{ "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: Return all subsets of a set.\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", "* Should the resulting subsets be unique?\n", " * Yes, treat 'ab' and 'bc' as the same\n", "* Is the empty set included as a subset?\n", " * Yes\n", "* Are the inputs unique?\n", " * No\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", "
```\n",
"* None -> None\n",
"* [] -> [[]]\n",
"* ['a'] -> [[], \n",
"            ['a']]\n",
"* ['a', 'b'] -> [[], \n",
"                 ['a'], \n",
"                 ['b'], \n",
"                 ['a', 'b']]\n",
"* ['a', 'b', 'c'] -> [[], \n",
"                      ['a'], \n",
"                      ['b'], \n",
"                      ['c'],\n",
"                      ['a', 'b'], \n",
"                      ['a', 'c'], \n",
"                      ['b', 'c'],\n",
"                      ['a', 'b', 'c']]\n",
"```
" ] }, { "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 Sets(object):\n", "\n", " def find_power_set_recursive(self, input_set):\n", " # TODO: Implement me\n", " pass\n", "\n", " def find_power_set_iterative(self, input_set):\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_power_set.py\n", "import unittest\n", "\n", "\n", "class TestPowerSet(unittest.TestCase):\n", "\n", " def test_power_set(self):\n", " input_set = []\n", " expected = [[]]\n", " self.run_test(input_set, expected)\n", " input_set = ['a']\n", " expected = [['a'], []]\n", " self.run_test(input_set, expected)\n", " input_set = ['a', 'b']\n", " expected = [['a'], ['a', 'b'], ['b'], []]\n", " self.run_test(input_set, expected)\n", " input_set = ['a', 'b', 'c']\n", " expected = [['a'], ['a', 'b'], ['b'], ['a', 'c'], \n", " ['a', 'b', 'c'], ['b', 'c'], ['c'], []]\n", " self.run_test(input_set, expected)\n", " print('Success: test_power_set')\n", "\n", " def run_test(self, input_set, expected):\n", " combinatoric = Combinatoric()\n", " result = combinatoric.find_power_set_recursive(input_set)\n", " self.assertEqual(result, expected)\n", " result = combinatoric.find_power_set_iterative(input_set)\n", " self.assertEqual(result, expected)\n", "\n", "\n", "def main():\n", " test = TestPowerSet()\n", " test.test_power_set()\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 }