{ "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: You are running up n steps. If you can take a single, double, or triple step, how many possible ways are there to run up to the nth step?\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", "* If n == 0, what should the result be?\n", " * Go with 1, but discuss different approaches\n", "* Can we assume the inputs are valid?\n", " * No\n", "* Can we assume this fits memory?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "* None or negative input -> Exception\n", "* n == 0 -> 1\n", "* n == 1 -> 1\n", "* n == 2 -> 2\n", "* n == 3 -> 4\n", "* n == 4 -> 7\n", "* n == 10 -> 274" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithm\n", "\n", "Refer to the [Solution Notebook](). 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": [ "class Steps(object):\n", "\n", " def count_ways(self, num_steps):\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_steps.py\n", "import unittest\n", "\n", "\n", "class TestSteps(unittest.TestCase):\n", "\n", " def test_steps(self):\n", " steps = Steps()\n", " self.assertRaises(TypeError, steps.count_ways, None)\n", " self.assertRaises(TypeError, steps.count_ways, -1)\n", " self.assertEqual(steps.count_ways(0), 1)\n", " self.assertEqual(steps.count_ways(1), 1)\n", " self.assertEqual(steps.count_ways(2), 2)\n", " self.assertEqual(steps.count_ways(3), 4)\n", " self.assertEqual(steps.count_ways(4), 7)\n", " self.assertEqual(steps.count_ways(10), 274)\n", " print('Success: test_steps')\n", "\n", "\n", "def main():\n", " test = TestSteps()\n", " test.test_steps()\n", "\n", "\n", "if __name__ == '__main__':\n", " main()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Solution Notebook\n", "\n", "Review the [Solution Notebook]() 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 }