name of a custom terminology resource to add to the translation job. This resource lists examples source terms and the desired translation for each term.</p> <p>This parameter accepts only one custom terminology resource.</p> <p>If you specify multiple target languages for the job, translate uses the designated terminology for each requested target language that has an entry for the source term in the terminology file.</p> <p>For a list of available custom terminology resources, use the <a>ListTerminologies</a> operation.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/translate/latest/dg/how-custom-terminology.html">Custom terminology</a>.</p>
        parallel_data_names: <p>The name of a parallel data resource to add to the translation job. This resource consists of examples that show how you want segments of text to be translated. If you specify multiple target languages for the job, the parallel data file must include translations for all the target languages.</p> <p>When you add parallel data to a translation job, you create an <i>Active Custom Translation</i> job. </p> <p>This parameter accepts only one parallel data resource.</p> <note> <p>Active Custom Translation jobs are priced at a higher rate than other jobs that don't use parallel data. For more information, see <a href="http://aws.amazon.com/translate/pricing/">Amazon Translate pricing</a>.</p> </note> <p>For a list of available parallel data resources, use the <a>ListParallelData</a> operation.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/translate/latest/dg/customizing-translations-parallel-data.html"> Customizing your translations with parallel data</a>.</p>
        client_token: <p>A unique identifier for the request. This token is generated for you when using the Amazon Translate SDK.</p>
        settings: <p>Settings to configure your translation output. You can configure the following options:</p> <ul> <li> <p>Brevity: not supported.</p> </li> <li> <p>Formality: sets the formality level of the output text.</p> </li> <li> <p>Profanity: masks profane words and phrases in your translation output.</p> </li> </ul>

    Raises:
        capo_translate.errors.internal_server_exception.InternalServerException: <p>An internal server error occurred. Retry your request.</p>
        capo_translate.errors.invalid_parameter_value_exception.InvalidParameterValueException: <p>The value of the parameter is not valid. Review the value of the parameter you are using to correct it, and then retry your operation.</p>
        capo_translate.errors.invalid_request_exception.InvalidRequestException: <p> The request that you made is not valid. Check your request to determine why it's not valid and then retry the request. </p>
        capo_translate.errors.resource_not_found_exception.ResourceNotFoundException: <p>The resource you are looking for has not been found. Review the resource you're looking for and see if a different resource will accomplish your needs before retrying the revised request.</p>
        capo_translate.errors.too_many_requests_exception.TooManyRequestsException: <p> You have made too many requests within a short period of time. Wait for a short time and then try your request again.</p>
        capo_translate.errors.unsupported_language_pair_exception.UnsupportedLanguagePairException: <p>Amazon Translate does not support translation from the language of the source text into the requested target language. For more information, see <a href="https://docs.aws.amazon.com/translate/latest/dg/what-is-languages.html">Supported languages</a>. </p>
        capo_translate.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_translate.types.start_text_translation_job_request.StartTextTranslationJobRequest]",
    ) -> AsyncOperationResponse[
        "capo_translate.types.start_text_translation_job_response.StartTextTranslationJobResponse"
    ]:
        import capo_translate._operations.aws_shine_frontend_service_20170701.start_text_translation_job

        (
            output,
            http_response,
        ) = await capo_translate._operations.aws_shine_frontend_service_20170701.start_text_translation_job.async_start_text_translation_job(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("StartTextTranslationJob")
    )
    input_: capo_translate.types.start_text_translation_job_request.StartTextTranslationJobRequest = {
        "input_data_config": input_data_config,
        "output_data_config": output_data_config,
        "data_access_role_arn": data_access_role_arn,
        "source_language_code": source_language_code,
        "target_language_codes": target_language_codes,
        "client_token": client_token,
    }
    if job_name is not None:
        input_["job_name"] = job_name
    if terminology_names is not None:
        input_["terminology_names"] = terminology_names
    if parallel_data_names is not None:
        input_["parallel_data_names"] = parallel_data_names
    if settings is not None:
        input_["settings"] = settings

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output