Personalize / Paginator / ListRecommenders

ListRecommenders

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,
                'trainingDataConfig': {
                    'excludedDatasetColumns': {
                        'string': [
                            'string',
                        ]
                    }
                },
                'enableMetadataWithRecommendations': True|False
            },
            '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. A high minRecommendationRequestsPerSecond will increase your bill. We recommend starting with 1 for minRecommendationRequestsPerSecond (the default). Track your usage using Amazon CloudWatch metrics, and increase the minRecommendationRequestsPerSecond as necessary.

        • trainingDataConfig (dict) –

          Specifies the training data configuration to use when creating a domain recommender.

          • excludedDatasetColumns (dict) –

            Specifies the columns to exclude from training. Each key is a dataset type, and each value is a list of columns. Exclude columns to control what data Amazon Personalize uses to generate recommendations.

            For example, you might have a column that you want to use only to filter recommendations. You can exclude this column from training and Amazon Personalize considers it only when filtering.

            • (string) –

              • (list) –

                • (string) –

        • enableMetadataWithRecommendations (boolean) –

          Whether metadata with recommendations is enabled for the recommender. If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response. For information about enabling metadata for a recommender, see Enabling metadata in recommendations for a recommender.

          If you enable metadata in recommendations, you will incur additional costs. For more information, see Amazon Personalize pricing.

      • 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.