Timeouts and optimization

class RollingWindowAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2021, 1, 1)
        self.set_cash(100000)
        self.universe_settings.resolution = Resolution.DAILY
        self.add_universe(self.coarse_filter)
        # Dictionary to hold rolling windows
        self.rolling_windows: dict[Symbol, RollingWindow[TradeBar]] = {}
        self.window_size = 100
    def coarse_filter(self, coarse) -> list:
        # Keep invested securities and filter for US stocks for rolling window
        return [x.Symbol for x in coarse if x.Symbol.value.endswith('.O') or self.portfolio[x.Symbol].invested]
    def update_rolling_window(self, symbol, price) -> None:
        if symbol not in self.rolling_windows:
            self.rolling_windows[symbol] = RollingWindow[TradeBar](self.window_size)
        self.rolling_windows[symbol].add(TradeBar(self.Time, symbol, price, price, price, price, 100))
    def on_data(self, slice) -> None:
        for symbol, trade_bar in slice.bars.items():
            self.update_rolling_window(symbol, trade_bar.close)
        if len(self.rolling_windows) > 0:
            # Calculate price change for the last 100 days
            changes = {
                symbol: (window[0].close - window[self.window_size - 1].close) / window[self.window_size - 1].close
                for symbol, window in self.rolling_windows.items() if window.is_ready}
            # Sort and take top 10
            top_10 = sorted(changes, key=lambda x: changes[x], reverse=True)[:10]
            self.rebalance(top_10)
    def rebalance(self, top_10) -> None:
        for symbol in list(self.active_symbols):
            if symbol not in top_10:
                self.liquidate(symbol)
        for symbol in top_10:
            self.set_holdings(symbol, 0.1)  # Equal weight
    def on_securities_changed(self, changes) -> None:
        self.active_symbols = {sec.Symbol for sec in changes.added_securities}

This corrected version adheres to Python's type hinting and fixes potential attribute errors. Make sure to verify the specific usage of RollingWindow and TradeBar within your QuantConnect environment as appropriate for your implementation.

Sources: Short Term Reversal Strategy In Stocks, Coarse Fundamental Top3 Algorithm, Momentum And State Of Market Filters, Coarse Fine Fundamental Combo Algorithm, Fundamental Factor Long Short Strategy