pdstools.infinity.resources.prediction_studio.v24_2
===================================================

.. py:module:: pdstools.infinity.resources.prediction_studio.v24_2


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/pdstools/infinity/resources/prediction_studio/v24_2/champion_challenger/index
   /autoapi/pdstools/infinity/resources/prediction_studio/v24_2/datamart_export/index
   /autoapi/pdstools/infinity/resources/prediction_studio/v24_2/model/index
   /autoapi/pdstools/infinity/resources/prediction_studio/v24_2/model_upload/index
   /autoapi/pdstools/infinity/resources/prediction_studio/v24_2/prediction/index
   /autoapi/pdstools/infinity/resources/prediction_studio/v24_2/prediction_studio/index
   /autoapi/pdstools/infinity/resources/prediction_studio/v24_2/repository/index


Classes
-------

.. autoapisummary::

   pdstools.infinity.resources.prediction_studio.v24_2.AsyncPredictionStudio
   pdstools.infinity.resources.prediction_studio.v24_2.PredictionStudio
   pdstools.infinity.resources.prediction_studio.v24_2.Repository


Package Contents
----------------

.. py:class:: AsyncPredictionStudio(client: pdstools.infinity.client.AsyncAPIClient)

   Bases: :py:obj:`pdstools.infinity.resources.prediction_studio.v24_1.AsyncPredictionStudio`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:attribute:: version
      :type:  str
      :value: '24.2'



.. py:class:: PredictionStudio(client: pdstools.infinity.client.SyncAPIClient)

   Bases: :py:obj:`pdstools.infinity.resources.prediction_studio.v24_1.PredictionStudio`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:attribute:: version
      :type:  str
      :value: '24.2'



   .. py:method:: 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.
      :rtype: Repository



   .. py:method:: 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.

      This function gets information about all the models stored in Prediction Studio.

      :param return_df: Set to True to get the results as a DataFrame. By default, it's False, and you get a PaginatedList.
      :type return_df: bool, optional

      :returns: Returns a list of models or a DataFrame with model information, based on the `return_df` parameter.
      :rtype: PaginatedList[Model] or polars.DataFrame



   .. py:method:: 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.

      This function gets information about all the predictions stored in Prediction Studio.

      :param return_df: Set to True to get the results as a DataFrame. By default, it's False, and you get a list.
      :type return_df: bool, optional

      :returns: Returns a list of models or a DataFrame with model information, based on the `as_df` parameter.
      :rtype: PaginatedList[Model] or polar.DataFrame



   .. py:method:: get_prediction(prediction_id: Optional[str] = None, label: Optional[str] = None, **kwargs) -> pdstools.infinity.resources.prediction_studio.v24_2.prediction.Prediction

      Finds and returns a specific prediction from Prediction Studio.

      This function looks for a prediction using its ID or label. You can also use other details to narrow down the search.
      It's useful when you need to get information about one particular prediction.

      :param id: The unique ID of the prediction you're looking for. By default, it's None.
      :type id: str, optional
      :param label: The label of the prediction you're interested in. Also None by default.
      :type label: str, optional
      :param \*\*kwargs: Other details you can specify to help find the prediction.
      :type \*\*kwargs: dict, optional

      :returns: The prediction that matches your search criteria.
      :rtype: Prediction

      :raises ValueError: If you don't provide an ID or label, it will tell you that you need at least one of them.



   .. py:method:: get_model(model_id: Optional[str] = None, label: Optional[str] = None, **kwargs) -> pdstools.infinity.resources.prediction_studio.v24_2.model.Model

      Finds and returns a specific model from Prediction Studio.

      This function searches for a model using its ID or label. You can also use other details to help find exactly what you're looking for.
      It's handy when you need details about a particular model.

      :param id: The unique ID of the model you want to find.
      :type id: str, optional
      :param label: The label of the model you're interested in.
      :type label: str, optional
      :param \*\*kwargs: Other details you can specify to help find the model.
      :type \*\*kwargs: dict, optional

      :returns: The model that matches your search.
      :rtype: Model

      :raises ValueError: If you don't provide an ID or label, it will tell you that you need at least one of them.



   .. py:method:: trigger_datamart_export() -> pdstools.infinity.resources.prediction_studio.v24_2.datamart_export.DatamartExport

      Initiates an export of model data to the Repository.

      This function begins the process of moving model data from Prediction Studio to the Repository.

      :returns: An object with information about the data export process.
      :rtype: DataMartExport



   .. py:method:: upload_model(model: pdstools.infinity.resources.prediction_studio.base.LocalModel, file_name: str) -> pdstools.infinity.resources.prediction_studio.v24_2.model_upload.UploadedModel

      Uploads a model to the repository.

      This function handles the uploading of a model to the Repository, creating an UploadedModel object for further MLops processes.

      :param model: The model to be uploaded. This can be specified either as a file path (str) to the model file or as an ONNX model object.
      :type model: str or ONNX model object
      :param file_name: The name of the file (including extension) to be uploaded to the repository.
      :type file_name: str

      :returns: Details about the uploaded model, including API response data.
      :rtype: UploadedModel

      :raises ValueError: Raised if an attempt is made to upload an ONNX model without the required conversion library.
      :raises ModelValidationError: If the model validation fails.



   .. py:method:: get_model_categories()

      Gets a list of model categories from Prediction Studio.

      This function gives you back a list where each item tells you about one type of model.
      Which can be useful for adding a condional model to a prediction.

      :returns: Each dictionary in the list has details about a model category, like its name and other useful information.
      :rtype: list of dict



   .. py:method:: get_notifications(category: Optional[pdstools.infinity.resources.prediction_studio.types.NotificationCategory] = None, return_df: Literal[False] = False) -> pdstools.infinity.internal._pagination.PaginatedList[pdstools.infinity.resources.prediction_studio.base.Notification]
                  get_notifications(category: Optional[pdstools.infinity.resources.prediction_studio.types.NotificationCategory] = None, return_df: Literal[True] = True) -> polars.DataFrame

      Fetches a list of notifications from Prediction Studio.

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

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

      :returns: A list of notifications or a DataFrame containing the notifications, depending on the value of `return_df`.
      :rtype: PaginatedList[Notification] or polars.DataFrame



.. py:class:: Repository(client, type, repository_name, bucket_name, root_path, datamart_export_location)

   Bases: :py:obj:`pdstools.infinity.resources.prediction_studio.v24_1.Repository`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:attribute:: type


   .. py:attribute:: bucket_name


   .. py:attribute:: root_path


   .. py:attribute:: datamart_export_location


   .. py:property:: s3_url