data_client
===========

.. py:module:: data_client


Classes
-------

.. autoapisummary::

   data_client.DataClient


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

.. py:class:: DataClient(source_config: Optional[Dict[str, Dict[str, Any]]] = None)

   The main public interface (Facade) for fetching data and metadata.
   It selects, delegates, and caches the appropriate vendor adapter.


   .. py:attribute:: ADAPTER_MAPPING
      :type:  Dict[str, Type[cryptodatapy.extract.adapters.base_adapter.BaseAdapter]]


   .. py:attribute:: _source_config


   .. py:attribute:: _adapters
      :type:  Dict[str, cryptodatapy.extract.adapters.base_adapter.BaseAdapter]


   .. py:method:: _get_adapter(source_name: str) -> cryptodatapy.extract.adapters.base_adapter.BaseAdapter

      Retrieves an instantiated adapter from the cache, or instantiates and caches it if missing.
      This handles lazy loading and passing the correct, vendor-specific configuration.

      :param source_name: The name of the data source/vendor (e.g., 'defillama', 'coinmetrics', 'ccxt').
      :type source_name: str



   .. py:method:: get_data(request: cryptodatapy.core.data_request.DataRequest) -> pandas.DataFrame

      Routes the standardized DataRequest to the correct data source adapter and returns the result.

      :param request: The standardized data request object containing all necessary parameters.
      :type request: DataRequest

      :returns: A DataFrame containing the requested time series data.
      :rtype: pd.DataFrame



   .. py:method:: get_assets_info(source_name: str, as_list: bool = False, **kwargs) -> Union[pandas.DataFrame, list]

      Delegates the request for canonical asset metadata to the specified data source adapter.

      :param source_name: The data source to use for fetching asset info. Default is 'defillama'.
      :type source_name: str
      :param as_list: If True, returns a list of asset identifiers instead of a DataFrame.
      :type as_list: bool

      :returns: A DataFrame containing asset metadata.
      :rtype: pd.DataFrame



   .. py:method:: get_markets_info(source_name: str, as_list: bool = False, **kwargs) -> Union[pandas.DataFrame, list]

      Delegates the request for market metadata to the specified data source adapter.

      :param source_name: The data source to use for fetching market info. Default is 'defillama'.
      :type source_name: str
      :param as_list: If True, returns a list of market identifiers instead of a DataFrame.
      :type as_list: bool

      :returns: A DataFrame containing market metadata.
      :rtype: pd.DataFrame



   .. py:method:: get_fields_info(source_name: str, as_list: bool = False, **kwargs) -> Union[pandas.DataFrame, list]

      Delegates the request for field (metric) definitions to the specified data source adapter.

      :param source_name: The data source to use for fetching field info. Default is 'defillama'.
      :type source_name: str
      :param as_list: If True, returns a list of field/metric names instead of a DataFrame.
      :type as_list: bool

      :returns: A DataFrame containing field/metric definitions.
      :rtype: pd.DataFrame