{ "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: Implement 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 the graph directed?\n", " * Implement both\n", "* Do the edges have weights?\n", " * Yes\n", "* Can the graph have cycles?\n", " * Yes\n", "* If we try to add a node that already exists, do we just do nothing?\n", " * Yes\n", "* If we try to delete a node that doesn't exist, do we just do nothing?\n", " * Yes\n", "* Can we assume this is a connected graph?\n", " * Yes\n", "* Can we assume the inputs are valid?\n", " * Yes\n", "* Can we assume this fits memory?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "Input:\n", "* `add_edge(source, destination, weight)`\n", "\n", "```\n", "graph.add_edge(0, 1, 5)\n", "graph.add_edge(0, 5, 2)\n", "graph.add_edge(1, 2, 3)\n", "graph.add_edge(2, 3, 4)\n", "graph.add_edge(3, 4, 5)\n", "graph.add_edge(3, 5, 6)\n", "graph.add_edge(4, 0, 7)\n", "graph.add_edge(5, 4, 8)\n", "graph.add_edge(5, 2, 9)\n", "```\n", "\n", "Result:\n", "* `source` and `destination` nodes within `graph` are connected with specified `weight`.\n", "\n", "Note: \n", "* The Graph class will be used as a building block for more complex graph challenges." ] }, { "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/graph_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": {}, "outputs": [], "source": [ "from enum import Enum # Python 2 users: Run pip install enum34\n", "\n", "\n", "class State(Enum):\n", "\n", " unvisited = 0\n", " visiting = 1\n", " visited = 2\n", "\n", "\n", "class Node:\n", "\n", " def __init__(self, key):\n", " self.key = key\n", " self.visit_state = State.unvisited\n", " self.incoming_edges = 0\n", " self.adj_nodes = {} # Key = key, val = Node\n", " self.adj_weights = {} # Key = key, val = weight\n", "\n", " def __repr__(self):\n", " return str(self.key)\n", "\n", " def __lt__(self, other):\n", " return self.key < other.key\n", "\n", " def add_neighbor(self, neighbor, weight=0):\n", " # TODO: Implement me\n", " pass\n", "\n", " def remove_neighbor(self, neighbor):\n", " # TODO: Implement me\n", " pass\n", "\n", "\n", "class Graph:\n", "\n", " def __init__(self):\n", " self.nodes = {} # Key = key, val = Node\n", "\n", " def add_node(self, id):\n", " # TODO: Implement me\n", " pass\n", "\n", " def add_edge(self, source, dest, weight=0):\n", " # TODO: Implement me\n", " pass\n", "\n", " def add_undirected_edge(self, source, dest, weight=0):\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_graph.py\n", "import unittest\n", "\n", "\n", "class TestGraph(unittest.TestCase):\n", "\n", " def create_graph(self):\n", " graph = Graph()\n", " for key in range(0, 6):\n", " graph.add_node(key)\n", " return graph\n", "\n", " def test_graph(self):\n", " graph = self.create_graph()\n", " graph.add_edge(0, 1, weight=5)\n", " graph.add_edge(0, 5, weight=2)\n", " graph.add_edge(1, 2, weight=3)\n", " graph.add_edge(2, 3, weight=4)\n", " graph.add_edge(3, 4, weight=5)\n", " graph.add_edge(3, 5, weight=6)\n", " graph.add_edge(4, 0, weight=7)\n", " graph.add_edge(5, 4, weight=8)\n", " graph.add_edge(5, 2, weight=9)\n", "\n", " self.assertEqual(graph.nodes[0].adj_weights[graph.nodes[1].key], 5)\n", " self.assertEqual(graph.nodes[0].adj_weights[graph.nodes[5].key], 2)\n", " self.assertEqual(graph.nodes[1].adj_weights[graph.nodes[2].key], 3)\n", " self.assertEqual(graph.nodes[2].adj_weights[graph.nodes[3].key], 4)\n", " self.assertEqual(graph.nodes[3].adj_weights[graph.nodes[4].key], 5)\n", " self.assertEqual(graph.nodes[3].adj_weights[graph.nodes[5].key], 6)\n", " self.assertEqual(graph.nodes[4].adj_weights[graph.nodes[0].key], 7)\n", " self.assertEqual(graph.nodes[5].adj_weights[graph.nodes[4].key], 8)\n", " self.assertEqual(graph.nodes[5].adj_weights[graph.nodes[2].key], 9)\n", "\n", " self.assertEqual(graph.nodes[0].incoming_edges, 1)\n", " self.assertEqual(graph.nodes[1].incoming_edges, 1)\n", " self.assertEqual(graph.nodes[2].incoming_edges, 2)\n", " self.assertEqual(graph.nodes[3].incoming_edges, 1)\n", " self.assertEqual(graph.nodes[4].incoming_edges, 2)\n", " self.assertEqual(graph.nodes[5].incoming_edges, 2)\n", "\n", " graph.nodes[0].remove_neighbor(graph.nodes[1])\n", " self.assertEqual(graph.nodes[1].incoming_edges, 0)\n", " graph.nodes[3].remove_neighbor(graph.nodes[4])\n", " self.assertEqual(graph.nodes[4].incoming_edges, 1)\n", "\n", " self.assertEqual(graph.nodes[0] < graph.nodes[1], True)\n", "\n", " print('Success: test_graph')\n", "\n", " def test_graph_undirected(self):\n", " graph = self.create_graph()\n", " graph.add_undirected_edge(0, 1, weight=5)\n", " graph.add_undirected_edge(0, 5, weight=2)\n", " graph.add_undirected_edge(1, 2, weight=3)\n", "\n", " self.assertEqual(graph.nodes[0].adj_weights[graph.nodes[1].key], 5)\n", " self.assertEqual(graph.nodes[1].adj_weights[graph.nodes[0].key], 5)\n", " self.assertEqual(graph.nodes[0].adj_weights[graph.nodes[5].key], 2)\n", " self.assertEqual(graph.nodes[5].adj_weights[graph.nodes[0].key], 2)\n", " self.assertEqual(graph.nodes[1].adj_weights[graph.nodes[2].key], 3)\n", " self.assertEqual(graph.nodes[2].adj_weights[graph.nodes[1].key], 3)\n", "\n", " print('Success: test_graph_undirected')\n", "\n", "\n", "def main():\n", " test = TestGraph()\n", " test.test_graph()\n", " test.test_graph_undirected()\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/graphs/graph_solution.ipynb) for a discussion on algorithms and code solutions." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.2" } }, "nbformat": 4, "nbformat_minor": 1 }