abacusai.batch_prediction_version ================================= .. py:module:: abacusai.batch_prediction_version Classes ------- .. autoapisummary:: abacusai.batch_prediction_version.BatchPredictionVersion Module Contents --------------- .. py:class:: 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: :py:obj:`abacusai.return_class.AbstractApiClass` Batch Prediction Version :param client: An authenticated API Client instance :type client: ApiClient :param batchPredictionVersion: The unique identifier of the batch prediction version :type batchPredictionVersion: str :param batchPredictionId: The unique identifier of the batch prediction :type batchPredictionId: str :param status: The current status of the batch prediction :type status: str :param driftMonitorStatus: The status of the drift monitor for this batch prediction version :type driftMonitorStatus: str :param deploymentId: The deployment used to make the predictions :type deploymentId: str :param modelId: The model used to make the predictions :type modelId: str :param modelVersion: The model version used to make the predictions :type modelVersion: str :param predictionsStartedAt: Predictions start date and time :type predictionsStartedAt: str :param predictionsCompletedAt: Predictions completion date and time :type predictionsCompletedAt: str :param databaseOutputError: If true, there were errors reported by the database connector while writing :type databaseOutputError: bool :param totalPredictions: Number of predictions performed in this batch prediction job :type totalPredictions: int :param failedPredictions: Number of predictions that failed :type failedPredictions: int :param databaseConnectorId: The database connector to write the results to :type databaseConnectorId: str :param databaseOutputConfiguration: Contains information about where the batch predictions are written to :type databaseOutputConfiguration: dict :param fileConnectorOutputLocation: Contains information about where the batch predictions are written to :type fileConnectorOutputLocation: str :param fileOutputFormat: The format of the batch prediction output (CSV or JSON) :type fileOutputFormat: str :param connectorType: Null if writing to internal console, else FEATURE_GROUP | FILE_CONNECTOR | DATABASE_CONNECTOR :type connectorType: str :param legacyInputLocation: The location of the input data :type legacyInputLocation: str :param error: Relevant error if the status is FAILED :type error: str :param driftMonitorError: Error message for the drift monitor of this batch predcition :type driftMonitorError: str :param monitorWarnings: Relevant warning if there are issues found in drift or data integrity :type monitorWarnings: str :param csvInputPrefix: A prefix to prepend to the input columns, only applies when output format is CSV :type csvInputPrefix: str :param csvPredictionPrefix: A prefix to prepend to the prediction columns, only applies when output format is CSV :type csvPredictionPrefix: str :param csvExplanationsPrefix: A prefix to prepend to the explanation columns, only applies when output format is CSV :type csvExplanationsPrefix: str :param databaseOutputTotalWrites: 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) :type databaseOutputTotalWrites: int :param databaseOutputFailedWrites: The number of failed writes to the Database Connector :type databaseOutputFailedWrites: int :param outputIncludesMetadata: If true, output will contain columns including prediction start time, batch prediction version, and model version :type outputIncludesMetadata: bool :param resultInputColumns: If present, will limit result files or feature groups to only include columns present in this list :type resultInputColumns: list[str] :param modelMonitorVersion: The version of the model monitor :type modelMonitorVersion: str :param algoName: The name of the algorithm used to train the model :type algoName: str :param algorithm: The algorithm that is currently deployed. :type algorithm: str :param outputFeatureGroupId: The Batch Prediction output feature group ID if applicable :type outputFeatureGroupId: str :param outputFeatureGroupVersion: The Batch Prediction output feature group version if applicable :type outputFeatureGroupVersion: str :param outputFeatureGroupTableName: The Batch Prediction output feature group name if applicable :type outputFeatureGroupTableName: str :param batchPredictionWarnings: Relevant warnings if any issues are found :type batchPredictionWarnings: str :param bpAcrossVersionsMonitorVersion: The version of the batch prediction across versions monitor :type bpAcrossVersionsMonitorVersion: str :param batchPredictionArgsType: The type of the batch prediction args :type batchPredictionArgsType: str :param batchInputs: Inputs to the batch prediction :type batchInputs: PredictionInput :param inputFeatureGroups: List of prediction feature groups :type inputFeatureGroups: PredictionFeatureGroup :param globalPredictionArgs: :type globalPredictionArgs: BatchPredictionArgs :param batchPredictionArgs: Argument(s) passed to every prediction call :type batchPredictionArgs: BatchPredictionArgs .. py:attribute:: batch_prediction_version :value: None .. py:attribute:: batch_prediction_id :value: None .. py:attribute:: status :value: None .. py:attribute:: drift_monitor_status :value: None .. py:attribute:: deployment_id :value: None .. py:attribute:: model_id :value: None .. py:attribute:: model_version :value: None .. py:attribute:: predictions_started_at :value: None .. py:attribute:: predictions_completed_at :value: None .. py:attribute:: database_output_error :value: None .. py:attribute:: total_predictions :value: None .. py:attribute:: failed_predictions :value: None .. py:attribute:: database_connector_id :value: None .. py:attribute:: database_output_configuration :value: None .. py:attribute:: file_connector_output_location :value: None .. py:attribute:: file_output_format :value: None .. py:attribute:: connector_type :value: None .. py:attribute:: legacy_input_location :value: None .. py:attribute:: error :value: None .. py:attribute:: drift_monitor_error :value: None .. py:attribute:: monitor_warnings :value: None .. py:attribute:: csv_input_prefix :value: None .. py:attribute:: csv_prediction_prefix :value: None .. py:attribute:: csv_explanations_prefix :value: None .. py:attribute:: database_output_total_writes :value: None .. py:attribute:: database_output_failed_writes :value: None .. py:attribute:: output_includes_metadata :value: None .. py:attribute:: result_input_columns :value: None .. py:attribute:: model_monitor_version :value: None .. py:attribute:: algo_name :value: None .. py:attribute:: algorithm :value: None .. py:attribute:: output_feature_group_id :value: None .. py:attribute:: output_feature_group_version :value: None .. py:attribute:: output_feature_group_table_name :value: None .. py:attribute:: batch_prediction_warnings :value: None .. py:attribute:: bp_across_versions_monitor_version :value: None .. py:attribute:: batch_prediction_args_type :value: None .. py:attribute:: batch_inputs .. py:attribute:: input_feature_groups .. py:attribute:: global_prediction_args .. py:attribute:: batch_prediction_args .. py:attribute:: deprecated_keys .. py:method:: __repr__() .. py:method:: to_dict() Get a dict representation of the parameters in this class :returns: The dict value representation of the class parameters :rtype: dict .. py:method:: download_batch_prediction_result_chunk(offset = 0, chunk_size = 10485760) Returns a stream containing the batch prediction results. :param offset: The offset to read from. :type offset: int :param chunk_size: The maximum amount of data to read. :type chunk_size: int .. py:method:: 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. :param batch_prediction_version: Unique string identifier of the batch prediction job to get the errors for. :type batch_prediction_version: str .. py:method:: refresh() Calls describe and refreshes the current object's fields :returns: The current object :rtype: BatchPredictionVersion .. py:method:: describe() Describes a Batch Prediction Version. :param batch_prediction_version: Unique string identifier of the Batch Prediction Version. :type batch_prediction_version: str :returns: The Batch Prediction Version. :rtype: BatchPredictionVersion .. py:method:: get_logs() Retrieves the batch prediction logs. :param batch_prediction_version: The unique version ID of the batch prediction version. :type batch_prediction_version: str :returns: The logs for the specified batch prediction version. :rtype: BatchPredictionVersionLogs .. py:method:: download_result_to_file(file) Downloads the batch prediction version in a local file. :param file: A file object opened in a binary mode e.g., file=open('/tmp/output', 'wb'). :type file: file object .. py:method:: wait_for_predictions(timeout=86400) A waiting call until batch prediction version is ready. :param timeout: 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. :type timeout: int .. py:method:: wait_for_drift_monitor(timeout=86400) A waiting call until batch prediction drift monitor calculations are ready. :param timeout: 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. :type timeout: int .. py:method:: 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. :rtype: str .. py:method:: load_results_as_pandas() Loads the output feature groups into a python pandas dataframe. :returns: A pandas dataframe with annotations and text_snippet columns. :rtype: DataFrame