{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook was prepared by [Donne Martin](https://github.com/donnemartin). Source and license info is on [GitHub](https://github.com/donnemartin/interactive-coding-challenges)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Challenge Notebook" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Problem: Find the shortest path between two nodes in a graph.\n", "\n", "* [Constraints](#Constraints)\n", "* [Test Cases](#Test-Cases)\n", "* [Algorithm](#Algorithm)\n", "* [Code](#Code)\n", "* [Unit Test](#Unit-Test)\n", "* [Solution Notebook](#Solution-Notebook)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Constraints\n", "\n", "* Is this a directional graph?\n", " * Yes\n", "* Could the graph have cycles?\n", " * Yes\n", " * Note: If the answer were no, this would be a DAG. \n", " * DAGs can be solved with a [topological sort](http://www.geeksforgeeks.org/shortest-path-for-directed-acyclic-graphs/)\n", "* Are the edges weighted?\n", " * Yes\n", " * Note: If the edges were not weighted, we could do a BFS\n", "* Are the edges all non-negative numbers?\n", " * Yes\n", " * Note: Graphs with negative edges can be done with Bellman-Ford\n", " * Graphs with negative cost cycles do not have a defined shortest path\n", "* Do we have to check for non-negative edges?\n", " * No\n", "* Can we assume this is a connected graph?\n", " * Yes\n", "* Can we assume the inputs are valid?\n", " * No\n", "* Can we assume we already have a graph class?\n", " * Yes\n", "* Can we assume we already have a priority queue class?\n", " * Yes\n", "* Can we assume this fits memory?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "The constraints state we don't have to check for negative edges, so we test with the general case.\n", "\n", "
\n",
"graph.add_edge('a', 'b', weight=5)\n",
"graph.add_edge('a', 'c', weight=3)\n",
"graph.add_edge('a', 'e', weight=2)\n",
"graph.add_edge('b', 'd', weight=2)\n",
"graph.add_edge('c', 'b', weight=1)\n",
"graph.add_edge('c', 'd', weight=1)\n",
"graph.add_edge('d', 'a', weight=1)\n",
"graph.add_edge('d', 'g', weight=2)\n",
"graph.add_edge('d', 'h', weight=1)\n",
"graph.add_edge('e', 'a', weight=1)\n",
"graph.add_edge('e', 'h', weight=4)\n",
"graph.add_edge('e', 'i', weight=7)\n",
"graph.add_edge('f', 'b', weight=3)\n",
"graph.add_edge('f', 'g', weight=1)\n",
"graph.add_edge('g', 'c', weight=3)\n",
"graph.add_edge('g', 'i', weight=2)\n",
"graph.add_edge('h', 'c', weight=2)\n",
"graph.add_edge('h', 'f', weight=2)\n",
"graph.add_edge('h', 'g', weight=2)\n",
"shortest_path = ShortestPath(graph)\n",
"result = shortest_path.find_shortest_path('a', 'i')\n",
"self.assertEqual(result, ['a', 'c', 'd', 'g', 'i'])\n",
"self.assertEqual(shortest_path.path_weight['i'], 8)\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Algorithm\n",
"\n",
"Refer to the [Solution Notebook](http://nbviewer.jupyter.org/github/donnemartin/interactive-coding-challenges/blob/master/graphs_trees/graph_shortest_path/graph_shortest_path_solution.ipynb). If you are stuck and need a hint, the solution notebook's algorithm discussion might be a good place to start."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Code"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%run ../../arrays_strings/priority_queue/priority_queue.py\n",
"%load ../../arrays_strings/priority_queue/priority_queue.py"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%run ../graph/graph.py\n",
"%load ../graph/graph.py"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"class ShortestPath(object):\n",
"\n",
" def __init__(self, graph):\n",
" # TODO: Implement me\n",
" pass\n",
"\n",
" def find_shortest_path(self, start_node_key, end_node_key):\n",
" # TODO: Implement me\n",
" pass"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Unit Test"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**The following unit test is expected to fail until you solve the challenge.**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# %load test_shortest_path.py\n",
"import unittest\n",
"\n",
"\n",
"class TestShortestPath(unittest.TestCase):\n",
"\n",
" def test_shortest_path(self):\n",
" graph = Graph()\n",
" graph.add_edge('a', 'b', weight=5)\n",
" graph.add_edge('a', 'c', weight=3)\n",
" graph.add_edge('a', 'e', weight=2)\n",
" graph.add_edge('b', 'd', weight=2)\n",
" graph.add_edge('c', 'b', weight=1)\n",
" graph.add_edge('c', 'd', weight=1)\n",
" graph.add_edge('d', 'a', weight=1)\n",
" graph.add_edge('d', 'g', weight=2)\n",
" graph.add_edge('d', 'h', weight=1)\n",
" graph.add_edge('e', 'a', weight=1)\n",
" graph.add_edge('e', 'h', weight=4)\n",
" graph.add_edge('e', 'i', weight=7)\n",
" graph.add_edge('f', 'b', weight=3)\n",
" graph.add_edge('f', 'g', weight=1)\n",
" graph.add_edge('g', 'c', weight=3)\n",
" graph.add_edge('g', 'i', weight=2)\n",
" graph.add_edge('h', 'c', weight=2)\n",
" graph.add_edge('h', 'f', weight=2)\n",
" graph.add_edge('h', 'g', weight=2)\n",
" shortest_path = ShortestPath(graph)\n",
" result = shortest_path.find_shortest_path('a', 'i')\n",
" self.assertEqual(result, ['a', 'c', 'd', 'g', 'i'])\n",
" self.assertEqual(shortest_path.path_weight['i'], 8)\n",
"\n",
" print('Success: test_shortest_path')\n",
"\n",
"\n",
"def main():\n",
" test = TestShortestPath()\n",
" test.test_shortest_path()\n",
"\n",
"\n",
"if __name__ == '__main__':\n",
" main()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Solution Notebook\n",
"\n",
"Review the [Solution Notebook](https://github.com/donnemartin/interactive-coding-challenges/graphs_trees/graph_shortest_path/graph_shortest_path_solution.ipynb) for a discussion on algorithms and code solutions."
]
}
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