Error in sample code for upcomming splits

Here is the corrected code to resolve the error:

from AlgorithmImports import *

class UpcomingSplitsExampleAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2020, 1, 1)
        self.set_end_date(2024, 10, 1)
        self.set_cash(100000)

        # Trade on daily basis based on daily upcoming splits signals.
        self.universe_settings.resolution = Resolution.DAILY
        # Universe consists of equities with upcoming splits events.
        self._universe = self.add_universe(EODHDUpcomingSplits, self.selection)

    def selection(self, splits: List[EODHDUpcomingSplits]) -> List[Symbol]:
        # Split (more shares with lower price) will make the stock more affordable and drive up demand.
        # Hence, include all stocks that will have a split within the next 7 days.
        # Note that splitting up the stock means split_factor > 1.
        return [x.symbol for x in splits if x.split_factor > 1]

    def on_data(self, slice: Slice) -> None:
        # Equally invest in each member of the universe to evenly share risk.
        total_count = len(self._universe.members)
        if total_count == 0:
            return
        targets = [PortfolioTarget(symbol, 1.0 / total_count) for symbol in self._universe.members]
        self.set_holdings(targets)

    def on_securities_changed(self, changes: SecurityChanges) -> None:
        for removed in changes.removed_securities:
            # Liquidate those that leave the universe to realize any gains from the split event.
            self.liquidate(removed.symbol)

Key Changes & Reasoning:

• Access self._universe.members directly as a dictionary, not as a callable function.
• Loop directly over self._universe.members to get symbols (iterating the dict yields keys).
• Added a guard clause (if total_count == 0: return) to prevent division by zero.

This should resolve the error and correctly allocate holdings across the active universe.

Sources: docs writing algorithms datasets eod historical data upcoming splits, docs writing algorithms datasets eod historical data upcoming dividends, docs writing algorithms universes dataless scheduled universes, Earnings Quality Factor, True Beats - QuantConnect.com