strong baseline with extend env

[lorrp1]

def my_process_data(df, window_size, frame_bound):
    prices = df.loc[:, 'NDX'].to_numpy()
    prices[frame_bound[0] - window_size]  # validate index (TODO: Improve validation)
    prices = prices[frame_bound[0]-window_size:frame_bound[1]]
    signal_features = df.to_numpy()#np.column_stack((prices, diff))
    return prices, signal_features

class MyForexEnv(StocksEnv):
    def __init__(self, prices, signal_features, **kwargs):
        self._prices = prices
        self._signal_features = signal_features
        super().__init__(**kwargs)
    def _process_data(self):
        return self._prices, self._signal_features

window_size = 30
start_index = window_size
end_index = len(df)

#env = MyForexEnv(df=df, window_size=10, frame_bound=(start_index, end_index))
prices, signal_features = my_process_data(df=df, window_size=window_size, frame_bound=(start_index, end_index))
env = MyForexEnv( prices, signal_features, df=df, window_size=window_size, frame_bound=(start_index, end_index))

env_maker = lambda: gym.make('env')

env = DummyVecEnv([env_maker])

im trying using the extended env with strong baseline but i keep getting errors:
TypeError: argument of type 'MyForexEnv' is not iterable
or

class MyForexEnv(StocksEnv):
    def __init__(self, prices = prices, signal_features = signal_features, **kwargs):
        self._prices = prices
        self._signal_features = signal_features
        super().__init__(**kwargs)
    def _process_data(self):
        return self._prices, self._signal_features
window_size = 30
start_index = window_size
end_index = len(df)
prices, signal_features = my_process_data(df=df, window_size=window_size, frame_bound=(start_index, end_index))
env_maker = lambda: gym.make(MyForexEnv,prices =prices, signal_features =signal_features, df=df, window_size=window_size, frame_bound=(start_index, end_index) )
env = DummyVecEnv([env_maker])

which returns:
TypeError: argument of type 'type' is not iterable

i have also tried using just the def in the new class definition to get the data but makes no difference.
or:

class MyForexEnv(gym.ActionWrapper):
    def __init__(self, env, prices = prices, signal_features = signal_features, **kwargs):
        self.trade_fee_bid_percent = 0.05
        self.trade_fee_ask_percent = 0.05
        self._prices = prices
        self._signal_features = signal_features
        super(MyForexEnv, self).__init__(env)
    def _process_data(self):
        return self._prices, self._signal_features
env = MyForexEnv(gym.make("stocks-v0"), prices, signal_features, df=df, window_size=window_size, frame_bound=(start_index, end_index))

still not working. any idea?

[lorrp1]

forgot the "lambda: "

[Karlheinzniebuhr]

using just the def in the new class definition to ge

Could you please share where exactly you forgot the lambda? I'm getting the same issue.

** Edit **
Got it,
env_maker = lambda: my_env