{ "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: Implement n stacks using a single array.\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", "* Are the stacks and array a fixed size?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "* Test the following on the three stacks:\n", " * Push to full stack -> Exception\n", " * Push to non-full stack\n", " * Pop on empty stack -> Exception\n", " * Pop on non-empty 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/n_stacks/n_stacks_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": [ "class Stacks(object):\n", "\n", " def __init__(self, num_stacks, stack_size):\n", " # TODO: Implement me\n", " pass\n", "\n", " def abs_index(self, stack_index):\n", " # TODO: Implement me\n", " pass\n", "\n", " def push(self, stack_index, data):\n", " # TODO: Implement me\n", " pass\n", "\n", " def pop(self, stack_index):\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": { "collapsed": false }, "outputs": [], "source": [ "# %load test_n_stacks.py\n", "from nose.tools import assert_equal\n", "from nose.tools import raises\n", "\n", "\n", "class TestStacks(object):\n", "\n", " @raises(Exception)\n", " def test_pop_on_empty(self, num_stacks, stack_size):\n", " print('Test: Pop on empty stack')\n", " stacks = Stacks(num_stacks, stack_size)\n", " stacks.pop(0)\n", "\n", " @raises(Exception)\n", " def test_push_on_full(self, num_stacks, stack_size):\n", " print('Test: Push to full stack')\n", " stacks = Stacks(num_stacks, stack_size)\n", " for i in range(0, stack_size):\n", " stacks.push(2, i)\n", " stacks.push(2, stack_size)\n", "\n", " def test_stacks(self, num_stacks, stack_size):\n", " print('Test: Push to non-full stack')\n", " stacks = Stacks(num_stacks, stack_size)\n", " stacks.push(0, 1)\n", " stacks.push(0, 2)\n", " stacks.push(1, 3)\n", " stacks.push(2, 4)\n", "\n", " print('Test: Pop on non-empty stack')\n", " assert_equal(stacks.pop(0), 2)\n", " assert_equal(stacks.pop(0), 1)\n", " assert_equal(stacks.pop(1), 3)\n", " assert_equal(stacks.pop(2), 4)\n", "\n", " print('Success: test_stacks\\n')\n", "\n", "\n", "def main():\n", " num_stacks = 3\n", " stack_size = 100\n", " test = TestStacks()\n", " test.test_pop_on_empty(num_stacks, stack_size)\n", " test.test_push_on_full(num_stacks, stack_size)\n", " test.test_stacks(num_stacks, stack_size)\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/n_stacks/n_stacks_solution.ipynb) for a discussion on algorithms and code solutions." ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.10" } }, "nbformat": 4, "nbformat_minor": 0 }