{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from collections import deque\n",
    "def topologicalOrdering(g):\n",
    "    \n",
    "    # find indegrees of each node\n",
    "    out = reduce(lambda a,b: a+b, g.values())\n",
    "    indegrees = {}\n",
    "    for node in set(out + g.keys()):\n",
    "        if node not in out:\n",
    "            indegrees[node] = 0\n",
    "        else:\n",
    "            indegrees[node] = out.count(node)\n",
    "\n",
    "    # collect set of all nodes in graph with zero indegrees\n",
    "    candidates = deque()\n",
    "    for node in indegrees:\n",
    "        if indegrees[node] == 0:\n",
    "            candidates.appendleft(node)\n",
    "\n",
    "    L = [] # list for order of nodes\n",
    "    \n",
    "    # choose zero indegree node and remove it from graph\n",
    "    while candidates:\n",
    "        a = candidates.pop()\n",
    "        L.append(a)\n",
    "        if a in g:\n",
    "            for b in g[a]:\n",
    "                indegrees[b] -= 1\n",
    "                if indegrees[b] == 0:\n",
    "                    candidates.appendleft(b)           \n",
    "    \n",
    "    #if graph has edges that have not been removed/if there is a cycle\n",
    "    for node in indegrees:\n",
    "        if indegrees[node] != 0:\n",
    "            return \"the input graph is not a DAG\"\n",
    "    else:\n",
    "        return L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 4, 5, 2, 3]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graph = {1:[2], 2:[3], 4:[2], 5:[3]}\n",
    "topologicalOrdering(graph)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 2, 3, 4, 5, 6, 7, 10, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19]\n"
     ]
    }
   ],
   "source": [
    "g = dict()\n",
    "f = open('input/rosalind_ba5n.txt', 'r')\n",
    "for line in f:\n",
    "    line = line.strip().split('->')\n",
    "    g[int(line[0])] = map(int,line[1].split(','))\n",
    "print topologicalOrdering(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['a', 'b', 'e', 'c', 'f', 'd']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = {'a': ['b', 'c', 'd', 'e', 'f'],\n",
    "    'b': ['c', 'f'],\n",
    "    'c': ['d'],\n",
    "    'd': [], \n",
    "    'e': ['d', 'f'],\n",
    "    'f': []}\n",
    "topologicalOrdering(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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