lories.components.weather.forecast
==================================

.. py:module:: lories.components.weather.forecast

.. autoapi-nested-parse::

   lories.components.weather.forecast
   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~




Classes
-------

.. autoapisummary::

   lories.components.weather.forecast.WeatherForecast


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

.. py:class:: WeatherForecast(context: lories._core._registrator.RegistratorContext, configs: Optional[lories._core._configurations.Configurations] = None, **kwargs)

   Bases: :py:obj:`lories.components.weather.Weather`

   .. autoapi-inheritance-diagram:: lories.components.weather.forecast.WeatherForecast
      :parts: 1
      :private-bases:


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


   .. py:method:: get(start: Optional[pandas.Timestamp, datetime.datetime, str] = None, end: Optional[pandas.Timestamp, datetime.datetime, str] = None, timezone: Optional[pytz.BaseTzInfo | str | int | float] = None, **kwargs) -> pandas.DataFrame

      Retrieves the forecasted data for a specified time interval

      :param start:
          the start timestamp for which forecasted data will be looked up for.
          For many applications, passing datetime.datetime.now() will suffice.
      :type start:
          :class:`pandas.Timestamp`, datetime or str

      :param end:
          the end timestamp for which forecasted data will be looked up for.
      :type end:
          :class:`pandas.Timestamp`, datetime or str

      :param timezone:
          the timezone for the timestamps data will be looked up for.
      :type timezone:
          :class:`pytz.BaseTzInfo`, str or number

      :returns:
          the forecasted data, indexed in a specific time interval.

      :rtype:
          :class:`pandas.DataFrame`