{
 "nbformat": 3, 
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 "worksheets": [
  {
   "cells": [
    {
     "source": [
      "> This is one of the 100 recipes of the [IPython Cookbook](http://ipython-books.github.io/), the definitive guide to high-performance scientific computing and data science in Python.\n"
     ], 
     "cell_type": "markdown", 
     "metadata": []
    }, 
    {
     "source": [
      "# 4.1. Evaluating the time taken by a statement in IPython"
     ], 
     "cell_type": "markdown", 
     "metadata": {}
    }, 
    {
     "cell_type": "code", 
     "language": "python", 
     "outputs": [], 
     "collapsed": false, 
     "input": [
      "n = 100000"
     ], 
     "metadata": {}
    }, 
    {
     "cell_type": "code", 
     "language": "python", 
     "outputs": [], 
     "collapsed": false, 
     "input": [
      "%timeit sum([1. / i**2 for i in range(1, n)])"
     ], 
     "metadata": {}
    }, 
    {
     "cell_type": "code", 
     "language": "python", 
     "outputs": [], 
     "collapsed": false, 
     "input": [
      "%%timeit s = 0.\n", 
      "for i in range(1, n):\n", 
      "    s += 1. / i**2"
     ], 
     "metadata": {}
    }, 
    {
     "cell_type": "code", 
     "language": "python", 
     "outputs": [], 
     "collapsed": false, 
     "input": [
      "import numpy as np"
     ], 
     "metadata": {}
    }, 
    {
     "cell_type": "code", 
     "language": "python", 
     "outputs": [], 
     "collapsed": false, 
     "input": [
      "%timeit np.sum(1. / np.arange(1., n) ** 2)"
     ], 
     "metadata": {}
    }, 
    {
     "source": [
      "> You'll find all the explanations, figures, references, and much more in the book (to be released later this summer).\n\n> [IPython Cookbook](http://ipython-books.github.io/), by [Cyrille Rossant](http://cyrille.rossant.net), Packt Publishing, 2014 (500 pages)."
     ], 
     "cell_type": "markdown", 
     "metadata": {}
    }
   ], 
   "metadata": {}
  }
 ], 
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