Personalize / Client / describe_recommender

describe_recommender

Personalize.Client.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,
            'trainingDataConfig': {
                'excludedDatasetColumns': {
                    'string': [
                        'string',
                    ]
                }
            },
            'enableMetadataWithRecommendations': True|False
        },
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'status': 'string',
        'failureReason': 'string',
        'latestRecommenderUpdate': {
            'recommenderConfig': {
                'itemExplorationConfig': {
                    'string': 'string'
                },
                'minRecommendationRequestsPerSecond': 123,
                'trainingDataConfig': {
                    'excludedDatasetColumns': {
                        'string': [
                            'string',
                        ]
                    }
                },
                'enableMetadataWithRecommendations': True|False
            },
            '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. 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.

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

    • 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. 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.

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

      • 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

• Personalize.Client.exceptions.InvalidInputException

• Personalize.Client.exceptions.ResourceNotFoundException