abacusai.batch_prediction
Module Contents
Classes
Batch predictions |
- class abacusai.batch_prediction.BatchPrediction(client, batchPredictionId=None, createdAt=None, name=None, deploymentId=None, fileConnectorOutputLocation=None, globalPredictionArgs=None, databaseConnectorId=None, databaseOutputConfiguration=None, explanations=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, featureGroupTableName=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, outputIncludesMetadata=None, resultInputColumns=None, batchInputs={}, latestBatchPredictionVersion={}, refreshSchedules={})
Bases:
abacusai.return_class.AbstractApiClass
Batch predictions
- Parameters:
client (ApiClient) – An authenticated API Client instance
batchPredictionId (str) – The unique identifier of the batch prediction request
createdAt (str) – When the batch prediction was created
name (str) – Name given to the batch prediction object
deploymentId (str) – The deployment used to make the predictions
fileConnectorOutputLocation (str) – Contains information about where the batch predictions are written to
globalPredictionArgs (dict) – Argument(s) passed to every prediction call
databaseConnectorId (str) – The database connector to write the results to
databaseOutputConfiguration (dict) – Contains information about where the batch predictions are written to
explanations (bool) – If true, explanations for each prediction were created
fileOutputFormat (str) – The format of the batch prediction output (CSV or JSON)
connectorType (str) – Null if writing to internal console, else FEATURE_GROUP | FILE_CONNECTOR | DATABASE_CONNECTOR
legacyInputLocation (str) – The location of the input data
featureGroupTableName (str) – The table name of the Batch Prediction feature group
csvInputPrefix (str) – A prefix to prepend to the input columns, only applies when output format is CSV
csvPredictionPrefix (str) – A prefix to prepend to the prediction columns, only applies when output format is CSV
csvExplanationsPrefix (str) – A prefix to prepend to the explanation columns, only applies when output format is CSV
outputIncludesMetadata (bool) – If true, output will contain columns including prediction start time, batch prediction version, and model version
resultInputColumns (list of string) – If present, will limit result files or feature groups to only include columns present in this list
batchInputs (PredictionInput) – Inputs to the batch prediction
latestBatchPredictionVersion (BatchPredictionVersion) – The latest batch prediction version
refreshSchedules (RefreshSchedule) – List of refresh schedules that dictate the next time the batch prediction will be run
- __repr__()
Return repr(self).
- to_dict()
Get a dict representation of the parameters in this class
- Returns:
The dict value representation of the class parameters
- Return type:
- start()
Creates a new batch prediction version job for a given batch prediction job description
- Parameters:
batch_prediction_id (str) – The unique identifier of the batch prediction to create a new version of
- Returns:
The batch prediction version started by this method call.
- Return type:
- refresh()
Calls describe and refreshes the current object’s fields
- Returns:
The current object
- Return type:
- describe()
Describes the batch prediction
- Parameters:
batch_prediction_id (str) – The unique ID associated with the batch prediction.
- Returns:
The batch prediction description.
- Return type:
- list_versions(limit=100, start_after_version=None)
Retrieves a list of versions of a given batch prediction
- Parameters:
- Returns:
A list of batch prediction versions.
- Return type:
- update(deployment_id=None, global_prediction_args=None, explanations=None, output_format=None, csv_input_prefix=None, csv_prediction_prefix=None, csv_explanations_prefix=None, output_includes_metadata=None, result_input_columns=None)
Updates a batch prediction job description
- Parameters:
deployment_id (str) – The unique identifier to a deployment.
global_prediction_args (dict) – Argument(s) to pass on every prediction call.
explanations (bool) – If true, will provide SHAP Explanations for each prediction, if supported by the use case.
output_format (str) – If specified, sets the format of the batch prediction output (CSV or JSON).
csv_input_prefix (str) – A prefix to prepend to the input columns, only applies when output format is CSV
csv_prediction_prefix (str) – A prefix to prepend to the prediction columns, only applies when output format is CSV
csv_explanations_prefix (str) – A prefix to prepend to the explanation columns, only applies when output format is CSV
output_includes_metadata (bool) – If true, output will contain columns including prediction start time, batch prediction version, and model version
result_input_columns (list) – If present, will limit result files or feature groups to only include columns present in this list
- Returns:
The batch prediction description.
- Return type:
- set_file_connector_output(output_format=None, output_location=None)
Updates the file connector output configuration of the batch prediction
- Parameters:
- Returns:
The batch prediction description.
- Return type:
- set_database_connector_output(database_connector_id=None, database_output_config=None)
Updates the database connector output configuration of the batch prediction
- Parameters:
- Returns:
The batch prediction description.
- Return type:
- set_feature_group_output(table_name)
Creates a feature group and sets it to be the batch prediction output
- Parameters:
table_name (str) – The name of the feature group table to create
- Returns:
The batch prediction after the output has been applied
- Return type:
- set_output_to_console()
Sets the batch prediction output to the console, clearing both the file connector and database connector config
- Parameters:
batch_prediction_id (str) – The unique identifier of the batch prediction
- Returns:
The batch prediction description.
- Return type:
- set_dataset(dataset_type, dataset_id=None)
[Deprecated] Sets the batch prediction input dataset. Only applicable for legacy dataset-based projects
- Parameters:
- Returns:
The batch prediction description.
- Return type:
- set_feature_group(feature_group_type, feature_group_id=None)
Sets the batch prediction input feature group.
- Parameters:
feature_group_type (str) – The feature group type to set. The feature group type of the feature group. The type is based on the use case under which the feature group is being created. For example, Catalog Attributes can be a feature group type under personalized recommendation use case.
feature_group_id (str) – The feature group to set as input to the batch prediction
- Returns:
The batch prediction description.
- Return type:
- set_dataset_remap(dataset_id_remap)
For the purpose of this batch prediction, will swap out datasets in the input feature groups
- Parameters:
dataset_id_remap (dict) – Key/value pairs of dataset_ids to replace during batch predictions
- Returns:
Batch Prediction object
- Return type:
- delete()
Deletes a batch prediction
- Parameters:
batch_prediction_id (str) – The unique identifier of the batch prediction
- wait_for_predictions(timeout=86400)
A waiting call until batch predictions are ready.
- Parameters:
timeout (int, optional) – The waiting time given to the call to finish, if it doesn’t finish by the allocated time, the call is said to be timed out.
- wait_for_drift_monitor(timeout=86400)
A waiting call until batch prediction drift monitor calculations are ready.
- Parameters:
timeout (int, optional) – The waiting time given to the call to finish, if it doesn’t finish by the allocated time, the call is said to be timed out.
- get_status()
Gets the status of the latest batch prediction version.
- Returns:
A string describing the status of the latest batch prediction version e.g., pending, complete, etc.
- Return type:
- create_refresh_policy(cron)
To create a refresh policy for a batch prediction.
- Parameters:
cron (str) – A cron style string to set the refresh time.
- Returns:
The refresh policy object.
- Return type:
- list_refresh_policies()
Gets the refresh policies in a list.
- Returns:
A list of refresh policy objects.
- Return type:
List[RefreshPolicy]
- describe_output_feature_group()
Gets the results feature group for this batch prediction
- Returns:
A feature group object.
- Return type: