#!/usr/bin/env python
#Reduce function for computing matrix multiply A*B

#Input arguments:
#variable n should be set to the inner dimension of the matrix product (i.e., the number of columns of A/rows of B)

import sys
import string
import numpy
#number of columns of A/rows of B
n = int(sys.argv[1])

#Create data structures to hold the current row/column values (if needed; your code goes here)
is_first = True
globalStore = {}
globalSum = {}

# input comes from STDIN (stream data that goes to the program)
for line in sys.stdin:
    #Remove leading and trailing whitespace
    line = line.strip()
    #Get key/value
    key, value = line.split('\t',1)
    #Parse key/value input (your code goes here)
    #string to tuple
    value_tuple = tuple(value[1:-1].split(','))
    which_matrix = value_tuple[0].replace("'",'')
    which_value = int(value_tuple[1])
    single_value = float(value_tuple[2])
    currentkey = key


    #If we are still on the same key...
    if currentkey in globalStore:

        #Process key/value pair (your code goes here)
        currentStore = globalStore[currentkey]
        if which_value in currentStore:
            another_value = currentStore.pop(which_value, None)
            globalSum[currentkey] += single_value * another_value
        else:
            currentStore[which_value] = single_value


    #Otherwise, if this is a new key...
    else:
        #If this is a new key and not the first key we've seen
        if not is_first:

            #compute/output result to STDOUT (your code goes here)
            print (currentkey, globalSum[currentkey])



        #Process input for new key (your code goes here)
        is_first = False
        newKeyStore = {}
        newKeyStore[which_value] = single_value
        globalStore[currentkey] = newKeyStore
        globalSum[currentkey] = 0

#Compute/output result for the last key (your code goes here)
print (currentkey, globalSum[currentkey])