Table of Contents
A low-level client representing Amazon Personalize
Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.
import boto3
client = boto3.client('personalize')
These are the available methods:
Check if an operation can be paginated.
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
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'
}
}
)
[REQUIRED]
The name of the batch inference job to create.
[REQUIRED]
The Amazon Resource Name (ARN) of the solution version that will be used to generate the batch inference recommendations.
[REQUIRED]
The Amazon S3 path that leads to the input file to base your recommendations on. The input material must be in JSON format.
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.
The file path of the Amazon S3 bucket.
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 of a batch inference job.
[REQUIRED]
The path to the Amazon S3 bucket where the job's output will be stored.
Information on the Amazon S3 bucket in which the batch inference job's output is stored.
The file path of the Amazon S3 bucket.
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 of a batch inference job.
[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.
The configuration details of a batch inference job.
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 .
dict
Response Syntax
{
'batchInferenceJobArn': 'string'
}
Response Structure
(dict) --
batchInferenceJobArn (string) --
The ARN of the batch inference job.
Exceptions
Creates a campaign by deploying 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:
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'
}
}
)
[REQUIRED]
A name for the new campaign. The campaign name must be unique within your account.
[REQUIRED]
The Amazon Resource Name (ARN) of the solution version to deploy.
The configuration details of a campaign.
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. Provide itemExplorationConfig data only if your solution uses the User-Personalization recipe.
dict
Response Syntax
{
'campaignArn': 'string'
}
Response Structure
(dict) --
campaignArn (string) --
The Amazon Resource Name (ARN) of the campaign.
Exceptions
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:
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:
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'
)
[REQUIRED]
The name for the dataset.
[REQUIRED]
The ARN of the schema to associate with the dataset. The schema defines the dataset fields.
[REQUIRED]
The Amazon Resource Name (ARN) of the dataset group to add the dataset to.
[REQUIRED]
The type of dataset.
One of the following (case insensitive) values:
dict
Response Syntax
{
'datasetArn': 'string'
}
Response Structure
(dict) --
datasetArn (string) --
The ARN of the dataset.
Exceptions
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:
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'
}
}
)
[REQUIRED]
The name for the dataset export job.
[REQUIRED]
The Amazon Resource Name (ARN) of the dataset that contains the data to export.
[REQUIRED]
The Amazon Resource Name (ARN) of the IAM service role that has permissions to add data to your output Amazon S3 bucket.
[REQUIRED]
The path to the Amazon S3 bucket where the job's output is stored.
The configuration details of an Amazon S3 input or output bucket.
The file path of the Amazon S3 bucket.
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 of a batch inference job.
dict
Response Syntax
{
'datasetExportJobArn': 'string'
}
Response Structure
(dict) --
datasetExportJobArn (string) --
The Amazon Resource Name (ARN) of the dataset export job.
Exceptions
Creates an empty dataset group. A dataset group contains related datasets that supply data for training a model. A dataset group can contain at most three datasets, one for each type of dataset:
To train a model (create a solution), a dataset group that contains an Interactions dataset is required. Call CreateDataset to add a dataset to the group.
A dataset group can be in one of the following states:
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'
)
[REQUIRED]
The name for the new dataset group.
dict
Response Syntax
{
'datasetGroupArn': 'string'
}
Response Structure
(dict) --
datasetGroupArn (string) --
The Amazon Resource Name (ARN) of the new dataset group.
Exceptions
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
The dataset import job replaces any existing data in the dataset that you imported in bulk.
Status
A dataset import job can be in one of the following states:
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'
)
[REQUIRED]
The name for the dataset import job.
[REQUIRED]
The ARN of the dataset that receives the imported data.
[REQUIRED]
The Amazon S3 bucket that contains the training data to import.
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/
[REQUIRED]
The ARN of the IAM role that has permissions to read from the Amazon S3 data source.
dict
Response Syntax
{
'datasetImportJobArn': 'string'
}
Response Structure
(dict) --
datasetImportJobArn (string) --
The ARN of the dataset import job.
Exceptions
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:
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'
)
[REQUIRED]
The name for the event tracker.
[REQUIRED]
The Amazon Resource Name (ARN) of the dataset group that receives the event data.
dict
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
Creates a recommendation filter. For more information, see filter .
See also: AWS API Documentation
Request Syntax
response = client.create_filter(
name='string',
datasetGroupArn='string',
filterExpression='string'
)
[REQUIRED]
The name of the filter to create.
[REQUIRED]
The ARN of the dataset group that the filter will belong to.
[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 .
dict
Response Syntax
{
'filterArn': 'string'
}
Response Structure
(dict) --
filterArn (string) --
The ARN of the new filter.
Exceptions
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. 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'
)
[REQUIRED]
The name for the schema.
[REQUIRED]
A schema in Avro JSON format.
dict
Response Syntax
{
'schemaArn': 'string'
}
Response Structure
(dict) --
schemaArn (string) --
The Amazon Resource Name (ARN) of the created schema.
Exceptions
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:
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'
}
}
)
[REQUIRED]
The name for the solution.
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 .
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.
[REQUIRED]
The Amazon Resource Name (ARN) of the dataset group that provides the training data.
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.
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.
Only events with a value greater than or equal to this threshold are used for training a model.
Describes the properties for hyperparameter optimization (HPO).
The metric to optimize during HPO.
Note
Amazon Personalize doesn't support configuring the hpoObjective at this time.
The type of the metric. Valid values are Maximize and Minimize .
The name of the metric.
A regular expression for finding the metric in the training job logs.
Describes the resource configuration for HPO.
The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40 .
The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10 .
The hyperparameters and their allowable ranges.
The integer-valued hyperparameters and their ranges.
Provides the name and range of an integer-valued hyperparameter.
The name of the hyperparameter.
The minimum allowable value for the hyperparameter.
The maximum allowable value for the hyperparameter.
The continuous hyperparameters and their ranges.
Provides the name and range of a continuous hyperparameter.
The name of the hyperparameter.
The minimum allowable value for the hyperparameter.
The maximum allowable value for the hyperparameter.
The categorical hyperparameters and their ranges.
Provides the name and range of a categorical hyperparameter.
The name of the hyperparameter.
A list of the categories for the hyperparameter.
Lists the hyperparameter names and ranges.
Lists the feature transformation parameters.
The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
The metric to optimize.
The list of candidate recipes.
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution .
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).
Specifies how Amazon Personalize balances the importance of your optimization objective versus relevance.
dict
Response Syntax
{
'solutionArn': 'string'
}
Response Structure
(dict) --
solutionArn (string) --
The ARN of the solution.
Exceptions
Trains or retrains an active solution. 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:
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(
solutionArn='string',
trainingMode='FULL'|'UPDATE'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the solution containing the training configuration information.
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.
dict
Response Syntax
{
'solutionVersionArn': 'string'
}
Response Structure
(dict) --
solutionVersionArn (string) --
The ARN of the new solution version.
Exceptions
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 more information on campaigns, see CreateCampaign .
See also: AWS API Documentation
Request Syntax
response = client.delete_campaign(
campaignArn='string'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the campaign to delete.
Exceptions
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the dataset to delete.
Exceptions
Deletes a dataset group. Before you delete a dataset group, you must delete the following:
See also: AWS API Documentation
Request Syntax
response = client.delete_dataset_group(
datasetGroupArn='string'
)
[REQUIRED]
The ARN of the dataset group to delete.
Exceptions
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the event tracker to delete.
Exceptions
Deletes a filter.
See also: AWS API Documentation
Request Syntax
response = client.delete_filter(
filterArn='string'
)
[REQUIRED]
The ARN of the filter to delete.
Exceptions
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the schema to delete.
Exceptions
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'
)
[REQUIRED]
The ARN of the solution to delete.
Exceptions
Describes the given algorithm.
See also: AWS API Documentation
Request Syntax
response = client.describe_algorithm(
algorithmArn='string'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the algorithm to describe.
{
'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
A listing of the properties of the algorithm.
The name of the algorithm.
The Amazon Resource Name (ARN) of the algorithm.
The URI of the Docker container for the algorithm image.
The name of the algorithm image.
The URI of the Docker container for the algorithm image.
Specifies the default hyperparameters.
Specifies the default hyperparameters, their ranges, and whether they are tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).
The integer-valued hyperparameters and their default ranges.
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).
The name of the hyperparameter.
The minimum allowable value for the hyperparameter.
The maximum allowable value for the hyperparameter.
Indicates whether the hyperparameter is tunable.
The continuous hyperparameters and their default ranges.
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).
The name of the hyperparameter.
The minimum allowable value for the hyperparameter.
The maximum allowable value for the hyperparameter.
Whether the hyperparameter is tunable.
The categorical hyperparameters and their default ranges.
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).
The name of the hyperparameter.
A list of the categories for the hyperparameter.
Whether the hyperparameter is tunable.
Specifies the default maximum number of training jobs and parallel training jobs.
The training input mode.
The Amazon Resource Name (ARN) of the role.
The date and time (in Unix time) that the algorithm was created.
The date and time (in Unix time) that the algorithm was last updated.
Exceptions
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'
)
[REQUIRED]
The ARN of the batch inference job to describe.
{
'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
Information on the specified batch inference job.
The name of the batch inference job.
The Amazon Resource Name (ARN) of the batch inference job.
The ARN of the filter used on the batch inference job.
If the batch inference job failed, the reason for the failure.
The Amazon Resource Name (ARN) of the solution version from which the batch inference job was created.
The number of recommendations generated by the batch inference job. This number includes the error messages generated for failed input records.
The Amazon S3 path that leads to the input data used to generate the batch inference job.
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.
The file path of the Amazon S3 bucket.
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 of a batch inference job.
The Amazon S3 bucket that contains the output data generated by the batch inference job.
Information on the Amazon S3 bucket in which the batch inference job's output is stored.
The file path of the Amazon S3 bucket.
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 of a batch inference job.
A string to string map of the configuration details of a batch inference job.
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 .
The ARN of the Amazon Identity and Access Management (IAM) role that requested the batch inference job.
The status of the batch inference job. The status is one of the following values:
The time at which the batch inference job was created.
The time at which the batch inference job was last updated.
Exceptions
Describes the given campaign, including its status.
A campaign can be in one of the following states:
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the campaign.
{
'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
The properties of the campaign.
The name of the campaign.
The Amazon Resource Name (ARN) of the campaign.
The Amazon Resource Name (ARN) of a specific version of the solution.
Specifies the requested minimum provisioned transactions (recommendations) per second.
The configuration details of a campaign.
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. Provide itemExplorationConfig data only if your solution uses the User-Personalization recipe.
The status of the campaign.
A campaign can be in one of the following states:
If a campaign fails, the reason behind the failure.
The date and time (in Unix format) that the campaign was created.
The date and time (in Unix format) that the campaign was last updated.
Provides a summary of the properties of a campaign update. For a complete listing, call the DescribeCampaign API.
The Amazon Resource Name (ARN) of the deployed solution version.
Specifies the requested minimum provisioned transactions (recommendations) per second that Amazon Personalize will support.
The configuration details of a campaign.
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. Provide itemExplorationConfig data only if your solution uses the User-Personalization recipe.
The status of the campaign update.
A campaign update can be in one of the following states:
If a campaign update fails, the reason behind the failure.
The date and time (in Unix time) that the campaign update was created.
The date and time (in Unix time) that the campaign update was last updated.
Exceptions
Describes the given dataset. For more information on datasets, see CreateDataset .
See also: AWS API Documentation
Request Syntax
response = client.describe_dataset(
datasetArn='string'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the dataset to describe.
{
'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
A listing of the dataset's properties.
The name of the dataset.
The Amazon Resource Name (ARN) of the dataset that you want metadata for.
The Amazon Resource Name (ARN) of the dataset group.
One of the following values:
The ARN of the associated schema.
The status of the dataset.
A dataset can be in one of the following states:
The creation date and time (in Unix time) of the dataset.
A time stamp that shows when the dataset was updated.
Exceptions
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the dataset export job to describe.
{
'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
Information about the dataset export job, including the status.
The status is one of the following values:
The name of the export job.
The Amazon Resource Name (ARN) of the dataset export job.
The Amazon Resource Name (ARN) of the dataset to export.
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 .
The Amazon Resource Name (ARN) of the IAM service role that has permissions to add data to your output Amazon S3 bucket.
The status of the dataset export job.
A dataset export job can be in one of the following states:
The path to the Amazon S3 bucket where the job's output is stored. For example:
s3://bucket-name/folder-name/
The configuration details of an Amazon S3 input or output bucket.
The file path of the Amazon S3 bucket.
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 of a batch inference job.
The creation date and time (in Unix time) of the dataset export job.
The date and time (in Unix time) the status of the dataset export job was last updated.
If a dataset export job fails, provides the reason why.
Exceptions
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the dataset group to describe.
{
'datasetGroup': {
'name': 'string',
'datasetGroupArn': 'string',
'status': 'string',
'roleArn': 'string',
'kmsKeyArn': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1),
'failureReason': 'string'
}
}
Response Structure
A listing of the dataset group's properties.
The name of the dataset group.
The Amazon Resource Name (ARN) of the dataset group.
The current status of the dataset group.
A dataset group can be in one of the following states:
The ARN of the IAM role that has permissions to create the dataset group.
The Amazon Resource Name (ARN) of the Key Management Service (KMS) key used to encrypt the datasets.
The creation date and time (in Unix time) of the dataset group.
The last update date and time (in Unix time) of the dataset group.
If creating a dataset group fails, provides the reason why.
Exceptions
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the dataset import job to describe.
{
'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'
}
}
Response Structure
Information about the dataset import job, including the status.
The status is one of the following values:
The name of the import job.
The ARN of the dataset import job.
The Amazon Resource Name (ARN) of the dataset that receives the imported data.
The Amazon S3 bucket that contains the training data to import.
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/
The ARN of the IAM role that has permissions to read from the Amazon S3 data source.
The status of the dataset import job.
A dataset import job can be in one of the following states:
The creation date and time (in Unix time) of the dataset import job.
The date and time (in Unix time) the dataset was last updated.
If a dataset import job fails, provides the reason why.
Exceptions
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the event tracker to describe.
{
'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
An object that describes the event tracker.
The name of the event tracker.
The ARN of the event tracker.
The Amazon Web Services account that owns the event tracker.
The ID of the event tracker. Include this ID in requests to the PutEvents API.
The Amazon Resource Name (ARN) of the dataset group that receives the event data.
The status of the event tracker.
An event tracker can be in one of the following states:
The date and time (in Unix format) that the event tracker was created.
The date and time (in Unix time) that the event tracker was last updated.
Exceptions
Describes the given feature transformation.
See also: AWS API Documentation
Request Syntax
response = client.describe_feature_transformation(
featureTransformationArn='string'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the feature transformation to describe.
{
'featureTransformation': {
'name': 'string',
'featureTransformationArn': 'string',
'defaultParameters': {
'string': 'string'
},
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1),
'status': 'string'
}
}
Response Structure
A listing of the FeatureTransformation properties.
The name of the feature transformation.
The Amazon Resource Name (ARN) of the FeatureTransformation object.
Provides the default parameters for feature transformation.
The creation date and time (in Unix time) of the feature transformation.
The last update date and time (in Unix time) of the feature transformation.
The status of the feature transformation.
A feature transformation can be in one of the following states:
Exceptions
Describes a filter's properties.
See also: AWS API Documentation
Request Syntax
response = client.describe_filter(
filterArn='string'
)
[REQUIRED]
The ARN of the filter to describe.
{
'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
The filter's details.
The name of the filter.
The ARN of the filter.
The time at which the filter was created.
The time at which the filter was last updated.
The ARN of the dataset group to which the filter belongs.
If the filter failed, the reason for its failure.
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 .
The status of the filter.
Exceptions
Describes a recipe.
A recipe contains three items:
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the recipe to describe.
{
'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
An object that describes the recipe.
The name of the recipe.
The Amazon Resource Name (ARN) of the recipe.
The Amazon Resource Name (ARN) of the algorithm that Amazon Personalize uses to train the model.
The ARN of the FeatureTransformation object.
The status of the recipe.
The description of the recipe.
The date and time (in Unix format) that the recipe was created.
One of the following values:
The date and time (in Unix format) that the recipe was last updated.
Exceptions
Describes a schema. For more information on schemas, see CreateSchema .
See also: AWS API Documentation
Request Syntax
response = client.describe_schema(
schemaArn='string'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the schema to retrieve.
{
'schema': {
'name': 'string',
'schemaArn': 'string',
'schema': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1)
}
}
Response Structure
The requested schema.
The name of the schema.
The Amazon Resource Name (ARN) of the schema.
The schema.
The date and time (in Unix time) that the schema was created.
The date and time (in Unix time) that the schema was last updated.
Exceptions
Describes a solution. For more information on solutions, see CreateSolution .
See also: AWS API Documentation
Request Syntax
response = client.describe_solution(
solutionArn='string'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the solution to describe.
{
'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
An object that describes the solution.
The name of the solution.
The ARN of the solution.
Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false .
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.
The ARN of the recipe used to create the solution.
The Amazon Resource Name (ARN) of the dataset group that provides the training data.
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.
Describes the configuration properties for the solution.
Only events with a value greater than or equal to this threshold are used for training a model.
Describes the properties for hyperparameter optimization (HPO).
The metric to optimize during HPO.
Note
Amazon Personalize doesn't support configuring the hpoObjective at this time.
The type of the metric. Valid values are Maximize and Minimize .
The name of the metric.
A regular expression for finding the metric in the training job logs.
Describes the resource configuration for HPO.
The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40 .
The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10 .
The hyperparameters and their allowable ranges.
The integer-valued hyperparameters and their ranges.
Provides the name and range of an integer-valued hyperparameter.
The name of the hyperparameter.
The minimum allowable value for the hyperparameter.
The maximum allowable value for the hyperparameter.
The continuous hyperparameters and their ranges.
Provides the name and range of a continuous hyperparameter.
The name of the hyperparameter.
The minimum allowable value for the hyperparameter.
The maximum allowable value for the hyperparameter.
The categorical hyperparameters and their ranges.
Provides the name and range of a categorical hyperparameter.
The name of the hyperparameter.
A list of the categories for the hyperparameter.
Lists the hyperparameter names and ranges.
Lists the feature transformation parameters.
The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
The metric to optimize.
The list of candidate recipes.
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution .
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).
Specifies how Amazon Personalize balances the importance of your optimization objective versus relevance.
When performAutoML is true, specifies the best recipe found.
The Amazon Resource Name (ARN) of the best recipe.
The status of the solution.
A solution can be in one of the following states:
The creation date and time (in Unix time) of the solution.
The date and time (in Unix time) that the solution was last updated.
Describes the latest version of the solution, including the status and the ARN.
The Amazon Resource Name (ARN) of the solution version.
The status of the solution version.
A solution version can be in one of the following states:
The date and time (in Unix time) that this version of a solution was created.
The date and time (in Unix time) that the solution version was last updated.
If a solution version fails, the reason behind the failure.
Exceptions
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the solution version.
{
'solutionVersion': {
'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
The solution version.
The ARN of the solution version.
The ARN of the solution.
Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false .
When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When false (the default), Amazon Personalize uses recipeArn .
The ARN of the recipe used in the solution.
The event type (for example, 'click' or 'like') that is used for training the model.
The Amazon Resource Name (ARN) of the dataset group providing the training data.
Describes the configuration properties for the solution.
Only events with a value greater than or equal to this threshold are used for training a model.
Describes the properties for hyperparameter optimization (HPO).
The metric to optimize during HPO.
Note
Amazon Personalize doesn't support configuring the hpoObjective at this time.
The type of the metric. Valid values are Maximize and Minimize .
The name of the metric.
A regular expression for finding the metric in the training job logs.
Describes the resource configuration for HPO.
The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40 .
The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10 .
The hyperparameters and their allowable ranges.
The integer-valued hyperparameters and their ranges.
Provides the name and range of an integer-valued hyperparameter.
The name of the hyperparameter.
The minimum allowable value for the hyperparameter.
The maximum allowable value for the hyperparameter.
The continuous hyperparameters and their ranges.
Provides the name and range of a continuous hyperparameter.
The name of the hyperparameter.
The minimum allowable value for the hyperparameter.
The maximum allowable value for the hyperparameter.
The categorical hyperparameters and their ranges.
Provides the name and range of a categorical hyperparameter.
The name of the hyperparameter.
A list of the categories for the hyperparameter.
Lists the hyperparameter names and ranges.
Lists the feature transformation parameters.
The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
The metric to optimize.
The list of candidate recipes.
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution .
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).
Specifies how Amazon Personalize balances the importance of your optimization objective versus relevance.
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.
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.
If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.
A list of the hyperparameter values of the best performing model.
The status of the solution version.
A solution version can be in one of the following states:
If training a solution version fails, the reason for the failure.
The date and time (in Unix time) that this version of the solution was created.
The date and time (in Unix time) that the solution was last updated.
Exceptions
Create a paginator for an operation.
Gets the metrics for the specified solution version.
See also: AWS API Documentation
Request Syntax
response = client.get_solution_metrics(
solutionVersionArn='string'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the solution version for which to get metrics.
{
'solutionVersionArn': 'string',
'metrics': {
'string': 123.0
}
}
Response Structure
The same solution version ARN as specified in the request.
The metrics for the solution version.
Exceptions
Returns an object that can wait for some condition.
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
)
dict
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 datatype. 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:
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
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
)
dict
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:
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
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
)
dict
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:
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
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
)
dict
Response Syntax
{
'datasetGroups': [
{
'name': 'string',
'datasetGroupArn': 'string',
'status': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1),
'failureReason': 'string'
},
],
'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:
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.
nextToken (string) --
A token for getting the next set of dataset groups (if they exist).
Exceptions
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
)
dict
Response Syntax
{
'datasetImportJobs': [
{
'datasetImportJobArn': 'string',
'jobName': 'string',
'status': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1),
'failureReason': 'string'
},
],
'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:
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.
nextToken (string) --
A token for getting the next set of dataset import jobs (if they exist).
Exceptions
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
)
dict
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:
status (string) --
The status of the dataset.
A dataset can be in one of the following states:
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
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
)
dict
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:
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
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
)
dict
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
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
)
dict
Response Syntax
{
'recipes': [
{
'name': 'string',
'recipeArn': 'string',
'status': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1)
},
],
'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.
nextToken (string) --
A token for getting the next set of recipes.
Exceptions
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
)
dict
Response Syntax
{
'schemas': [
{
'name': 'string',
'schemaArn': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1)
},
],
'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.
nextToken (string) --
A token used to get the next set of schemas (if they exist).
Exceptions
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). For more information on solutions, see CreateSolution .
See also: AWS API Documentation
Request Syntax
response = client.list_solution_versions(
solutionArn='string',
nextToken='string',
maxResults=123
)
dict
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:
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
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
)
dict
Response Syntax
{
'solutions': [
{
'name': 'string',
'solutionArn': 'string',
'status': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1)
},
],
'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:
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.
nextToken (string) --
A token for getting the next set of solutions (if they exist).
Exceptions
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:
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'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the solution version you want to stop creating.
Exceptions
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 API.
Note
You must wait until the status of the updated campaign is ACTIVE before asking the campaign for recommendations.
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'
}
}
)
[REQUIRED]
The Amazon Resource Name (ARN) of the campaign.
The configuration details of a campaign.
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. Provide itemExplorationConfig data only if your solution uses the User-Personalization recipe.
dict
Response Syntax
{
'campaignArn': 'string'
}
Response Structure
(dict) --
campaignArn (string) --
The same campaign ARN as given in the request.
Exceptions
The available paginators are:
paginator = client.get_paginator('list_batch_inference_jobs')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
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 datatype. 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:
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.
paginator = client.get_paginator('list_campaigns')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
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:
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.
paginator = client.get_paginator('list_dataset_export_jobs')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
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:
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.
paginator = client.get_paginator('list_dataset_groups')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
{
'datasetGroups': [
{
'name': 'string',
'datasetGroupArn': 'string',
'status': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1),
'failureReason': 'string'
},
],
'NextToken': 'string'
}
Response Structure
The list of your dataset groups.
Provides a summary of the properties of a dataset group. For a complete listing, call the DescribeDatasetGroup API.
The name of the dataset group.
The Amazon Resource Name (ARN) of the dataset group.
The status of the dataset group.
A dataset group can be in one of the following states:
The date and time (in Unix time) that the dataset group was created.
The date and time (in Unix time) that the dataset group was last updated.
If creating a dataset group fails, the reason behind the failure.
A token to resume pagination.
paginator = client.get_paginator('list_dataset_import_jobs')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'datasetImportJobs': [
{
'datasetImportJobArn': 'string',
'jobName': 'string',
'status': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1),
'failureReason': 'string'
},
],
'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:
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.
NextToken (string) --
A token to resume pagination.
paginator = client.get_paginator('list_datasets')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
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:
status (string) --
The status of the dataset.
A dataset can be in one of the following states:
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.
paginator = client.get_paginator('list_event_trackers')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
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:
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.
paginator = client.get_paginator('list_filters')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
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.
paginator = client.get_paginator('list_recipes')
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',
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'recipes': [
{
'name': 'string',
'recipeArn': 'string',
'status': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1)
},
],
'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.
NextToken (string) --
A token to resume pagination.
paginator = client.get_paginator('list_schemas')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
{
'schemas': [
{
'name': 'string',
'schemaArn': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1)
},
],
'NextToken': 'string'
}
Response Structure
A list of schemas.
Provides a summary of the properties of a dataset schema. For a complete listing, call the DescribeSchema API.
The name of the schema.
The Amazon Resource Name (ARN) of the schema.
The date and time (in Unix time) that the schema was created.
The date and time (in Unix time) that the schema was last updated.
A token to resume pagination.
paginator = client.get_paginator('list_solution_versions')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
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:
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.
paginator = client.get_paginator('list_solutions')
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'
}
)
A dictionary that provides parameters to control pagination.
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.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'solutions': [
{
'name': 'string',
'solutionArn': 'string',
'status': 'string',
'creationDateTime': datetime(2015, 1, 1),
'lastUpdatedDateTime': datetime(2015, 1, 1)
},
],
'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:
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.
NextToken (string) --
A token to resume pagination.