{ "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: Given an array, find the two indices that sum to a specific value.\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 there exactly one solution?\n", " * Yes\n", "* Is there always a solution?\n", " * Yes\n", "* Is the array an array of ints?\n", " * Yes\n", "* Is the array sorted?\n", " No\n", "* Are negative values possible?\n", " * Yes\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 input -> TypeError\n", "* [] -> ValueError\n", "* [1, 3, 2, -7, 5], 7 -> [2, 4]" ] }, { "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": { "collapsed": false }, "outputs": [], "source": [ "class Solution(object):\n", "\n", " def two_sum(self, nums, val):\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": { "collapsed": false }, "outputs": [], "source": [ "# %load test_two_sum.py\n", "from nose.tools import assert_equal, assert_raises\n", "\n", "\n", "class TestTwoSum(object):\n", "\n", " def test_two_sum(self):\n", " solution = Solution()\n", " assert_raises(TypeError, solution.two_sum, None)\n", " assert_equal(solution.two_sum(0), 0)\n", " print('Success: test_two_sum')\n", "\n", "\n", "def main():\n", " test = TestTwoSum()\n", " test.test_two_sum()\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": "3.5.0" } }, "nbformat": 4, "nbformat_minor": 0 }