Personalize

Client

class Personalize.Client

A low-level client representing Amazon Personalize

Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.

client = session.create_client('personalize')

These are the available methods:

can_paginate(operation_name)

Check if an operation can be paginated.

Parameters
operation_name (string) -- The operation name. This is the same name as the method name on the client. For example, if the method name is create_foo, and you'd normally invoke the operation as client.create_foo(**kwargs), if the create_foo operation can be paginated, you can use the call client.get_paginator("create_foo").
Returns
True if the operation can be paginated, False otherwise.
close()

Closes underlying endpoint connections.

create_batch_inference_job(**kwargs)

Creates a batch inference job. The operation can handle up to 50 million records and the input file must be in JSON format. For more information, see Creating a batch inference job.

See also: AWS API Documentation

Request Syntax

response = client.create_batch_inference_job(
    jobName='string',
    solutionVersionArn='string',
    filterArn='string',
    numResults=123,
    jobInput={
        's3DataSource': {
            'path': 'string',
            'kmsKeyArn': 'string'
        }
    },
    jobOutput={
        's3DataDestination': {
            'path': 'string',
            'kmsKeyArn': 'string'
        }
    },
    roleArn='string',
    batchInferenceJobConfig={
        'itemExplorationConfig': {
            'string': 'string'
        }
    },
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • jobName (string) --

    [REQUIRED]

    The name of the batch inference job to create.

  • solutionVersionArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the solution version that will be used to generate the batch inference recommendations.

  • filterArn (string) -- The ARN of the filter to apply to the batch inference job. For more information on using filters, see Filtering batch recommendations.
  • numResults (integer) -- The number of recommendations to retrieve.
  • jobInput (dict) --

    [REQUIRED]

    The Amazon S3 path that leads to the input file to base your recommendations on. The input material must be in JSON format.

    • s3DataSource (dict) -- [REQUIRED]

      The URI of the Amazon S3 location that contains your input data. The Amazon S3 bucket must be in the same region as the API endpoint you are calling.

      • path (string) -- [REQUIRED]

        The file path of the Amazon S3 bucket.

      • kmsKeyArn (string) --

        The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

  • jobOutput (dict) --

    [REQUIRED]

    The path to the Amazon S3 bucket where the job's output will be stored.

    • s3DataDestination (dict) -- [REQUIRED]

      Information on the Amazon S3 bucket in which the batch inference job's output is stored.

      • path (string) -- [REQUIRED]

        The file path of the Amazon S3 bucket.

      • kmsKeyArn (string) --

        The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

  • roleArn (string) --

    [REQUIRED]

    The ARN of the Amazon Identity and Access Management role that has permissions to read and write to your input and output Amazon S3 buckets respectively.

  • batchInferenceJobConfig (dict) --

    The configuration details of a batch inference job.

    • itemExplorationConfig (dict) --

      A string to string map specifying the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. See User-Personalization.

      • (string) --
        • (string) --
  • tags (list) --

    A list of tags to apply to the batch inference job.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'batchInferenceJobArn': 'string'
}

Response Structure

  • (dict) --

    • batchInferenceJobArn (string) --

      The ARN of the batch inference job.

Exceptions

create_batch_segment_job(**kwargs)

Creates a batch segment job. The operation can handle up to 50 million records and the input file must be in JSON format. For more information, see Getting batch recommendations and user segments.

See also: AWS API Documentation

Request Syntax

response = client.create_batch_segment_job(
    jobName='string',
    solutionVersionArn='string',
    filterArn='string',
    numResults=123,
    jobInput={
        's3DataSource': {
            'path': 'string',
            'kmsKeyArn': 'string'
        }
    },
    jobOutput={
        's3DataDestination': {
            'path': 'string',
            'kmsKeyArn': 'string'
        }
    },
    roleArn='string',
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • jobName (string) --

    [REQUIRED]

    The name of the batch segment job to create.

  • solutionVersionArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the solution version you want the batch segment job to use to generate batch segments.

  • filterArn (string) -- The ARN of the filter to apply to the batch segment job. For more information on using filters, see Filtering batch recommendations.
  • numResults (integer) -- The number of predicted users generated by the batch segment job for each line of input data.
  • jobInput (dict) --

    [REQUIRED]

    The Amazon S3 path for the input data used to generate the batch segment job.

    • s3DataSource (dict) -- [REQUIRED]

      The configuration details of an Amazon S3 input or output bucket.

      • path (string) -- [REQUIRED]

        The file path of the Amazon S3 bucket.

      • kmsKeyArn (string) --

        The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

  • jobOutput (dict) --

    [REQUIRED]

    The Amazon S3 path for the bucket where the job's output will be stored.

    • s3DataDestination (dict) -- [REQUIRED]

      The configuration details of an Amazon S3 input or output bucket.

      • path (string) -- [REQUIRED]

        The file path of the Amazon S3 bucket.

      • kmsKeyArn (string) --

        The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

  • roleArn (string) --

    [REQUIRED]

    The ARN of the Amazon Identity and Access Management role that has permissions to read and write to your input and output Amazon S3 buckets respectively.

  • tags (list) --

    A list of tags to apply to the batch segment job.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'batchSegmentJobArn': 'string'
}

Response Structure

  • (dict) --

    • batchSegmentJobArn (string) --

      The ARN of the batch segment job.

Exceptions

create_campaign(**kwargs)

Creates a campaign that deploys a solution version. When a client calls the GetRecommendations and GetPersonalizedRanking APIs, a campaign is specified in the request.

Minimum Provisioned TPS and Auto-Scaling

A transaction is a single GetRecommendations or GetPersonalizedRanking call. Transactions per second (TPS) is the throughput and unit of billing for Amazon Personalize. The minimum provisioned TPS ( minProvisionedTPS ) specifies the baseline throughput provisioned by Amazon Personalize, and thus, the minimum billing charge.

If your TPS increases beyond minProvisionedTPS , Amazon Personalize auto-scales the provisioned capacity up and down, but never below minProvisionedTPS . There's a short time delay while the capacity is increased that might cause loss of transactions.

The actual TPS used is calculated as the average requests/second within a 5-minute window. You pay for maximum of either the minimum provisioned TPS or the actual TPS. We recommend starting with a low minProvisionedTPS , track your usage using Amazon CloudWatch metrics, and then increase the minProvisionedTPS as necessary.

Status

A campaign can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING > DELETE IN_PROGRESS

To get the campaign status, call DescribeCampaign.

Note

Wait until the status of the campaign is ACTIVE before asking the campaign for recommendations.

Related APIs

See also: AWS API Documentation

Request Syntax

response = client.create_campaign(
    name='string',
    solutionVersionArn='string',
    minProvisionedTPS=123,
    campaignConfig={
        'itemExplorationConfig': {
            'string': 'string'
        }
    },
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • name (string) --

    [REQUIRED]

    A name for the new campaign. The campaign name must be unique within your account.

  • solutionVersionArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the solution version to deploy.

  • minProvisionedTPS (integer) -- Specifies the requested minimum provisioned transactions (recommendations) per second that Amazon Personalize will support.
  • campaignConfig (dict) --

    The configuration details of a campaign.

    • itemExplorationConfig (dict) --

      Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your solution uses the User-Personalization recipe.

      • (string) --
        • (string) --
  • tags (list) --

    A list of tags to apply to the campaign.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'campaignArn': 'string'
}

Response Structure

  • (dict) --

    • campaignArn (string) --

      The Amazon Resource Name (ARN) of the campaign.

Exceptions

create_dataset(**kwargs)

Creates an empty dataset and adds it to the specified dataset group. Use CreateDatasetImportJob to import your training data to a dataset.

There are three types of datasets:

  • Interactions
  • Items
  • Users

Each dataset type has an associated schema with required field types. Only the Interactions dataset is required in order to train a model (also referred to as creating a solution).

A dataset can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING > DELETE IN_PROGRESS

To get the status of the dataset, call DescribeDataset.

Related APIs

See also: AWS API Documentation

Request Syntax

response = client.create_dataset(
    name='string',
    schemaArn='string',
    datasetGroupArn='string',
    datasetType='string',
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • name (string) --

    [REQUIRED]

    The name for the dataset.

  • schemaArn (string) --

    [REQUIRED]

    The ARN of the schema to associate with the dataset. The schema defines the dataset fields.

  • datasetGroupArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the dataset group to add the dataset to.

  • datasetType (string) --

    [REQUIRED]

    The type of dataset.

    One of the following (case insensitive) values:

    • Interactions
    • Items
    • Users
  • tags (list) --

    A list of tags to apply to the dataset.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'datasetArn': 'string'
}

Response Structure

  • (dict) --

    • datasetArn (string) --

      The ARN of the dataset.

Exceptions

create_dataset_export_job(**kwargs)

Creates a job that exports data from your dataset to an Amazon S3 bucket. To allow Amazon Personalize to export the training data, you must specify an service-linked IAM role that gives Amazon Personalize PutObject permissions for your Amazon S3 bucket. For information, see Exporting a dataset in the Amazon Personalize developer guide.

Status

A dataset export job can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

To get the status of the export job, call DescribeDatasetExportJob, and specify the Amazon Resource Name (ARN) of the dataset export job. The dataset export is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed.

See also: AWS API Documentation

Request Syntax

response = client.create_dataset_export_job(
    jobName='string',
    datasetArn='string',
    ingestionMode='BULK'|'PUT'|'ALL',
    roleArn='string',
    jobOutput={
        's3DataDestination': {
            'path': 'string',
            'kmsKeyArn': 'string'
        }
    },
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • jobName (string) --

    [REQUIRED]

    The name for the dataset export job.

  • datasetArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the dataset that contains the data to export.

  • ingestionMode (string) -- The data to export, based on how you imported the data. You can choose to export only BULK data that you imported using a dataset import job, only PUT data that you imported incrementally (using the console, PutEvents, PutUsers and PutItems operations), or ALL for both types. The default value is PUT .
  • roleArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the IAM service role that has permissions to add data to your output Amazon S3 bucket.

  • jobOutput (dict) --

    [REQUIRED]

    The path to the Amazon S3 bucket where the job's output is stored.

    • s3DataDestination (dict) -- [REQUIRED]

      The configuration details of an Amazon S3 input or output bucket.

      • path (string) -- [REQUIRED]

        The file path of the Amazon S3 bucket.

      • kmsKeyArn (string) --

        The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

  • tags (list) --

    A list of tags to apply to the dataset export job.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'datasetExportJobArn': 'string'
}

Response Structure

  • (dict) --

    • datasetExportJobArn (string) --

      The Amazon Resource Name (ARN) of the dataset export job.

Exceptions

create_dataset_group(**kwargs)

Creates an empty dataset group. A dataset group is a container for Amazon Personalize resources. A dataset group can contain at most three datasets, one for each type of dataset:

  • Interactions
  • Items
  • Users

A dataset group can be a Domain dataset group, where you specify a domain and use pre-configured resources like recommenders, or a Custom dataset group, where you use custom resources, such as a solution with a solution version, that you deploy with a campaign. If you start with a Domain dataset group, you can still add custom resources such as solutions and solution versions trained with recipes for custom use cases and deployed with campaigns.

A dataset group can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING

To get the status of the dataset group, call DescribeDatasetGroup. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the creation failed.

Note

You must wait until the status of the dataset group is ACTIVE before adding a dataset to the group.

You can specify an Key Management Service (KMS) key to encrypt the datasets in the group. If you specify a KMS key, you must also include an Identity and Access Management (IAM) role that has permission to access the key.

APIs that require a dataset group ARN in the request
Related APIs

See also: AWS API Documentation

Request Syntax

response = client.create_dataset_group(
    name='string',
    roleArn='string',
    kmsKeyArn='string',
    domain='ECOMMERCE'|'VIDEO_ON_DEMAND',
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • name (string) --

    [REQUIRED]

    The name for the new dataset group.

  • roleArn (string) -- The ARN of the Identity and Access Management (IAM) role that has permissions to access the Key Management Service (KMS) key. Supplying an IAM role is only valid when also specifying a KMS key.
  • kmsKeyArn (string) -- The Amazon Resource Name (ARN) of a Key Management Service (KMS) key used to encrypt the datasets.
  • domain (string) -- The domain of the dataset group. Specify a domain to create a Domain dataset group. The domain you specify determines the default schemas for datasets and the use cases available for recommenders. If you don't specify a domain, you create a Custom dataset group with solution versions that you deploy with a campaign.
  • tags (list) --

    A list of tags to apply to the dataset group.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'datasetGroupArn': 'string',
    'domain': 'ECOMMERCE'|'VIDEO_ON_DEMAND'
}

Response Structure

  • (dict) --

    • datasetGroupArn (string) --

      The Amazon Resource Name (ARN) of the new dataset group.

    • domain (string) --

      The domain for the new Domain dataset group.

Exceptions

create_dataset_import_job(**kwargs)

Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset. To allow Amazon Personalize to import the training data, you must specify an IAM service role that has permission to read from the data source, as Amazon Personalize makes a copy of your data and processes it internally. For information on granting access to your Amazon S3 bucket, see Giving Amazon Personalize Access to Amazon S3 Resources.

Warning

By default, a dataset import job replaces any existing data in the dataset that you imported in bulk. To add new records without replacing existing data, specify INCREMENTAL for the import mode in the CreateDatasetImportJob operation.

Status

A dataset import job can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

To get the status of the import job, call DescribeDatasetImportJob, providing the Amazon Resource Name (ARN) of the dataset import job. The dataset import is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed.

Note

Importing takes time. You must wait until the status shows as ACTIVE before training a model using the dataset.

Related APIs

See also: AWS API Documentation

Request Syntax

response = client.create_dataset_import_job(
    jobName='string',
    datasetArn='string',
    dataSource={
        'dataLocation': 'string'
    },
    roleArn='string',
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ],
    importMode='FULL'|'INCREMENTAL',
    publishAttributionMetricsToS3=True|False
)
Parameters
  • jobName (string) --

    [REQUIRED]

    The name for the dataset import job.

  • datasetArn (string) --

    [REQUIRED]

    The ARN of the dataset that receives the imported data.

  • dataSource (dict) --

    [REQUIRED]

    The Amazon S3 bucket that contains the training data to import.

    • dataLocation (string) --

      The path to the Amazon S3 bucket where the data that you want to upload to your dataset is stored. For example:

      s3://bucket-name/folder-name/
  • roleArn (string) --

    [REQUIRED]

    The ARN of the IAM role that has permissions to read from the Amazon S3 data source.

  • tags (list) --

    A list of tags to apply to the dataset import job.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

  • importMode (string) --

    Specify how to add the new records to an existing dataset. The default import mode is FULL . If you haven't imported bulk records into the dataset previously, you can only specify FULL .

    • Specify FULL to overwrite all existing bulk data in your dataset. Data you imported individually is not replaced.
    • Specify INCREMENTAL to append the new records to the existing data in your dataset. Amazon Personalize replaces any record with the same ID with the new one.
  • publishAttributionMetricsToS3 (boolean) -- If you created a metric attribution, specify whether to publish metrics for this import job to Amazon S3
Return type

dict

Returns

Response Syntax

{
    'datasetImportJobArn': 'string'
}

Response Structure

  • (dict) --

    • datasetImportJobArn (string) --

      The ARN of the dataset import job.

Exceptions

create_event_tracker(**kwargs)

Creates an event tracker that you use when adding event data to a specified dataset group using the PutEvents API.

Note

Only one event tracker can be associated with a dataset group. You will get an error if you call CreateEventTracker using the same dataset group as an existing event tracker.

When you create an event tracker, the response includes a tracking ID, which you pass as a parameter when you use the PutEvents operation. Amazon Personalize then appends the event data to the Interactions dataset of the dataset group you specify in your event tracker.

The event tracker can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING > DELETE IN_PROGRESS

To get the status of the event tracker, call DescribeEventTracker.

Note

The event tracker must be in the ACTIVE state before using the tracking ID.

Related APIs

See also: AWS API Documentation

Request Syntax

response = client.create_event_tracker(
    name='string',
    datasetGroupArn='string',
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • name (string) --

    [REQUIRED]

    The name for the event tracker.

  • datasetGroupArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the dataset group that receives the event data.

  • tags (list) --

    A list of tags to apply to the event tracker.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'eventTrackerArn': 'string',
    'trackingId': 'string'
}

Response Structure

  • (dict) --

    • eventTrackerArn (string) --

      The ARN of the event tracker.

    • trackingId (string) --

      The ID of the event tracker. Include this ID in requests to the PutEvents API.

Exceptions

create_filter(**kwargs)

Creates a recommendation filter. For more information, see Filtering recommendations and user segments.

See also: AWS API Documentation

Request Syntax

response = client.create_filter(
    name='string',
    datasetGroupArn='string',
    filterExpression='string',
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • name (string) --

    [REQUIRED]

    The name of the filter to create.

  • datasetGroupArn (string) --

    [REQUIRED]

    The ARN of the dataset group that the filter will belong to.

  • filterExpression (string) --

    [REQUIRED]

    The filter expression defines which items are included or excluded from recommendations. Filter expression must follow specific format rules. For information about filter expression structure and syntax, see Filter expressions.

  • tags (list) --

    A list of tags to apply to the filter.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'filterArn': 'string'
}

Response Structure

  • (dict) --

    • filterArn (string) --

      The ARN of the new filter.

Exceptions

create_metric_attribution(**kwargs)

Creates a metric attribution. A metric attribution creates reports on the data that you import into Amazon Personalize. Depending on how you imported the data, you can view reports in Amazon CloudWatch or Amazon S3. For more information, see Measuring impact of recommendations.

See also: AWS API Documentation

Request Syntax

response = client.create_metric_attribution(
    name='string',
    datasetGroupArn='string',
    metrics=[
        {
            'eventType': 'string',
            'metricName': 'string',
            'expression': 'string'
        },
    ],
    metricsOutputConfig={
        's3DataDestination': {
            'path': 'string',
            'kmsKeyArn': 'string'
        },
        'roleArn': 'string'
    }
)
Parameters
  • name (string) --

    [REQUIRED]

    A name for the metric attribution.

  • datasetGroupArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the destination dataset group for the metric attribution.

  • metrics (list) --

    [REQUIRED]

    A list of metric attributes for the metric attribution. Each metric attribute specifies an event type to track and a function. Available functions are SUM() or SAMPLECOUNT() . For SUM() functions, provide the dataset type (either Interactions or Items) and column to sum as a parameter. For example SUM(Items.PRICE).

    • (dict) --

      Contains information on a metric that a metric attribution reports on. For more information, see Measuring impact of recommendations.

      • eventType (string) -- [REQUIRED]

        The metric's event type.

      • metricName (string) -- [REQUIRED]

        The metric's name. The name helps you identify the metric in Amazon CloudWatch or Amazon S3.

      • expression (string) -- [REQUIRED]

        The attribute's expression. Available functions are SUM() or SAMPLECOUNT() . For SUM() functions, provide the dataset type (either Interactions or Items) and column to sum as a parameter. For example SUM(Items.PRICE).

  • metricsOutputConfig (dict) --

    [REQUIRED]

    The output configuration details for the metric attribution.

    • s3DataDestination (dict) --

      The configuration details of an Amazon S3 input or output bucket.

      • path (string) -- [REQUIRED]

        The file path of the Amazon S3 bucket.

      • kmsKeyArn (string) --

        The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

    • roleArn (string) -- [REQUIRED]

      The Amazon Resource Name (ARN) of the IAM service role that has permissions to add data to your output Amazon S3 bucket and add metrics to Amazon CloudWatch. For more information, see Measuring impact of recommendations.

Return type

dict

Returns

Response Syntax

{
    'metricAttributionArn': 'string'
}

Response Structure

  • (dict) --

    • metricAttributionArn (string) --

      The Amazon Resource Name (ARN) for the new metric attribution.

Exceptions

create_recommender(**kwargs)

Creates a recommender with the recipe (a Domain dataset group use case) you specify. You create recommenders for a Domain dataset group and specify the recommender's Amazon Resource Name (ARN) when you make a GetRecommendations request.

Minimum recommendation requests per second

When you create a recommender, you can configure the recommender's minimum recommendation requests per second. The minimum recommendation requests per second ( minRecommendationRequestsPerSecond ) specifies the baseline recommendation request throughput provisioned by Amazon Personalize. The default minRecommendationRequestsPerSecond is 1 . A recommendation request is a single GetRecommendations operation. Request throughput is measured in requests per second and Amazon Personalize uses your requests per second to derive your requests per hour and the price of your recommender usage.

If your requests per second increases beyond minRecommendationRequestsPerSecond , Amazon Personalize auto-scales the provisioned capacity up and down, but never below minRecommendationRequestsPerSecond . There's a short time delay while the capacity is increased that might cause loss of requests.

Your bill is the greater of either the minimum requests per hour (based on minRecommendationRequestsPerSecond) or the actual number of requests. The actual request throughput used is calculated as the average requests/second within a one-hour window. We recommend starting with the default minRecommendationRequestsPerSecond , track your usage using Amazon CloudWatch metrics, and then increase the minRecommendationRequestsPerSecond as necessary.

Status

A recommender can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
  • DELETE PENDING > DELETE IN_PROGRESS

To get the recommender status, call DescribeRecommender.

Note

Wait until the status of the recommender is ACTIVE before asking the recommender for recommendations.

Related APIs

See also: AWS API Documentation

Request Syntax

response = client.create_recommender(
    name='string',
    datasetGroupArn='string',
    recipeArn='string',
    recommenderConfig={
        'itemExplorationConfig': {
            'string': 'string'
        },
        'minRecommendationRequestsPerSecond': 123
    },
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • name (string) --

    [REQUIRED]

    The name of the recommender.

  • datasetGroupArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the destination domain dataset group for the recommender.

  • recipeArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the recipe that the recommender will use. For a recommender, a recipe is a Domain dataset group use case. Only Domain dataset group use cases can be used to create a recommender. For information about use cases see Choosing recommender use cases.

  • recommenderConfig (dict) --

    The configuration details of the recommender.

    • itemExplorationConfig (dict) --

      Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your recommenders generate personalized recommendations for a user (not popular items or similar items).

      • (string) --
        • (string) --
    • minRecommendationRequestsPerSecond (integer) --

      Specifies the requested minimum provisioned recommendation requests per second that Amazon Personalize will support.

  • tags (list) --

    A list of tags to apply to the recommender.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'recommenderArn': 'string'
}

Response Structure

  • (dict) --

    • recommenderArn (string) --

      The Amazon Resource Name (ARN) of the recommender.

Exceptions

create_schema(**kwargs)

Creates an Amazon Personalize schema from the specified schema string. The schema you create must be in Avro JSON format.

Amazon Personalize recognizes three schema variants. Each schema is associated with a dataset type and has a set of required field and keywords. If you are creating a schema for a dataset in a Domain dataset group, you provide the domain of the Domain dataset group. You specify a schema when you call CreateDataset.

Related APIs

See also: AWS API Documentation

Request Syntax

response = client.create_schema(
    name='string',
    schema='string',
    domain='ECOMMERCE'|'VIDEO_ON_DEMAND'
)
Parameters
  • name (string) --

    [REQUIRED]

    The name for the schema.

  • schema (string) --

    [REQUIRED]

    A schema in Avro JSON format.

  • domain (string) -- The domain for the schema. If you are creating a schema for a dataset in a Domain dataset group, specify the domain you chose when you created the Domain dataset group.
Return type

dict

Returns

Response Syntax

{
    'schemaArn': 'string'
}

Response Structure

  • (dict) --

    • schemaArn (string) --

      The Amazon Resource Name (ARN) of the created schema.

Exceptions

create_solution(**kwargs)

Creates the configuration for training a model. A trained model is known as a solution. After the configuration is created, you train the model (create a solution) by calling the CreateSolutionVersion operation. Every time you call CreateSolutionVersion , a new version of the solution is created.

After creating a solution version, you check its accuracy by calling GetSolutionMetrics. When you are satisfied with the version, you deploy it using CreateCampaign. The campaign provides recommendations to a client through the GetRecommendations API.

To train a model, Amazon Personalize requires training data and a recipe. The training data comes from the dataset group that you provide in the request. A recipe specifies the training algorithm and a feature transformation. You can specify one of the predefined recipes provided by Amazon Personalize. Alternatively, you can specify performAutoML and Amazon Personalize will analyze your data and select the optimum USER_PERSONALIZATION recipe for you.

Note

Amazon Personalize doesn't support configuring the hpoObjective for solution hyperparameter optimization at this time.

Status

A solution can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING > DELETE IN_PROGRESS

To get the status of the solution, call DescribeSolution. Wait until the status shows as ACTIVE before calling CreateSolutionVersion .

Related APIs

See also: AWS API Documentation

Request Syntax

response = client.create_solution(
    name='string',
    performHPO=True|False,
    performAutoML=True|False,
    recipeArn='string',
    datasetGroupArn='string',
    eventType='string',
    solutionConfig={
        'eventValueThreshold': 'string',
        'hpoConfig': {
            'hpoObjective': {
                'type': 'string',
                'metricName': 'string',
                'metricRegex': 'string'
            },
            'hpoResourceConfig': {
                'maxNumberOfTrainingJobs': 'string',
                'maxParallelTrainingJobs': 'string'
            },
            'algorithmHyperParameterRanges': {
                'integerHyperParameterRanges': [
                    {
                        'name': 'string',
                        'minValue': 123,
                        'maxValue': 123
                    },
                ],
                'continuousHyperParameterRanges': [
                    {
                        'name': 'string',
                        'minValue': 123.0,
                        'maxValue': 123.0
                    },
                ],
                'categoricalHyperParameterRanges': [
                    {
                        'name': 'string',
                        'values': [
                            'string',
                        ]
                    },
                ]
            }
        },
        'algorithmHyperParameters': {
            'string': 'string'
        },
        'featureTransformationParameters': {
            'string': 'string'
        },
        'autoMLConfig': {
            'metricName': 'string',
            'recipeList': [
                'string',
            ]
        },
        'optimizationObjective': {
            'itemAttribute': 'string',
            'objectiveSensitivity': 'LOW'|'MEDIUM'|'HIGH'|'OFF'
        }
    },
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • name (string) --

    [REQUIRED]

    The name for the solution.

  • performHPO (boolean) --

    Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false .

    When performing AutoML, this parameter is always true and you should not set it to false .

  • performAutoML (boolean) --

    Whether to perform automated machine learning (AutoML). The default is false . For this case, you must specify recipeArn .

    When set to true , Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn . Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.

  • recipeArn (string) -- The ARN of the recipe to use for model training. Only specified when performAutoML is false.
  • datasetGroupArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the dataset group that provides the training data.

  • eventType (string) --

    When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.

    If you do not provide an eventType , Amazon Personalize will use all interactions for training with equal weight regardless of type.

  • solutionConfig (dict) --

    The configuration to use with the solution. When performAutoML is set to true, Amazon Personalize only evaluates the autoMLConfig section of the solution configuration.

    Note

    Amazon Personalize doesn't support configuring the hpoObjective at this time.

    • eventValueThreshold (string) --

      Only events with a value greater than or equal to this threshold are used for training a model.

    • hpoConfig (dict) --

      Describes the properties for hyperparameter optimization (HPO).

      • hpoObjective (dict) --

        The metric to optimize during HPO.

        Note

        Amazon Personalize doesn't support configuring the hpoObjective at this time.

        • type (string) --

          The type of the metric. Valid values are Maximize and Minimize .

        • metricName (string) --

          The name of the metric.

        • metricRegex (string) --

          A regular expression for finding the metric in the training job logs.

      • hpoResourceConfig (dict) --

        Describes the resource configuration for HPO.

        • maxNumberOfTrainingJobs (string) --

          The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40 .

        • maxParallelTrainingJobs (string) --

          The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10 .

      • algorithmHyperParameterRanges (dict) --

        The hyperparameters and their allowable ranges.

        • integerHyperParameterRanges (list) --

          The integer-valued hyperparameters and their ranges.

          • (dict) --

            Provides the name and range of an integer-valued hyperparameter.

            • name (string) --

              The name of the hyperparameter.

            • minValue (integer) --

              The minimum allowable value for the hyperparameter.

            • maxValue (integer) --

              The maximum allowable value for the hyperparameter.

        • continuousHyperParameterRanges (list) --

          The continuous hyperparameters and their ranges.

          • (dict) --

            Provides the name and range of a continuous hyperparameter.

            • name (string) --

              The name of the hyperparameter.

            • minValue (float) --

              The minimum allowable value for the hyperparameter.

            • maxValue (float) --

              The maximum allowable value for the hyperparameter.

        • categoricalHyperParameterRanges (list) --

          The categorical hyperparameters and their ranges.

          • (dict) --

            Provides the name and range of a categorical hyperparameter.

            • name (string) --

              The name of the hyperparameter.

            • values (list) --

              A list of the categories for the hyperparameter.

              • (string) --
    • algorithmHyperParameters (dict) --

      Lists the hyperparameter names and ranges.

      • (string) --
        • (string) --
    • featureTransformationParameters (dict) --

      Lists the feature transformation parameters.

      • (string) --
        • (string) --
    • autoMLConfig (dict) --

      The AutoMLConfig object containing a list of recipes to search when AutoML is performed.

      • metricName (string) --

        The metric to optimize.

      • recipeList (list) --

        The list of candidate recipes.

        • (string) --
    • optimizationObjective (dict) --

      Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.

      • itemAttribute (string) --

        The numerical metadata column in an Items dataset related to the optimization objective. For example, VIDEO_LENGTH (to maximize streaming minutes), or PRICE (to maximize revenue).

      • objectiveSensitivity (string) --

        Specifies how Amazon Personalize balances the importance of your optimization objective versus relevance.

  • tags (list) --

    A list of tags to apply to the solution.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'solutionArn': 'string'
}

Response Structure

  • (dict) --

    • solutionArn (string) --

      The ARN of the solution.

Exceptions

create_solution_version(**kwargs)

Trains or retrains an active solution in a Custom dataset group. A solution is created using the CreateSolution operation and must be in the ACTIVE state before calling CreateSolutionVersion . A new version of the solution is created every time you call this operation.

Status

A solution version can be in one of the following states:

  • CREATE PENDING
  • CREATE IN_PROGRESS
  • ACTIVE
  • CREATE FAILED
  • CREATE STOPPING
  • CREATE STOPPED

To get the status of the version, call DescribeSolutionVersion. Wait until the status shows as ACTIVE before calling CreateCampaign .

If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed.

Related APIs

See also: AWS API Documentation

Request Syntax

response = client.create_solution_version(
    name='string',
    solutionArn='string',
    trainingMode='FULL'|'UPDATE',
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • name (string) -- The name of the solution version.
  • solutionArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the solution containing the training configuration information.

  • trainingMode (string) --

    The scope of training to be performed when creating the solution version. The FULL option trains the solution version based on the entirety of the input solution's training data, while the UPDATE option processes only the data that has changed in comparison to the input solution. Choose UPDATE when you want to incrementally update your solution version instead of creating an entirely new one.

    Warning

    The UPDATE option can only be used when you already have an active solution version created from the input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the HRNN-Coldstart recipe.

  • tags (list) --

    A list of tags to apply to the solution version.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{
    'solutionVersionArn': 'string'
}

Response Structure

  • (dict) --

    • solutionVersionArn (string) --

      The ARN of the new solution version.

Exceptions

delete_campaign(**kwargs)

Removes a campaign by deleting the solution deployment. The solution that the campaign is based on is not deleted and can be redeployed when needed. A deleted campaign can no longer be specified in a GetRecommendations request. For information on creating campaigns, see CreateCampaign.

See also: AWS API Documentation

Request Syntax

response = client.delete_campaign(
    campaignArn='string'
)
Parameters
campaignArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the campaign to delete.

Returns
None

Exceptions

delete_dataset(**kwargs)

Deletes a dataset. You can't delete a dataset if an associated DatasetImportJob or SolutionVersion is in the CREATE PENDING or IN PROGRESS state. For more information on datasets, see CreateDataset.

See also: AWS API Documentation

Request Syntax

response = client.delete_dataset(
    datasetArn='string'
)
Parameters
datasetArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the dataset to delete.

Returns
None

Exceptions

delete_dataset_group(**kwargs)

Deletes a dataset group. Before you delete a dataset group, you must delete the following:

  • All associated event trackers.
  • All associated solutions.
  • All datasets in the dataset group.

See also: AWS API Documentation

Request Syntax

response = client.delete_dataset_group(
    datasetGroupArn='string'
)
Parameters
datasetGroupArn (string) --

[REQUIRED]

The ARN of the dataset group to delete.

Returns
None

Exceptions

delete_event_tracker(**kwargs)

Deletes the event tracker. Does not delete the event-interactions dataset from the associated dataset group. For more information on event trackers, see CreateEventTracker.

See also: AWS API Documentation

Request Syntax

response = client.delete_event_tracker(
    eventTrackerArn='string'
)
Parameters
eventTrackerArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the event tracker to delete.

Returns
None

Exceptions

delete_filter(**kwargs)

Deletes a filter.

See also: AWS API Documentation

Request Syntax

response = client.delete_filter(
    filterArn='string'
)
Parameters
filterArn (string) --

[REQUIRED]

The ARN of the filter to delete.

Returns
None

Exceptions

delete_metric_attribution(**kwargs)

Deletes a metric attribution.

See also: AWS API Documentation

Request Syntax

response = client.delete_metric_attribution(
    metricAttributionArn='string'
)
Parameters
metricAttributionArn (string) --

[REQUIRED]

The metric attribution's Amazon Resource Name (ARN).

Returns
None

Exceptions

delete_recommender(**kwargs)

Deactivates and removes a recommender. A deleted recommender can no longer be specified in a GetRecommendations request.

See also: AWS API Documentation

Request Syntax

response = client.delete_recommender(
    recommenderArn='string'
)
Parameters
recommenderArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the recommender to delete.

Returns
None

Exceptions

delete_schema(**kwargs)

Deletes a schema. Before deleting a schema, you must delete all datasets referencing the schema. For more information on schemas, see CreateSchema.

See also: AWS API Documentation

Request Syntax

response = client.delete_schema(
    schemaArn='string'
)
Parameters
schemaArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the schema to delete.

Returns
None

Exceptions

delete_solution(**kwargs)

Deletes all versions of a solution and the Solution object itself. Before deleting a solution, you must delete all campaigns based on the solution. To determine what campaigns are using the solution, call ListCampaigns and supply the Amazon Resource Name (ARN) of the solution. You can't delete a solution if an associated SolutionVersion is in the CREATE PENDING or IN PROGRESS state. For more information on solutions, see CreateSolution.

See also: AWS API Documentation

Request Syntax

response = client.delete_solution(
    solutionArn='string'
)
Parameters
solutionArn (string) --

[REQUIRED]

The ARN of the solution to delete.

Returns
None

Exceptions

describe_algorithm(**kwargs)

Describes the given algorithm.

See also: AWS API Documentation

Request Syntax

response = client.describe_algorithm(
    algorithmArn='string'
)
Parameters
algorithmArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the algorithm to describe.

Return type
dict
Returns
Response Syntax
{
    'algorithm': {
        'name': 'string',
        'algorithmArn': 'string',
        'algorithmImage': {
            'name': 'string',
            'dockerURI': 'string'
        },
        'defaultHyperParameters': {
            'string': 'string'
        },
        'defaultHyperParameterRanges': {
            'integerHyperParameterRanges': [
                {
                    'name': 'string',
                    'minValue': 123,
                    'maxValue': 123,
                    'isTunable': True|False
                },
            ],
            'continuousHyperParameterRanges': [
                {
                    'name': 'string',
                    'minValue': 123.0,
                    'maxValue': 123.0,
                    'isTunable': True|False
                },
            ],
            'categoricalHyperParameterRanges': [
                {
                    'name': 'string',
                    'values': [
                        'string',
                    ],
                    'isTunable': True|False
                },
            ]
        },
        'defaultResourceConfig': {
            'string': 'string'
        },
        'trainingInputMode': 'string',
        'roleArn': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1)
    }
}

Response Structure

  • (dict) --
    • algorithm (dict) --

      A listing of the properties of the algorithm.

      • name (string) --

        The name of the algorithm.

      • algorithmArn (string) --

        The Amazon Resource Name (ARN) of the algorithm.

      • algorithmImage (dict) --

        The URI of the Docker container for the algorithm image.

        • name (string) --

          The name of the algorithm image.

        • dockerURI (string) --

          The URI of the Docker container for the algorithm image.

      • defaultHyperParameters (dict) --

        Specifies the default hyperparameters.

        • (string) --
          • (string) --
      • defaultHyperParameterRanges (dict) --

        Specifies the default hyperparameters, their ranges, and whether they are tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).

        • integerHyperParameterRanges (list) --

          The integer-valued hyperparameters and their default ranges.

          • (dict) --

            Provides the name and default range of a integer-valued hyperparameter and whether the hyperparameter is tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).

            • name (string) --

              The name of the hyperparameter.

            • minValue (integer) --

              The minimum allowable value for the hyperparameter.

            • maxValue (integer) --

              The maximum allowable value for the hyperparameter.

            • isTunable (boolean) --

              Indicates whether the hyperparameter is tunable.

        • continuousHyperParameterRanges (list) --

          The continuous hyperparameters and their default ranges.

          • (dict) --

            Provides the name and default range of a continuous hyperparameter and whether the hyperparameter is tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).

            • name (string) --

              The name of the hyperparameter.

            • minValue (float) --

              The minimum allowable value for the hyperparameter.

            • maxValue (float) --

              The maximum allowable value for the hyperparameter.

            • isTunable (boolean) --

              Whether the hyperparameter is tunable.

        • categoricalHyperParameterRanges (list) --

          The categorical hyperparameters and their default ranges.

          • (dict) --

            Provides the name and default range of a categorical hyperparameter and whether the hyperparameter is tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).

            • name (string) --

              The name of the hyperparameter.

            • values (list) --

              A list of the categories for the hyperparameter.

              • (string) --
            • isTunable (boolean) --

              Whether the hyperparameter is tunable.

      • defaultResourceConfig (dict) --

        Specifies the default maximum number of training jobs and parallel training jobs.

        • (string) --
          • (string) --
      • trainingInputMode (string) --

        The training input mode.

      • roleArn (string) --

        The Amazon Resource Name (ARN) of the role.

      • creationDateTime (datetime) --

        The date and time (in Unix time) that the algorithm was created.

      • lastUpdatedDateTime (datetime) --

        The date and time (in Unix time) that the algorithm was last updated.

Exceptions

describe_batch_inference_job(**kwargs)

Gets the properties of a batch inference job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate the recommendations.

See also: AWS API Documentation

Request Syntax

response = client.describe_batch_inference_job(
    batchInferenceJobArn='string'
)
Parameters
batchInferenceJobArn (string) --

[REQUIRED]

The ARN of the batch inference job to describe.

Return type
dict
Returns
Response Syntax
{
    'batchInferenceJob': {
        'jobName': 'string',
        'batchInferenceJobArn': 'string',
        'filterArn': 'string',
        'failureReason': 'string',
        'solutionVersionArn': 'string',
        'numResults': 123,
        'jobInput': {
            's3DataSource': {
                'path': 'string',
                'kmsKeyArn': 'string'
            }
        },
        'jobOutput': {
            's3DataDestination': {
                'path': 'string',
                'kmsKeyArn': 'string'
            }
        },
        'batchInferenceJobConfig': {
            'itemExplorationConfig': {
                'string': 'string'
            }
        },
        'roleArn': 'string',
        'status': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1)
    }
}

Response Structure

  • (dict) --
    • batchInferenceJob (dict) --

      Information on the specified batch inference job.

      • jobName (string) --

        The name of the batch inference job.

      • batchInferenceJobArn (string) --

        The Amazon Resource Name (ARN) of the batch inference job.

      • filterArn (string) --

        The ARN of the filter used on the batch inference job.

      • failureReason (string) --

        If the batch inference job failed, the reason for the failure.

      • solutionVersionArn (string) --

        The Amazon Resource Name (ARN) of the solution version from which the batch inference job was created.

      • numResults (integer) --

        The number of recommendations generated by the batch inference job. This number includes the error messages generated for failed input records.

      • jobInput (dict) --

        The Amazon S3 path that leads to the input data used to generate the batch inference job.

        • s3DataSource (dict) --

          The URI of the Amazon S3 location that contains your input data. The Amazon S3 bucket must be in the same region as the API endpoint you are calling.

          • path (string) --

            The file path of the Amazon S3 bucket.

          • kmsKeyArn (string) --

            The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

      • jobOutput (dict) --

        The Amazon S3 bucket that contains the output data generated by the batch inference job.

        • s3DataDestination (dict) --

          Information on the Amazon S3 bucket in which the batch inference job's output is stored.

          • path (string) --

            The file path of the Amazon S3 bucket.

          • kmsKeyArn (string) --

            The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

      • batchInferenceJobConfig (dict) --

        A string to string map of the configuration details of a batch inference job.

        • itemExplorationConfig (dict) --

          A string to string map specifying the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. See User-Personalization.

          • (string) --
            • (string) --
      • roleArn (string) --

        The ARN of the Amazon Identity and Access Management (IAM) role that requested the batch inference job.

      • status (string) --

        The status of the batch inference job. The status is one of the following values:

        • PENDING
        • IN PROGRESS
        • ACTIVE
        • CREATE FAILED
      • creationDateTime (datetime) --

        The time at which the batch inference job was created.

      • lastUpdatedDateTime (datetime) --

        The time at which the batch inference job was last updated.

Exceptions

describe_batch_segment_job(**kwargs)

Gets the properties of a batch segment job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate segments.

See also: AWS API Documentation

Request Syntax

response = client.describe_batch_segment_job(
    batchSegmentJobArn='string'
)
Parameters
batchSegmentJobArn (string) --

[REQUIRED]

The ARN of the batch segment job to describe.

Return type
dict
Returns
Response Syntax
{
    'batchSegmentJob': {
        'jobName': 'string',
        'batchSegmentJobArn': 'string',
        'filterArn': 'string',
        'failureReason': 'string',
        'solutionVersionArn': 'string',
        'numResults': 123,
        'jobInput': {
            's3DataSource': {
                'path': 'string',
                'kmsKeyArn': 'string'
            }
        },
        'jobOutput': {
            's3DataDestination': {
                'path': 'string',
                'kmsKeyArn': 'string'
            }
        },
        'roleArn': 'string',
        'status': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1)
    }
}

Response Structure

  • (dict) --
    • batchSegmentJob (dict) --

      Information on the specified batch segment job.

      • jobName (string) --

        The name of the batch segment job.

      • batchSegmentJobArn (string) --

        The Amazon Resource Name (ARN) of the batch segment job.

      • filterArn (string) --

        The ARN of the filter used on the batch segment job.

      • failureReason (string) --

        If the batch segment job failed, the reason for the failure.

      • solutionVersionArn (string) --

        The Amazon Resource Name (ARN) of the solution version used by the batch segment job to generate batch segments.

      • numResults (integer) --

        The number of predicted users generated by the batch segment job for each line of input data.

      • jobInput (dict) --

        The Amazon S3 path that leads to the input data used to generate the batch segment job.

        • s3DataSource (dict) --

          The configuration details of an Amazon S3 input or output bucket.

          • path (string) --

            The file path of the Amazon S3 bucket.

          • kmsKeyArn (string) --

            The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

      • jobOutput (dict) --

        The Amazon S3 bucket that contains the output data generated by the batch segment job.

        • s3DataDestination (dict) --

          The configuration details of an Amazon S3 input or output bucket.

          • path (string) --

            The file path of the Amazon S3 bucket.

          • kmsKeyArn (string) --

            The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

      • roleArn (string) --

        The ARN of the Amazon Identity and Access Management (IAM) role that requested the batch segment job.

      • status (string) --

        The status of the batch segment job. The status is one of the following values:

        • PENDING
        • IN PROGRESS
        • ACTIVE
        • CREATE FAILED
      • creationDateTime (datetime) --

        The time at which the batch segment job was created.

      • lastUpdatedDateTime (datetime) --

        The time at which the batch segment job last updated.

Exceptions

describe_campaign(**kwargs)

Describes the given campaign, including its status.

A campaign can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • DELETE PENDING > DELETE IN_PROGRESS

When the status is CREATE FAILED , the response includes the failureReason key, which describes why.

For more information on campaigns, see CreateCampaign.

See also: AWS API Documentation

Request Syntax

response = client.describe_campaign(
    campaignArn='string'
)
Parameters
campaignArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the campaign.

Return type
dict
Returns
Response Syntax
{
    'campaign': {
        'name': 'string',
        'campaignArn': 'string',
        'solutionVersionArn': 'string',
        'minProvisionedTPS': 123,
        'campaignConfig': {
            'itemExplorationConfig': {
                'string': 'string'
            }
        },
        'status': 'string',
        'failureReason': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'latestCampaignUpdate': {
            'solutionVersionArn': 'string',
            'minProvisionedTPS': 123,
            'campaignConfig': {
                'itemExplorationConfig': {
                    'string': 'string'
                }
            },
            'status': 'string',
            'failureReason': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1)
        }
    }
}

Response Structure

  • (dict) --
    • campaign (dict) --

      The properties of the campaign.

      • name (string) --

        The name of the campaign.

      • campaignArn (string) --

        The Amazon Resource Name (ARN) of the campaign.

      • solutionVersionArn (string) --

        The Amazon Resource Name (ARN) of a specific version of the solution.

      • minProvisionedTPS (integer) --

        Specifies the requested minimum provisioned transactions (recommendations) per second.

      • campaignConfig (dict) --

        The configuration details of a campaign.

        • itemExplorationConfig (dict) --

          Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your solution uses the User-Personalization recipe.

          • (string) --
            • (string) --
      • status (string) --

        The status of the campaign.

        A campaign can be in one of the following states:

        • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • DELETE PENDING > DELETE IN_PROGRESS
      • failureReason (string) --

        If a campaign fails, the reason behind the failure.

      • creationDateTime (datetime) --

        The date and time (in Unix format) that the campaign was created.

      • lastUpdatedDateTime (datetime) --

        The date and time (in Unix format) that the campaign was last updated.

      • latestCampaignUpdate (dict) --

        Provides a summary of the properties of a campaign update. For a complete listing, call the DescribeCampaign API.

        • solutionVersionArn (string) --

          The Amazon Resource Name (ARN) of the deployed solution version.

        • minProvisionedTPS (integer) --

          Specifies the requested minimum provisioned transactions (recommendations) per second that Amazon Personalize will support.

        • campaignConfig (dict) --

          The configuration details of a campaign.

          • itemExplorationConfig (dict) --

            Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your solution uses the User-Personalization recipe.

            • (string) --
              • (string) --
        • status (string) --

          The status of the campaign update.

          A campaign update can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING > DELETE IN_PROGRESS
        • failureReason (string) --

          If a campaign update fails, the reason behind the failure.

        • creationDateTime (datetime) --

          The date and time (in Unix time) that the campaign update was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the campaign update was last updated.

Exceptions

describe_dataset(**kwargs)

Describes the given dataset. For more information on datasets, see CreateDataset.

See also: AWS API Documentation

Request Syntax

response = client.describe_dataset(
    datasetArn='string'
)
Parameters
datasetArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the dataset to describe.

Return type
dict
Returns
Response Syntax
{
    'dataset': {
        'name': 'string',
        'datasetArn': 'string',
        'datasetGroupArn': 'string',
        'datasetType': 'string',
        'schemaArn': 'string',
        'status': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1)
    }
}

Response Structure

  • (dict) --
    • dataset (dict) --

      A listing of the dataset's properties.

      • name (string) --

        The name of the dataset.

      • datasetArn (string) --

        The Amazon Resource Name (ARN) of the dataset that you want metadata for.

      • datasetGroupArn (string) --

        The Amazon Resource Name (ARN) of the dataset group.

      • datasetType (string) --

        One of the following values:

        • Interactions
        • Items
        • Users
      • schemaArn (string) --

        The ARN of the associated schema.

      • status (string) --

        The status of the dataset.

        A dataset can be in one of the following states:

        • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • DELETE PENDING > DELETE IN_PROGRESS
      • creationDateTime (datetime) --

        The creation date and time (in Unix time) of the dataset.

      • lastUpdatedDateTime (datetime) --

        A time stamp that shows when the dataset was updated.

Exceptions

describe_dataset_export_job(**kwargs)

Describes the dataset export job created by CreateDatasetExportJob, including the export job status.

See also: AWS API Documentation

Request Syntax

response = client.describe_dataset_export_job(
    datasetExportJobArn='string'
)
Parameters
datasetExportJobArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the dataset export job to describe.

Return type
dict
Returns
Response Syntax
{
    'datasetExportJob': {
        'jobName': 'string',
        'datasetExportJobArn': 'string',
        'datasetArn': 'string',
        'ingestionMode': 'BULK'|'PUT'|'ALL',
        'roleArn': 'string',
        'status': 'string',
        'jobOutput': {
            's3DataDestination': {
                'path': 'string',
                'kmsKeyArn': 'string'
            }
        },
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'failureReason': 'string'
    }
}

Response Structure

  • (dict) --
    • datasetExportJob (dict) --

      Information about the dataset export job, including the status.

      The status is one of the following values:

      • CREATE PENDING
      • CREATE IN_PROGRESS
      • ACTIVE
      • CREATE FAILED
      • jobName (string) --

        The name of the export job.

      • datasetExportJobArn (string) --

        The Amazon Resource Name (ARN) of the dataset export job.

      • datasetArn (string) --

        The Amazon Resource Name (ARN) of the dataset to export.

      • ingestionMode (string) --

        The data to export, based on how you imported the data. You can choose to export BULK data that you imported using a dataset import job, PUT data that you imported incrementally (using the console, PutEvents, PutUsers and PutItems operations), or ALL for both types. The default value is PUT .

      • roleArn (string) --

        The Amazon Resource Name (ARN) of the IAM service role that has permissions to add data to your output Amazon S3 bucket.

      • status (string) --

        The status of the dataset export job.

        A dataset export job can be in one of the following states:

        • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
      • jobOutput (dict) --

        The path to the Amazon S3 bucket where the job's output is stored. For example:

        s3://bucket-name/folder-name/
        • s3DataDestination (dict) --

          The configuration details of an Amazon S3 input or output bucket.

          • path (string) --

            The file path of the Amazon S3 bucket.

          • kmsKeyArn (string) --

            The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

      • creationDateTime (datetime) --

        The creation date and time (in Unix time) of the dataset export job.

      • lastUpdatedDateTime (datetime) --

        The date and time (in Unix time) the status of the dataset export job was last updated.

      • failureReason (string) --

        If a dataset export job fails, provides the reason why.

Exceptions

describe_dataset_group(**kwargs)

Describes the given dataset group. For more information on dataset groups, see CreateDatasetGroup.

See also: AWS API Documentation

Request Syntax

response = client.describe_dataset_group(
    datasetGroupArn='string'
)
Parameters
datasetGroupArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the dataset group to describe.

Return type
dict
Returns
Response Syntax
{
    'datasetGroup': {
        'name': 'string',
        'datasetGroupArn': 'string',
        'status': 'string',
        'roleArn': 'string',
        'kmsKeyArn': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'failureReason': 'string',
        'domain': 'ECOMMERCE'|'VIDEO_ON_DEMAND'
    }
}

Response Structure

  • (dict) --
    • datasetGroup (dict) --

      A listing of the dataset group's properties.

      • name (string) --

        The name of the dataset group.

      • datasetGroupArn (string) --

        The Amazon Resource Name (ARN) of the dataset group.

      • status (string) --

        The current status of the dataset group.

        A dataset group can be in one of the following states:

        • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • DELETE PENDING
      • roleArn (string) --

        The ARN of the IAM role that has permissions to create the dataset group.

      • kmsKeyArn (string) --

        The Amazon Resource Name (ARN) of the Key Management Service (KMS) key used to encrypt the datasets.

      • creationDateTime (datetime) --

        The creation date and time (in Unix time) of the dataset group.

      • lastUpdatedDateTime (datetime) --

        The last update date and time (in Unix time) of the dataset group.

      • failureReason (string) --

        If creating a dataset group fails, provides the reason why.

      • domain (string) --

        The domain of a Domain dataset group.

Exceptions

describe_dataset_import_job(**kwargs)

Describes the dataset import job created by CreateDatasetImportJob, including the import job status.

See also: AWS API Documentation

Request Syntax

response = client.describe_dataset_import_job(
    datasetImportJobArn='string'
)
Parameters
datasetImportJobArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the dataset import job to describe.

Return type
dict
Returns
Response Syntax
{
    'datasetImportJob': {
        'jobName': 'string',
        'datasetImportJobArn': 'string',
        'datasetArn': 'string',
        'dataSource': {
            'dataLocation': 'string'
        },
        'roleArn': 'string',
        'status': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'failureReason': 'string',
        'importMode': 'FULL'|'INCREMENTAL',
        'publishAttributionMetricsToS3': True|False
    }
}

Response Structure

  • (dict) --
    • datasetImportJob (dict) --

      Information about the dataset import job, including the status.

      The status is one of the following values:

      • CREATE PENDING
      • CREATE IN_PROGRESS
      • ACTIVE
      • CREATE FAILED
      • jobName (string) --

        The name of the import job.

      • datasetImportJobArn (string) --

        The ARN of the dataset import job.

      • datasetArn (string) --

        The Amazon Resource Name (ARN) of the dataset that receives the imported data.

      • dataSource (dict) --

        The Amazon S3 bucket that contains the training data to import.

        • dataLocation (string) --

          The path to the Amazon S3 bucket where the data that you want to upload to your dataset is stored. For example:

          s3://bucket-name/folder-name/
      • roleArn (string) --

        The ARN of the IAM role that has permissions to read from the Amazon S3 data source.

      • status (string) --

        The status of the dataset import job.

        A dataset import job can be in one of the following states:

        • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
      • creationDateTime (datetime) --

        The creation date and time (in Unix time) of the dataset import job.

      • lastUpdatedDateTime (datetime) --

        The date and time (in Unix time) the dataset was last updated.

      • failureReason (string) --

        If a dataset import job fails, provides the reason why.

      • importMode (string) --

        The import mode used by the dataset import job to import new records.

      • publishAttributionMetricsToS3 (boolean) --

        Whether the job publishes metrics to Amazon S3 for a metric attribution.

Exceptions

describe_event_tracker(**kwargs)

Describes an event tracker. The response includes the trackingId and status of the event tracker. For more information on event trackers, see CreateEventTracker.

See also: AWS API Documentation

Request Syntax

response = client.describe_event_tracker(
    eventTrackerArn='string'
)
Parameters
eventTrackerArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the event tracker to describe.

Return type
dict
Returns
Response Syntax
{
    'eventTracker': {
        'name': 'string',
        'eventTrackerArn': 'string',
        'accountId': 'string',
        'trackingId': 'string',
        'datasetGroupArn': 'string',
        'status': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1)
    }
}

Response Structure

  • (dict) --
    • eventTracker (dict) --

      An object that describes the event tracker.

      • name (string) --

        The name of the event tracker.

      • eventTrackerArn (string) --

        The ARN of the event tracker.

      • accountId (string) --

        The Amazon Web Services account that owns the event tracker.

      • trackingId (string) --

        The ID of the event tracker. Include this ID in requests to the PutEvents API.

      • datasetGroupArn (string) --

        The Amazon Resource Name (ARN) of the dataset group that receives the event data.

      • status (string) --

        The status of the event tracker.

        An event tracker can be in one of the following states:

        • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • DELETE PENDING > DELETE IN_PROGRESS
      • creationDateTime (datetime) --

        The date and time (in Unix format) that the event tracker was created.

      • lastUpdatedDateTime (datetime) --

        The date and time (in Unix time) that the event tracker was last updated.

Exceptions

describe_feature_transformation(**kwargs)

Describes the given feature transformation.

See also: AWS API Documentation

Request Syntax

response = client.describe_feature_transformation(
    featureTransformationArn='string'
)
Parameters
featureTransformationArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the feature transformation to describe.

Return type
dict
Returns
Response Syntax
{
    'featureTransformation': {
        'name': 'string',
        'featureTransformationArn': 'string',
        'defaultParameters': {
            'string': 'string'
        },
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'status': 'string'
    }
}

Response Structure

  • (dict) --
    • featureTransformation (dict) --

      A listing of the FeatureTransformation properties.

      • name (string) --

        The name of the feature transformation.

      • featureTransformationArn (string) --

        The Amazon Resource Name (ARN) of the FeatureTransformation object.

      • defaultParameters (dict) --

        Provides the default parameters for feature transformation.

        • (string) --
          • (string) --
      • creationDateTime (datetime) --

        The creation date and time (in Unix time) of the feature transformation.

      • lastUpdatedDateTime (datetime) --

        The last update date and time (in Unix time) of the feature transformation.

      • status (string) --

        The status of the feature transformation.

        A feature transformation can be in one of the following states:

        • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

Exceptions

describe_filter(**kwargs)

Describes a filter's properties.

See also: AWS API Documentation

Request Syntax

response = client.describe_filter(
    filterArn='string'
)
Parameters
filterArn (string) --

[REQUIRED]

The ARN of the filter to describe.

Return type
dict
Returns
Response Syntax
{
    'filter': {
        'name': 'string',
        'filterArn': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'datasetGroupArn': 'string',
        'failureReason': 'string',
        'filterExpression': 'string',
        'status': 'string'
    }
}

Response Structure

  • (dict) --
    • filter (dict) --

      The filter's details.

      • name (string) --

        The name of the filter.

      • filterArn (string) --

        The ARN of the filter.

      • creationDateTime (datetime) --

        The time at which the filter was created.

      • lastUpdatedDateTime (datetime) --

        The time at which the filter was last updated.

      • datasetGroupArn (string) --

        The ARN of the dataset group to which the filter belongs.

      • failureReason (string) --

        If the filter failed, the reason for its failure.

      • filterExpression (string) --

        Specifies the type of item interactions to filter out of recommendation results. The filter expression must follow specific format rules. For information about filter expression structure and syntax, see Filter expressions.

      • status (string) --

        The status of the filter.

Exceptions

describe_metric_attribution(**kwargs)

Describes a metric attribution.

See also: AWS API Documentation

Request Syntax

response = client.describe_metric_attribution(
    metricAttributionArn='string'
)
Parameters
metricAttributionArn (string) --

[REQUIRED]

The metric attribution's Amazon Resource Name (ARN).

Return type
dict
Returns
Response Syntax
{
    'metricAttribution': {
        'name': 'string',
        'metricAttributionArn': 'string',
        'datasetGroupArn': 'string',
        'metricsOutputConfig': {
            's3DataDestination': {
                'path': 'string',
                'kmsKeyArn': 'string'
            },
            'roleArn': 'string'
        },
        'status': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'failureReason': 'string'
    }
}

Response Structure

  • (dict) --
    • metricAttribution (dict) --

      The details of the metric attribution.

      • name (string) --

        The metric attribution's name.

      • metricAttributionArn (string) --

        The metric attribution's Amazon Resource Name (ARN).

      • datasetGroupArn (string) --

        The metric attribution's dataset group Amazon Resource Name (ARN).

      • metricsOutputConfig (dict) --

        The metric attribution's output configuration.

        • s3DataDestination (dict) --

          The configuration details of an Amazon S3 input or output bucket.

          • path (string) --

            The file path of the Amazon S3 bucket.

          • kmsKeyArn (string) --

            The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

        • roleArn (string) --

          The Amazon Resource Name (ARN) of the IAM service role that has permissions to add data to your output Amazon S3 bucket and add metrics to Amazon CloudWatch. For more information, see Measuring impact of recommendations.

      • status (string) --

        The metric attribution's status.

      • creationDateTime (datetime) --

        The metric attribution's creation date time.

      • lastUpdatedDateTime (datetime) --

        The metric attribution's last updated date time.

      • failureReason (string) --

        The metric attribution's failure reason.

Exceptions

describe_recipe(**kwargs)

Describes a recipe.

A recipe contains three items:

  • An algorithm that trains a model.
  • Hyperparameters that govern the training.
  • Feature transformation information for modifying the input data before training.

Amazon Personalize provides a set of predefined recipes. You specify a recipe when you create a solution with the CreateSolution API. CreateSolution trains a model by using the algorithm in the specified recipe and a training dataset. The solution, when deployed as a campaign, can provide recommendations using the GetRecommendations API.

See also: AWS API Documentation

Request Syntax

response = client.describe_recipe(
    recipeArn='string'
)
Parameters
recipeArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the recipe to describe.

Return type
dict
Returns
Response Syntax
{
    'recipe': {
        'name': 'string',
        'recipeArn': 'string',
        'algorithmArn': 'string',
        'featureTransformationArn': 'string',
        'status': 'string',
        'description': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'recipeType': 'string',
        'lastUpdatedDateTime': datetime(2015, 1, 1)
    }
}

Response Structure

  • (dict) --
    • recipe (dict) --

      An object that describes the recipe.

      • name (string) --

        The name of the recipe.

      • recipeArn (string) --

        The Amazon Resource Name (ARN) of the recipe.

      • algorithmArn (string) --

        The Amazon Resource Name (ARN) of the algorithm that Amazon Personalize uses to train the model.

      • featureTransformationArn (string) --

        The ARN of the FeatureTransformation object.

      • status (string) --

        The status of the recipe.

      • description (string) --

        The description of the recipe.

      • creationDateTime (datetime) --

        The date and time (in Unix format) that the recipe was created.

      • recipeType (string) --

        One of the following values:

        • PERSONALIZED_RANKING
        • RELATED_ITEMS
        • USER_PERSONALIZATION
      • lastUpdatedDateTime (datetime) --

        The date and time (in Unix format) that the recipe was last updated.

Exceptions

describe_recommender(**kwargs)

Describes the given recommender, including its status.

A recommender can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
  • STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
  • DELETE PENDING > DELETE IN_PROGRESS

When the status is CREATE FAILED , the response includes the failureReason key, which describes why.

The modelMetrics key is null when the recommender is being created or deleted.

For more information on recommenders, see CreateRecommender.

See also: AWS API Documentation

Request Syntax

response = client.describe_recommender(
    recommenderArn='string'
)
Parameters
recommenderArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the recommender to describe.

Return type
dict
Returns
Response Syntax
{
    'recommender': {
        'recommenderArn': 'string',
        'datasetGroupArn': 'string',
        'name': 'string',
        'recipeArn': 'string',
        'recommenderConfig': {
            'itemExplorationConfig': {
                'string': 'string'
            },
            'minRecommendationRequestsPerSecond': 123
        },
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'status': 'string',
        'failureReason': 'string',
        'latestRecommenderUpdate': {
            'recommenderConfig': {
                'itemExplorationConfig': {
                    'string': 'string'
                },
                'minRecommendationRequestsPerSecond': 123
            },
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'status': 'string',
            'failureReason': 'string'
        },
        'modelMetrics': {
            'string': 123.0
        }
    }
}

Response Structure

  • (dict) --
    • recommender (dict) --

      The properties of the recommender.

      • recommenderArn (string) --

        The Amazon Resource Name (ARN) of the recommender.

      • datasetGroupArn (string) --

        The Amazon Resource Name (ARN) of the Domain dataset group that contains the recommender.

      • name (string) --

        The name of the recommender.

      • recipeArn (string) --

        The Amazon Resource Name (ARN) of the recipe (Domain dataset group use case) that the recommender was created for.

      • recommenderConfig (dict) --

        The configuration details of the recommender.

        • itemExplorationConfig (dict) --

          Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your recommenders generate personalized recommendations for a user (not popular items or similar items).

          • (string) --
            • (string) --
        • minRecommendationRequestsPerSecond (integer) --

          Specifies the requested minimum provisioned recommendation requests per second that Amazon Personalize will support.

      • creationDateTime (datetime) --

        The date and time (in Unix format) that the recommender was created.

      • lastUpdatedDateTime (datetime) --

        The date and time (in Unix format) that the recommender was last updated.

      • status (string) --

        The status of the recommender.

        A recommender can be in one of the following states:

        • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
        • DELETE PENDING > DELETE IN_PROGRESS
      • failureReason (string) --

        If a recommender fails, the reason behind the failure.

      • latestRecommenderUpdate (dict) --

        Provides a summary of the latest updates to the recommender.

        • recommenderConfig (dict) --

          The configuration details of the recommender update.

          • itemExplorationConfig (dict) --

            Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your recommenders generate personalized recommendations for a user (not popular items or similar items).

            • (string) --
              • (string) --
          • minRecommendationRequestsPerSecond (integer) --

            Specifies the requested minimum provisioned recommendation requests per second that Amazon Personalize will support.

        • creationDateTime (datetime) --

          The date and time (in Unix format) that the recommender update was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the recommender update was last updated.

        • status (string) --

          The status of the recommender update.

          A recommender can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
          • DELETE PENDING > DELETE IN_PROGRESS
        • failureReason (string) --

          If a recommender update fails, the reason behind the failure.

      • modelMetrics (dict) --

        Provides evaluation metrics that help you determine the performance of a recommender. For more information, see Evaluating a recommender.

        • (string) --
          • (float) --

Exceptions

describe_schema(**kwargs)

Describes a schema. For more information on schemas, see CreateSchema.

See also: AWS API Documentation

Request Syntax

response = client.describe_schema(
    schemaArn='string'
)
Parameters
schemaArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the schema to retrieve.

Return type
dict
Returns
Response Syntax
{
    'schema': {
        'name': 'string',
        'schemaArn': 'string',
        'schema': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'domain': 'ECOMMERCE'|'VIDEO_ON_DEMAND'
    }
}

Response Structure

  • (dict) --
    • schema (dict) --

      The requested schema.

      • name (string) --

        The name of the schema.

      • schemaArn (string) --

        The Amazon Resource Name (ARN) of the schema.

      • schema (string) --

        The schema.

      • creationDateTime (datetime) --

        The date and time (in Unix time) that the schema was created.

      • lastUpdatedDateTime (datetime) --

        The date and time (in Unix time) that the schema was last updated.

      • domain (string) --

        The domain of a schema that you created for a dataset in a Domain dataset group.

Exceptions

describe_solution(**kwargs)

Describes a solution. For more information on solutions, see CreateSolution.

See also: AWS API Documentation

Request Syntax

response = client.describe_solution(
    solutionArn='string'
)
Parameters
solutionArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the solution to describe.

Return type
dict
Returns
Response Syntax
{
    'solution': {
        'name': 'string',
        'solutionArn': 'string',
        'performHPO': True|False,
        'performAutoML': True|False,
        'recipeArn': 'string',
        'datasetGroupArn': 'string',
        'eventType': 'string',
        'solutionConfig': {
            'eventValueThreshold': 'string',
            'hpoConfig': {
                'hpoObjective': {
                    'type': 'string',
                    'metricName': 'string',
                    'metricRegex': 'string'
                },
                'hpoResourceConfig': {
                    'maxNumberOfTrainingJobs': 'string',
                    'maxParallelTrainingJobs': 'string'
                },
                'algorithmHyperParameterRanges': {
                    'integerHyperParameterRanges': [
                        {
                            'name': 'string',
                            'minValue': 123,
                            'maxValue': 123
                        },
                    ],
                    'continuousHyperParameterRanges': [
                        {
                            'name': 'string',
                            'minValue': 123.0,
                            'maxValue': 123.0
                        },
                    ],
                    'categoricalHyperParameterRanges': [
                        {
                            'name': 'string',
                            'values': [
                                'string',
                            ]
                        },
                    ]
                }
            },
            'algorithmHyperParameters': {
                'string': 'string'
            },
            'featureTransformationParameters': {
                'string': 'string'
            },
            'autoMLConfig': {
                'metricName': 'string',
                'recipeList': [
                    'string',
                ]
            },
            'optimizationObjective': {
                'itemAttribute': 'string',
                'objectiveSensitivity': 'LOW'|'MEDIUM'|'HIGH'|'OFF'
            }
        },
        'autoMLResult': {
            'bestRecipeArn': 'string'
        },
        'status': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'latestSolutionVersion': {
            'solutionVersionArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string'
        }
    }
}

Response Structure

  • (dict) --
    • solution (dict) --

      An object that describes the solution.

      • name (string) --

        The name of the solution.

      • solutionArn (string) --

        The ARN of the solution.

      • performHPO (boolean) --

        Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false .

      • performAutoML (boolean) --

        When true, Amazon Personalize performs a search for the best USER_PERSONALIZATION recipe from the list specified in the solution configuration ( recipeArn must not be specified). When false (the default), Amazon Personalize uses recipeArn for training.

      • recipeArn (string) --

        The ARN of the recipe used to create the solution.

      • datasetGroupArn (string) --

        The Amazon Resource Name (ARN) of the dataset group that provides the training data.

      • eventType (string) --

        The event type (for example, 'click' or 'like') that is used for training the model. If no eventType is provided, Amazon Personalize uses all interactions for training with equal weight regardless of type.

      • solutionConfig (dict) --

        Describes the configuration properties for the solution.

        • eventValueThreshold (string) --

          Only events with a value greater than or equal to this threshold are used for training a model.

        • hpoConfig (dict) --

          Describes the properties for hyperparameter optimization (HPO).

          • hpoObjective (dict) --

            The metric to optimize during HPO.

            Note

            Amazon Personalize doesn't support configuring the hpoObjective at this time.

            • type (string) --

              The type of the metric. Valid values are Maximize and Minimize .

            • metricName (string) --

              The name of the metric.

            • metricRegex (string) --

              A regular expression for finding the metric in the training job logs.

          • hpoResourceConfig (dict) --

            Describes the resource configuration for HPO.

            • maxNumberOfTrainingJobs (string) --

              The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40 .

            • maxParallelTrainingJobs (string) --

              The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10 .

          • algorithmHyperParameterRanges (dict) --

            The hyperparameters and their allowable ranges.

            • integerHyperParameterRanges (list) --

              The integer-valued hyperparameters and their ranges.

              • (dict) --

                Provides the name and range of an integer-valued hyperparameter.

                • name (string) --

                  The name of the hyperparameter.

                • minValue (integer) --

                  The minimum allowable value for the hyperparameter.

                • maxValue (integer) --

                  The maximum allowable value for the hyperparameter.

            • continuousHyperParameterRanges (list) --

              The continuous hyperparameters and their ranges.

              • (dict) --

                Provides the name and range of a continuous hyperparameter.

                • name (string) --

                  The name of the hyperparameter.

                • minValue (float) --

                  The minimum allowable value for the hyperparameter.

                • maxValue (float) --

                  The maximum allowable value for the hyperparameter.

            • categoricalHyperParameterRanges (list) --

              The categorical hyperparameters and their ranges.

              • (dict) --

                Provides the name and range of a categorical hyperparameter.

                • name (string) --

                  The name of the hyperparameter.

                • values (list) --

                  A list of the categories for the hyperparameter.

                  • (string) --
        • algorithmHyperParameters (dict) --

          Lists the hyperparameter names and ranges.

          • (string) --
            • (string) --
        • featureTransformationParameters (dict) --

          Lists the feature transformation parameters.

          • (string) --
            • (string) --
        • autoMLConfig (dict) --

          The AutoMLConfig object containing a list of recipes to search when AutoML is performed.

          • metricName (string) --

            The metric to optimize.

          • recipeList (list) --

            The list of candidate recipes.

            • (string) --
        • optimizationObjective (dict) --

          Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.

          • itemAttribute (string) --

            The numerical metadata column in an Items dataset related to the optimization objective. For example, VIDEO_LENGTH (to maximize streaming minutes), or PRICE (to maximize revenue).

          • objectiveSensitivity (string) --

            Specifies how Amazon Personalize balances the importance of your optimization objective versus relevance.

      • autoMLResult (dict) --

        When performAutoML is true, specifies the best recipe found.

        • bestRecipeArn (string) --

          The Amazon Resource Name (ARN) of the best recipe.

      • status (string) --

        The status of the solution.

        A solution can be in one of the following states:

        • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • DELETE PENDING > DELETE IN_PROGRESS
      • creationDateTime (datetime) --

        The creation date and time (in Unix time) of the solution.

      • lastUpdatedDateTime (datetime) --

        The date and time (in Unix time) that the solution was last updated.

      • latestSolutionVersion (dict) --

        Describes the latest version of the solution, including the status and the ARN.

        • solutionVersionArn (string) --

          The Amazon Resource Name (ARN) of the solution version.

        • status (string) --

          The status of the solution version.

          A solution version can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • creationDateTime (datetime) --

          The date and time (in Unix time) that this version of a solution was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the solution version was last updated.

        • failureReason (string) --

          If a solution version fails, the reason behind the failure.

Exceptions

describe_solution_version(**kwargs)

Describes a specific version of a solution. For more information on solutions, see CreateSolution

See also: AWS API Documentation

Request Syntax

response = client.describe_solution_version(
    solutionVersionArn='string'
)
Parameters
solutionVersionArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the solution version.

Return type
dict
Returns
Response Syntax
{
    'solutionVersion': {
        'name': 'string',
        'solutionVersionArn': 'string',
        'solutionArn': 'string',
        'performHPO': True|False,
        'performAutoML': True|False,
        'recipeArn': 'string',
        'eventType': 'string',
        'datasetGroupArn': 'string',
        'solutionConfig': {
            'eventValueThreshold': 'string',
            'hpoConfig': {
                'hpoObjective': {
                    'type': 'string',
                    'metricName': 'string',
                    'metricRegex': 'string'
                },
                'hpoResourceConfig': {
                    'maxNumberOfTrainingJobs': 'string',
                    'maxParallelTrainingJobs': 'string'
                },
                'algorithmHyperParameterRanges': {
                    'integerHyperParameterRanges': [
                        {
                            'name': 'string',
                            'minValue': 123,
                            'maxValue': 123
                        },
                    ],
                    'continuousHyperParameterRanges': [
                        {
                            'name': 'string',
                            'minValue': 123.0,
                            'maxValue': 123.0
                        },
                    ],
                    'categoricalHyperParameterRanges': [
                        {
                            'name': 'string',
                            'values': [
                                'string',
                            ]
                        },
                    ]
                }
            },
            'algorithmHyperParameters': {
                'string': 'string'
            },
            'featureTransformationParameters': {
                'string': 'string'
            },
            'autoMLConfig': {
                'metricName': 'string',
                'recipeList': [
                    'string',
                ]
            },
            'optimizationObjective': {
                'itemAttribute': 'string',
                'objectiveSensitivity': 'LOW'|'MEDIUM'|'HIGH'|'OFF'
            }
        },
        'trainingHours': 123.0,
        'trainingMode': 'FULL'|'UPDATE',
        'tunedHPOParams': {
            'algorithmHyperParameters': {
                'string': 'string'
            }
        },
        'status': 'string',
        'failureReason': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1)
    }
}

Response Structure

  • (dict) --
    • solutionVersion (dict) --

      The solution version.

      • name (string) --

        The name of the solution version.

      • solutionVersionArn (string) --

        The ARN of the solution version.

      • solutionArn (string) --

        The ARN of the solution.

      • performHPO (boolean) --

        Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false .

      • performAutoML (boolean) --

        When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When false (the default), Amazon Personalize uses recipeArn .

      • recipeArn (string) --

        The ARN of the recipe used in the solution.

      • eventType (string) --

        The event type (for example, 'click' or 'like') that is used for training the model.

      • datasetGroupArn (string) --

        The Amazon Resource Name (ARN) of the dataset group providing the training data.

      • solutionConfig (dict) --

        Describes the configuration properties for the solution.

        • eventValueThreshold (string) --

          Only events with a value greater than or equal to this threshold are used for training a model.

        • hpoConfig (dict) --

          Describes the properties for hyperparameter optimization (HPO).

          • hpoObjective (dict) --

            The metric to optimize during HPO.

            Note

            Amazon Personalize doesn't support configuring the hpoObjective at this time.

            • type (string) --

              The type of the metric. Valid values are Maximize and Minimize .

            • metricName (string) --

              The name of the metric.

            • metricRegex (string) --

              A regular expression for finding the metric in the training job logs.

          • hpoResourceConfig (dict) --

            Describes the resource configuration for HPO.

            • maxNumberOfTrainingJobs (string) --

              The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40 .

            • maxParallelTrainingJobs (string) --

              The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10 .

          • algorithmHyperParameterRanges (dict) --

            The hyperparameters and their allowable ranges.

            • integerHyperParameterRanges (list) --

              The integer-valued hyperparameters and their ranges.

              • (dict) --

                Provides the name and range of an integer-valued hyperparameter.

                • name (string) --

                  The name of the hyperparameter.

                • minValue (integer) --

                  The minimum allowable value for the hyperparameter.

                • maxValue (integer) --

                  The maximum allowable value for the hyperparameter.

            • continuousHyperParameterRanges (list) --

              The continuous hyperparameters and their ranges.

              • (dict) --

                Provides the name and range of a continuous hyperparameter.

                • name (string) --

                  The name of the hyperparameter.

                • minValue (float) --

                  The minimum allowable value for the hyperparameter.

                • maxValue (float) --

                  The maximum allowable value for the hyperparameter.

            • categoricalHyperParameterRanges (list) --

              The categorical hyperparameters and their ranges.

              • (dict) --

                Provides the name and range of a categorical hyperparameter.

                • name (string) --

                  The name of the hyperparameter.

                • values (list) --

                  A list of the categories for the hyperparameter.

                  • (string) --
        • algorithmHyperParameters (dict) --

          Lists the hyperparameter names and ranges.

          • (string) --
            • (string) --
        • featureTransformationParameters (dict) --

          Lists the feature transformation parameters.

          • (string) --
            • (string) --
        • autoMLConfig (dict) --

          The AutoMLConfig object containing a list of recipes to search when AutoML is performed.

          • metricName (string) --

            The metric to optimize.

          • recipeList (list) --

            The list of candidate recipes.

            • (string) --
        • optimizationObjective (dict) --

          Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.

          • itemAttribute (string) --

            The numerical metadata column in an Items dataset related to the optimization objective. For example, VIDEO_LENGTH (to maximize streaming minutes), or PRICE (to maximize revenue).

          • objectiveSensitivity (string) --

            Specifies how Amazon Personalize balances the importance of your optimization objective versus relevance.

      • trainingHours (float) --

        The time used to train the model. You are billed for the time it takes to train a model. This field is visible only after Amazon Personalize successfully trains a model.

      • trainingMode (string) --

        The scope of training to be performed when creating the solution version. The FULL option trains the solution version based on the entirety of the input solution's training data, while the UPDATE option processes only the data that has changed in comparison to the input solution. Choose UPDATE when you want to incrementally update your solution version instead of creating an entirely new one.

        Warning

        The UPDATE option can only be used when you already have an active solution version created from the input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the HRNN-Coldstart recipe.

      • tunedHPOParams (dict) --

        If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.

        • algorithmHyperParameters (dict) --

          A list of the hyperparameter values of the best performing model.

          • (string) --
            • (string) --
      • status (string) --

        The status of the solution version.

        A solution version can be in one of the following states:

        • CREATE PENDING
        • CREATE IN_PROGRESS
        • ACTIVE
        • CREATE FAILED
        • CREATE STOPPING
        • CREATE STOPPED
      • failureReason (string) --

        If training a solution version fails, the reason for the failure.

      • creationDateTime (datetime) --

        The date and time (in Unix time) that this version of the solution was created.

      • lastUpdatedDateTime (datetime) --

        The date and time (in Unix time) that the solution was last updated.

Exceptions

get_paginator(operation_name)

Create a paginator for an operation.

Parameters
operation_name (string) -- The operation name. This is the same name as the method name on the client. For example, if the method name is create_foo, and you'd normally invoke the operation as client.create_foo(**kwargs), if the create_foo operation can be paginated, you can use the call client.get_paginator("create_foo").
Raises OperationNotPageableError
Raised if the operation is not pageable. You can use the client.can_paginate method to check if an operation is pageable.
Return type
L{botocore.paginate.Paginator}
Returns
A paginator object.
get_solution_metrics(**kwargs)

Gets the metrics for the specified solution version.

See also: AWS API Documentation

Request Syntax

response = client.get_solution_metrics(
    solutionVersionArn='string'
)
Parameters
solutionVersionArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the solution version for which to get metrics.

Return type
dict
Returns
Response Syntax
{
    'solutionVersionArn': 'string',
    'metrics': {
        'string': 123.0
    }
}

Response Structure

  • (dict) --
    • solutionVersionArn (string) --

      The same solution version ARN as specified in the request.

    • metrics (dict) --

      The metrics for the solution version. For more information, see Evaluating a solution version with metrics.

      • (string) --
        • (float) --

Exceptions

get_waiter(waiter_name)

Returns an object that can wait for some condition.

Parameters
waiter_name (str) -- The name of the waiter to get. See the waiters section of the service docs for a list of available waiters.
Returns
The specified waiter object.
Return type
botocore.waiter.Waiter
list_batch_inference_jobs(**kwargs)

Gets a list of the batch inference jobs that have been performed off of a solution version.

See also: AWS API Documentation

Request Syntax

response = client.list_batch_inference_jobs(
    solutionVersionArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • solutionVersionArn (string) -- The Amazon Resource Name (ARN) of the solution version from which the batch inference jobs were created.
  • nextToken (string) -- The token to request the next page of results.
  • maxResults (integer) -- The maximum number of batch inference job results to return in each page. The default value is 100.
Return type

dict

Returns

Response Syntax

{
    'batchInferenceJobs': [
        {
            'batchInferenceJobArn': 'string',
            'jobName': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string',
            'solutionVersionArn': 'string'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • batchInferenceJobs (list) --

      A list containing information on each job that is returned.

      • (dict) --

        A truncated version of the BatchInferenceJob. The ListBatchInferenceJobs operation returns a list of batch inference job summaries.

        • batchInferenceJobArn (string) --

          The Amazon Resource Name (ARN) of the batch inference job.

        • jobName (string) --

          The name of the batch inference job.

        • status (string) --

          The status of the batch inference job. The status is one of the following values:

          • PENDING
          • IN PROGRESS
          • ACTIVE
          • CREATE FAILED
        • creationDateTime (datetime) --

          The time at which the batch inference job was created.

        • lastUpdatedDateTime (datetime) --

          The time at which the batch inference job was last updated.

        • failureReason (string) --

          If the batch inference job failed, the reason for the failure.

        • solutionVersionArn (string) --

          The ARN of the solution version used by the batch inference job.

    • nextToken (string) --

      The token to use to retrieve the next page of results. The value is null when there are no more results to return.

Exceptions

list_batch_segment_jobs(**kwargs)

Gets a list of the batch segment jobs that have been performed off of a solution version that you specify.

See also: AWS API Documentation

Request Syntax

response = client.list_batch_segment_jobs(
    solutionVersionArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • solutionVersionArn (string) -- The Amazon Resource Name (ARN) of the solution version that the batch segment jobs used to generate batch segments.
  • nextToken (string) -- The token to request the next page of results.
  • maxResults (integer) -- The maximum number of batch segment job results to return in each page. The default value is 100.
Return type

dict

Returns

Response Syntax

{
    'batchSegmentJobs': [
        {
            'batchSegmentJobArn': 'string',
            'jobName': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string',
            'solutionVersionArn': 'string'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • batchSegmentJobs (list) --

      A list containing information on each job that is returned.

      • (dict) --

        A truncated version of the BatchSegmentJob datatype. ListBatchSegmentJobs operation returns a list of batch segment job summaries.

        • batchSegmentJobArn (string) --

          The Amazon Resource Name (ARN) of the batch segment job.

        • jobName (string) --

          The name of the batch segment job.

        • status (string) --

          The status of the batch segment job. The status is one of the following values:

          • PENDING
          • IN PROGRESS
          • ACTIVE
          • CREATE FAILED
        • creationDateTime (datetime) --

          The time at which the batch segment job was created.

        • lastUpdatedDateTime (datetime) --

          The time at which the batch segment job was last updated.

        • failureReason (string) --

          If the batch segment job failed, the reason for the failure.

        • solutionVersionArn (string) --

          The Amazon Resource Name (ARN) of the solution version used by the batch segment job to generate batch segments.

    • nextToken (string) --

      The token to use to retrieve the next page of results. The value is null when there are no more results to return.

Exceptions

list_campaigns(**kwargs)

Returns a list of campaigns that use the given solution. When a solution is not specified, all the campaigns associated with the account are listed. The response provides the properties for each campaign, including the Amazon Resource Name (ARN). For more information on campaigns, see CreateCampaign.

See also: AWS API Documentation

Request Syntax

response = client.list_campaigns(
    solutionArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • solutionArn (string) -- The Amazon Resource Name (ARN) of the solution to list the campaigns for. When a solution is not specified, all the campaigns associated with the account are listed.
  • nextToken (string) -- A token returned from the previous call to ListCampaigns for getting the next set of campaigns (if they exist).
  • maxResults (integer) -- The maximum number of campaigns to return.
Return type

dict

Returns

Response Syntax

{
    'campaigns': [
        {
            'name': 'string',
            'campaignArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • campaigns (list) --

      A list of the campaigns.

      • (dict) --

        Provides a summary of the properties of a campaign. For a complete listing, call the DescribeCampaign API.

        • name (string) --

          The name of the campaign.

        • campaignArn (string) --

          The Amazon Resource Name (ARN) of the campaign.

        • status (string) --

          The status of the campaign.

          A campaign can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING > DELETE IN_PROGRESS
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the campaign was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the campaign was last updated.

        • failureReason (string) --

          If a campaign fails, the reason behind the failure.

    • nextToken (string) --

      A token for getting the next set of campaigns (if they exist).

Exceptions

list_dataset_export_jobs(**kwargs)

Returns a list of dataset export jobs that use the given dataset. When a dataset is not specified, all the dataset export jobs associated with the account are listed. The response provides the properties for each dataset export job, including the Amazon Resource Name (ARN). For more information on dataset export jobs, see CreateDatasetExportJob. For more information on datasets, see CreateDataset.

See also: AWS API Documentation

Request Syntax

response = client.list_dataset_export_jobs(
    datasetArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • datasetArn (string) -- The Amazon Resource Name (ARN) of the dataset to list the dataset export jobs for.
  • nextToken (string) -- A token returned from the previous call to ListDatasetExportJobs for getting the next set of dataset export jobs (if they exist).
  • maxResults (integer) -- The maximum number of dataset export jobs to return.
Return type

dict

Returns

Response Syntax

{
    'datasetExportJobs': [
        {
            'datasetExportJobArn': 'string',
            'jobName': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • datasetExportJobs (list) --

      The list of dataset export jobs.

      • (dict) --

        Provides a summary of the properties of a dataset export job. For a complete listing, call the DescribeDatasetExportJob API.

        • datasetExportJobArn (string) --

          The Amazon Resource Name (ARN) of the dataset export job.

        • jobName (string) --

          The name of the dataset export job.

        • status (string) --

          The status of the dataset export job.

          A dataset export job can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the dataset export job was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the dataset export job status was last updated.

        • failureReason (string) --

          If a dataset export job fails, the reason behind the failure.

    • nextToken (string) --

      A token for getting the next set of dataset export jobs (if they exist).

Exceptions

list_dataset_groups(**kwargs)

Returns a list of dataset groups. The response provides the properties for each dataset group, including the Amazon Resource Name (ARN). For more information on dataset groups, see CreateDatasetGroup.

See also: AWS API Documentation

Request Syntax

response = client.list_dataset_groups(
    nextToken='string',
    maxResults=123
)
Parameters
  • nextToken (string) -- A token returned from the previous call to ListDatasetGroups for getting the next set of dataset groups (if they exist).
  • maxResults (integer) -- The maximum number of dataset groups to return.
Return type

dict

Returns

Response Syntax

{
    'datasetGroups': [
        {
            'name': 'string',
            'datasetGroupArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string',
            'domain': 'ECOMMERCE'|'VIDEO_ON_DEMAND'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • datasetGroups (list) --

      The list of your dataset groups.

      • (dict) --

        Provides a summary of the properties of a dataset group. For a complete listing, call the DescribeDatasetGroup API.

        • name (string) --

          The name of the dataset group.

        • datasetGroupArn (string) --

          The Amazon Resource Name (ARN) of the dataset group.

        • status (string) --

          The status of the dataset group.

          A dataset group can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the dataset group was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the dataset group was last updated.

        • failureReason (string) --

          If creating a dataset group fails, the reason behind the failure.

        • domain (string) --

          The domain of a Domain dataset group.

    • nextToken (string) --

      A token for getting the next set of dataset groups (if they exist).

Exceptions

list_dataset_import_jobs(**kwargs)

Returns a list of dataset import jobs that use the given dataset. When a dataset is not specified, all the dataset import jobs associated with the account are listed. The response provides the properties for each dataset import job, including the Amazon Resource Name (ARN). For more information on dataset import jobs, see CreateDatasetImportJob. For more information on datasets, see CreateDataset.

See also: AWS API Documentation

Request Syntax

response = client.list_dataset_import_jobs(
    datasetArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • datasetArn (string) -- The Amazon Resource Name (ARN) of the dataset to list the dataset import jobs for.
  • nextToken (string) -- A token returned from the previous call to ListDatasetImportJobs for getting the next set of dataset import jobs (if they exist).
  • maxResults (integer) -- The maximum number of dataset import jobs to return.
Return type

dict

Returns

Response Syntax

{
    'datasetImportJobs': [
        {
            'datasetImportJobArn': 'string',
            'jobName': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string',
            'importMode': 'FULL'|'INCREMENTAL'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • datasetImportJobs (list) --

      The list of dataset import jobs.

      • (dict) --

        Provides a summary of the properties of a dataset import job. For a complete listing, call the DescribeDatasetImportJob API.

        • datasetImportJobArn (string) --

          The Amazon Resource Name (ARN) of the dataset import job.

        • jobName (string) --

          The name of the dataset import job.

        • status (string) --

          The status of the dataset import job.

          A dataset import job can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the dataset import job was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the dataset import job status was last updated.

        • failureReason (string) --

          If a dataset import job fails, the reason behind the failure.

        • importMode (string) --

          The import mode the dataset import job used to update the data in the dataset. For more information see Updating existing bulk data.

    • nextToken (string) --

      A token for getting the next set of dataset import jobs (if they exist).

Exceptions

list_datasets(**kwargs)

Returns the list of datasets contained in the given dataset group. The response provides the properties for each dataset, including the Amazon Resource Name (ARN). For more information on datasets, see CreateDataset.

See also: AWS API Documentation

Request Syntax

response = client.list_datasets(
    datasetGroupArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • datasetGroupArn (string) -- The Amazon Resource Name (ARN) of the dataset group that contains the datasets to list.
  • nextToken (string) -- A token returned from the previous call to ListDatasetImportJobs for getting the next set of dataset import jobs (if they exist).
  • maxResults (integer) -- The maximum number of datasets to return.
Return type

dict

Returns

Response Syntax

{
    'datasets': [
        {
            'name': 'string',
            'datasetArn': 'string',
            'datasetType': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1)
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • datasets (list) --

      An array of Dataset objects. Each object provides metadata information.

      • (dict) --

        Provides a summary of the properties of a dataset. For a complete listing, call the DescribeDataset API.

        • name (string) --

          The name of the dataset.

        • datasetArn (string) --

          The Amazon Resource Name (ARN) of the dataset.

        • datasetType (string) --

          The dataset type. One of the following values:

          • Interactions
          • Items
          • Users
          • Event-Interactions
        • status (string) --

          The status of the dataset.

          A dataset can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING > DELETE IN_PROGRESS
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the dataset was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the dataset was last updated.

    • nextToken (string) --

      A token for getting the next set of datasets (if they exist).

Exceptions

list_event_trackers(**kwargs)

Returns the list of event trackers associated with the account. The response provides the properties for each event tracker, including the Amazon Resource Name (ARN) and tracking ID. For more information on event trackers, see CreateEventTracker.

See also: AWS API Documentation

Request Syntax

response = client.list_event_trackers(
    datasetGroupArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • datasetGroupArn (string) -- The ARN of a dataset group used to filter the response.
  • nextToken (string) -- A token returned from the previous call to ListEventTrackers for getting the next set of event trackers (if they exist).
  • maxResults (integer) -- The maximum number of event trackers to return.
Return type

dict

Returns

Response Syntax

{
    'eventTrackers': [
        {
            'name': 'string',
            'eventTrackerArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1)
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • eventTrackers (list) --

      A list of event trackers.

      • (dict) --

        Provides a summary of the properties of an event tracker. For a complete listing, call the DescribeEventTracker API.

        • name (string) --

          The name of the event tracker.

        • eventTrackerArn (string) --

          The Amazon Resource Name (ARN) of the event tracker.

        • status (string) --

          The status of the event tracker.

          An event tracker can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING > DELETE IN_PROGRESS
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the event tracker was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the event tracker was last updated.

    • nextToken (string) --

      A token for getting the next set of event trackers (if they exist).

Exceptions

list_filters(**kwargs)

Lists all filters that belong to a given dataset group.

See also: AWS API Documentation

Request Syntax

response = client.list_filters(
    datasetGroupArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • datasetGroupArn (string) -- The ARN of the dataset group that contains the filters.
  • nextToken (string) -- A token returned from the previous call to ListFilters for getting the next set of filters (if they exist).
  • maxResults (integer) -- The maximum number of filters to return.
Return type

dict

Returns

Response Syntax

{
    'Filters': [
        {
            'name': 'string',
            'filterArn': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'datasetGroupArn': 'string',
            'failureReason': 'string',
            'status': 'string'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • Filters (list) --

      A list of returned filters.

      • (dict) --

        A short summary of a filter's attributes.

        • name (string) --

          The name of the filter.

        • filterArn (string) --

          The ARN of the filter.

        • creationDateTime (datetime) --

          The time at which the filter was created.

        • lastUpdatedDateTime (datetime) --

          The time at which the filter was last updated.

        • datasetGroupArn (string) --

          The ARN of the dataset group to which the filter belongs.

        • failureReason (string) --

          If the filter failed, the reason for the failure.

        • status (string) --

          The status of the filter.

    • nextToken (string) --

      A token for getting the next set of filters (if they exist).

Exceptions

list_metric_attribution_metrics(**kwargs)

Lists the metrics for the metric attribution.

See also: AWS API Documentation

Request Syntax

response = client.list_metric_attribution_metrics(
    metricAttributionArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • metricAttributionArn (string) -- The Amazon Resource Name (ARN) of the metric attribution to retrieve attributes for.
  • nextToken (string) -- Specify the pagination token from a previous request to retrieve the next page of results.
  • maxResults (integer) -- The maximum number of metrics to return in one page of results.
Return type

dict

Returns

Response Syntax

{
    'metrics': [
        {
            'eventType': 'string',
            'metricName': 'string',
            'expression': 'string'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • metrics (list) --

      The metrics for the specified metric attribution.

      • (dict) --

        Contains information on a metric that a metric attribution reports on. For more information, see Measuring impact of recommendations.

        • eventType (string) --

          The metric's event type.

        • metricName (string) --

          The metric's name. The name helps you identify the metric in Amazon CloudWatch or Amazon S3.

        • expression (string) --

          The attribute's expression. Available functions are SUM() or SAMPLECOUNT() . For SUM() functions, provide the dataset type (either Interactions or Items) and column to sum as a parameter. For example SUM(Items.PRICE).

    • nextToken (string) --

      Specify the pagination token from a previous ListMetricAttributionMetricsResponse request to retrieve the next page of results.

Exceptions

list_metric_attributions(**kwargs)

Lists metric attributions.

See also: AWS API Documentation

Request Syntax

response = client.list_metric_attributions(
    datasetGroupArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • datasetGroupArn (string) -- The metric attributions' dataset group Amazon Resource Name (ARN).
  • nextToken (string) -- Specify the pagination token from a previous request to retrieve the next page of results.
  • maxResults (integer) -- The maximum number of metric attributions to return in one page of results.
Return type

dict

Returns

Response Syntax

{
    'metricAttributions': [
        {
            'name': 'string',
            'metricAttributionArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • metricAttributions (list) --

      The list of metric attributions.

      • (dict) --

        Provides a summary of the properties of a metric attribution. For a complete listing, call the DescribeMetricAttribution.

        • name (string) --

          The name of the metric attribution.

        • metricAttributionArn (string) --

          The metric attribution's Amazon Resource Name (ARN).

        • status (string) --

          The metric attribution's status.

        • creationDateTime (datetime) --

          The metric attribution's creation date time.

        • lastUpdatedDateTime (datetime) --

          The metric attribution's last updated date time.

        • failureReason (string) --

          The metric attribution's failure reason.

    • nextToken (string) --

      Specify the pagination token from a previous request to retrieve the next page of results.

Exceptions

list_recipes(**kwargs)

Returns a list of available recipes. The response provides the properties for each recipe, including the recipe's Amazon Resource Name (ARN).

See also: AWS API Documentation

Request Syntax

response = client.list_recipes(
    recipeProvider='SERVICE',
    nextToken='string',
    maxResults=123,
    domain='ECOMMERCE'|'VIDEO_ON_DEMAND'
)
Parameters
  • recipeProvider (string) -- The default is SERVICE .
  • nextToken (string) -- A token returned from the previous call to ListRecipes for getting the next set of recipes (if they exist).
  • maxResults (integer) -- The maximum number of recipes to return.
  • domain (string) -- Filters returned recipes by domain for a Domain dataset group. Only recipes (Domain dataset group use cases) for this domain are included in the response. If you don't specify a domain, all recipes are returned.
Return type

dict

Returns

Response Syntax

{
    'recipes': [
        {
            'name': 'string',
            'recipeArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'domain': 'ECOMMERCE'|'VIDEO_ON_DEMAND'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • recipes (list) --

      The list of available recipes.

      • (dict) --

        Provides a summary of the properties of a recipe. For a complete listing, call the DescribeRecipe API.

        • name (string) --

          The name of the recipe.

        • recipeArn (string) --

          The Amazon Resource Name (ARN) of the recipe.

        • status (string) --

          The status of the recipe.

        • creationDateTime (datetime) --

          The date and time (in Unix time) that the recipe was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the recipe was last updated.

        • domain (string) --

          The domain of the recipe (if the recipe is a Domain dataset group use case).

    • nextToken (string) --

      A token for getting the next set of recipes.

Exceptions

list_recommenders(**kwargs)

Returns a list of recommenders in a given Domain dataset group. When a Domain dataset group is not specified, all the recommenders associated with the account are listed. The response provides the properties for each recommender, including the Amazon Resource Name (ARN). For more information on recommenders, see CreateRecommender.

See also: AWS API Documentation

Request Syntax

response = client.list_recommenders(
    datasetGroupArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • datasetGroupArn (string) -- The Amazon Resource Name (ARN) of the Domain dataset group to list the recommenders for. When a Domain dataset group is not specified, all the recommenders associated with the account are listed.
  • nextToken (string) -- A token returned from the previous call to ListRecommenders for getting the next set of recommenders (if they exist).
  • maxResults (integer) -- The maximum number of recommenders to return.
Return type

dict

Returns

Response Syntax

{
    'recommenders': [
        {
            'name': 'string',
            'recommenderArn': 'string',
            'datasetGroupArn': 'string',
            'recipeArn': 'string',
            'recommenderConfig': {
                'itemExplorationConfig': {
                    'string': 'string'
                },
                'minRecommendationRequestsPerSecond': 123
            },
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1)
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • recommenders (list) --

      A list of the recommenders.

      • (dict) --

        Provides a summary of the properties of the recommender.

        • name (string) --

          The name of the recommender.

        • recommenderArn (string) --

          The Amazon Resource Name (ARN) of the recommender.

        • datasetGroupArn (string) --

          The Amazon Resource Name (ARN) of the Domain dataset group that contains the recommender.

        • recipeArn (string) --

          The Amazon Resource Name (ARN) of the recipe (Domain dataset group use case) that the recommender was created for.

        • recommenderConfig (dict) --

          The configuration details of the recommender.

          • itemExplorationConfig (dict) --

            Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your recommenders generate personalized recommendations for a user (not popular items or similar items).

            • (string) --
              • (string) --
          • minRecommendationRequestsPerSecond (integer) --

            Specifies the requested minimum provisioned recommendation requests per second that Amazon Personalize will support.

        • status (string) --

          The status of the recommender. A recommender can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
          • DELETE PENDING > DELETE IN_PROGRESS
        • creationDateTime (datetime) --

          The date and time (in Unix format) that the recommender was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix format) that the recommender was last updated.

    • nextToken (string) --

      A token for getting the next set of recommenders (if they exist).

Exceptions

list_schemas(**kwargs)

Returns the list of schemas associated with the account. The response provides the properties for each schema, including the Amazon Resource Name (ARN). For more information on schemas, see CreateSchema.

See also: AWS API Documentation

Request Syntax

response = client.list_schemas(
    nextToken='string',
    maxResults=123
)
Parameters
  • nextToken (string) -- A token returned from the previous call to ListSchemas for getting the next set of schemas (if they exist).
  • maxResults (integer) -- The maximum number of schemas to return.
Return type

dict

Returns

Response Syntax

{
    'schemas': [
        {
            'name': 'string',
            'schemaArn': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'domain': 'ECOMMERCE'|'VIDEO_ON_DEMAND'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • schemas (list) --

      A list of schemas.

      • (dict) --

        Provides a summary of the properties of a dataset schema. For a complete listing, call the DescribeSchema API.

        • name (string) --

          The name of the schema.

        • schemaArn (string) --

          The Amazon Resource Name (ARN) of the schema.

        • creationDateTime (datetime) --

          The date and time (in Unix time) that the schema was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the schema was last updated.

        • domain (string) --

          The domain of a schema that you created for a dataset in a Domain dataset group.

    • nextToken (string) --

      A token used to get the next set of schemas (if they exist).

Exceptions

list_solution_versions(**kwargs)

Returns a list of solution versions for the given solution. When a solution is not specified, all the solution versions associated with the account are listed. The response provides the properties for each solution version, including the Amazon Resource Name (ARN).

See also: AWS API Documentation

Request Syntax

response = client.list_solution_versions(
    solutionArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • solutionArn (string) -- The Amazon Resource Name (ARN) of the solution.
  • nextToken (string) -- A token returned from the previous call to ListSolutionVersions for getting the next set of solution versions (if they exist).
  • maxResults (integer) -- The maximum number of solution versions to return.
Return type

dict

Returns

Response Syntax

{
    'solutionVersions': [
        {
            'solutionVersionArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • solutionVersions (list) --

      A list of solution versions describing the version properties.

      • (dict) --

        Provides a summary of the properties of a solution version. For a complete listing, call the DescribeSolutionVersion API.

        • solutionVersionArn (string) --

          The Amazon Resource Name (ARN) of the solution version.

        • status (string) --

          The status of the solution version.

          A solution version can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • creationDateTime (datetime) --

          The date and time (in Unix time) that this version of a solution was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the solution version was last updated.

        • failureReason (string) --

          If a solution version fails, the reason behind the failure.

    • nextToken (string) --

      A token for getting the next set of solution versions (if they exist).

Exceptions

list_solutions(**kwargs)

Returns a list of solutions that use the given dataset group. When a dataset group is not specified, all the solutions associated with the account are listed. The response provides the properties for each solution, including the Amazon Resource Name (ARN). For more information on solutions, see CreateSolution.

See also: AWS API Documentation

Request Syntax

response = client.list_solutions(
    datasetGroupArn='string',
    nextToken='string',
    maxResults=123
)
Parameters
  • datasetGroupArn (string) -- The Amazon Resource Name (ARN) of the dataset group.
  • nextToken (string) -- A token returned from the previous call to ListSolutions for getting the next set of solutions (if they exist).
  • maxResults (integer) -- The maximum number of solutions to return.
Return type

dict

Returns

Response Syntax

{
    'solutions': [
        {
            'name': 'string',
            'solutionArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'recipeArn': 'string'
        },
    ],
    'nextToken': 'string'
}

Response Structure

  • (dict) --

    • solutions (list) --

      A list of the current solutions.

      • (dict) --

        Provides a summary of the properties of a solution. For a complete listing, call the DescribeSolution API.

        • name (string) --

          The name of the solution.

        • solutionArn (string) --

          The Amazon Resource Name (ARN) of the solution.

        • status (string) --

          The status of the solution.

          A solution can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING > DELETE IN_PROGRESS
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the solution was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the solution was last updated.

        • recipeArn (string) --

          The Amazon Resource Name (ARN) of the recipe used by the solution.

    • nextToken (string) --

      A token for getting the next set of solutions (if they exist).

Exceptions

list_tags_for_resource(**kwargs)

Get a list of tags attached to a resource.

See also: AWS API Documentation

Request Syntax

response = client.list_tags_for_resource(
    resourceArn='string'
)
Parameters
resourceArn (string) --

[REQUIRED]

The resource's Amazon Resource Name.

Return type
dict
Returns
Response Syntax
{
    'tags': [
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
}

Response Structure

  • (dict) --
    • tags (list) --

      The resource's tags.

      • (dict) --

        The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

        • tagKey (string) --

          One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

        • tagValue (string) --

          The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Exceptions

start_recommender(**kwargs)

Starts a recommender that is INACTIVE. Starting a recommender does not create any new models, but resumes billing and automatic retraining for the recommender.

See also: AWS API Documentation

Request Syntax

response = client.start_recommender(
    recommenderArn='string'
)
Parameters
recommenderArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the recommender to start.

Return type
dict
Returns
Response Syntax
{
    'recommenderArn': 'string'
}

Response Structure

  • (dict) --
    • recommenderArn (string) --

      The Amazon Resource Name (ARN) of the recommender you started.

Exceptions

stop_recommender(**kwargs)

Stops a recommender that is ACTIVE. Stopping a recommender halts billing and automatic retraining for the recommender.

See also: AWS API Documentation

Request Syntax

response = client.stop_recommender(
    recommenderArn='string'
)
Parameters
recommenderArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the recommender to stop.

Return type
dict
Returns
Response Syntax
{
    'recommenderArn': 'string'
}

Response Structure

  • (dict) --
    • recommenderArn (string) --

      The Amazon Resource Name (ARN) of the recommender you stopped.

Exceptions

stop_solution_version_creation(**kwargs)

Stops creating a solution version that is in a state of CREATE_PENDING or CREATE IN_PROGRESS.

Depending on the current state of the solution version, the solution version state changes as follows:

  • CREATE_PENDING > CREATE_STOPPED or
  • CREATE_IN_PROGRESS > CREATE_STOPPING > CREATE_STOPPED

You are billed for all of the training completed up until you stop the solution version creation. You cannot resume creating a solution version once it has been stopped.

See also: AWS API Documentation

Request Syntax

response = client.stop_solution_version_creation(
    solutionVersionArn='string'
)
Parameters
solutionVersionArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the solution version you want to stop creating.

Returns
None

Exceptions

tag_resource(**kwargs)

Add a list of tags to a resource.

See also: AWS API Documentation

Request Syntax

response = client.tag_resource(
    resourceArn='string',
    tags=[
        {
            'tagKey': 'string',
            'tagValue': 'string'
        },
    ]
)
Parameters
  • resourceArn (string) --

    [REQUIRED]

    The resource's Amazon Resource Name (ARN).

  • tags (list) --

    [REQUIRED]

    Tags to apply to the resource. For more information see Tagging Personalize resources.

    • (dict) --

      The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.

      • tagKey (string) -- [REQUIRED]

        One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

      • tagValue (string) -- [REQUIRED]

        The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

Return type

dict

Returns

Response Syntax

{}

Response Structure

  • (dict) --

Exceptions

untag_resource(**kwargs)

Remove tags that are attached to a resource.

See also: AWS API Documentation

Request Syntax

response = client.untag_resource(
    resourceArn='string',
    tagKeys=[
        'string',
    ]
)
Parameters
  • resourceArn (string) --

    [REQUIRED]

    The resource's Amazon Resource Name (ARN).

  • tagKeys (list) --

    [REQUIRED]

    Keys to remove from the resource's tags.

    • (string) --
Return type

dict

Returns

Response Syntax

{}

Response Structure

  • (dict) --

Exceptions

update_campaign(**kwargs)

Updates a campaign by either deploying a new solution or changing the value of the campaign's minProvisionedTPS parameter.

To update a campaign, the campaign status must be ACTIVE or CREATE FAILED. Check the campaign status using the DescribeCampaign operation.

Note

You can still get recommendations from a campaign while an update is in progress. The campaign will use the previous solution version and campaign configuration to generate recommendations until the latest campaign update status is Active .

For more information on campaigns, see CreateCampaign.

See also: AWS API Documentation

Request Syntax

response = client.update_campaign(
    campaignArn='string',
    solutionVersionArn='string',
    minProvisionedTPS=123,
    campaignConfig={
        'itemExplorationConfig': {
            'string': 'string'
        }
    }
)
Parameters
  • campaignArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the campaign.

  • solutionVersionArn (string) -- The ARN of a new solution version to deploy.
  • minProvisionedTPS (integer) -- Specifies the requested minimum provisioned transactions (recommendations) per second that Amazon Personalize will support.
  • campaignConfig (dict) --

    The configuration details of a campaign.

    • itemExplorationConfig (dict) --

      Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your solution uses the User-Personalization recipe.

      • (string) --
        • (string) --
Return type

dict

Returns

Response Syntax

{
    'campaignArn': 'string'
}

Response Structure

  • (dict) --

    • campaignArn (string) --

      The same campaign ARN as given in the request.

Exceptions

update_metric_attribution(**kwargs)

Updates a metric attribution.

See also: AWS API Documentation

Request Syntax

response = client.update_metric_attribution(
    addMetrics=[
        {
            'eventType': 'string',
            'metricName': 'string',
            'expression': 'string'
        },
    ],
    removeMetrics=[
        'string',
    ],
    metricsOutputConfig={
        's3DataDestination': {
            'path': 'string',
            'kmsKeyArn': 'string'
        },
        'roleArn': 'string'
    },
    metricAttributionArn='string'
)
Parameters
  • addMetrics (list) --

    Add new metric attributes to the metric attribution.

    • (dict) --

      Contains information on a metric that a metric attribution reports on. For more information, see Measuring impact of recommendations.

      • eventType (string) -- [REQUIRED]

        The metric's event type.

      • metricName (string) -- [REQUIRED]

        The metric's name. The name helps you identify the metric in Amazon CloudWatch or Amazon S3.

      • expression (string) -- [REQUIRED]

        The attribute's expression. Available functions are SUM() or SAMPLECOUNT() . For SUM() functions, provide the dataset type (either Interactions or Items) and column to sum as a parameter. For example SUM(Items.PRICE).

  • removeMetrics (list) --

    Remove metric attributes from the metric attribution.

    • (string) --
  • metricsOutputConfig (dict) --

    An output config for the metric attribution.

    • s3DataDestination (dict) --

      The configuration details of an Amazon S3 input or output bucket.

      • path (string) -- [REQUIRED]

        The file path of the Amazon S3 bucket.

      • kmsKeyArn (string) --

        The Amazon Resource Name (ARN) of the Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files.

    • roleArn (string) -- [REQUIRED]

      The Amazon Resource Name (ARN) of the IAM service role that has permissions to add data to your output Amazon S3 bucket and add metrics to Amazon CloudWatch. For more information, see Measuring impact of recommendations.

  • metricAttributionArn (string) -- The Amazon Resource Name (ARN) for the metric attribution to update.
Return type

dict

Returns

Response Syntax

{
    'metricAttributionArn': 'string'
}

Response Structure

  • (dict) --

    • metricAttributionArn (string) --

      The Amazon Resource Name (ARN) for the metric attribution that you updated.

Exceptions

update_recommender(**kwargs)

Updates the recommender to modify the recommender configuration.

See also: AWS API Documentation

Request Syntax

response = client.update_recommender(
    recommenderArn='string',
    recommenderConfig={
        'itemExplorationConfig': {
            'string': 'string'
        },
        'minRecommendationRequestsPerSecond': 123
    }
)
Parameters
  • recommenderArn (string) --

    [REQUIRED]

    The Amazon Resource Name (ARN) of the recommender to modify.

  • recommenderConfig (dict) --

    [REQUIRED]

    The configuration details of the recommender.

    • itemExplorationConfig (dict) --

      Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your recommenders generate personalized recommendations for a user (not popular items or similar items).

      • (string) --
        • (string) --
    • minRecommendationRequestsPerSecond (integer) --

      Specifies the requested minimum provisioned recommendation requests per second that Amazon Personalize will support.

Return type

dict

Returns

Response Syntax

{
    'recommenderArn': 'string'
}

Response Structure

  • (dict) --

    • recommenderArn (string) --

      The same recommender Amazon Resource Name (ARN) as given in the request.

Exceptions

Client Exceptions

Client exceptions are available on a client instance via the exceptions property. For more detailed instructions and examples on the exact usage of client exceptions, see the error handling user guide.

The available client exceptions are:

class Personalize.Client.exceptions.InvalidInputException

Provide a valid value for the field or parameter.

Example

try:
  ...
except client.exceptions.InvalidInputException as e:
  print(e.response)
response

The parsed error response. All exceptions have a top level Error key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.

Syntax

{
    'message': 'string',
    'Error': {
        'Code': 'string',
        'Message': 'string'
    }
}

Structure

  • (dict) --

    Provide a valid value for the field or parameter.

    • message (string) --
    • Error (dict) -- Normalized access to common exception attributes.
      • Code (string) -- An identifier specifying the exception type.
      • Message (string) -- A descriptive message explaining why the exception occured.
class Personalize.Client.exceptions.InvalidNextTokenException

The token is not valid.

Example

try:
  ...
except client.exceptions.InvalidNextTokenException as e:
  print(e.response)
response

The parsed error response. All exceptions have a top level Error key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.

Syntax

{
    'message': 'string',
    'Error': {
        'Code': 'string',
        'Message': 'string'
    }
}

Structure

  • (dict) --

    The token is not valid.

    • message (string) --
    • Error (dict) -- Normalized access to common exception attributes.
      • Code (string) -- An identifier specifying the exception type.
      • Message (string) -- A descriptive message explaining why the exception occured.
class Personalize.Client.exceptions.LimitExceededException

The limit on the number of requests per second has been exceeded.

Example

try:
  ...
except client.exceptions.LimitExceededException as e:
  print(e.response)
response

The parsed error response. All exceptions have a top level Error key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.

Syntax

{
    'message': 'string',
    'Error': {
        'Code': 'string',
        'Message': 'string'
    }
}

Structure

  • (dict) --

    The limit on the number of requests per second has been exceeded.

    • message (string) --
    • Error (dict) -- Normalized access to common exception attributes.
      • Code (string) -- An identifier specifying the exception type.
      • Message (string) -- A descriptive message explaining why the exception occured.
class Personalize.Client.exceptions.ResourceAlreadyExistsException

The specified resource already exists.

Example

try:
  ...
except client.exceptions.ResourceAlreadyExistsException as e:
  print(e.response)
response

The parsed error response. All exceptions have a top level Error key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.

Syntax

{
    'message': 'string',
    'Error': {
        'Code': 'string',
        'Message': 'string'
    }
}

Structure

  • (dict) --

    The specified resource already exists.

    • message (string) --
    • Error (dict) -- Normalized access to common exception attributes.
      • Code (string) -- An identifier specifying the exception type.
      • Message (string) -- A descriptive message explaining why the exception occured.
class Personalize.Client.exceptions.ResourceInUseException

The specified resource is in use.

Example

try:
  ...
except client.exceptions.ResourceInUseException as e:
  print(e.response)
response

The parsed error response. All exceptions have a top level Error key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.

Syntax

{
    'message': 'string',
    'Error': {
        'Code': 'string',
        'Message': 'string'
    }
}

Structure

  • (dict) --

    The specified resource is in use.

    • message (string) --
    • Error (dict) -- Normalized access to common exception attributes.
      • Code (string) -- An identifier specifying the exception type.
      • Message (string) -- A descriptive message explaining why the exception occured.
class Personalize.Client.exceptions.ResourceNotFoundException

Could not find the specified resource.

Example

try:
  ...
except client.exceptions.ResourceNotFoundException as e:
  print(e.response)
response

The parsed error response. All exceptions have a top level Error key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.

Syntax

{
    'message': 'string',
    'Error': {
        'Code': 'string',
        'Message': 'string'
    }
}

Structure

  • (dict) --

    Could not find the specified resource.

    • message (string) --
    • Error (dict) -- Normalized access to common exception attributes.
      • Code (string) -- An identifier specifying the exception type.
      • Message (string) -- A descriptive message explaining why the exception occured.
class Personalize.Client.exceptions.TooManyTagKeysException

The request contains more tag keys than can be associated with a resource (50 tag keys per resource).

Example

try:
  ...
except client.exceptions.TooManyTagKeysException as e:
  print(e.response)
response

The parsed error response. All exceptions have a top level Error key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.

Syntax

{
    'message': 'string',
    'Error': {
        'Code': 'string',
        'Message': 'string'
    }
}

Structure

  • (dict) --

    The request contains more tag keys than can be associated with a resource (50 tag keys per resource).

    • message (string) --
    • Error (dict) -- Normalized access to common exception attributes.
      • Code (string) -- An identifier specifying the exception type.
      • Message (string) -- A descriptive message explaining why the exception occured.
class Personalize.Client.exceptions.TooManyTagsException

You have exceeded the maximum number of tags you can apply to this resource.

Example

try:
  ...
except client.exceptions.TooManyTagsException as e:
  print(e.response)
response

The parsed error response. All exceptions have a top level Error key that provides normalized access to common exception atrributes. All other keys are specific to this service or exception class.

Syntax

{
    'message': 'string',
    'Error': {
        'Code': 'string',
        'Message': 'string'
    }
}

Structure

  • (dict) --

    You have exceeded the maximum number of tags you can apply to this resource.

    • message (string) --
    • Error (dict) -- Normalized access to common exception attributes.
      • Code (string) -- An identifier specifying the exception type.
      • Message (string) -- A descriptive message explaining why the exception occured.

Paginators

The available paginators are:

class Personalize.Paginator.ListBatchInferenceJobs
paginator = client.get_paginator('list_batch_inference_jobs')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_batch_inference_jobs().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    solutionVersionArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • solutionVersionArn (string) -- The Amazon Resource Name (ARN) of the solution version from which the batch inference jobs were created.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'batchInferenceJobs': [
        {
            'batchInferenceJobArn': 'string',
            'jobName': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string',
            'solutionVersionArn': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • batchInferenceJobs (list) --

      A list containing information on each job that is returned.

      • (dict) --

        A truncated version of the BatchInferenceJob. The ListBatchInferenceJobs operation returns a list of batch inference job summaries.

        • batchInferenceJobArn (string) --

          The Amazon Resource Name (ARN) of the batch inference job.

        • jobName (string) --

          The name of the batch inference job.

        • status (string) --

          The status of the batch inference job. The status is one of the following values:

          • PENDING
          • IN PROGRESS
          • ACTIVE
          • CREATE FAILED
        • creationDateTime (datetime) --

          The time at which the batch inference job was created.

        • lastUpdatedDateTime (datetime) --

          The time at which the batch inference job was last updated.

        • failureReason (string) --

          If the batch inference job failed, the reason for the failure.

        • solutionVersionArn (string) --

          The ARN of the solution version used by the batch inference job.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListBatchSegmentJobs
paginator = client.get_paginator('list_batch_segment_jobs')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_batch_segment_jobs().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    solutionVersionArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • solutionVersionArn (string) -- The Amazon Resource Name (ARN) of the solution version that the batch segment jobs used to generate batch segments.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'batchSegmentJobs': [
        {
            'batchSegmentJobArn': 'string',
            'jobName': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string',
            'solutionVersionArn': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • batchSegmentJobs (list) --

      A list containing information on each job that is returned.

      • (dict) --

        A truncated version of the BatchSegmentJob datatype. ListBatchSegmentJobs operation returns a list of batch segment job summaries.

        • batchSegmentJobArn (string) --

          The Amazon Resource Name (ARN) of the batch segment job.

        • jobName (string) --

          The name of the batch segment job.

        • status (string) --

          The status of the batch segment job. The status is one of the following values:

          • PENDING
          • IN PROGRESS
          • ACTIVE
          • CREATE FAILED
        • creationDateTime (datetime) --

          The time at which the batch segment job was created.

        • lastUpdatedDateTime (datetime) --

          The time at which the batch segment job was last updated.

        • failureReason (string) --

          If the batch segment job failed, the reason for the failure.

        • solutionVersionArn (string) --

          The Amazon Resource Name (ARN) of the solution version used by the batch segment job to generate batch segments.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListCampaigns
paginator = client.get_paginator('list_campaigns')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_campaigns().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    solutionArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • solutionArn (string) -- The Amazon Resource Name (ARN) of the solution to list the campaigns for. When a solution is not specified, all the campaigns associated with the account are listed.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'campaigns': [
        {
            'name': 'string',
            'campaignArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • campaigns (list) --

      A list of the campaigns.

      • (dict) --

        Provides a summary of the properties of a campaign. For a complete listing, call the DescribeCampaign API.

        • name (string) --

          The name of the campaign.

        • campaignArn (string) --

          The Amazon Resource Name (ARN) of the campaign.

        • status (string) --

          The status of the campaign.

          A campaign can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING > DELETE IN_PROGRESS
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the campaign was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the campaign was last updated.

        • failureReason (string) --

          If a campaign fails, the reason behind the failure.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListDatasetExportJobs
paginator = client.get_paginator('list_dataset_export_jobs')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_dataset_export_jobs().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    datasetArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • datasetArn (string) -- The Amazon Resource Name (ARN) of the dataset to list the dataset export jobs for.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'datasetExportJobs': [
        {
            'datasetExportJobArn': 'string',
            'jobName': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • datasetExportJobs (list) --

      The list of dataset export jobs.

      • (dict) --

        Provides a summary of the properties of a dataset export job. For a complete listing, call the DescribeDatasetExportJob API.

        • datasetExportJobArn (string) --

          The Amazon Resource Name (ARN) of the dataset export job.

        • jobName (string) --

          The name of the dataset export job.

        • status (string) --

          The status of the dataset export job.

          A dataset export job can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the dataset export job was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the dataset export job status was last updated.

        • failureReason (string) --

          If a dataset export job fails, the reason behind the failure.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListDatasetGroups
paginator = client.get_paginator('list_dataset_groups')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_dataset_groups().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
PaginationConfig (dict) --

A dictionary that provides parameters to control pagination.

  • MaxItems (integer) --

    The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

  • PageSize (integer) --

    The size of each page.

  • StartingToken (string) --

    A token to specify where to start paginating. This is the NextToken from a previous response.

Return type
dict
Returns
Response Syntax
{
    'datasetGroups': [
        {
            'name': 'string',
            'datasetGroupArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string',
            'domain': 'ECOMMERCE'|'VIDEO_ON_DEMAND'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --
    • datasetGroups (list) --

      The list of your dataset groups.

      • (dict) --

        Provides a summary of the properties of a dataset group. For a complete listing, call the DescribeDatasetGroup API.

        • name (string) --

          The name of the dataset group.

        • datasetGroupArn (string) --

          The Amazon Resource Name (ARN) of the dataset group.

        • status (string) --

          The status of the dataset group.

          A dataset group can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the dataset group was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the dataset group was last updated.

        • failureReason (string) --

          If creating a dataset group fails, the reason behind the failure.

        • domain (string) --

          The domain of a Domain dataset group.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListDatasetImportJobs
paginator = client.get_paginator('list_dataset_import_jobs')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_dataset_import_jobs().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    datasetArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • datasetArn (string) -- The Amazon Resource Name (ARN) of the dataset to list the dataset import jobs for.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'datasetImportJobs': [
        {
            'datasetImportJobArn': 'string',
            'jobName': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string',
            'importMode': 'FULL'|'INCREMENTAL'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • datasetImportJobs (list) --

      The list of dataset import jobs.

      • (dict) --

        Provides a summary of the properties of a dataset import job. For a complete listing, call the DescribeDatasetImportJob API.

        • datasetImportJobArn (string) --

          The Amazon Resource Name (ARN) of the dataset import job.

        • jobName (string) --

          The name of the dataset import job.

        • status (string) --

          The status of the dataset import job.

          A dataset import job can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the dataset import job was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the dataset import job status was last updated.

        • failureReason (string) --

          If a dataset import job fails, the reason behind the failure.

        • importMode (string) --

          The import mode the dataset import job used to update the data in the dataset. For more information see Updating existing bulk data.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListDatasets
paginator = client.get_paginator('list_datasets')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_datasets().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    datasetGroupArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • datasetGroupArn (string) -- The Amazon Resource Name (ARN) of the dataset group that contains the datasets to list.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'datasets': [
        {
            'name': 'string',
            'datasetArn': 'string',
            'datasetType': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1)
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • datasets (list) --

      An array of Dataset objects. Each object provides metadata information.

      • (dict) --

        Provides a summary of the properties of a dataset. For a complete listing, call the DescribeDataset API.

        • name (string) --

          The name of the dataset.

        • datasetArn (string) --

          The Amazon Resource Name (ARN) of the dataset.

        • datasetType (string) --

          The dataset type. One of the following values:

          • Interactions
          • Items
          • Users
          • Event-Interactions
        • status (string) --

          The status of the dataset.

          A dataset can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING > DELETE IN_PROGRESS
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the dataset was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the dataset was last updated.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListEventTrackers
paginator = client.get_paginator('list_event_trackers')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_event_trackers().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    datasetGroupArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • datasetGroupArn (string) -- The ARN of a dataset group used to filter the response.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'eventTrackers': [
        {
            'name': 'string',
            'eventTrackerArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1)
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • eventTrackers (list) --

      A list of event trackers.

      • (dict) --

        Provides a summary of the properties of an event tracker. For a complete listing, call the DescribeEventTracker API.

        • name (string) --

          The name of the event tracker.

        • eventTrackerArn (string) --

          The Amazon Resource Name (ARN) of the event tracker.

        • status (string) --

          The status of the event tracker.

          An event tracker can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING > DELETE IN_PROGRESS
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the event tracker was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the event tracker was last updated.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListFilters
paginator = client.get_paginator('list_filters')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_filters().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    datasetGroupArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • datasetGroupArn (string) -- The ARN of the dataset group that contains the filters.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'Filters': [
        {
            'name': 'string',
            'filterArn': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'datasetGroupArn': 'string',
            'failureReason': 'string',
            'status': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • Filters (list) --

      A list of returned filters.

      • (dict) --

        A short summary of a filter's attributes.

        • name (string) --

          The name of the filter.

        • filterArn (string) --

          The ARN of the filter.

        • creationDateTime (datetime) --

          The time at which the filter was created.

        • lastUpdatedDateTime (datetime) --

          The time at which the filter was last updated.

        • datasetGroupArn (string) --

          The ARN of the dataset group to which the filter belongs.

        • failureReason (string) --

          If the filter failed, the reason for the failure.

        • status (string) --

          The status of the filter.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListMetricAttributionMetrics
paginator = client.get_paginator('list_metric_attribution_metrics')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_metric_attribution_metrics().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    metricAttributionArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • metricAttributionArn (string) -- The Amazon Resource Name (ARN) of the metric attribution to retrieve attributes for.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'metrics': [
        {
            'eventType': 'string',
            'metricName': 'string',
            'expression': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • metrics (list) --

      The metrics for the specified metric attribution.

      • (dict) --

        Contains information on a metric that a metric attribution reports on. For more information, see Measuring impact of recommendations.

        • eventType (string) --

          The metric's event type.

        • metricName (string) --

          The metric's name. The name helps you identify the metric in Amazon CloudWatch or Amazon S3.

        • expression (string) --

          The attribute's expression. Available functions are SUM() or SAMPLECOUNT() . For SUM() functions, provide the dataset type (either Interactions or Items) and column to sum as a parameter. For example SUM(Items.PRICE).

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListMetricAttributions
paginator = client.get_paginator('list_metric_attributions')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_metric_attributions().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    datasetGroupArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • datasetGroupArn (string) -- The metric attributions' dataset group Amazon Resource Name (ARN).
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'metricAttributions': [
        {
            'name': 'string',
            'metricAttributionArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • metricAttributions (list) --

      The list of metric attributions.

      • (dict) --

        Provides a summary of the properties of a metric attribution. For a complete listing, call the DescribeMetricAttribution.

        • name (string) --

          The name of the metric attribution.

        • metricAttributionArn (string) --

          The metric attribution's Amazon Resource Name (ARN).

        • status (string) --

          The metric attribution's status.

        • creationDateTime (datetime) --

          The metric attribution's creation date time.

        • lastUpdatedDateTime (datetime) --

          The metric attribution's last updated date time.

        • failureReason (string) --

          The metric attribution's failure reason.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListRecipes
paginator = client.get_paginator('list_recipes')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_recipes().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    recipeProvider='SERVICE',
    domain='ECOMMERCE'|'VIDEO_ON_DEMAND',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • recipeProvider (string) -- The default is SERVICE .
  • domain (string) -- Filters returned recipes by domain for a Domain dataset group. Only recipes (Domain dataset group use cases) for this domain are included in the response. If you don't specify a domain, all recipes are returned.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'recipes': [
        {
            'name': 'string',
            'recipeArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'domain': 'ECOMMERCE'|'VIDEO_ON_DEMAND'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • recipes (list) --

      The list of available recipes.

      • (dict) --

        Provides a summary of the properties of a recipe. For a complete listing, call the DescribeRecipe API.

        • name (string) --

          The name of the recipe.

        • recipeArn (string) --

          The Amazon Resource Name (ARN) of the recipe.

        • status (string) --

          The status of the recipe.

        • creationDateTime (datetime) --

          The date and time (in Unix time) that the recipe was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the recipe was last updated.

        • domain (string) --

          The domain of the recipe (if the recipe is a Domain dataset group use case).

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListRecommenders
paginator = client.get_paginator('list_recommenders')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_recommenders().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    datasetGroupArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • datasetGroupArn (string) -- The Amazon Resource Name (ARN) of the Domain dataset group to list the recommenders for. When a Domain dataset group is not specified, all the recommenders associated with the account are listed.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'recommenders': [
        {
            'name': 'string',
            'recommenderArn': 'string',
            'datasetGroupArn': 'string',
            'recipeArn': 'string',
            'recommenderConfig': {
                'itemExplorationConfig': {
                    'string': 'string'
                },
                'minRecommendationRequestsPerSecond': 123
            },
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1)
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • recommenders (list) --

      A list of the recommenders.

      • (dict) --

        Provides a summary of the properties of the recommender.

        • name (string) --

          The name of the recommender.

        • recommenderArn (string) --

          The Amazon Resource Name (ARN) of the recommender.

        • datasetGroupArn (string) --

          The Amazon Resource Name (ARN) of the Domain dataset group that contains the recommender.

        • recipeArn (string) --

          The Amazon Resource Name (ARN) of the recipe (Domain dataset group use case) that the recommender was created for.

        • recommenderConfig (dict) --

          The configuration details of the recommender.

          • itemExplorationConfig (dict) --

            Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff , you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your recommenders generate personalized recommendations for a user (not popular items or similar items).

            • (string) --
              • (string) --
          • minRecommendationRequestsPerSecond (integer) --

            Specifies the requested minimum provisioned recommendation requests per second that Amazon Personalize will support.

        • status (string) --

          The status of the recommender. A recommender can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
          • DELETE PENDING > DELETE IN_PROGRESS
        • creationDateTime (datetime) --

          The date and time (in Unix format) that the recommender was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix format) that the recommender was last updated.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListSchemas
paginator = client.get_paginator('list_schemas')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_schemas().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
PaginationConfig (dict) --

A dictionary that provides parameters to control pagination.

  • MaxItems (integer) --

    The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

  • PageSize (integer) --

    The size of each page.

  • StartingToken (string) --

    A token to specify where to start paginating. This is the NextToken from a previous response.

Return type
dict
Returns
Response Syntax
{
    'schemas': [
        {
            'name': 'string',
            'schemaArn': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'domain': 'ECOMMERCE'|'VIDEO_ON_DEMAND'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --
    • schemas (list) --

      A list of schemas.

      • (dict) --

        Provides a summary of the properties of a dataset schema. For a complete listing, call the DescribeSchema API.

        • name (string) --

          The name of the schema.

        • schemaArn (string) --

          The Amazon Resource Name (ARN) of the schema.

        • creationDateTime (datetime) --

          The date and time (in Unix time) that the schema was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the schema was last updated.

        • domain (string) --

          The domain of a schema that you created for a dataset in a Domain dataset group.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListSolutionVersions
paginator = client.get_paginator('list_solution_versions')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_solution_versions().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    solutionArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • solutionArn (string) -- The Amazon Resource Name (ARN) of the solution.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'solutionVersions': [
        {
            'solutionVersionArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • solutionVersions (list) --

      A list of solution versions describing the version properties.

      • (dict) --

        Provides a summary of the properties of a solution version. For a complete listing, call the DescribeSolutionVersion API.

        • solutionVersionArn (string) --

          The Amazon Resource Name (ARN) of the solution version.

        • status (string) --

          The status of the solution version.

          A solution version can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
        • creationDateTime (datetime) --

          The date and time (in Unix time) that this version of a solution was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the solution version was last updated.

        • failureReason (string) --

          If a solution version fails, the reason behind the failure.

    • NextToken (string) --

      A token to resume pagination.

class Personalize.Paginator.ListSolutions
paginator = client.get_paginator('list_solutions')
paginate(**kwargs)

Creates an iterator that will paginate through responses from Personalize.Client.list_solutions().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    datasetGroupArn='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • datasetGroupArn (string) -- The Amazon Resource Name (ARN) of the dataset group.
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'solutions': [
        {
            'name': 'string',
            'solutionArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'recipeArn': 'string'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • solutions (list) --

      A list of the current solutions.

      • (dict) --

        Provides a summary of the properties of a solution. For a complete listing, call the DescribeSolution API.

        • name (string) --

          The name of the solution.

        • solutionArn (string) --

          The Amazon Resource Name (ARN) of the solution.

        • status (string) --

          The status of the solution.

          A solution can be in one of the following states:

          • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
          • DELETE PENDING > DELETE IN_PROGRESS
        • creationDateTime (datetime) --

          The date and time (in Unix time) that the solution was created.

        • lastUpdatedDateTime (datetime) --

          The date and time (in Unix time) that the solution was last updated.

        • recipeArn (string) --

          The Amazon Resource Name (ARN) of the recipe used by the solution.

    • NextToken (string) --

      A token to resume pagination.