Changed Quanld source to correctly retrieve csv data, along with simp…

…le cleanup of import statements and use of Decimal

Algorithm.Python/CustomModelsAlgorithm.py

@@ -24,7 +24,6 @@
 from QuantConnect.Securities import *
 from QuantConnect.Orders.Fills import *
 import numpy as np
-import decimal as d
 import random
 
 ### <summary>
@@ -102,7 +101,7 @@ def GetOrderFee(self, parameters):
         # custom fee math
         fee = max(1, parameters.Security.Price
                   * parameters.Order.AbsoluteQuantity
-                  * d.Decimal(0.00001))
+                  * 0.00001)
         self.algorithm.Log("CustomFeeModel: " + str(fee))
         return OrderFee(CashAmount(fee, "USD"))
 
@@ -112,6 +111,6 @@ def __init__(self, algorithm):
 
     def GetSlippageApproximation(self, asset, order):
         # custom slippage math
-        slippage = asset.Price * d.Decimal(0.0001 * np.log10(2*float(order.AbsoluteQuantity)))
+        slippage = asset.Price * 0.0001 * np.log10(2*float(order.AbsoluteQuantity))
         self.algorithm.Log("CustomSlippageModel: " + str(slippage))
         return slippage

Algorithm.Python/ETFGlobalRotationAlgorithm.py

@@ -23,9 +23,7 @@
 from QuantConnect.Algorithm import *
 from QuantConnect.Indicators import *
 from System.Collections.Generic import List
-import decimal as d
 from datetime import datetime, timedelta
-from decimal import Decimal
 
 ### <summary>
 ### Strategy example using a portfolio of ETF Global Rotation
@@ -89,7 +87,7 @@ def OnData(self, data):
                 if (self.Portfolio[bestGrowth[0]].Quantity == 0):
                     self.Log("PREBUY>>LIQUIDATE>>")
                     self.Liquidate()
-                self.Log(">>BUY>>" + str(bestGrowth[0]) + "@" + str(Decimal(100) * bestGrowth[1].Current.Value))
+                self.Log(">>BUY>>" + str(bestGrowth[0]) + "@" + str(100 * bestGrowth[1].Current.Value))
                 qty = self.Portfolio.MarginRemaining / self.Securities[bestGrowth[0]].Close
                 self.MarketOrder(bestGrowth[0], int(qty)) 
             else:

Algorithm.Python/FractionalQuantityRegressionAlgorithm.py

@@ -27,7 +27,6 @@
 from QuantConnect.Data.Market import *
 from QuantConnect.Data.Consolidators import *
 
-import decimal as d
 from datetime import timedelta
 from math import floor
 

Algorithm.Python/FuturesMomentumAlgorithm.py

@@ -21,7 +21,6 @@
 from QuantConnect.Algorithm import *
 from QuantConnect.Securities import *
 from datetime import timedelta
-import decimal as d
 import numpy as np
 
 ### <summary>
@@ -43,7 +42,7 @@ def Initialize(self):
         self.SetCash(100000)
         fastPeriod = 20
         slowPeriod = 60
-        self._tolerance = d.Decimal(1 + 0.001)
+        self._tolerance = 1 + 0.001
         self.IsUpTrend = False
         self.IsDownTrend = False
         self.SetWarmUp(max(fastPeriod, slowPeriod))

Algorithm.Python/IndicatorWarmupAlgorithm.py

@@ -25,7 +25,6 @@
 from QuantConnect.Indicators import *
 from QuantConnect.Orders import *
 from QuantConnect.Securities import *
-import decimal as d
 
 ### <summary>
 ### Regression test for history and warm up using the data available in open source.
@@ -111,7 +110,7 @@ def __init__(self, symbol, algorithm):
         def Update(self):
             self.IsReady = self.Close.IsReady and self.ADX.IsReady and self.EMA.IsReady and self.MACD.IsReady
 
-            tolerance = d.Decimal(1 - self.PercentTolerance)
+            tolerance = 1 - self.PercentTolerance
             self.IsUptrend = self.MACD.Signal.Current.Value > self.MACD.Current.Value * tolerance and\
                 self.EMA.Current.Value > self.Close.Current.Value * tolerance
 
@@ -147,7 +146,7 @@ def TryExit(self):
 
             limit = 0
             qty = self.Security.Holdings.Quantity
-            exitTolerance = d.Decimal(1 + 2 * self.PercentTolerance)
+            exitTolerance = 1 + 2 * self.PercentTolerance
             if self.Security.Holdings.IsLong and self.Close.Current.Value * exitTolerance < self.EMA.Current.Value:
                 limit = self.Security.High
             elif self.Security.Holdings.IsShort and self.Close.Current.Value > self.EMA.Current.Value * exitTolerance:
@@ -164,8 +163,8 @@ def OnOrderEvent(self, fill):
 
             # if we just finished entering, place a stop loss as well
             if self.Security.Invested:
-                stop = fill.FillPrice*d.Decimal(1 - self.PercentGlobalStopLoss) if self.Security.Holdings.IsLong \
-                    else fill.FillPrice*d.Decimal(1 + self.PercentGlobalStopLoss)
+                stop = fill.FillPrice*(1 - self.PercentGlobalStopLoss) if self.Security.Holdings.IsLong \
+                    else fill.FillPrice*(1 + self.PercentGlobalStopLoss)
 
                 self.__currentStopLoss = self.__algorithm.StopMarketOrder(self.Symbol, -qty, stop, "StopLoss at: {0}".format(stop))
 

Algorithm.Python/LiveFeaturesAlgorithm.py

@@ -27,7 +27,6 @@
 
 import numpy as np
 from datetime import datetime
-import decimal
 import json
 
 
@@ -103,7 +102,7 @@ def Reader(self, config, line, date, isLiveMode):
                 liveBTC = json.loads(line)
 
                 # If value is zero, return None
-                value = decimal.Decimal(liveBTC["last"])
+                value = liveBTC["last"]
                 if value == 0: return None
 
                 coin.Time = datetime.now()

Algorithm.Python/MarginCallEventsAlgorithm.py

@@ -21,7 +21,6 @@
 from QuantConnect.Orders import *
 from QuantConnect.Algorithm import QCAlgorithm
 import numpy as np
-import decimal as d 
 from datetime import datetime, timedelta
 
 ### <summary>
@@ -61,7 +60,7 @@ def OnMarginCall(self, requests):
         for order in requests:
 
             # liquidate an extra 10% each time we get a margin call to give us more padding
-            newQuantity = int(np.sign(order.Quantity) * order.Quantity * d.Decimal(1.1))
+            newQuantity = int(np.sign(order.Quantity) * order.Quantity * 1.1)
             requests.remove(order)
             requests.append(SubmitOrderRequest(order.OrderType, order.SecurityType, order.Symbol, newQuantity, order.StopPrice, order.LimitPrice, self.Time, "OnMarginCall"))
 
@@ -74,6 +73,6 @@ def OnMarginCallWarning(self):
         # a chance to prevent a margin call from occurring
 
         spyHoldings = self.Securities["SPY"].Holdings.Quantity
-        shares = int(-spyHoldings * d.Decimal(0.005))
+        shares = int(-spyHoldings * 0.005)
         self.Error("{0} - OnMarginCallWarning(): Liquidating {1} shares of SPY to avoid margin call.".format(self.Time, shares))
         self.MarketOrder("SPY", shares)

Algorithm.Python/MovingAverageCrossAlgorithm.py

@@ -21,7 +21,6 @@
 from QuantConnect import *
 from QuantConnect.Algorithm import *
 from QuantConnect.Indicators import *
-import decimal as d
 
 ### <summary>
 ### In this example we look at the canonical 15/30 day moving average cross. This algorithm
@@ -75,7 +74,7 @@ def OnData(self, data):
         # 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 self.fast.Current.Value > self.slow.Current.Value * d.Decimal(1 + tolerance):
+            if self.fast.Current.Value > self.slow.Current.Value *(1 + tolerance):
                 self.Log("BUY  >> {0}".format(self.Securities["SPY"].Price))
                 self.SetHoldings("SPY", 1.0)
 

Algorithm.Python/OrderTicketDemoAlgorithm.py

@@ -21,7 +21,6 @@
 from QuantConnect.Algorithm import *
 from QuantConnect.Orders import *
 from QuantConnect.Data import *
-import decimal as d
 
 ### <summary>
 ### In this algorithm we submit/update/cancel each order type
@@ -113,11 +112,11 @@ def LimitOrders(self):
 
             # submit a limit order to buy 10 shares at .1% below the bar's close
             close = self.Securities[self.spy.Value].Close
-            newTicket = self.LimitOrder(self.spy, 10, close * d.Decimal(.999))
+            newTicket = self.LimitOrder(self.spy, 10, close * .999)
             self.__openLimitOrders.append(newTicket)
 
             # submit another limit order to sell 10 shares at .1% above the bar's close
-            newTicket = self.LimitOrder(self.spy, -10, close * d.Decimal(1.001))
+            newTicket = self.LimitOrder(self.spy, -10, close * 1.001)
             self.__openLimitOrders.append(newTicket)
 
         # when we submitted new limit orders we placed them into this list,
@@ -133,8 +132,8 @@ def LimitOrders(self):
                 return
 
             # if niether order has filled, bring in the limits by a penny
-            newLongLimit = longOrder.Get(OrderField.LimitPrice) + d.Decimal(0.01)
-            newShortLimit = shortOrder.Get(OrderField.LimitPrice) - d.Decimal(0.01)
+            newLongLimit = longOrder.Get(OrderField.LimitPrice) + 0.01
+            newShortLimit = shortOrder.Get(OrderField.LimitPrice) - 0.01
             self.Log("Updating limits - Long: {0:.2f} Short: {1:.2f}".format(newLongLimit, newShortLimit))
 
             updateOrderFields = UpdateOrderFields()
@@ -165,12 +164,12 @@ def StopMarketOrders(self):
             # a long stop is triggered when the price rises above the value
             # so we'll set a long stop .25% above the current bar's close
             close = self.Securities[self.spy.Value].Close
-            newTicket = self.StopMarketOrder(self.spy, 10, close * d.Decimal(1.0025))
+            newTicket = self.StopMarketOrder(self.spy, 10, close * 1.0025)
             self.__openStopMarketOrders.append(newTicket)
 
             # a short stop is triggered when the price falls below the value
             # so we'll set a short stop .25% below the current bar's close
-            newTicket = self.StopMarketOrder(self.spy, -10, close * d.Decimal(.9975))
+            newTicket = self.StopMarketOrder(self.spy, -10, close * .9975)
             self.__openStopMarketOrders.append(newTicket)
 
         # when we submitted new stop market orders we placed them into this list,
@@ -184,8 +183,8 @@ def StopMarketOrders(self):
                 return
 
             # if neither order has filled, bring in the stops by a penny
-            newLongStop = longOrder.Get(OrderField.StopPrice) - d.Decimal(0.01)
-            newShortStop = shortOrder.Get(OrderField.StopPrice) + d.Decimal(0.01)
+            newLongStop = longOrder.Get(OrderField.StopPrice) - 0.01
+            newShortStop = shortOrder.Get(OrderField.StopPrice) + 0.01
             self.Log("Updating stops - Long: {0:.2f} Short: {1:.2f}".format(newLongStop, newShortStop))
 
             updateOrderFields = UpdateOrderFields()
@@ -224,7 +223,7 @@ def StopLimitOrders(self):
             # so make the limit price a little higher than the stop price
 
             close = self.Securities[self.spy.Value].Close
-            newTicket = self.StopLimitOrder(self.spy, 10, close * d.Decimal(1.001), close * d.Decimal(1.0025))
+            newTicket = self.StopLimitOrder(self.spy, 10, close * 1.001, close * 1.0025)
             self.__openStopLimitOrders.append(newTicket)
 
             # a short stop is triggered when the price falls below the
@@ -233,7 +232,7 @@ def StopLimitOrders(self):
             # gauranteed to get at least the limit price for our fills,
             # so make the limit price a little softer than the stop price
 
-            newTicket = self.StopLimitOrder(self.spy, -10, close * d.Decimal(.999), close * d.Decimal(0.9975))
+            newTicket = self.StopLimitOrder(self.spy, -10, close * .999, close * 0.9975)
             self.__openStopLimitOrders.append(newTicket)
 
         # when we submitted new stop limit orders we placed them into this list,
@@ -247,10 +246,10 @@ def StopLimitOrders(self):
 
             # if neither order has filled, bring in the stops/limits in by a penny
 
-            newLongStop = longOrder.Get(OrderField.StopPrice) - d.Decimal(0.01)
-            newLongLimit = longOrder.Get(OrderField.LimitPrice) + d.Decimal(0.01)
-            newShortStop = shortOrder.Get(OrderField.StopPrice) + d.Decimal(0.01)
-            newShortLimit = shortOrder.Get(OrderField.LimitPrice) - d.Decimal(0.01)
+            newLongStop = longOrder.Get(OrderField.StopPrice) - 0.01
+            newLongLimit = longOrder.Get(OrderField.LimitPrice) + 0.01
+            newShortStop = shortOrder.Get(OrderField.StopPrice) + 0.01
+            newShortLimit = shortOrder.Get(OrderField.LimitPrice) - 0.01
             self.Log("Updating stops  - Long: {0:.2f} Short: {1:.2f}".format(newLongStop, newShortStop))
             self.Log("Updating limits - Long: {0:.2f}  Short: {1:.2f}".format(newLongLimit, newShortLimit))
 

Algorithm.Python/ParameterizedAlgorithm.py

@@ -22,7 +22,6 @@
 from QuantConnect.Algorithm import *
 from QuantConnect.Indicators import *
 from QuantConnect.Parameters import *
-import decimal as d
 
 ### <summary>
 ### Demonstration of the parameter system of QuantConnect. Using parameters you can pass the values required into C# algorithms for optimization.
@@ -62,7 +61,7 @@ def OnData(self, data):
         fast = self.fast.Current.Value
         slow = self.slow.Current.Value
 
-        if fast > slow * d.Decimal(1.001):
+        if fast > slow * 1.001:
             self.SetHoldings("SPY", 1)
-        elif fast < slow * d.Decimal(0.999):
+        elif fast < slow * 0.999:
             self.Liquidate("SPY")

Algorithm.Python/QCUWeatherBasedRebalancing.py

@@ -22,7 +22,6 @@
 from QuantConnect.Data import SubscriptionDataSource
 from QuantConnect.Python import PythonData
 from datetime import datetime, timedelta
-import decimal
 
 ### <summary>
 ### Using weather in NYC to rebalance portfolio. Assumption is people are happier when its warm.
@@ -86,7 +85,7 @@ def Reader(self, config, line, date, isLive):
         weather.Time = datetime.strptime(data[0], '%Y-%m-%d') + timedelta(hours=20) # Make sure we only get this data AFTER trading day - don't want forward bias.
         # If the second column is an invalid value (empty string), return None. The algorithm will discard it.
         if not data[2]: return None
-        weather.Value = decimal.Decimal(data[2])
+        weather.Value = data[2]
         weather["Max.C"] = float(data[1])   # Using a dot in the propety name, it will capitalize the first letter of each word:
         weather["Min.C"] = float(data[3])   # Max.C -> MaxC and Min.C -> MinC
 

Common/Data/Custom/Quandl.cs

@@ -137,7 +137,7 @@ public override BaseData Reader(SubscriptionDataConfig config, string line, Date
         /// <returns>STRING API Url for Quandl.</returns>
         public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode)
         {
-            var source = @"https://www.quantconnect.com/api/v2/proxy/quandl/api/v3/datasets/"
+            var source = @"https://www.quantconnect.com/api/v3/proxy/quandl/api/v3/datasets/"
                 + config.Symbol.Value + ".csv?order=asc&api_key=" + _authCode;
             return new SubscriptionDataSource(source, SubscriptionTransportMedium.RemoteFile);
         }