class example(Strategy):
 n1 = 1
 n2 = 20
 relax = 5 # how many days/periods to wait before trading again
 relax = pd.to_timedelta(relax, unit="D") # convert to a timedelta object
 def init(self):
 super().init()
 self.sma1 = self.I(SMA, self.data.Close, self.n1)
 self.sma2 = self.I(SMA, self.data.Close, self.n2)
 def next(self):
 super().next()
 price = self.data.Close[-1]
 if len(self.closed_trades) == 0: # If there hasn't been any trades yet
 last_trade_time = self.data.index[0]
 elif len(self.trades) == 0: # We are in cash no open trades
 last_trade_time = self.closed_trades[-1].exit_time # When did we exit our last trade
 else: # We have an open position
 last_trade_time = max(
 self.trades[-1].entry_time, self.closed_trades[-1].exit_time
 ) # the max of when we either entered that trade or exited it last
 current_time = self.data.index[-1] 
 dayssince = (
 current_time - last_trade_time
 ) # this will be used in concert with relax variable
 # Bullish Markets ---------------------------------
 if (
 not self.position.is_long
 and crossover(self.sma1, self.sma2)
 ):
 self.buy(size=0.9)
 elif (
 self.position.is_long
 and crossover(self.sma1, self.sma2)
 and dayssince > self.relax # Checks to make sure it has been at least the proper amount of days since last trade
 ):
 ...rest of code here....

import pandas as pd
...
 def next(self):
 cur_time = self.data.index[-1]
 for trade in self.trades:
 if cur_time - trade.entry_time >= pd.Timedelta('5 days'):
 trade.close()