Developer documentation > API reference > Python API client > Monitoring > Data exports

Data exports¶

PredictionDataExport¶

class datarobot.models.deployment.data_exports.PredictionDataExport

A prediction data export.

Added in version v3.4.

Variables

Attribute	Type	Description
`id`	`str`	The ID of the prediction data export.
`model_id`	`str`	The ID of the model (or null if not specified).
`created_at`	`datetime`	Prediction data export creation timestamp.
`period`	`Period`	A prediction data time range definition.
`status`	`ExportStatus`	A prediction data export processing state.
`error`	`ExportError`	Error description, appears when prediction data export job failed (status is FAILED).
`batches`	`ExportBatches`	Metadata associated with exported batch.
`deployment_id`	`str`	The ID of the deployment.

list()¶

classmethod list()

Retrieve a list of prediction data exports.

Parameters

Parameter	Type	Description
`deployment_id`	`str`	The ID of the deployment.
`model_id`	`Optional[str]`	The ID of the model used for prediction data export.
`status`	`Optional[ExportStatus]`	A prediction data export processing state.
`batch`	`Optional[bool]`	If true, only return batch exports. If false, only return real-time exports. If not provided, return both real-time and batch exports.
`limit`	`Optional[int]`	The maximum number of objects to return. The default is 100 (0 means no limit).
`offset`	`Optional[int]`	The starting offset of the results. The default is 0.

Returns

Returns	Description
prediction_data_exports	A list of PredictionDataExport objects.

Return type: list

Examples

from datarobot.models.deployment import PredictionDataExport

prediction_data_exports = PredictionDataExport.list(deployment_id='5c939e08962d741e34f609f0')

get()¶

classmethod get()

Retrieve a single prediction data export.

Parameters

Parameter	Type	Description
`deployment_id`	`str`	The ID of the deployment.
`export_id`	`str`	The ID of the prediction data export.

Returns

Returns	Description
prediction_data_export	A prediction data export.

Return type: PredictionDataExport

Examples

from datarobot.models.deployment import PredictionDataExport

prediction_data_export = PredictionDataExport.get(
    deployment_id='5c939e08962d741e34f609f0', export_id='65fbe59aaa3f847bd5acc75b'
    )

create()¶

classmethod create()

Create a deployment prediction data export. Waits until ready and fetches PredictionDataExport after the export finishes. This method is blocking.

Parameters

Parameter	Type	Description
`deployment_id`	`str`	The ID of the deployment.
`start`	`Union[datetime`, `str]`	Inclusive start of the time range.
`end`	`Union[datetime`, `str]`	Exclusive end of the time range.
`model_id`	`Optional[str]`	The ID of the model.
`batch_ids`	`Optional[List[str]]`	IDs of batches to export. Null for real-time data exports.
`max_wait`	`int,`	Seconds to wait for successful resolution.

Returns

Returns	Description
prediction_data_export	A prediction data export.

Return type: PredictionDataExport

Examples

from datetime import datetime, timedelta
from datarobot.models.deployment import PredictionDataExport

now=datetime.now()
prediction_data_export = PredictionDataExport.create(
    deployment_id='5c939e08962d741e34f609f0', start=now - timedelta(days=7), end=now
    )

fetch_data()¶

method fetch_data()

Return data from prediction export as datarobot Dataset.

Returns

Returns	Description
prediction_datasets	List of datasets for a given export, most often it is just one.

Return type: List[Dataset]

Examples

from datarobot.models.deployment import PredictionDataExport

prediction_data_export = PredictionDataExport.get(
    deployment_id='5c939e08962d741e34f609f0', export_id='65fbe59aaa3f847bd5acc75b'
    )
prediction_datasets = prediction_data_export.fetch_data()

ActualsDataExport¶

class datarobot.models.deployment.data_exports.ActualsDataExport

An actuals data export.

Added in version v3.4.

Variables

Attribute	Type	Description
`id`	`str`	The ID of the actuals data export.
`model_id`	`str`	The ID of the model (or null if not specified).
`created_at`	`datetime`	Actuals data export creation timestamp.
`period`	`Period`	A actuals data time range definition.
`status`	`ExportStatus`	A data export processing state.
`error`	`ExportError`	Error description, appears when actuals data export job failed (status is FAILED).
`only_matched_predictions`	`bool`	If true, exports actuals with matching predictions only.
`deployment_id`	`str`	The ID of the deployment.

list()¶

classmethod list()

Retrieve a list of actuals data exports.

Parameters

Parameter	Type	Description
`deployment_id`	`str`	The ID of the deployment.
`status`	`Optional[ExportStatus]`	Actuals data export processing state.
`limit`	`Optional[int]`	The maximum number of objects to return. The default is 100 (0 means no limit).
`offset`	`Optional[int]`	The starting offset of the results. The default is 0.

Returns

Returns	Description
actuals_data_exports	A list of ActualsDataExport objects.

Return type: list

Examples

from datarobot.models.deployment import ActualsDataExport

actuals_data_exports = ActualsDataExport.list(deployment_id='5c939e08962d741e34f609f0')

get()¶

classmethod get()

Retrieve a single actuals data export.

Parameters

Parameter	Type	Description
`deployment_id`	`str`	The ID of the deployment.
`export_id`	`str`	The ID of the actuals data export.

Returns

Returns	Description
actuals_data_export	An actuals data export.

Return type: ActualsDataExport

Examples

from datarobot.models.deployment import ActualsDataExport

actuals_data_export = ActualsDataExport.get(
    deployment_id='5c939e08962d741e34f609f0', export_id='65fb0a6c9bb187781cfdea36'
    )

create()¶

classmethod create()

Create a deployment actuals data export. Waits until ready and fetches ActualsDataExport after the export finishes. This method is blocking.

Parameters

Parameter	Type	Description
`deployment_id`	`str`	The ID of the deployment.
`start`	`Union[datetime`, `str]`	Inclusive start of the time range.
`end`	`Union[datetime`, `str]`	Exclusive end of the time range.
`model_id`	`Optional[str]`	The ID of the model.
`only_matched_predictions`	`Optional[bool]`	If true, exports actuals with matching predictions only.
`max_wait`	`int`	Seconds to wait for successful resolution.

Returns

Returns	Description
actuals_data_export	An actuals data export.

Return type: ActualsDataExport

Examples

from datetime import datetime, timedelta
from datarobot.models.deployment import ActualsDataExport

now=datetime.now()
actuals_data_export = ActualsDataExport.create(
    deployment_id='5c939e08962d741e34f609f0', start=now - timedelta(days=7), end=now
    )

fetch_data()¶

method fetch_data()

Return data from actuals export as datarobot Dataset.

Returns

Returns	Description
actuals_datasets	List of datasets for a given export, most often it is just one.

Return type: List[Dataset]

Examples

from datarobot.models.deployment import ActualsDataExport

actuals_data_export = ActualsDataExport.get(
    deployment_id='5c939e08962d741e34f609f0', export_id='65fb0a6c9bb187781cfdea36'
    )
actuals_datasets = actuals_data_export.fetch_data()

TrainingDataExport¶

class datarobot.models.deployment.data_exports.TrainingDataExport

A training data export.

Added in version v3.4.

Variables

Attribute	Type	Description
`id`	`str`	The ID of the training data export.
`model_id`	`str`	The ID of the model (or null if not specified).
`model_package_id`	`str`	The ID of the model package.
`created_at`	`datetime`	Training data export creation timestamp.
`deployment_id`	`str`	The ID of the deployment.

list()¶

classmethod list()

Retrieve a list of successful training data exports.

Parameters

Parameter	Type	Description
`deployment_id`	`str`	The ID of the deployment.

Returns

Returns	Description
training_data_exports	A list of TrainingDataExport objects.

Return type: list

Examples

from datarobot.models.deployment import TrainingDataExport

training_data_exports = TrainingDataExport.list(deployment_id='5c939e08962d741e34f609f0')

get()¶

classmethod get()

Retrieve a single training data export.

Parameters

Parameter	Type	Description
`deployment_id`	`str`	The ID of the deployment.
`export_id`	`str`	The ID of the training data export.

Returns

Returns	Description
training_data_export	A training data export.

Return type: TrainingDataExport

Examples

from datarobot.models.deployment import TrainingDataExport
training_data_export = TrainingDataExport.get(
    deployment_id='5c939e08962d741e34f609f0', export_id='65fbf2356124f1daa3acc522'
    )

create()¶

classmethod create()

Create a single training data export. Waits until ready and fetches TrainingDataExport after the export finishes. This method is blocking.

Parameters

Parameter	Type	Description
`deployment_id`	`str`	The ID of the deployment.
`model_id`	`Optional[str]`	The ID of the model.
`max_wait`	`int`	Seconds to wait for successful resolution.

Return type: str

Returns

Returns	Description
dataset_id (`str`)	A created dataset with training data. Examples * `--------` * `code-block:`: `python` – from datarobot.models.deployment import TrainingDataExport dataset_id = TrainingDataExport.create(deployment_id=’5c939e08962d741e34f609f0’)

fetch_data()¶

method fetch_data()

Return data from training data export as datarobot Dataset.

Returns

Returns	Description
training_dataset	A datasets for a given export.

Return type: Dataset

Examples

from datarobot.models.deployment import TrainingDataExport

training_data_export = TrainingDataExport.get(
    deployment_id='5c939e08962d741e34f609f0', export_id='65fbf2356124f1daa3acc522'
    )
training_data_export = training_data_export.fetch_data()

DataQualityExport¶

class datarobot.models.deployment.data_exports.DataQualityExport

A data quality export record.

Added in version v3.6.

Variables

Attribute	Type	Description
`association_id`	`str`	The association ID of the data quality export.
`timestamp`	`datetime`	The data quality export creation timestamp.
`deployment_id`	`str`	The ID of the deployment.
`prompt`	`Optional[str]`	The LLM prompt of the data quality export.
`predicted_value`	`str`	The predicted value of the data quality export.
`actual_value`	`Optional[str]`	The actual value (if available) of the data quality export.
`context`	`List[Dict[str`, `str]]`	Context data (context and link data) for the contexts associated with the data quality export.
`metrics`	`List[Dict[str`, `Any]]`	Custom-metrics data for the data quality export.

list()¶

classmethod list()

Retrieve a list of data-quality export records for a given deployment.

Added in version v3.6.

Parameters

Parameter	Type	Description
`deployment_id`	`str`	The ID of the deployment.
`start`	`Union[str`, `datetime]`	The earliest time of the objects to return.
`end`	`Union[str`, `datetime]`	The latest time of the objects to return.
`model_id`	`Optional[str]`	The ID of the model.
`prediction_pattern`	`Optional[str]`	The keywords to search in a predicted value for a text generation target.
`prompt_pattern`	`Optional[str]`	The keywords to search in a prompt value for a text generation target.
`actual_pattern`	`Optional[str]`	The keywords to search in an actual value for a text generation target.
`order_by`	`Optional[str]`	The field to sort by (e.g., associationId, timestamp, or customMetrics). Use a leading ‘-’ to indicate descending order. When ordering by a custom-metric, must also specify ‘order_metric’. The default is None, which equates to ‘-timestamp’.
`order_metric`	`Optional[str]`	When ‘order_by’ is a custom-metric, this specifies the custom-metric name or ID to use for ordering. The default is None.
`filter_metric`	`Optional[str]`	Specifies the metric name or ID to use for matching. Must also use ‘filter_value’ to specify the value that must be matched. The default is None.
`filter_value`	`Optional[str]`	Specifies the value associated with ‘filter_metric’ that must be matched. The default is None.
`offset`	`Optional[int]`	The starting offset of the results. The default is 0.
`limit`	`Optional[int]`	The maximum number of objects to return. The default is 100 (which is maximum).

Returns

Returns	Description
data_quality_exports	A list of DataQualityExport objects.

Return type: list

Examples

from datarobot.models.deployment import DataQualityExport

data_quality_exports = DataQualityExport.list(
    deployment_id='5c939e08962d741e34f609f0', start_time='2024-07-01', end_time='2024-08-01
)