agent0.chainsync.dashboard.usernames
====================================

.. py:module:: agent0.chainsync.dashboard.usernames

.. autoapi-nested-parse::

   Helper functions for mapping addresses to usernames.

   ..
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Functions
---------

.. autoapisummary::

   agent0.chainsync.dashboard.usernames.build_user_mapping
   agent0.chainsync.dashboard.usernames.map_addresses
   agent0.chainsync.dashboard.usernames.abbreviate_address


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

.. py:function:: build_user_mapping(addresses: pandas.Series, addr_to_username: pandas.DataFrame) -> pandas.DataFrame

   
   Builds a mapping from wallet addresses to usernames and any additional aliases
   that address may have.

   Given a pd.Series of wallet addresses, we build a corresponding dataframe that contains
   the mapping between that wallet address and any additional aliases that address may have.
   Specifically, the output dataframe contains the following columns:
       address: The original wallet address
       abbr_address: The wallet address abbreviated (e.g., 0x0000...0000)
       username: The one-to-one mapped username for that address gathered from the `addr_to_username` postgres table
       format_name: A formatted name for labels combining username with abbr_address

   If the address doesn't exist in the lookup, the username and user will reflect the abbr_address.

   :param addresses: The list of addresses to build the user map for.
   :type addresses: pd.Series
   :param addr_to_username: The mapping of addresses to username returned from `get_addr_to_username`.
   :type addr_to_username: pd.DataFrame

   :returns: A dataframe with 4 columns (address, abbr_address, username, format_name)
   :rtype: pd.Dataframe















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.. py:function:: map_addresses(key: str, user_map: pandas.DataFrame, map_column=None) -> pandas.Series
                 map_addresses(key: pandas.Series | list, user_map: pandas.DataFrame, map_column=None) -> pandas.Series

   
   Helper function to look up the aliases for an address.

   :param key: The pd.Series, list, or individual key(s) to look up.
   :type key: pd.Series | list | str
   :param user_map: The lookup dataframe returned from build_user_mapping
   :type user_map: pd.DataFrame
   :param map_column: The column that key is mapped to. If None, will default to address.
   :type map_column: str | None

   :returns: A dataframe or series with 5 columns (address, abbr_address, username, user, format_name) in the same order as
             the input addresses series.
             Will return a dataframe if a series or list is passed in
             Will return a series if a single key is passed in
   :rtype: pd.Dataframe | pd.Series















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.. py:function:: abbreviate_address(address: pandas.Series) -> pandas.Series
                 abbreviate_address(address: str) -> str

   
   Given a series of addresses, return the corresponding addresses in a human readable way.

   :param address:
   :type address: pd.Series | str

   :returns: The corresponding abbreviated addresses in the same order (with the same indices),
             or a single abbreviated address string.
   :rtype: pd.Series | str















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