44-Iterators and Generators Homework - Solution.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#Iterators and Generators Homework - Solution\n",
    "\n",
    "###Problem 1\n",
    "\n",
    "Create a generator that generates the squares of numbers up to some number N."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def gensquares(N):\n",
    "    for i in range(N):\n",
    "        yield i ** 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "4\n",
      "9\n",
      "16\n",
      "25\n",
      "36\n",
      "49\n",
      "64\n",
      "81\n"
     ]
    }
   ],
   "source": [
    "for x in gensquares(10):\n",
    "    print x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Problem 2\n",
    "\n",
    "Create a generator that yields \"n\" random numbers between a low and high number (that are inputs). Note: Use the random library. For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import random\n",
    "\n",
    "random.randint(1,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def rand_num(low,high,n):\n",
    "    \n",
    "    for i in range(n):\n",
    "        yield random.randint(low, high)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6\n",
      "7\n",
      "6\n",
      "9\n",
      "9\n",
      "4\n",
      "3\n",
      "7\n",
      "8\n",
      "1\n",
      "6\n",
      "1\n"
     ]
    }
   ],
   "source": [
    "for num in rand_num(1,10,12):\n",
    "    print num"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Problem 3\n",
    "\n",
    "Use the iter() function to convert the string below \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "h\n"
     ]
    }
   ],
   "source": [
    "s = 'hello'\n",
    "\n",
    "s = iter(s)\n",
    "\n",
    "print next(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Problem 4\n",
    "Explain a use case for a generator using a yield statement where you would not want to use a normal function with a return statement.\n",
    "\n",
    "**If the output has the potential of taking up a large amount of memory and you only intend to iterate through it, you would want to use a generator. (Multiple answers are acceptable here!)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extra Credit!\n",
    "Can you explain what bonus is in the code below? (Note: We never covered this in lecture!)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n",
      "5\n"
     ]
    }
   ],
   "source": [
    "my_list = [1,2,3,4,5]\n",
    "\n",
    "gencomp = (item for item in my_list if item > 3)\n",
    "\n",
    "for item in gencomp:\n",
    "    print item"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hint google: generator comprehension is!\n",
    "\n",
    "#Great Job!"
   ]
  }
 ],
 "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": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}