mirror of
https://github.com/donnemartin/interactive-coding-challenges.git
synced 2024-03-22 13:11:13 +08:00
203 lines
5.0 KiB
Python
203 lines
5.0 KiB
Python
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"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)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Challenge Notebook"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Problem: Return all subsets of a set.\n",
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"\n",
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"* [Constraints](#Constraints)\n",
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"* [Test Cases](#Test-Cases)\n",
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"* [Algorithm](#Algorithm)\n",
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"* [Code](#Code)\n",
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"* [Unit Test](#Unit-Test)\n",
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"* [Solution Notebook](#Solution-Notebook)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Constraints\n",
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"\n",
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"* Should the resulting subsets be unique?\n",
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" * Yes, treat 'ab' and 'bc' as the same\n",
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"* Is the empty set included as a subset?\n",
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" * Yes\n",
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"* Are the inputs unique?\n",
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" * No\n",
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"* Can we assume the inputs are valid?\n",
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" * No\n",
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"* Can we assume this fits memory?\n",
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" * Yes"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Test Cases\n",
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"\n",
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"<pre>\n",
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"* None -> None\n",
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"* [] -> [[]]\n",
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"* ['a'] -> [[], \n",
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" ['a']]\n",
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"* ['a', 'b'] -> [[], \n",
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" ['a'], \n",
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" ['b'], \n",
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" ['a', 'b']]\n",
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"* ['a', 'b', 'c'] -> [[], \n",
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" ['a'], \n",
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" ['b'], \n",
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" ['c'],\n",
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" ['a', 'b'], \n",
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" ['a', 'c'], \n",
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" ['b', 'c'],\n",
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" ['a', 'b', 'c']]\n",
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"</pre>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Algorithm\n",
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"\n",
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"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."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Code"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"class Sets(object):\n",
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"\n",
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" def find_power_set_recursive(self, input_set):\n",
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" # TODO: Implement me\n",
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" pass\n",
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"\n",
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" def find_power_set_iterative(self, input_set):\n",
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" # TODO: Implement me\n",
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" pass"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Unit Test"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**The following unit test is expected to fail until you solve the challenge.**"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"# %load test_power_set.py\n",
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"from nose.tools import assert_equal\n",
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"\n",
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"\n",
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"class TestPowerSet(object):\n",
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"\n",
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" def test_power_set(self):\n",
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" input_set = []\n",
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" expected = [[]]\n",
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" self.run_test(input_set, expected)\n",
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" input_set = ['a']\n",
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" expected = [['a'], []]\n",
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" self.run_test(input_set, expected)\n",
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" input_set = ['a', 'b']\n",
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" expected = [['a'], ['a', 'b'], ['b'], []]\n",
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" self.run_test(input_set, expected)\n",
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" input_set = ['a', 'b', 'c']\n",
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" expected = [['a'], ['a', 'b'], ['b'], ['a', 'c'], \n",
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" ['a', 'b', 'c'], ['b', 'c'], ['c'], []]\n",
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" self.run_test(input_set, expected)\n",
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" print('Success: test_power_set')\n",
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"\n",
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" def run_test(self, input_set, expected):\n",
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" combinatoric = Combinatoric()\n",
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" result = combinatoric.find_power_set_recursive(input_set)\n",
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" assert_equal(result, expected)\n",
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" result = combinatoric.find_power_set_iterative(input_set)\n",
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" assert_equal(result, expected)\n",
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"\n",
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"\n",
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"def main():\n",
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" test = TestPowerSet()\n",
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" test.test_power_set()\n",
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"\n",
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"\n",
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"if __name__ == '__main__':\n",
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" main()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Solution Notebook\n",
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"\n",
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"Review the [Solution Notebook]() for a discussion on algorithms and code solutions."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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