Amazon Personalize

Describes a filter's properties.

See also: AWS API Documentation

Request Syntax

client.describe_filter(
    filterArn='string'
)

type filterArn:

string

param filterArn:

[REQUIRED]

The ARN of the filter to describe.

rtype:

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 the following format:

      EXCLUDE itemId WHERE INTERACTIONS.event_type in ("EVENT_TYPE")

      Where "EVENT_TYPE" is the type of event to filter out. For more information, see Using Filters with Amazon Personalize.

    • status (string) --

      The status of the filter.

Lists all filters that belong to a given dataset group.

See also: AWS API Documentation

Request Syntax

client.list_filters(
    datasetGroupArn='string',
    nextToken='string',
    maxResults=123
)

type datasetGroupArn:

string

param datasetGroupArn:

The ARN of the dataset group that contains the filters.

type nextToken:

string

param nextToken:

A token returned from the previous call to ListFilters for getting the next set of filters (if they exist).

type maxResults:

integer

param maxResults:

The maximum number of filters to return.

rtype:

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).

Creates a recommendation filter. For more information, see Using Filters with Amazon Personalize.

See also: AWS API Documentation

Request Syntax

client.create_filter(
    name='string',
    datasetGroupArn='string',
    filterExpression='string'
)

type name:

string

param name:

[REQUIRED]

The name of the filter to create.

type datasetGroupArn:

string

param datasetGroupArn:

[REQUIRED]

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

type filterExpression:

string

param filterExpression:

[REQUIRED]

The filter expression that designates the interaction types that the filter will filter out. A filter expression must follow the following format:

EXCLUDE itemId WHERE INTERACTIONS.event_type in ("EVENT_TYPE")

Where "EVENT_TYPE" is the type of event to filter out. To filter out all items with any interactions history, set "*" as the EVENT_TYPE. For more information, see Using Filters with Amazon Personalize.

rtype:

dict

returns:

Response Syntax

{
    'filterArn': 'string'
}

Response Structure

• (dict) --

  • filterArn (string) --

    The ARN of the new filter.

Deletes a filter.

See also: AWS API Documentation

Request Syntax

client.delete_filter(
    filterArn='string'
)

type filterArn:

string

param filterArn:

[REQUIRED]

The ARN of the filter to delete.

returns:

None

{'filterArn': 'string'}

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 recommendations-batch.

See also: AWS API Documentation

Request Syntax

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'
)

type jobName:

string

param jobName:

[REQUIRED]

The name of the batch inference job to create.

type solutionVersionArn:

string

param solutionVersionArn:

[REQUIRED]

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

type filterArn:

string

param filterArn:

The ARN of the filter to apply to the batch inference job. For more information on using filters, see Using Filters with Amazon Personalize.

type numResults:

integer

param numResults:

The number of recommendations to retreive.

type jobInput:

dict

param jobInput:

[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 Amazon Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files of a batch inference job.

type jobOutput:

dict

param jobOutput:

[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 Amazon Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files of a batch inference job.

type roleArn:

string

param roleArn:

[REQUIRED]

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

rtype:

dict

returns:

Response Syntax

{
    'batchInferenceJobArn': 'string'
}

Response Structure

• (dict) --

  • batchInferenceJobArn (string) --

    The ARN of the batch inference job.

{'batchInferenceJob': {'filterArn': 'string'}}

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

client.describe_batch_inference_job(
    batchInferenceJobArn='string'
)

type batchInferenceJobArn:

string

param batchInferenceJobArn:

[REQUIRED]

The ARN of the batch inference job to describe.

rtype:

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'
            }
        },
        '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 Amazon Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files of a batch inference job.

    • 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 Amazon Key Management Service (KMS) key that Amazon Personalize uses to encrypt or decrypt the input and output files of a batch inference job.

    • 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.