Improves Universe Selection for python

In python algorithm using Universe Selection, the selector method should return a List<Symbol>. To make it more pythonic, we allow returning python list. The conversion is, then, performed in C# side.

Algorithm.Python/CoarseFineFundamentalComboAlgorithm.py

@@ -58,14 +58,7 @@ class CoarseFineFundamentalComboAlgorithm(QCAlgorithm):
         sortedByDollarVolume = sorted(coarse, key=lambda x: x.DollarVolume, reverse=True)
 
         # return the symbol objects of the top entries from our sorted collection
-        top5 = sortedByDollarVolume[:self.__numberOfSymbols]
-
-        # we need to return only the symbol objects
-        list = List[Symbol](len(top5))
-        for x in top5:
-            list.Add(x.Symbol)
-
-        return list
+        return [ x.Symbol for x in sortedByDollarVolume[:self.__numberOfSymbols] ]
 
     # sort the data by P/E ratio and take the top 'NumberOfSymbolsFine'
     def FineSelectionFunction(self, fine):
@@ -73,14 +66,7 @@ class CoarseFineFundamentalComboAlgorithm(QCAlgorithm):
         sortedByPeRatio = sorted(fine, key=lambda x: x.ValuationRatios.PERatio, reverse=True)
 
         # take the top entries from our sorted collection
-        topFine = sortedByPeRatio[:self.__numberOfSymbolsFine]
-
-        list = List[Symbol](len(topFine))
-        for x in topFine:
-            list.Add(x.Symbol)
-
-        return list
-
+        return [ x.Symbol for x in sortedByPeRatio[:self.__numberOfSymbolsFine] ]
 
     def OnData(self, data):
         # if we have no changes, do nothing

Algorithm.Python/EmaCrossUniverseSelectionAlgorithm.py

@@ -71,13 +71,11 @@ class EmaCrossUniverseSelectionAlgorithm(QCAlgorithm):
         # Sorts the values of the dict: we want those with greater difference between the moving averages
         values.sort(key=lambda x: x.scale, reverse=True)
 
-        # we need to return only the symbol objects
-        list = List[Symbol]()
         for x in values[:self.coarse_count]:
             self.Log('symbol: ' + str(x.symbol.Value) + '  scale: ' + str(x.scale))
-            list.Add(x.symbol)
-
-        return list
+        
+        # we need to return only the symbol objects
+        return [ x.symbol for x in values[:self.coarse_count] ]
 
     # this event fires whenever we have changes to our universe
     def OnSecuritiesChanged(self, changes):

Algorithm.Python/UniverseSelectionRegressionAlgorithm.py

@@ -52,11 +52,7 @@ class UniverseSelectionRegressionAlgorithm(QCAlgorithm):
 
 
     def CoarseSelectionFunction(self, coarse):
-        list = List[Symbol]()
-        for c in coarse:
-            if c.Symbol.Value == "GOOG" or c.Symbol.Value == "GOOCV" or c.Symbol.Value == "GOOAV" or c.Symbol.Value == "GOOGL":
-                list.Add(c.Symbol)
-        return list
+        return [ c.Symbol for c in coarse if c.Symbol.Value == "GOOG" or c.Symbol.Value == "GOOCV" or c.Symbol.Value == "GOOAV" or c.Symbol.Value == "GOOGL" ]
 
 
     def OnData(self, data):