Update ec2.py

ec2.py

 #!/usr/bin/python3
 
-from statistics import mean, stdev
 import math, random, sys, json
+from statistics import mean, stdev
 
 
-args = sys.stdin.read()
-session = json.loads(args)
+event = json.loads(sys.stdin.read())
 
 
-date = eval(session['key1'])
-close = eval(session['key2'])
-buy = eval(session['key3'])
-sell = eval(session['key4'])
-minhistory = int(session['key5'])
-shots = int(session['key6'])
-t = session['key7']
+dt = eval(event['key1'])
+close = eval(event['key2'])
+buy = eval(event['key3'])
+sell = eval(event['key4'])
+h = int(event['key5'])
+d = int(event['key6'])
+t = event['key7']
+minhistory = h
+shots = d
 var_95_list = []
 var_99_list = []
 dates = []
 
 for i in range(minhistory, len(close)):
-    if t == "sell":
-		if sell[i] == 1:  #If it is to sell
+	if t == "buy":
+		if buy[i] == 1: #If it is to buy
 			closing = close[i-minhistory:i]
-			percent_change = [(closing[i] - closing[i-1]) / closing[i-1] for i in range(1,len(closing))]#Calculating percenage change as dataframe method pct_change can't be used
+			percent_change = [(closing[i] - closing[i-1]) / closing[i-1] for i in range(1,len(closing))]
 			mean_value = mean(percent_change)
 			std_value = stdev(percent_change)
 			# generate much larger random number series with same broad characteristics 
@@ -34,11 +35,11 @@ for i in range(minhistory, len(close)):
 			var99 = simulated[int(len(simulated)*0.99)]
 			var_95_list.append(var95)
 			var_99_list.append(var99)
-			dates.append(str(date[i]))
-	if t == "buy":
-		if buy[i] == 1:  #If it is to buy
+			dates.append(str(dt[i]))
+	elif t == "sell":
+		if sell[i] == 1: #If it is to sell
 			closing = close[i-minhistory:i]
-			percent_change = [(closing[i] - closing[i-1]) / closing[i-1] for i in range(1,len(closing))]#Calculating percenage change as dataframe method pct_change can't be used
+			percent_change = [(closing[i] - closing[i-1]) / closing[i-1] for i in range(1,len(closing))]
 			mean_value = mean(percent_change)
 			std_value = stdev(percent_change)
 			# generate much larger random number series with same broad characteristics 
@@ -49,15 +50,15 @@ for i in range(minhistory, len(close)):
 			var99 = simulated[int(len(simulated)*0.99)]
 			var_95_list.append(var95)
 			var_99_list.append(var99)
-			dates.append(str(date[i]))
+			dates.append(str(dt[i]))
 
 output = {"dates" : dates,
 		"var95" : var_95_list,
 		"var99" : var_99_list
 		}
 
-final_output = json.dumps(output)
+output = json.dumps(output)
 
 print("Content-Type: application/json")
 print()
-print(final_output)
+print(output)