{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook was prepared by [Donne Martin](http://donnemartin.com). 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: Remove duplicates from a linked list.\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", "* Can we assume this is a non-circular, singly linked list?\n", " * Yes\n", "* Can you insert None values in the list?\n", " * No\n", "* Can we assume we already have a linked list class that can be used for this problem?\n", " * Yes\n", "* Can we use additional data structures?\n", " * Implement both solutions\n", "* Can we assume this fits in memory?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "* Empty linked list -> []\n", "* One element linked list -> [element]\n", "* General case with no duplicates\n", "* General case with duplicates" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithm\n", "\n", "Refer to the [Solution Notebook](http://nbviewer.ipython.org/github/donnemartin/interactive-coding-challenges/blob/master/linked_lists/remove_duplicates/remove_duplicates_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 ../linked_list/linked_list.py\n", "%load ../linked_list/linked_list.py" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "class MyLinkedList(LinkedList):\n", "\n", " def remove_dupes(self):\n", " # TODO: Implement me\n", " pass" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Unit Test" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "**The following unit test is expected to fail until you solve the challenge.**" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# %load test_remove_duplicates.py\n", "import unittest\n", "\n", "\n", "class TestRemoveDupes(unittest.TestCase):\n", "\n", " def test_remove_dupes(self, linked_list):\n", " print('Test: Empty list')\n", " linked_list.remove_dupes()\n", " self.assertEqual(linked_list.get_all_data(), [])\n", "\n", " print('Test: One element list')\n", " linked_list.insert_to_front(2)\n", " linked_list.remove_dupes()\n", " self.assertEqual(linked_list.get_all_data(), [2])\n", "\n", " print('Test: General case, duplicates')\n", " linked_list.insert_to_front(1)\n", " linked_list.insert_to_front(1)\n", " linked_list.insert_to_front(3)\n", " linked_list.insert_to_front(2)\n", " linked_list.insert_to_front(3)\n", " linked_list.insert_to_front(1)\n", " linked_list.insert_to_front(1)\n", " linked_list.remove_dupes()\n", " self.assertEqual(linked_list.get_all_data(), [1, 3, 2])\n", "\n", " print('Test: General case, no duplicates')\n", " linked_list.remove_dupes()\n", " self.assertEqual(linked_list.get_all_data(), [1, 3, 2])\n", "\n", " print('Success: test_remove_dupes\\n')\n", "\n", "\n", "def main():\n", " test = TestRemoveDupes()\n", " linked_list = MyLinkedList(None)\n", " test.test_remove_dupes(linked_list)\n", "\n", "\n", "if __name__ == '__main__':\n", " main()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Solution Notebook\n", "\n", "Review the [Solution Notebook](http://nbviewer.ipython.org/github/donnemartin/interactive-coding-challenges/blob/master/linked_lists/remove_duplicates/remove_duplicates_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 }