data_loader
===========

.. py:module:: data_loader


Classes
-------

.. autoapisummary::

   data_loader.DataSource
   data_loader.AlpacaDataLoader
   data_loader.DataLoader


Module Contents
---------------

.. py:class:: DataSource(**kwargs)

   Base class for all data sources in the Rambling Realms trading system.
   This class provides a common interface for fetching and processing data from various sources.
   Subclasses should implement the `get_data` method to fetch data from their respective sources.


   .. py:attribute:: _registry
      :type:  ClassVar[Dict[trading.cli.alg.config.DataSourceType, Type[DataSource]]]


   .. py:method:: get_data(fetch_data, request, df, cache_path, start_date, end_date, time_step_unit = TimeFrameUnit('Day'), cache_enabled = True, time_step_period = 1, **kwargs)
      :abstractmethod:



   .. py:method:: __init_subclass__(**kwargs)
      :classmethod:



   .. py:method:: factory(data)
      :classmethod:


      Factory method to create an instance of a DataSource subclass based on the provided data.
      The data dictionary must contain a 'source' key that matches one of the DataSourceType enum values.
      Raises ValueError if the 'source' key is missing or if the type is unknown.



.. py:class:: AlpacaDataLoader(**kwargs)

   Bases: :py:obj:`DataSource`


   ! TODO add columns to and from parquet



   .. py:attribute:: TYPE
      :type:  ClassVar[trading.cli.alg.config.DataSourceType]


   .. py:method:: get_data(fetch_data, request, df, cache_path, start_date, end_date, time_step_unit = TimeFrameUnit.Day, cache_enabled = True, time_step_period = 1, **kwargs)

      Fetches data from Alpaca and caches it locally.



.. py:class:: DataLoader(data_config, feature_config, fetch_data = False, **kwargs)

   DataLoader class for loading and processing data from various sources.
   It initializes with a DataConfig and FeatureConfig, fetches data from the specified sources,
   and applies the specified features to the data.

   ! todo no drop on on live


   .. py:attribute:: data_config


   .. py:attribute:: feature_config


   .. py:attribute:: df


   .. py:attribute:: columns


   .. py:attribute:: features


   .. py:method:: data_info(df)
      :classmethod:


      Returns a string representation of the dataframe.



   .. py:method:: get_train_test()

      Splits the DataFrame into training and validation sets based on the validation split ratio.



   .. py:method:: to_csv(path)

      Saves the DataFrame to a CSV file.