CustomerProfiles / Paginator / ListRecommenders

ListRecommenders¶

class CustomerProfiles.Paginator.ListRecommenders¶

paginator = client.get_paginator('list_recommenders')

paginate(**kwargs)¶

Creates an iterator that will paginate through responses from CustomerProfiles.Client.list_recommenders().

Request Syntax

response_iterator = paginator.paginate(
    DomainName='string',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)

Parameters:

DomainName (string) –
[REQUIRED]

The unique name of the domain.
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': [
        {
            'RecommenderName': 'string',
            'RecipeName': 'recommended-for-you'|'similar-items'|'frequently-paired-items'|'popular-items'|'trending-now'|'personalized-ranking',
            'RecommenderSchemaName': 'string',
            'RecommenderConfig': {
                'EventsConfig': {
                    'EventParametersList': [
                        {
                            'EventType': 'string',
                            'EventValueThreshold': 123.0,
                            'EventWeight': 123.0
                        },
                    ]
                },
                'TrainingFrequency': 123,
                'InferenceConfig': {
                    'MinProvisionedTPS': 123
                },
                'IncludedColumns': {
                    'string': [
                        'string',
                    ]
                }
            },
            'CreatedAt': datetime(2015, 1, 1),
            'Description': 'string',
            'Status': 'PENDING'|'IN_PROGRESS'|'ACTIVE'|'FAILED'|'STOPPING'|'INACTIVE'|'STARTING'|'DELETING',
            'LastUpdatedAt': datetime(2015, 1, 1),
            'Tags': {
                'string': 'string'
            },
            'FailureReason': 'string',
            'LatestRecommenderUpdate': {
                'RecommenderConfig': {
                    'EventsConfig': {
                        'EventParametersList': [
                            {
                                'EventType': 'string',
                                'EventValueThreshold': 123.0,
                                'EventWeight': 123.0
                            },
                        ]
                    },
                    'TrainingFrequency': 123,
                    'InferenceConfig': {
                        'MinProvisionedTPS': 123
                    },
                    'IncludedColumns': {
                        'string': [
                            'string',
                        ]
                    }
                },
                'Status': 'PENDING'|'IN_PROGRESS'|'ACTIVE'|'FAILED'|'STOPPING'|'INACTIVE'|'STARTING'|'DELETING',
                'CreatedAt': datetime(2015, 1, 1),
                'LastUpdatedAt': datetime(2015, 1, 1),
                'FailureReason': 'string'
            }
        },
    ]
}

Response Structure

(dict) –
- Recommenders (list) –
  
  A list of recommenders and their properties in the specified domain.
  - (dict) –
    
    Provides a summary of a recommender’s configuration and current state.
    - RecommenderName (string) –
      
      The name of the recommender.
    - RecipeName (string) –
      
      The name of the recipe used by this recommender.
    - RecommenderSchemaName (string) –
      
      The name of the recommender schema associated with this recommender.
    - RecommenderConfig (dict) –
      
      The configuration settings applied to this recommender.
      - EventsConfig (dict) –
        
        Configuration settings for how the recommender processes and uses events.
        
        EventParametersList (list) –
        
        A list of event parameters configurations that specify how different event types should be handled.
        
        (dict) –
        
        Configuration parameters for events in the personalization system.
        
        EventType (string) –
        
        The type of event being tracked (e.g., ‘click’, ‘purchase’, ‘view’).
        
        EventValueThreshold (float) –
        
        The minimum value threshold that an event must meet to be considered valid.
        
        EventWeight (float) –
        
        The weight of the event type. A higher weight means higher importance of the event type for the created solution.
      - TrainingFrequency (integer) –
        
        How often the recommender should retrain its model with new data.
      - InferenceConfig (dict) –
        
        Configuration settings for how the recommender handles inference requests.
        
        MinProvisionedTPS (integer) –
        
        The minimum provisioned transactions per second (TPS) that the recommender supports. The default value is 1. A high MinProvisionedTPS will increase your cost.
      - IncludedColumns (dict) –
        
        A map of dataset type to a list of column names to train on. The column names must be a subset of the columns defined in the recommender schema. If not specified, all columns in the schema are used for training. The following columns are always included and do not need to be specified: Item.Id, ItemList[].Id, EventTimestamp, EventType, and EventValue.
        
        (string) –
        
        (list) –
        
        (string) –
    - CreatedAt (datetime) –
      
      The timestamp when the recommender was created.
    - Description (string) –
      
      A description of the recommender’s purpose and characteristics.
    - Status (string) –
      
      The current operational status of the recommender.
    - LastUpdatedAt (datetime) –
      
      The timestamp of when the recommender was edited.
    - Tags (dict) –
      
      The tags used to organize, track, or control access for this resource.
      - (string) –
        
        (string) –
    - FailureReason (string) –
      
      If the recommender is in a failed state, provides the reason for the failure.
    - LatestRecommenderUpdate (dict) –
      
      Information about the most recent update performed on the recommender, including its status and timing.
      - RecommenderConfig (dict) –
        
        The updated configuration settings applied to the recommender during this update.
        
        EventsConfig (dict) –
        
        Configuration settings for how the recommender processes and uses events.
        
        EventParametersList (list) –
        
        A list of event parameters configurations that specify how different event types should be handled.
        
        (dict) –
        
        Configuration parameters for events in the personalization system.
        
        EventType (string) –
        
        The type of event being tracked (e.g., ‘click’, ‘purchase’, ‘view’).
        
        EventValueThreshold (float) –
        
        The minimum value threshold that an event must meet to be considered valid.
        
        EventWeight (float) –
        
        The weight of the event type. A higher weight means higher importance of the event type for the created solution.
        
        TrainingFrequency (integer) –
        
        How often the recommender should retrain its model with new data.
        
        InferenceConfig (dict) –
        
        Configuration settings for how the recommender handles inference requests.
        
        MinProvisionedTPS (integer) –
        
        The minimum provisioned transactions per second (TPS) that the recommender supports. The default value is 1. A high MinProvisionedTPS will increase your cost.
        
        IncludedColumns (dict) –
        
        A map of dataset type to a list of column names to train on. The column names must be a subset of the columns defined in the recommender schema. If not specified, all columns in the schema are used for training. The following columns are always included and do not need to be specified: Item.Id, ItemList[].Id, EventTimestamp, EventType, and EventValue.
        
        (string) –
        
        (list) –
        
        (string) –
      - Status (string) –
        
        The current status of the recommender update operation.
      - CreatedAt (datetime) –
        
        The timestamp when this recommender update was initiated.
      - LastUpdatedAt (datetime) –
        
        The timestamp of when the recommender was edited.
      - FailureReason (string) –
        
        If the update operation failed, provides the reason for the failure.