modular_trader.indicator.handler
================================

.. py:module:: modular_trader.indicator.handler


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/modular_trader/indicator/handler/alpaca/index
   /autoapi/modular_trader/indicator/handler/base/index


Classes
-------

.. autoapisummary::

   modular_trader.indicator.handler.AlpacaIndicatorHandler
   modular_trader.indicator.handler.BaseIndicatorHandler


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

.. py:class:: AlpacaIndicatorHandler

   Bases: :py:obj:`modular_trader.indicator.handler.base.BaseIndicatorHandler`

   .. autoapi-inheritance-diagram:: modular_trader.indicator.handler.AlpacaIndicatorHandler
      :parts: 1
      :private-bases:


   Alpaca indicator handler.

   This class is used to handle indicators for Alpaca.

   Attributes:
       indicators (list[BaseIndicator]):
           The list of indicators to be used.
       frequency (Frequency):
           The frequency of the indicator handler.
       warmup_length (int | None):
           The length of the warmup period. If None, it is set to the maximum
           cache size of the indicators.
       _attached_indicators (benedict):
           The dictionary of attached indicators. The keys are the symbol names
           and the values are the indicator objects.


   .. py:method:: __iter__() -> Generator[modular_trader.indicator.technical.base.BaseIndicator, None, None]

      Iterate over the indicators.

      Yields:
          BaseIndicator: The next indicator.



   .. py:method:: __post_init__() -> None

      Find the minimum cache size of the indicators and use it to set the warmup
      length. If warmup_length is already set, it is not changed.



   .. py:method:: get(symbol: str, name: str | None = None) -> modular_trader.indicator.technical.base.BaseIndicator | Mapping[str, modular_trader.indicator.technical.base.BaseIndicator] | None

      Get the indicator(s) by symbol and name.

      Args:
          symbol (str): The symbol name.
          name (str | None): The indicator name. If None, it returns all
              indicators for the symbol.

      Returns:
          BaseIndicator | Mapping[str, BaseIndicator] | None: The indicator or
              all indicators for the symbol if name is None. If the symbol or
              indicator is not found, it returns None.



   .. py:method:: init_indicator(universe: modular_trader.universe.AssetUniverse) -> None

      Initialize the indicators for added symbols and remove them for removed
      symbols.

      Args:
          universe (AssetUniverse): The asset universe.

      Returns:
          None



   .. py:method:: update(bar: alpaca.data.models.bars.Bar) -> None

      Update the indicators for the given symbol.

      Args:
          bar (Bar): The bar to update the indicators with.

      Returns:
          None



   .. py:method:: warmup(data: pandas.DataFrame) -> None

      Warm up the indicators from historical data.

      Args:
          data (pd.DataFrame): The historical data to warm up the indicators.
              The DataFrame should have a MultiIndex [symbol, ...].

      Returns:
          None



   .. py:attribute:: _attached_indicators
      :type:  benedict.benedict
      :value: None



   .. py:attribute:: attached_indicators


   .. py:attribute:: frequency
      :type:  Frequency
      :value: None



   .. py:attribute:: indicators
      :type:  list[modular_trader.indicator.technical.base.BaseIndicator]
      :value: None



   .. py:property:: is_warmup
      :type: bool


      Check if the warmup period is finished.

      Returns:
          bool: True if the warmup period is finished, False otherwise.



   .. py:attribute:: symbols


   .. py:attribute:: warmup_length
      :type:  int | None
      :value: None



.. py:class:: BaseIndicatorHandler

   Bases: :py:obj:`abc.ABC`

   .. autoapi-inheritance-diagram:: modular_trader.indicator.handler.BaseIndicatorHandler
      :parts: 1
      :private-bases:


   Abstract base class for indicator handlers.


   .. py:method:: update()
      :abstractmethod:


      Update the indicators.

      This method is called for each new bar.



   .. py:method:: warmup()
      :abstractmethod:


      Warmup the indicators.

      This method is called once when the indicator handler is created.