interactive-coding-challenges/arrays_strings/group_items/group_ordered_solution.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<small><i>This notebook was prepared by [wdonahoe](https://github.com/wdonahoe). Source and license info is on [GitHub](https://github.com/donnemartin/interactive-coding-challenges).</i></small>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Solution Notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Problem: Implement a function that groups identical items based on their order in the list.\n",
    "\n",
    "* [Constraints](#Constraints)\n",
    "* [Test Cases](#Test-Cases)\n",
    "* [Algorithm: Modified Selection Sort](#Algorithm: Modified Selection Sort)\n",
    "* [Code: Modified Selection Sort](#Code: Modified Selection Sort)\n",
    "* [Algorithm: Ordered Dict](#Algorithm: Ordered Dict)\n",
    "* [Code: Ordered Dict](#Code:-Ordered-Dict)\n",
    "* [Unit Test](#Unit-Test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Constraints\n",
    "\n",
    "* Can we use extra data structures?\n",
    "    * Yes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Cases\n",
    "\n",
    "* group_ordered([1,2,1,3,2]) -> [1,1,2,2,3]\n",
    "* group_ordered(['a','b','a') -> ['a','a','b']\n",
    "* group_ordered([1,1,2,3,4,5,2,1]-> [1,1,1,2,2,3,4,5]\n",
    "* group_ordered([]) -> []\n",
    "* group_ordered([1]) -> [1]\n",
    "* group_ordered(None) -> None\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algorithm: Modified Selection Sort\n",
    "\n",
    "* Save the relative position of the first-occurence of each item in a list.\n",
    "* Iterate through list of unique items.\n",
    "    * Keep an outer index; scan rest of list, swapping matching items with outer index and incrementing outer index each time. \n",
    "    \n",
    "Complexity:\n",
    "* Time: O(n^2)\n",
    "* Space: O(n)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Code: Modified Selection Sort"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def make_order_list(list_in):\n",
    "    order_list = []\n",
    "    for item in list_in:\n",
    "        if item not in order_list:\n",
    "            order_list.append(item)\n",
    "    return order_list\n",
    "\n",
    "\n",
    "def group_ordered(list_in):\n",
    "    if list_in is None:\n",
    "        return None\n",
    "    order_list = make_order_list(list_in)\n",
    "    current = 0\n",
    "    for item in order_list:\n",
    "        search = current + 1\n",
    "        while True:\n",
    "            try:\n",
    "                if list_in[search] != item:\n",
    "                    search += 1\n",
    "                else:\n",
    "                    current += 1\n",
    "                    list_in[current], list_in[search] = list_in[search], list_in[current]\n",
    "                    search += 1\n",
    "            except IndexError:\n",
    "                break\n",
    "    return list_in"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algorithm: Ordered Dict.\n",
    "\n",
    "* Use an ordered dict to track insertion order of each key\n",
    "* Flatten list of values.\n",
    "\n",
    "Complexity:\n",
    "\n",
    "* Time: O(n)\n",
    "* Space: O(n)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Code: Ordered Dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from collections import OrderedDict\n",
    "\n",
    "def group_ordered(list_in):\n",
    "    result = OrderedDict()\n",
    "    for value in list_in:\n",
    "        result.setdefault(value, []).append(value)\n",
    "    return [v for group in result.values() for v in group]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unit Test\n",
    "\n",
    "#### The following unit test is expected to fail until you solve the challenge."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting test_group_ordered.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile test_group_ordered.py\n",
    "from nose.tools import assert_equal\n",
    "\n",
    "class TestGroupOrdered(object):\n",
    "\n",
    "    def test_group_ordered(self):\n",
    "        assert_equal(group_ordered(None), None)\n",
    "        assert_equal(group_ordered([]), [])\n",
    "        assert_equal(group_ordered([1]), [1])\n",
    "        assert_equal(group_ordered([1,2,1,3,2]),[1,1,2,2,3])\n",
    "        assert_equal(group_ordered(['a','b','a']),['a','a','b'])\n",
    "        assert_equal(group_ordered([1,1,2,3,4,5,2,1]),[1,1,1,2,2,3,4,5])\n",
    "        assert_equal(group_ordered([1,2,3,4,3,4]),[1,2,3,3,4,4])\n",
    "\n",
    "def main():\n",
    "    test = TestGroupOrdered()\n",
    "    test.test_group_ordered()\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    main()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%run -i test_group_ordered.py"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Edit 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": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}