pdstools.infinity.resources.prediction_studio.v24_2¶

Submodules¶

Classes¶

`AsyncChampionChallenger`	The `ChampionChallenger` class manages champion and challenger models
`ChampionChallenger`	The `ChampionChallenger` class manages champion and challenger models
`AsyncDatamartExport`	v24.2 DatamartExport business logic — defined once.
`DatamartExport`	v24.2 DatamartExport business logic — defined once.
`AsyncModel`	v24.2 Model business logic — defined once.
`Model`	v24.2 Model business logic — defined once.
`AsyncPrediction`	Async variant of the v24.2 Prediction.
`Prediction`	The `Prediction` class provide functionality including retrieving
`AsyncPredictionStudio`	v24.2 PredictionStudio business logic — shared parts.
`PredictionStudio`	v24.2 PredictionStudio business logic — shared parts.
`AsyncRepository`	v24.2 Repository data — defined once.
`Repository`	v24.2 Repository data — defined once.

Package Contents¶

class AsyncChampionChallenger(client, prediction_id: str, active_model, cc_id: str | None = None, context: str | None = None, category: str | None = None, challenger_model=None, champion_percentage: float | None = None, model_objective: str | None = None)¶

Bases: _ChampionChallengerV24_2Mixin, pdstools.infinity.resources.prediction_studio.base.AsyncChampionChallenger

The ChampionChallenger class manages champion and challenger models within a prediction context. It provides functionalities for:

Refreshing champion challenger data
Deleting challenger models
Promoting challenger models
Updating challenger response percentages
Adding new models
Cloning an ADM active model
Adding/removing predictors

Parameters:

prediction_id (str)
cc_id (str | None)
context (str | None)
category (str | None)
champion_percentage (float | None)
model_objective (str | None)

client¶

The client used to interact with the API.

Type:: Client

prediction_id¶

The ID of the prediction.

Type:: str

active_model¶

The active model in the prediction.

Type:: Model

cc_id¶

The ID of the champion challenger.

Type:: str | None

context¶

The context of the prediction.

Type:: str | None

category¶

The category of the prediction.

Type:: str | None

challenger_model¶

The challenger model.

Type:: Model | None

champion_percentage¶

The percentage of responses attributed to the champion model.

Type:: float | None

model_objective¶

The objective of the model.

Type:: str | None

async list_available_models_to_add(return_df: bool = False) → pdstools.infinity.internal._pagination.AsyncPaginatedList | polars.DataFrame¶

Fetches a list of models eligible to be challengers.

Parameters:: return_df (bool, optional) – Determines the format of the returned data: a DataFrame if True, otherwise an async list of model instances. Defaults to False.
Returns:: An async list of model instances or a DataFrame of models.
Return type:: AsyncPaginatedList[AsyncModel] or pl.DataFrame

class ChampionChallenger(client, prediction_id: str, active_model, cc_id: str | None = None, context: str | None = None, category: str | None = None, challenger_model=None, champion_percentage: float | None = None, model_objective: str | None = None)¶

Bases: _ChampionChallengerV24_2Mixin, pdstools.infinity.resources.prediction_studio.base.ChampionChallenger

The ChampionChallenger class manages champion and challenger models within a prediction context. It provides functionalities for:

Refreshing champion challenger data
Deleting challenger models
Promoting challenger models
Updating challenger response percentages
Adding new models
Cloning an ADM active model
Adding/removing predictors

Parameters:

prediction_id (str)
cc_id (str | None)
context (str | None)
category (str | None)
champion_percentage (float | None)
model_objective (str | None)

client¶

The client used to interact with the API.

Type:: Client

prediction_id¶

The ID of the prediction.

Type:: str

active_model¶

The active model in the prediction.

Type:: Model

cc_id¶

The ID of the champion challenger.

Type:: str | None

context¶

The context of the prediction.

Type:: str | None

category¶

The category of the prediction.

Type:: str | None

challenger_model¶

The challenger model.

Type:: Model | None

champion_percentage¶

The percentage of responses attributed to the champion model.

Type:: float | None

model_objective¶

The objective of the model.

Type:: str | None

list_available_models_to_add(return_df: bool = False) → pdstools.infinity.internal._pagination.PaginatedList | polars.DataFrame¶

Fetches a list of models eligible to be challengers.

Queries for models that can be added as challengers to the current prediction for the current active model. Offers the option to return the results in a DataFrame format for easier data handling.

Parameters:: return_df (bool, optional) – Determines the format of the returned data: a DataFrame if True, otherwise a list of model instances. Defaults to False.
Returns:: A list of model instances or a DataFrame of models, based on the return_df parameter choice.
Return type:: PaginatedList[Model] or pl.DataFrame

class AsyncDatamartExport(client, referenceId: str, location: str, repositoryName: str)¶

Bases: _DatamartExportV24_2Mixin, pdstools.infinity.resources.prediction_studio.base.AsyncDataMartExport

v24.2 DatamartExport business logic — defined once.

Parameters:

referenceId (str)
location (str)
repositoryName (str)

class DatamartExport(client, referenceId: str, location: str, repositoryName: str)¶

Bases: _DatamartExportV24_2Mixin, pdstools.infinity.resources.prediction_studio.base.DataMartExport

v24.2 DatamartExport business logic — defined once.

Parameters:

referenceId (str)
location (str)
repositoryName (str)

class AsyncModel(client, *, modelId: str, label: str, modelType: str, status: str, componentName: str | None = None, source: str | None = None, lastUpdateTime: str | None = None, modelingTechnique: str | None = None, updatedBy: str | None = None)¶

Bases: _ModelV24_2Mixin, pdstools.infinity.resources.prediction_studio.base.AsyncModel

v24.2 Model business logic — defined once.

Parameters:

modelId (str)
label (str)
modelType (str)
status (str)
componentName (str | None)
source (str | None)
lastUpdateTime (str | None)
modelingTechnique (str | None)
updatedBy (str | None)

async get_notifications(category: pdstools.infinity.resources.prediction_studio.types.NotificationCategory | None = None, return_df: bool = False) → pdstools.infinity.internal._pagination.AsyncPaginatedList[pdstools.infinity.resources.prediction_studio.base.AsyncNotification] | polars.DataFrame¶

Fetches a list of notifications for a specific model.

Parameters:

category ({"All", "Responses", "Performance", "Model approval", "Output", "Predictors", "Prediction deployment", "Generic"} or None, optional) – The category of notifications to retrieve. If not specified, all notifications are fetched.
return_df (bool, default False) – If True, returns the notifications as a DataFrame. Otherwise, returns a list.

Returns:

A list of notifications or a DataFrame containing the notifications.

Return type:

AsyncPaginatedList[AsyncNotification] or polars.DataFrame

class Model(client, *, modelId: str, label: str, modelType: str, status: str, componentName: str | None = None, source: str | None = None, lastUpdateTime: str | None = None, modelingTechnique: str | None = None, updatedBy: str | None = None)¶

Bases: _ModelV24_2Mixin, pdstools.infinity.resources.prediction_studio.base.Model

v24.2 Model business logic — defined once.

Parameters:

modelId (str)
label (str)
modelType (str)
status (str)
componentName (str | None)
source (str | None)
lastUpdateTime (str | None)
modelingTechnique (str | None)
updatedBy (str | None)

get_notifications(category: pdstools.infinity.resources.prediction_studio.types.NotificationCategory | None = None, return_df: Literal[False] = False) → pdstools.infinity.internal._pagination.PaginatedList[pdstools.infinity.resources.prediction_studio.base.Notification]¶

get_notifications(category: pdstools.infinity.resources.prediction_studio.types.NotificationCategory | None = None, return_df: Literal[True] = True) → polars.DataFrame

Fetches a list of notifications for a specific model.

This function retrieves notifications related to a model. You can filter these notifications by their category. Optionally, the notifications can be returned as a DataFrame for easier analysis and visualization.

Parameters:

category ({"All", "Responses", "Performance", "Model approval", "Output", "Predictors", "Prediction deployment", "Generic"} or None, optional) – The category of notifications to retrieve. If not specified, all notifications are fetched.
return_df (bool, default False) – If True, returns the notifications as a DataFrame. Otherwise, returns a list.

Returns:

A list of notifications or a DataFrame containing the notifications, depending on the value of return_df.

Return type:

PaginatedList[Notification] or polars.DataFrame

class AsyncPrediction(client, *, predictionId: str, label: str, status: str, lastUpdateTime: str, objective: str | None = None, subject: str | None = None)¶

Bases: _PredictionV24_2Mixin, pdstools.infinity.resources.prediction_studio.v24_1.prediction.AsyncPrediction

Async variant of the v24.2 Prediction.

Parameters:

predictionId (str)
label (str)
status (str)
lastUpdateTime (str)
objective (str | None)
subject (str | None)

Fetches a list of notifications for a specific prediction.

Parameters:

category ({"All", "Responses", "Performance", "Model approval", "Output", "Predictors", "Prediction deployment", "Generic"} or None) – The category of notifications to retrieve.
return_df (bool, default False) – If True, returns the notifications as a DataFrame.

Returns:

A list of notifications or a DataFrame.

Return type:

AsyncPaginatedList[AsyncNotification] or polars.DataFrame

async get_champion_challengers()¶

Fetches list of ChampionChallenger objects linked to the prediction.

Returns:: Champion-challenger pairs from a prediction.
Return type:: list of AsyncChampionChallenger

async add_conditional_model(new_model, category: str, context: str | None = None)¶

Incorporates a new model into a prediction for a specified category and context.

Parameters:

new_model (str or AsyncModel) – Identifier of the model to be added.
category (str) – The category under which the model will be classified.
context (str, optional) – The specific context or scenario.

Returns:

An object detailing the updated configuration.

Return type:

AsyncChampionChallenger

class Prediction(client, *, predictionId: str, label: str, status: str, lastUpdateTime: str, objective: str | None = None, subject: str | None = None)¶

Bases: _PredictionV24_2Mixin, pdstools.infinity.resources.prediction_studio.v24_1.prediction.Prediction

The Prediction class provide functionality including retrieving notifications, models, adding conditional models, getting champion challengers, metrics, and plotting metrics.

Parameters:

predictionId (str)
label (str)
status (str)
lastUpdateTime (str)
objective (str | None)
subject (str | None)

get_notifications(category: pdstools.infinity.resources.prediction_studio.types.NotificationCategory | None = None, return_df: Literal[True] = True) → polars.DataFrame

Fetches a list of notifications for a specific prediction.

This function retrieves notifications related to a prediction. You can filter these notifications by their category. Optionally, the notifications can be returned as a DataFrame for easier analysis and visualization.

Parameters:

category ({"All", "Responses", "Performance", "Model approval", "Output", "Predictors", "Prediction deployment", "Generic"} or None) – The category of notifications to retrieve. If not specified, all notifications are fetched.
return_df (bool, default False) – If True, returns the notifications as a DataFrame. Otherwise, returns a list.

Returns:

A list of notifications or a DataFrame containing the notifications, depending on the value of return_df.

Return type:

PaginatedList[Notification] or polars.DataFrame

get_champion_challengers()¶

Fetches list of ChampionChallenger objects linked to the prediction.

This function fetches Champion-challenger pairs from a prediction. In cases where a challenger model is absent, it returns a ChampionChallenger object containing only the champion model.

Returns:: A list of entries, each pairing a primary model with its challenger across various segments of the prediction.
Return type:: list of ChampionChallenger

add_conditional_model(new_model, category: str, context: str | None = None)¶

Incorporates a new model into a prediction for a specified category and context.

Parameters:

new_model (str or Model) – Identifier of the model to be added.
category (str) – The category under which the model will be classified.
context (str, optional) – The specific context or scenario in which the model will be utilized.

Returns:

An object detailing the updated configuration with the newly added model.

Return type:

ChampionChallenger

class AsyncPredictionStudio(client: pdstools.infinity.internal._base_client.AsyncAPIClient)¶

Bases: _PredictionStudioV24_2Mixin, pdstools.infinity.resources.prediction_studio.v24_1.AsyncPredictionStudio

v24.2 PredictionStudio business logic — shared parts.

Parameters:: client (pdstools.infinity.internal._base_client.AsyncAPIClient)

version: str = '24.2'¶

async repository() → pdstools.infinity.resources.prediction_studio.v24_2.repository.AsyncRepository¶

Gets information about the repository from Prediction Studio.

Returns:: A simple object with the repository’s details.
Return type:: AsyncRepository

async list_models(return_df: bool = False) → pdstools.infinity.internal._pagination.AsyncPaginatedList[pdstools.infinity.resources.prediction_studio.v24_2.model.AsyncModel] | polars.DataFrame¶

Fetches a list of all models from Prediction Studio.

Parameters:: return_df (bool, optional) – Set to True to get the results as a DataFrame.
Return type:: AsyncPaginatedList[AsyncModel] or polars.DataFrame

async list_predictions(return_df: bool = False) → pdstools.infinity.internal._pagination.AsyncPaginatedList[pdstools.infinity.resources.prediction_studio.v24_2.prediction.AsyncPrediction] | polars.DataFrame¶

Fetches a list of all predictions from Prediction Studio.

Parameters:: return_df (bool, optional) – Set to True to get the results as a DataFrame.
Return type:: AsyncPaginatedList[AsyncPrediction] or polars.DataFrame

async get_prediction(prediction_id: str | None = None, label: str | None = None, **kwargs) → pdstools.infinity.resources.prediction_studio.v24_2.prediction.AsyncPrediction¶

Finds and returns a specific prediction from Prediction Studio.

Parameters:

prediction_id (str, optional) – The unique ID of the prediction.
label (str, optional) – The label of the prediction.

Return type:

AsyncPrediction

async get_model(model_id: str | None = None, label: str | None = None, **kwargs) → pdstools.infinity.resources.prediction_studio.v24_2.model.AsyncModel¶

Finds and returns a specific model from Prediction Studio.

Parameters:

model_id (str, optional) – The unique ID of the model.
label (str, optional) – The label of the model.

Return type:

AsyncModel

async trigger_datamart_export() → pdstools.infinity.resources.prediction_studio.v24_2.datamart_export.AsyncDatamartExport¶

Initiates an export of model data to the Repository.

Returns:: An object with information about the data export process.
Return type:: AsyncDatamartExport

Fetches a list of notifications from Prediction Studio.

Parameters:

category ({"All", "Responses", "Performance", "Model approval", "Output", "Predictors", "Prediction deployment", "Generic"} or None, optional) – The category of notifications to retrieve.
return_df (bool, default False) – If True, returns as a DataFrame.

Return type:

AsyncPaginatedList[AsyncNotification] or polars.DataFrame

class PredictionStudio(client: pdstools.infinity.internal._base_client.SyncAPIClient)¶

Bases: _PredictionStudioV24_2Mixin, pdstools.infinity.resources.prediction_studio.v24_1.PredictionStudio

v24.2 PredictionStudio business logic — shared parts.

Parameters:: client (pdstools.infinity.internal._base_client.SyncAPIClient)

version: str = '24.2'¶

repository() → pdstools.infinity.resources.prediction_studio.v24_2.repository.Repository¶

Gets information about the repository from Prediction Studio.

Returns:: A simple object with the repository’s details, ready to use.
Return type:: Repository

list_models(return_df: Literal[False] = False) → pdstools.infinity.internal._pagination.PaginatedList[pdstools.infinity.resources.prediction_studio.v24_2.model.Model]¶

list_models(return_df: Literal[True]) → polars.DataFrame

Fetches a list of all models from Prediction Studio.

Parameters:: return_df (bool, optional) – Set to True to get the results as a DataFrame. By default False.
Returns:: Returns a list of models or a DataFrame with model information.
Return type:: PaginatedList[Model] or polars.DataFrame

list_predictions(return_df: Literal[False] = False) → pdstools.infinity.internal._pagination.PaginatedList[pdstools.infinity.resources.prediction_studio.v24_2.prediction.Prediction]¶

list_predictions(return_df: Literal[True]) → polars.DataFrame

Fetches a list of all predictions from Prediction Studio.

Parameters:: return_df (bool, optional) – Set to True to get the results as a DataFrame. By default False.
Returns:: Returns a list of predictions or a DataFrame.
Return type:: PaginatedList[Prediction] or polars.DataFrame

get_prediction(prediction_id: str | None = None, label: str | None = None, **kwargs) → pdstools.infinity.resources.prediction_studio.v24_2.prediction.Prediction¶

Finds and returns a specific prediction from Prediction Studio.

Parameters:

prediction_id (str, optional) – The unique ID of the prediction.
label (str, optional) – The label of the prediction.
**kwargs (dict, optional) – Other details to narrow down the search.

Returns:

The prediction that matches your search criteria.

Return type:

Prediction

Raises:

ValueError – If you don’t provide an ID or label.

get_model(model_id: str | None = None, label: str | None = None, **kwargs) → pdstools.infinity.resources.prediction_studio.v24_2.model.Model¶

Finds and returns a specific model from Prediction Studio.

Parameters:

model_id (str, optional) – The unique ID of the model.
label (str, optional) – The label of the model.
**kwargs (dict, optional) – Other details to help find the model.

Returns:

The model that matches your search.

Return type:

Model

Raises:

ValueError – If you don’t provide an ID or label.

trigger_datamart_export() → pdstools.infinity.resources.prediction_studio.v24_2.datamart_export.DatamartExport¶

Initiates an export of model data to the Repository.

Returns:: An object with information about the data export process.
Return type:: DatamartExport

get_notifications(category: pdstools.infinity.resources.prediction_studio.types.NotificationCategory | None = None, return_df: Literal[True] = True) → polars.DataFrame

Fetches a list of notifications from Prediction Studio.

Parameters:

category ({"All", "Responses", "Performance", "Model approval", "Output", "Predictors", "Prediction deployment", "Generic"} or None, optional) – The category of notifications to retrieve.
return_df (bool, default False) – If True, returns the notifications as a DataFrame.

Returns:

A list of notifications or a DataFrame.

Return type:

PaginatedList[Notification] or polars.DataFrame

class AsyncRepository(client, type, repository_name, bucket_name, root_path, datamart_export_location)¶

Bases: _RepositoryV24_2Mixin, pdstools.infinity.resources.prediction_studio.v24_1.repository.AsyncRepository

v24.2 Repository data — defined once.

class Repository(client, type, repository_name, bucket_name, root_path, datamart_export_location)¶

Bases: _RepositoryV24_2Mixin, pdstools.infinity.resources.prediction_studio.v24_1.Repository

v24.2 Repository data — defined once.