agent0.chainsync.db.hyperdrive.event_getters
============================================

.. py:module:: agent0.chainsync.db.hyperdrive.event_getters

.. autoapi-nested-parse::

   Event getters specific to database.

   ..
       !! processed by numpydoc !!


Attributes
----------

.. autoapisummary::

   agent0.chainsync.db.hyperdrive.event_getters.EVENT_QUERY_PAGE_SIZE


Functions
---------

.. autoapisummary::

   agent0.chainsync.db.hyperdrive.event_getters.get_event_logs_for_db


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

.. py:data:: EVENT_QUERY_PAGE_SIZE
   :value: 80000


.. py:function:: get_event_logs_for_db(hyperdrive_interface: agent0.ethpy.hyperdrive.HyperdriveReadInterface, event_class: web3.contract.contract.ContractEvent, trade_base_unit_conversion: bool, from_block: web3.types.BlockIdentifier | None = None, argument_filters: dict[str, Any] | None = None, numeric_args_as_str: bool = True) -> list[dict[str, Any]]

   
   Get event logs based on the event_class, making necessary conversions for the database.

   :param hyperdrive_interface: The hyperdrive interface to use.
   :type hyperdrive_interface: HyperdriveReadInterface
   :param event_class: The event class to get logs for.
   :type event_class: type[ContractEvent]
   :param trade_base_unit_conversion: Whether to convert trade base units from steth "shares" to steth.
   :type trade_base_unit_conversion: bool
   :param from_block: The block to start getting events from. Defaults to "earliest", with some exceptions for specific chains.
   :type from_block: BlockIdentifier | None, optional
   :param argument_filters: A dictionary of filters to apply to the arguments of events. Defaults to None.
   :type argument_filters: dict[str, Any] | None, optional
   :param numeric_args_as_str: Whether to convert numeric event arguments to strings for keeping precision.
                               Defaults to True.
   :type numeric_args_as_str: bool, optional

   :returns: A list of emitted events.
   :rtype: list[dict[str, Any]]















   ..
       !! processed by numpydoc !!