old_contents: ﻿using System;
  namespace QuantConnect.Algorithm.Python.Benchmarks
  {
  	public class EmptySingleSecuritySecondEquityBenchmark
  	{
  		public EmptySingleSecuritySecondEquityBenchmark()
  		{
  		}
  	}
  }
  
new_contents: ﻿# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
  # Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  from clr import AddReference
  AddReference("System")
  AddReference("QuantConnect.Algorithm")
  AddReference("QuantConnect.Indicators")
  AddReference("QuantConnect.Common")
  
  from System import *
  from QuantConnect import *
  from QuantConnect.Data import *
  
  ### <summary>
  ### Benchmark Algorithm: Pure processing of 1 equity second resolution with the same benchmark.
  ### </summary>
  ### <remarks>
  ### This should eliminate the synchronization part of LEAN and focus on measuring the performance of a single datafeed and event handling system.
  ### </remarks>
  class EmptySingleSecuritySecondEquityBenchmark(QCAlgorithm):
  
      def Initialize(self):
          self.SetStartDate(2008, 1, 1)
          self.SetEndDate(2009, 1, 1)    
          self.SetBenchmark(lambda x: 1)
          self.AddEquity("SPY", Resolution.Second)
      
      def OnData(self, data):
          pass
subject: Add EmptySingleSecuritySecondEquityBenchmark algorithm