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class memstate:
	"""
	Takes a function with input:int and output:int
	creates memory
	"""
	def __init__(self,func):
		self.func=func
		self.memory = {}
	def __call__(self,inp):
		if inp in self.memory.keys():

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##########################################################################################################
## All below code is just calculation for each player type in game and there ELO from the training data ##
##########################################################################################################

################################################################
## General ELO rating functions ################################
################################################################
def expected_score(own_rating,opp_rating):
	return 1.0/(1.0+10.0**((float(opp_rating)-float(own_rating))/400.0))

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from random import random

n_games = int(raw_input())

def parse_game_data():
	dict_temp = {}

	dict_temp['game'] = i

	dict_temp['dice_prob'] = [float(x) for x in raw_input().strip().split(',')]

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from scipy.stats.stats import pearsonr 

n_tests = int(raw_input())

def parse():
	n_cases = int(raw_input())
	#print n_cases

	final_data = {}

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import requests
import htmlmin
import json
from bs4 import BeautifulSoup

from datetime import datetime, date, timedelta ##Basic Python

##define unique function
def uniq(seq): 
   # order preserving

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library(shiny)
require(rCharts)
library(reshape2)

cluster.data <- read.csv("./data/cluster_data.csv")


graphoptions<-as.list(colnames(cluster.data))
names(graphoptions)<-colnames(cluster.data)

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library(shiny)
library(rCharts)
library(reshape2)

cluster.data <- read.csv("./data/cluster_data.csv")


graphoptions<-as.list(colnames(cluster.data))
names(graphoptions)<-colnames(cluster.data)

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#install.packages("XML")
library(XML)
#install.package("caret")
library(caret)
#install.packages("lpSolve")
library(lpSolve)

###################################
## Take data from premier league website##
###################################

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#install.package("caret")
library(caret)
#install.packages("lpSolve")
library(lpSolve)

Opt.squad<-function(dat,cost,n.gk=2,n.df=5,n.md=5,n.fd=3) {
  #dat<-footy.data
  #cost<-100
  #n.gk=2
  #n.df=5

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<?xml version="1.0"?>
<root>
<item>
    <name>Change zero 9 part 1</name>
    <identifier>private.changezerotowierds1</identifier>
    <autogen>
	--KeyToKey-- 
	KeyCode::KEY_9, ModifierFlag::CONTROL_L,
	KeyCode::KEY_0
    </autogen>