How to specify the trading class for FuturesOption?

[RedheadedCoding]

For FutureOption how does one specify a trading class such as for natural gas (NG) options there are LNE and ON plus other trading classes?

[westonplatter]

@RedheadedCoding once you get the List[OptionChain] data from ibkr, you can filter down to the trading classes you want.

First part is to get the data from IBKR,

from ib_insync import util, OptionChain, Index
from typing import List

contract = Index("NG", exchange="NYMEX", currency="USD")
ib.qualifyContracts(contract)

# get option chains
ibkr_option_chains: List[OptionChain] = ib.reqSecDefOptParams(contract.symbol, 'CME', 'IND', contract.conId)

# helper method in ib_async to convert List[OptionChain] to a pd.DataFrame
ibkr_exchange_option_chains: pd.DataFrame = util.df(ibkr_option_chains)

Second step is to use a mix of ib_async methods and pandas methods to transform the data into a df that you can then filter down to get the LNE and ON trading classes you mentioned,

import re 

def lower_camel_case_to_snake_case(s):
    return re.sub(r"(?<!^)(?=[A-Z])", "_", s).lower()

def option_chain_df(df, underlying_symbol):
    """
    Transforms a 'compressed exchange option chain' to a pd.DataFrame
    with rows for each strike and expiration

    Args:
        df (pd.DataFrame): df, the result of util.df(ibkr_option_chains)
        underlying_symbol (str): underlying symbol. For example, NG

    Returns:
        pd.DataFrame: df with basic option chain columns: 
    """
    df = df.copy()

    df = df.explode("expirations")
    df = df.explode("strikes")
    df = df.rename(columns={"expirations": "expiry", "strikes": "strike"})
    df["expiry"] = pd.to_datetime(df["expiry"], format="%Y%m%d", errors="coerce")

    df = df.rename(columns=lower_camel_case_to_snake_case)

    df.strike = df.strike.astype("float64")

    df = df.sort_values(by=["expiry", "strike"])
    df = df.reset_index(drop=True)

    df.underlying_con_id = df.underlying_con_id.astype(int)

    # remove the EC{symbol} contracts
    df = df[~df.trading_class.str.startswith("EC")]

    # set underlying_symbol
    df["underlying_symbol"] = underlying_symbol

    return df

option_chain_df = option_chain_df(ibkr_exchange_option_chains, "NG")
option_chain_df

lne_option_chain = option_chain_df.query("trading_class == 'LNE'")
lne_option_chain

I've done a bit of work to pull down future options and match them to the specific underlying futures. This notebook demos that approach with /ES, /CL, and /GC, https://github.com/westonplatter/ib_insync_options/blob/main/example_downloads_for_es_gc_cl.ipynb.