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Below is my first attempt at modifying the code.  It is failing terribly.  Trying to get Lukas Eichler code to work, but haven't completely gone through porting all the code.  It is a work in-progress.

#region imports
from AlgorithmImports import *
import datetime
from io import StringIO
#import os
import pandas as pd
import numpy as np
import traceback
#import typing

#from SmartRollingWindow import *

#endregion

class OptimizedTransdimensionalReplicator(QCAlgorithm):

    def Initialize(self):
        self.InitAlgoParams()
        self.InitAssets()
        self.InitUniverse()
        self.InitBacktestParams()        
        self.ScheduleRoutines()


        self.SetStartDate(2020, 9, 19)  # Set Start Date
        self.SetCash(100000)  # Set Strategy Cash
        self.AddEquity("SPY", Resolution.Minute)
        self.AddEquity("BND", Resolution.Minute)
        self.AddEquity("AAPL", Resolution.Minute)

        try:
            #https://stackoverflow.com/questions/21269399/datetime-dtypes-in-pandas-read-csv
            #https://towardsdatascience.com/all-the-pandas-read-csv-you-should-know-to-speed-up-your-data-analysis-1e16fe1039f3
            #By default, the argument parse_dates will read date data with month first (MM/DD, MM DD, or MM-DD) format, and this arrangement is relatively unique in the United State.
            
        
            data = StringIO(self.Download("https://www.dropbox.com/s/eq4wnau47jyiase/Tips_20220326.csv?dl=1"))
            self.df1 = pd.read_csv(data,parse_dates=['startdate','enddate'],header=0)
            
            self.df2 = self.df1.groupby('Symbol')
            for name, group in self.df2:
                self.Log(name)
                #self.Log(group)

        except Exception:
            ex = traceback.format_exc
            print(ex)

    ## Set backtest params: dates, cash, etc. Called from Initialize().
    ## ----------------------------------------------------------------
    def InitBacktestParams(self):
        self.SetStartDate(2022, 1, 1)
        self.SetEndDate(2022, 2, 22)
        self.SetCash(100000)
        self.SetBenchmark(Symbol.Create("BTCUSDT", SecurityType.Crypto, Market.Binance))

       
        
    def SelectSymbols(self, dateTime):
        symbols = []
        #only want to look at symbols from list that are between startdate and enddate
        #top = self.SelectTopMarketCapCoins(dateTime.date(), 5)
        #self.Debug(f"Selected {top} at {dateTime.date()}")
        for name, group in self.df2:
            #self.Log(name)
            symbols.append(Symbol.Create(name, SecurityType.Equity, Market.USA))

        self.UniverseTickers = symbols
        return symbols

    ## Schedule routines
    ## ------------------------
    def ScheduleRoutines(self):
        
    # TODO
    # Check if the symbol is still within its insight start and end date, if not removed it

    # TODO 
    ## Check if rebalancing has happened in the last 7 days, 
    ## If it has, do not rebalance again 
        if(self.rebalanceWeekly):
            self.Schedule.On( self.DateRules.WeekStart(self.symbol),
                            self.TimeRules.AfterMarketOpen(self.symbol, 31),
                            self.RebalanceHoldings )

    ##
    ## Check if we are already holding the max # of open positions.
    ## TODO:
    ## When we start using limit orders, include pending holdings
    ## ------------------------------------------------------------
    @property
    def PortfolioAtCapacity(self):
        numHoldings = len([x.Key for x in self.Portfolio if self.IsInvested(x.Key)])
        return numHoldings >= self.maxHoldings
    
    ## TODO:
    ## Test logic below for pending holdings
    # pendingOrders  = len( [x for x in self.Transactions.GetOpenOrders()
    #                         if x.Direction == OrderDirection.Buy
    #                             and x.Type == OrderType.Limit ] )
    

    # --------------------
    def InitAlgoParams(self):
        self.emaSlowPeriod    = int(self.GetParameter('emaSlowPeriod'))
        self.emaFastPeriod    = int(self.GetParameter('emaFastPeriod'))
        self.mompPeriod       = int(self.GetParameter('mompPeriod'))       # used for momentum based weight
        self.minimumVolPeriod = int(self.GetParameter('minimumVolPeriod')) # used for volume threshold
        self.warmupPeriod     = max(self.emaSlowPeriod, self.mompPeriod, self.minimumVolPeriod)
        
        self.useMomWeight     = (int(self.GetParameter("useMomWeight")) == 1)                 
        self.maxExposurePct   = float(self.GetParameter("maxExposurePct"))/100
        self.rebalanceWeekly  = (int(self.GetParameter("rebalanceWeekly")) == 1)

        self.minimumVolume    = int(self.GetParameter("minimumVolume")) 
        self.maxHoldings      = int(self.GetParameter("maxHoldings"))
        
        self.minAmountToBeInvested = int(self.GetParameter("minAmountToBeInvested"))    

    def InitAssets(self):    
    #self.symbol = "SPY" 
        self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Cash)
        self.SetAccountCurrency("USD")
        self.AddEquity(self.symbol, Resolution.Daily)

        self.EnableAutomaticIndicatorWarmUp = True
        self.SetWarmUp(timedelta(self.warmupPeriod))
        self.SelectedSymbolsAndWeights = {}


    def InitUniverse(self):
        self.UniverseSettings.Resolution = Resolution.Daily
        self.symDataDict = { }
        self.UniverseTickers = ["AAPL", "TSLA"]

        universeSymbols = []

    self.SetUniverseSelection(ScheduledUniverseSelectionModel(
        self.DateRules.WeekStart(),
        self.TimeRules.At(0, 0),
        self.SelectSymbols
        ))


    def OnData(self, data):
        if not self.Portfolio.Invested:
            self.SetHoldings("SPY", 0.33)
            self.SetHoldings("BND", 0.33)
            self.SetHoldings("AAPL", 0.33)
        
        
    def CoarseSelectionFunction(self, coarse):
        return self.symbols
    
    def FineSelectionFunction(self, fine):
        return self.symbols