cryptodatapy.extract.exchanges.dydx
===================================

.. py:module:: cryptodatapy.extract.exchanges.dydx


Classes
-------

.. autoapisummary::

   cryptodatapy.extract.exchanges.dydx.Dydx


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

.. py:class:: Dydx(name: str = 'dydx', exch_type: str = 'dex', is_active: bool = True, categories: Union[str, List[str]] = 'crypto', assets: Optional[Dict[str, List[str]]] = None, markets: Optional[Dict[str, List[str]]] = None, market_types: List[str] = ['perpetual_future'], fields: Optional[List[str]] = ['open', 'high', 'low', 'close', 'volume', 'funding_rate'], frequencies: Optional[Dict[str, Union[str, int]]] = {'1m': '1MIN', '5m': '5MINS', '15m': '15MINS', '1h': '1HOUR', '4h': '4HOURS', '1d': '1DAY'}, fees: Optional[Dict[str, float]] = {'perpetual_future': {'maker': 0.0, 'taker': 0.0}}, base_url: Optional[str] = 'https://indexer.dydx.trade/v4', api_key: Optional[str] = None, max_obs_per_call: Optional[int] = 1000, rate_limit: Optional[Any] = None)

   Bases: :py:obj:`cryptodatapy.extract.exchanges.exchange.Exchange`


   Retrieves data from dydx exchange.


   .. py:attribute:: data_req
      :value: None



   .. py:attribute:: data


   .. py:method:: get_assets_info() -> pandas.DataFrame

      Gets info for available assets from dYdX.

      :returns: DataFrame with asset information.
      :rtype: pd.DataFrame



   .. py:method:: get_markets_info(quote_ccy: Optional[str] = None, mkt_type: Optional[str] = None, as_list: bool = False) -> Union[pandas.DataFrame, List[str]]

      Gets info for available markets from dYdX.

      :param quote_ccy: Quote currency to filter by (e.g., 'USD', 'USDC'). For dYdX, this is typically 'USD'.
      :type quote_ccy: str, optional
      :param mkt_type: Market type to filter by. For dYdX, this is typically 'perpetual_future'.
      :type mkt_type: str, optional
      :param as_list: If True, returns a list of ticker symbols instead of a DataFrame.
      :type as_list: bool, default False

      :returns: DataFrame with market information or list of ticker symbols.
      :rtype: pd.DataFrame or List[str]



   .. py:method:: get_fields_info(data_type: Optional[str] = None) -> pandas.DataFrame

      Gets info for available fields from dYdX.

      :param data_type: Type of data for which to return field information.
      :type data_type: str, optional

      :returns: DataFrame with field information.
      :rtype: pd.DataFrame



   .. py:method:: get_frequencies_info() -> pandas.DataFrame

      Gets info for available frequencies from dYdX.

      :returns: DataFrame with frequency information.
      :rtype: pd.DataFrame



   .. py:method:: get_rate_limit_info() -> Dict[str, Any]

      Gets rate limit information from dYdX.

      :returns: Dictionary with rate limit information.
      :rtype: Dict[str, Any]



   .. py:method:: get_metadata() -> Dict[str, Any]

      Gets metadata about the exchange.

      :returns: Dictionary with exchange metadata.
      :rtype: Dict[str, Any]



   .. py:method:: _fetch_ohlcv() -> pandas.DataFrame

      Fetches OHLCV data from dYdX for multiple markets with pagination support.

      The dYdX candles API has a limit (typically 1000 records) and returns data in
      reverse chronological order (newest first). For large date ranges, we need to
      implement pagination to retrieve all historical data.

      :returns: DataFrame with OHLCV data for all requested markets.
      :rtype: pd.DataFrame



   .. py:method:: _fetch_funding_rates() -> pandas.DataFrame

      Fetches funding rate data from dYdX for multiple markets with pagination support.

      Note: dYdX charges funding every hour, unlike other exchanges that typically
      use 8-hour funding cycles. This method retrieves the complete historical
      funding rate data for any requested date range, making multiple API calls as needed.

      :returns: DataFrame with hourly funding rate data for all requested markets.
      :rtype: pd.DataFrame



   .. py:method:: _fetch_open_interest() -> pandas.DataFrame

      Fetches current open interest from dYdX.
      Note: This implementation only provides current open interest values, not historical data.
      Historical open interest data is not available through the dYdX API.

      :returns: DataFrame with current open interest values.
                The DataFrame has a MultiIndex with 'date' and 'ticker' levels.
                The 'date' index will be the current timestamp for all entries.
      :rtype: pd.DataFrame



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

      Converts parameters for the data request using ConvertParams class.



   .. py:method:: _wrangle_data_resp(data_req: cryptodatapy.extract.datarequest.DataRequest, data_resp: Union[Dict[str, Any], pandas.DataFrame]) -> pandas.DataFrame
      :staticmethod:


      Wrangles data response from dYdX using WrangleData class.

      :param data_req: Parameters of data request.
      :type data_req: DataRequest
      :param data_resp: Data response from dYdX.
      :type data_resp: Union[Dict[str, Any], pd.DataFrame]

      :returns: Wrangled DataFrame.
      :rtype: pd.DataFrame



   .. py:method:: _fetch_tidy_ohlcv() -> pandas.DataFrame

      Fetches and tidies OHLCV data.

      :returns: Tidy DataFrame with OHLCV data.
      :rtype: pd.DataFrame



   .. py:method:: _fetch_tidy_funding_rates() -> pandas.DataFrame

      Fetches and tidies funding rates.

      :returns: Tidy DataFrame with funding rates.
      :rtype: pd.DataFrame



   .. py:method:: _fetch_tidy_open_interest() -> pandas.DataFrame

      Fetches and tidies open interest.

      :returns: Tidy DataFrame with open interest.
      :rtype: pd.DataFrame



   .. py:method:: get_data(data_req: cryptodatapy.extract.datarequest.DataRequest) -> pandas.DataFrame

      Gets market data from dYdX.

      :param data_req: Parameters of data request.
      :type data_req: DataRequest

      :returns: DataFrame with market data.
      :rtype: pd.DataFrame