abacusai.batch_prediction_version

Classes

BatchPredictionVersion

Batch Prediction Version

Module Contents

class abacusai.batch_prediction_version.BatchPredictionVersion(client, batchPredictionVersion=None, batchPredictionId=None, status=None, driftMonitorStatus=None, deploymentId=None, modelId=None, modelVersion=None, predictionsStartedAt=None, predictionsCompletedAt=None, databaseOutputError=None, totalPredictions=None, failedPredictions=None, databaseConnectorId=None, databaseOutputConfiguration=None, fileConnectorOutputLocation=None, fileOutputFormat=None, connectorType=None, legacyInputLocation=None, error=None, driftMonitorError=None, monitorWarnings=None, csvInputPrefix=None, csvPredictionPrefix=None, csvExplanationsPrefix=None, databaseOutputTotalWrites=None, databaseOutputFailedWrites=None, outputIncludesMetadata=None, resultInputColumns=None, modelMonitorVersion=None, algoName=None, algorithm=None, outputFeatureGroupId=None, outputFeatureGroupVersion=None, outputFeatureGroupTableName=None, batchPredictionWarnings=None, bpAcrossVersionsMonitorVersion=None, batchPredictionArgsType=None, batchInputs={}, inputFeatureGroups={}, globalPredictionArgs={}, batchPredictionArgs={})

Bases: abacusai.return_class.AbstractApiClass

Batch Prediction Version

Parameters:

  • client (ApiClient) – An authenticated API Client instance

  • batchPredictionVersion (str) – The unique identifier of the batch prediction version

  • batchPredictionId (str) – The unique identifier of the batch prediction

  • status (str) – The current status of the batch prediction

  • driftMonitorStatus (str) – The status of the drift monitor for this batch prediction version

  • deploymentId (str) – The deployment used to make the predictions

  • modelId (str) – The model used to make the predictions

  • modelVersion (str) – The model version used to make the predictions

  • predictionsStartedAt (str) – Predictions start date and time

  • predictionsCompletedAt (str) – Predictions completion date and time

  • databaseOutputError (bool) – If true, there were errors reported by the database connector while writing

  • totalPredictions (int) – Number of predictions performed in this batch prediction job

  • failedPredictions (int) – Number of predictions that failed

  • databaseConnectorId (str) – The database connector to write the results to

  • databaseOutputConfiguration (dict) – Contains information about where the batch predictions are written to

  • fileConnectorOutputLocation (str) – Contains information about where the batch predictions are written to

  • 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

  • error (str) – Relevant error if the status is FAILED

  • driftMonitorError (str) – Error message for the drift monitor of this batch predcition

  • monitorWarnings (str) – Relevant warning if there are issues found in drift or data integrity

  • 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

  • databaseOutputTotalWrites (int) – The total number of rows attempted to write (may be less than total_predictions if write mode is UPSERT and multiple rows share the same ID)

  • databaseOutputFailedWrites (int) – The number of failed writes to the Database Connector

  • outputIncludesMetadata (bool) – If true, output will contain columns including prediction start time, batch prediction version, and model version

  • resultInputColumns (list[str]) – If present, will limit result files or feature groups to only include columns present in this list

  • modelMonitorVersion (str) – The version of the model monitor

  • algoName (str) – The name of the algorithm used to train the model

  • algorithm (str) – The algorithm that is currently deployed.

  • outputFeatureGroupId (str) – The Batch Prediction output feature group ID if applicable

  • outputFeatureGroupVersion (str) – The Batch Prediction output feature group version if applicable

  • outputFeatureGroupTableName (str) – The Batch Prediction output feature group name if applicable

  • batchPredictionWarnings (str) – Relevant warnings if any issues are found

  • bpAcrossVersionsMonitorVersion (str) – The version of the batch prediction across versions monitor

  • batchPredictionArgsType (str) – The type of the batch prediction args

  • batchInputs (PredictionInput) – Inputs to the batch prediction

  • inputFeatureGroups (PredictionFeatureGroup) – List of prediction feature groups

  • globalPredictionArgs (BatchPredictionArgs)

  • batchPredictionArgs (BatchPredictionArgs) – Argument(s) passed to every prediction call

batch_prediction_version
batch_prediction_id
status
drift_monitor_status
deployment_id
model_id
model_version
predictions_started_at
predictions_completed_at
database_output_error
total_predictions
failed_predictions
database_connector_id
database_output_configuration
file_connector_output_location
file_output_format
connector_type
legacy_input_location
error
drift_monitor_error
monitor_warnings
csv_input_prefix
csv_prediction_prefix
csv_explanations_prefix
database_output_total_writes
database_output_failed_writes
output_includes_metadata
result_input_columns
model_monitor_version
algo_name
algorithm
output_feature_group_id
output_feature_group_version
output_feature_group_table_name
batch_prediction_warnings
bp_across_versions_monitor_version
batch_prediction_args_type
batch_inputs
input_feature_groups
global_prediction_args
batch_prediction_args
deprecated_keys
__repr__()
to_dict()

Get a dict representation of the parameters in this class

Returns:

The dict value representation of the class parameters

Return type:

dict

download_batch_prediction_result_chunk(offset=0, chunk_size=10485760)

Returns a stream containing the batch prediction results.

Parameters:

  • offset (int) – The offset to read from.

  • chunk_size (int) – The maximum amount of data to read.

get_batch_prediction_connector_errors()

Returns a stream containing the batch prediction database connection write errors, if any writes failed for the specified batch prediction job.

Parameters:

batch_prediction_version (str) – Unique string identifier of the batch prediction job to get the errors for.

refresh()

Calls describe and refreshes the current object’s fields

Returns:

The current object

Return type:

BatchPredictionVersion

describe()

Describes a Batch Prediction Version.

Parameters:

batch_prediction_version (str) – Unique string identifier of the Batch Prediction Version.

Returns:

The Batch Prediction Version.

Return type:

BatchPredictionVersion

get_logs()

Retrieves the batch prediction logs.

Parameters:

batch_prediction_version (str) – The unique version ID of the batch prediction version.

Returns:

The logs for the specified batch prediction version.

Return type:

BatchPredictionVersionLogs

download_result_to_file(file)

Downloads the batch prediction version in a local file.

Parameters:

file (file object) – A file object opened in a binary mode e.g., file=open(‘/tmp/output’, ‘wb’).

wait_for_predictions(timeout=86400)

A waiting call until batch prediction version is ready.

Parameters:

timeout (int) – 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) – 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(drift_monitor_status=False)

Gets the status of the batch prediction version.

Returns:

A string describing the status of the batch prediction version, for e.g., pending, complete, etc.

Return type:

str

Parameters:

drift_monitor_status (bool)

load_results_as_pandas()

Loads the output feature groups into a python pandas dataframe.

Returns:

A pandas dataframe with annotations and text_snippet columns.

Return type:

DataFrame