{ "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: Sort a stack. You can use another stack as a buffer.\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", "* When sorted, should the largest element be at the top or bottom?\n", " * Top\n", "* Can you have duplicate values like 5, 5?\n", " * Yes\n", "* Can we assume we already have a stack class that can be used for this problem?\n", " * Yes\n", "* Can we assume this fits memory?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "* Empty stack -> None\n", "* One element stack\n", "* Two or more element stack (general case)\n", "* Already sorted stack" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithm\n", "\n", "Refer to the [Solution Notebook](http://nbviewer.ipython.org/github/donnemartin/interactive-coding-challenges/blob/master/stacks_queues/sort_stack/sort_stack_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 ../stack/stack.py\n", "%load ../stack/stack.py" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "class MyStack(Stack):\n", "\n", " def sort(self):\n", " # TODO: Implement me\n", " pass" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Unit Test\n", "\n", "\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_sort_stack.py\n", "from random import randint\n", "import unittest\n", "\n", "\n", "class TestSortStack(unittest.TestCase):\n", "\n", " def get_sorted_stack(self, stack, numbers):\n", " for x in numbers:\n", " stack.push(x)\n", " sorted_stack = stack.sort()\n", " return sorted_stack\n", "\n", " def test_sort_stack(self, stack):\n", " print('Test: Empty stack')\n", " sorted_stack = self.get_sorted_stack(stack, [])\n", " self.assertEqual(sorted_stack.pop(), None)\n", "\n", " print('Test: One element stack')\n", " sorted_stack = self.get_sorted_stack(stack, [1])\n", " self.assertEqual(sorted_stack.pop(), 1)\n", "\n", " print('Test: Two or more element stack (general case)')\n", " num_items = 10\n", " numbers = [randint(0, 10) for x in range(num_items)]\n", " sorted_stack = self.get_sorted_stack(stack, numbers)\n", " sorted_numbers = []\n", " for _ in range(num_items):\n", " sorted_numbers.append(sorted_stack.pop())\n", " self.assertEqual(sorted_numbers, sorted(numbers, reverse=True))\n", "\n", " print('Success: test_sort_stack')\n", "\n", "\n", "def main():\n", " test = TestSortStack()\n", " test.test_sort_stack(MyStack())\n", " try:\n", " test.test_sort_stack(MyStackSimplified())\n", " except NameError:\n", " # Alternate solutions are only defined\n", " # in the solutions file\n", " pass\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/stacks_queues/sort_stack/sort_stack_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 }