Discrete : 01-knapsack: dynamic programming solver + malloc error when to many values

1 files changed, 16 insertions, 33 deletions

diff --git a/01-knapsack/solver.py b/01-knapsack/solver.py
index 81a6d79..ffb1852 100755
--- a/01-knapsack/solver.py
+++ b/01-knapsack/solver.py
@@ -1,47 +1,30 @@
-#!/usr/bin/python2.7
+#!/usr/bin/python2
 # -*- coding: utf-8 -*-
 
+import os
+from subprocess import Popen, PIPE
 
-def solveIt(inputData):
-    # Modify this code to run your optimization algorithm
-
-    # parse the input
-    lines = inputData.split('\n')
 
-    firstLine = lines[0].split()
-    items = int(firstLine[0])
-    capacity = int(firstLine[1])
+def solveIt(inputData):
 
-    values = []
-    weights = []
+    # Writes the inputData to a temporay file
 
-    for i in range(1, items+1):
-        line = lines[i]
-        parts = line.split()
+    tmpFileName = 'tmp.data'
+    tmpFile = open(tmpFileName, 'w')
+    tmpFile.write(inputData)
+    tmpFile.close()
 
-        values.append(int(parts[0]))
-        weights.append(int(parts[1]))
+    # Runs the command: java Solver -file=tmp.data
 
-    items = len(values)
+    process = Popen(['./ks_dp', tmpFileName],
+                    stdout=PIPE)
+    (stdout, stderr) = process.communicate()
 
-    # a trivial greedy algorithm for filling the knapsack
-    # it takes items in-order until the knapsack is full
-    value = 0
-    weight = 0
-    taken = []
+    # removes the temporay file
 
-    for i in range(0, items):
-        if weight + weights[i] <= capacity:
-            taken.append(1)
-            value += values[i]
-            weight += weights[i]
-        else:
-            taken.append(0)
+    os.remove(tmpFileName)
 
-    # prepare the solution in the specified output format
-    outputData = str(value) + ' ' + str(0) + '\n'
-    outputData += ' '.join(map(str, taken))
-    return outputData
+    return stdout.strip()
 
 
 import sys