Branch 1

problem1/problem1_template.py

@@ -16,6 +16,11 @@
 from sklearn import linear_model
 from sklearn import metrics as sm
 from problem1_trading_params import MyTradingParams
+try:
+    from urllib2 import urlopen
+except ImportError:
+    from urllib.request import urlopen
+import collections
 
 ## Make your changes to the functions below.
 ## SPECIFY the symbols you are modeling for in getSymbolsToTrade() below
@@ -31,10 +36,7 @@ class MyTradingFunctions():
     def __init__(self):  #Put any global variables here
         self.lookback = 1200  ## max number of historical datapoints you want at any given time
         self.targetVariable = 'Y'
-        if datetime.today() < datetime(2018, 7, 3):
-            self.dataSetId = 'QQ3DataSample'
-        else:
-            self.dataSetId = 'QQ3DataDownSampled'
+        self.dataSetId = ''
         self.params = {}
 
         # for example you can import and store an ML model from scikit learn in this dict
@@ -260,8 +262,37 @@ def computeForInstrument(cls, updateNum, time, featureParams, featureKey, instru
         else:
             return currentValue * 0.5
 
+def version():
+    try:
+        f = open("currentversion","r")
+        response =  urlopen("https://raw.githubusercontent.com/Auquan/data_set_id/master/versions.txt")
+        script = response.read().decode('utf8').split()
+        para = f.read().split()
+        f.close()
+        list= collections.defaultdict(lambda : '0')
+        for i in range(len(para)):
+            list[para[i]]=para[i]
+        for i in range(len(script)):
+            if(list[script[i]]!= script[i]):
+                list[script[i]] = script[i]
+                f = open("currentversion","a+")
+                f.write(script[i] + "\n")
+                new_response = urlopen("https://raw.githubusercontent.com/Auquan/data_set_id/master/" + script[i] + ".py")
+                code = new_response.read().decode('utf8')
+                exec(code)
+    except FileNotFoundError:
+        response =  urlopen("https://raw.githubusercontent.com/Auquan/data_set_id/master/versions.txt")
+        script = response.read().decode('utf8').split()
+        for i in range(len(script)):
+            f = open("currentversion","a+")
+            f.write(script[i] + "\n")
+            new_response = urlopen("https://raw.githubusercontent.com/Auquan/data_set_id/master/" + script[i] + ".py")
+            code = new_response.read().decode('utf8')
+            exec(code)
 
 if __name__ == "__main__":
+    version()
+
     if updateCheck():
         print('Your version of the auquan toolbox package is old. Please update by running the following command:')
         print('pip install -U auquan_toolbox')

problem1/problem1_trading_params.py

@@ -15,6 +15,10 @@
 import sys
 from sklearn import linear_model
 from sklearn import metrics as sm
+try:
+    from urllib2 import urlopen
+except ImportError:
+    from urllib.request import urlopen
 
 ## Make your changes to the functions below.
 ## SPECIFY the symbols you are modeling for in getSymbolsToTrade() below
@@ -32,7 +36,11 @@ class MyTradingParams(TradingSystemParameters):
     '''
     def __init__(self, tradingFunctions):
         self.__tradingFunctions = tradingFunctions
-        self.__dataSetId = self.__tradingFunctions.getDataSetId()
+
+        url = "https://raw.githubusercontent.com/Auquan/data_set_id/master/DataSetId.txt"
+        response = urlopen(url)
+        self.__dataSetId = response.read().decode('utf8').rstrip() + self.__tradingFunctions.getDataSetId()
+
         self.__instrumentIds = self.__tradingFunctions.getSymbolsToTrade()
         self.__priceKey = 'F5'
         self.__additionalInstrumentFeatureConfigDicts = []