I'm new to QuantConnect and I have to say this is totally awesome! Quick question. Seems like a lot of things are taken care of when using the Cloud-based IDE when streaming data. Everything seems like a line of code around here so I was wondering how I can stream real-time 1 min data to my desktop. I have downloaded the source from github. For example I would like to do this but in my desk top app:

using System;
using System.Linq;
using QuantConnect.Indicators;
using QuantConnect.Models;

namespace QuantConnect.Algorithm.Examples
/// <summary>
/// QuantConnect University: EMA + SMA Cross
/// In this example we look at the canonical 15/30 day moving average cross. This algorithm
/// will go long when the 15 crosses above the 30 and will liquidate when the 15 crosses
/// back below the 30.
/// </summary>
public class QCUMovingAverageCross : QCAlgorithm
private const string Symbol = "NLNK";

private ExponentialMovingAverage fast;
private ExponentialMovingAverage slow;
private SimpleMovingAverage[] ribbon;

public override void Initialize()
// set up our analysis span
SetStartDate(2009, 01, 01);
SetEndDate(2017, 09, 11);

// request SPY data with minute resolution
AddSecurity(SecurityType.Equity, Symbol, Resolution.Minute);

// create a 15 day exponential moving average
fast = EMA(Symbol, 15, Resolution.Daily);

// create a 30 day exponential moving average
slow = EMA(Symbol, 30, Resolution.Daily);

// the following lines produce a simple moving average ribbon, this isn't
// actually used in the algorithm's logic, but shows how easy it is to make
// indicators and plot them!

// note how we can easily define these indicators to receive hourly data
int ribbonCount = 7;
int ribbonInterval = 15*8;
ribbon = new SimpleMovingAverage[ribbonCount];

for(int i = 0; i < ribbonCount; i++)
ribbon[i] = SMA(Symbol, (i + 1)*ribbonInterval, Resolution.Hour);

private DateTime previous;
public void OnData(TradeBars data)
// a couple things to notice in this method:
// 1. We never need to 'update' our indicators with the data, the engine takes care of this for us
// 2. We can use indicators directly in math expressions
// 3. We can easily plot many indicators at the same time

// wait for our slow ema to fully initialize
if (!slow.IsReady) return;

// only once per day
if (previous.Date == data.Time.Date) return;

// define a small tolerance on our checks to avoid bouncing
const decimal tolerance = 0.00015m;
var holdings = Portfolio[Symbol].Quantity;

// we only want to go long if we're currently short or flat
if (holdings <= 0)
// if the fast is greater than the slow, we'll go long
if (fast > slow * (1 + tolerance))
Log("BUY >> " + Securities[Symbol].Price);
SetHoldings(Symbol, 1.0);

// we only want to liquidate if we're currently long
// if the fast is less than the slow we'll liquidate our long
if (holdings > 0 && fast < slow)
Log("SELL >> " + Securities[Symbol].Price);

Plot(Symbol, "Price", data[Symbol].Price);
Plot("Ribbon", "Price", data[Symbol].Price);

// easily plot indicators, the series name will be the name of the indicator
Plot(Symbol, fast, slow);
Plot("Ribbon", ribbon);

previous = data.Time;