pep8 conversion of python algorithms #3 (#7934)

* raw pep8 conversion

* Minor fixes

---------

Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>

Algorithm.Python/BasicTemplateOptionsHistoryAlgorithm.py

@@ -23,55 +23,55 @@ from AlgorithmImports import *
 class BasicTemplateOptionsHistoryAlgorithm(QCAlgorithm):
     ''' This example demonstrates how to get access to options history for a given underlying equity security.'''
 
-    def Initialize(self):
+    def initialize(self):
         # this test opens position in the first day of trading, lives through stock split (7 for 1), and closes adjusted position on the second day
-        self.SetStartDate(2015, 12, 24)
-        self.SetEndDate(2015, 12, 24)
-        self.SetCash(1000000)
+        self.set_start_date(2015, 12, 24)
+        self.set_end_date(2015, 12, 24)
+        self.set_cash(1000000)
 
-        option = self.AddOption("GOOG")
+        option = self.add_option("GOOG")
         # add the initial contract filter 
         # SetFilter method accepts timedelta objects or integer for days.
         # The following statements yield the same filtering criteria
-        option.SetFilter(-2, +2, 0, 180)
-        # option.SetFilter(-2,2, timedelta(0), timedelta(180))
+        option.set_filter(-2, +2, 0, 180)
+        # option.set_filter(-2,2, timedelta(0), timedelta(180))
 
         # set the pricing model for Greeks and volatility
         # find more pricing models https://www.quantconnect.com/lean/documentation/topic27704.html
-        option.PriceModel = OptionPriceModels.CrankNicolsonFD()
+        option.price_model = OptionPriceModels.crank_nicolson_fd()
         # set the warm-up period for the pricing model
-        self.SetWarmUp(TimeSpan.FromDays(4))
+        self.set_warm_up(TimeSpan.from_days(4))
         # set the benchmark to be the initial cash
-        self.SetBenchmark(lambda x: 1000000)
+        self.set_benchmark(lambda x: 1000000)
 
-    def OnData(self,slice):
-        if self.IsWarmingUp: return
-        if not self.Portfolio.Invested:
-            for chain in slice.OptionChains:
-                volatility = self.Securities[chain.Key.Underlying].VolatilityModel.Volatility
-                for contract in chain.Value:
-                    self.Log("{0},Bid={1} Ask={2} Last={3} OI={4} sigma={5:.3f} NPV={6:.3f} \
+    def on_data(self,slice):
+        if self.is_warming_up: return
+        if not self.portfolio.invested:
+            for chain in slice.option_chains:
+                volatility = self.securities[chain.key.underlying].volatility_model.volatility
+                for contract in chain.value:
+                    self.log("{0},Bid={1} Ask={2} Last={3} OI={4} sigma={5:.3f} NPV={6:.3f} \
                               delta={7:.3f} gamma={8:.3f} vega={9:.3f} beta={10:.2f} theta={11:.2f} IV={12:.2f}".format(
-                    contract.Symbol.Value,
-                    contract.BidPrice,
-                    contract.AskPrice,
-                    contract.LastPrice,
-                    contract.OpenInterest,
+                    contract.symbol.value,
+                    contract.bid_price,
+                    contract.ask_price,
+                    contract.last_price,
+                    contract.open_interest,
                     volatility,
-                    contract.TheoreticalPrice,
-                    contract.Greeks.Delta,
-                    contract.Greeks.Gamma,
-                    contract.Greeks.Vega,
-                    contract.Greeks.Rho,
-                    contract.Greeks.Theta / 365,
-                    contract.ImpliedVolatility))
+                    contract.theoretical_price,
+                    contract.greeks.delta,
+                    contract.greeks.gamma,
+                    contract.greeks.vega,
+                    contract.greeks.rho,
+                    contract.greeks.theta / 365,
+                    contract.implied_volatility))
 
-    def OnSecuritiesChanged(self, changes):
-        for change in changes.AddedSecurities:
+    def on_securities_changed(self, changes):
+        for change in changes.added_securities:
             # only print options price
-            if change.Symbol.Value == "GOOG": return
-            history = self.History(change.Symbol, 10, Resolution.Minute).sort_index(level='time', ascending=False)[:3]
+            if change.symbol.value == "GOOG": return
+            history = self.history(change.symbol, 10, Resolution.MINUTE).sort_index(level='time', ascending=False)[:3]
             for index, row in history.iterrows():
-                self.Log("History: " + str(index[3])
+                self.log("History: " + str(index[3])
                         + ": " + index[4].strftime("%m/%d/%Y %I:%M:%S %p")
                         + " > " + str(row.close))