create_dataset_group `async` ¶

create_dataset_group(
    dataset_group_name: Name,
    domain: Domain,
    *,
    config_overrides: Optional[AsyncforecastClientConfig] = None,
    dataset_arns: Optional[ArnList] = None,
    tags: Optional[Tags] = None,
) -> CreateDatasetGroupResponse

Creates a dataset group, which holds a collection of related datasets. You can add datasets to the dataset group when you create the dataset group, or later by using the UpdateDatasetGroup operation.

After creating a dataset group and adding datasets, you use the dataset group when you create a predictor. For more information, see Dataset groups.

To get a list of all your datasets groups, use the ListDatasetGroups operation.

The Status of a dataset group must be ACTIVE before you can use the dataset group to create a predictor. To get the status, use the DescribeDatasetGroup operation.

Parameters:

dataset_group_name (Name) –

A name for the dataset group.
domain (Domain) –

The domain associated with the dataset group. When you add a dataset to a dataset group, this value and the value specified for the Domain parameter of the CreateDataset operation must match.

The Domain and DatasetType that you choose determine the fields that must be present in training data that you import to a dataset. For example, if you choose the RETAIL domain and TARGET_TIME_SERIES as the DatasetType, Amazon Forecast requires that item_id, timestamp, and demand fields are present in your data. For more information, see Dataset groups.
dataset_arns (Optional[ArnList], default: None ) –

An array of Amazon Resource Names (ARNs) of the datasets that you want to include in the dataset group.
tags (Optional[Tags], default: None ) –
The optional metadata that you apply to the dataset group to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:
- Maximum number of tags per resource - 50.
- For each resource, each tag key must be unique, and each tag key can have only one value.
- Maximum key length - 128 Unicode characters in UTF-8.
- Maximum value length - 256 Unicode characters in UTF-8.
- If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
- Tag keys and values are case sensitive.
- Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

Raises:

InvalidInputException –

We can't process the request because it includes an invalid value or a value that exceeds the valid range.
LimitExceededException –

The limit on the number of resources per account has been exceeded.
ResourceAlreadyExistsException –

There is already a resource with this name. Try again with a different name.
ResourceInUseException –

The specified resource is in use.
ResourceNotFoundException –

We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.
UnknownServiceError –

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

Source code in docs_src/capo_forecast/_services/async_forecast.py

async def create_dataset_group(
    self,
    dataset_group_name: "capo_forecast.types.name.Name",
    domain: "capo_forecast.types.domain.Domain",
    *,
    config_overrides: Optional[AsyncforecastClientConfig] = None,
    dataset_arns: Optional["capo_forecast.types.arn_list.ArnList"] = None,
    tags: Optional["capo_forecast.types.tags.Tags"] = None,
) -> "capo_forecast.types.create_dataset_group_response.CreateDatasetGroupResponse":
    """<p>Creates a dataset group, which holds a collection of related datasets. You can add datasets to the dataset group when you create the dataset group, or later by using the <a href="https://docs.aws.amazon.com/forecast/latest/dg/API_UpdateDatasetGroup.html">UpdateDatasetGroup</a> operation.</p> <p>After creating a dataset group and adding datasets, you use the dataset group when you create a predictor. For more information, see <a href="https://docs.aws.amazon.com/forecast/latest/dg/howitworks-datasets-groups.html">Dataset groups</a>.</p> <p>To get a list of all your datasets groups, use the <a href="https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasetGroups.html">ListDatasetGroups</a> operation.</p> <note> <p>The <code>Status</code> of a dataset group must be <code>ACTIVE</code> before you can use the dataset group to create a predictor. To get the status, use the <a href="https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDatasetGroup.html">DescribeDatasetGroup</a> operation.</p> </note>

    Args:
        dataset_group_name: <p>A name for the dataset group.</p>
        domain: <p>The domain associated with the dataset group. When you add a dataset to a dataset group, this value and the value specified for the <code>Domain</code> parameter of the <a href="https://docs.aws.amazon.com/forecast/latest/dg/API_CreateDataset.html">CreateDataset</a> operation must match.</p> <p>The <code>Domain</code> and <code>DatasetType</code> that you choose determine the fields that must be present in training data that you import to a dataset. For example, if you choose the <code>RETAIL</code> domain and <code>TARGET_TIME_SERIES</code> as the <code>DatasetType</code>, Amazon Forecast requires that <code>item_id</code>, <code>timestamp</code>, and <code>demand</code> fields are present in your data. For more information, see <a href="https://docs.aws.amazon.com/forecast/latest/dg/howitworks-datasets-groups.html">Dataset groups</a>.</p>
        dataset_arns: <p>An array of Amazon Resource Names (ARNs) of the datasets that you want to include in the dataset group.</p>
        tags: <p>The optional metadata that you apply to the dataset group to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.</p> <p>The following basic restrictions apply to tags:</p> <ul> <li> <p>Maximum number of tags per resource - 50.</p> </li> <li> <p>For each resource, each tag key must be unique, and each tag key can have only one value.</p> </li> <li> <p>Maximum key length - 128 Unicode characters in UTF-8.</p> </li> <li> <p>Maximum value length - 256 Unicode characters in UTF-8.</p> </li> <li> <p>If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.</p> </li> <li> <p>Tag keys and values are case sensitive.</p> </li> <li> <p>Do not use <code>aws:</code>, <code>AWS:</code>, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has <code>aws</code> as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of <code>aws</code> do not count against your tags per resource limit.</p> </li> </ul>

    Raises:
        capo_forecast.errors.invalid_input_exception.InvalidInputException: <p>We can't process the request because it includes an invalid value or a value that exceeds the valid range.</p>
        capo_forecast.errors.limit_exceeded_exception.LimitExceededException: <p>The limit on the number of resources per account has been exceeded.</p>
        capo_forecast.errors.resource_already_exists_exception.ResourceAlreadyExistsException: <p>There is already a resource with this name. Try again with a different name.</p>
        capo_forecast.errors.resource_in_use_exception.ResourceInUseException: <p>The specified resource is in use.</p>
        capo_forecast.errors.resource_not_found_exception.ResourceNotFoundException: <p>We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.</p>
        capo_forecast.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_forecast.types.create_dataset_group_request.CreateDatasetGroupRequest]",
    ) -> AsyncOperationResponse[
        "capo_forecast.types.create_dataset_group_response.CreateDatasetGroupResponse"
    ]:
        import capo_forecast._operations.amazon_forecast.create_dataset_group

        (
            output,
            http_response,
        ) = await capo_forecast._operations.amazon_forecast.create_dataset_group.async_create_dataset_group(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_forecast.types.create_dataset_group_request.CreateDatasetGroupRequest",
    ) -> dict[str, Any]:
        import capo_forecast.types.create_dataset_group_request

        return capo_forecast.types.create_dataset_group_request.redact_sensitive(
            input_
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("CreateDatasetGroup", redact_input=_redact_input),
    )
    input_: capo_forecast.types.create_dataset_group_request.CreateDatasetGroupRequest = {
        "dataset_group_name": dataset_group_name,
        "domain": domain,
    }
    if dataset_arns is not None:
        input_["dataset_arns"] = dataset_arns
    if tags is not None:
        input_["tags"] = tags

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

create_dataset_group async ¶

create_dataset_group `async` ¶