examples/notebooks/Part 1 - Running Code.ipynb

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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Running Code in the IPython Notebook"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "First and foremost, the IPython Notebook is an interactive environment for writing and running Python code."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Code cells allow you to enter and run Python code"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Run a code cell using `Shift-Enter` or pressing the \"Play\" button in the toolbar above:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a = 10"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print(a)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10\n"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Managing the IPython Kernel"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Code is run in a separate process called the IPython Kernel.  The Kernel can be interrupted or restarted.  Try running the following cell and then hit the \"Stop\" button in the toolbar above."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import time\n",
      "time.sleep(10)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "KeyboardInterrupt",
       "evalue": "",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-16-d7b436e260d5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "If the Kernel dies you will be prompted to restart it. Here we call the low-level system libc.time routine with the wrong argument via\n",
      "ctypes to segfault the Python interpreter:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import sys\n",
      "from ctypes import CDLL\n",
      "# This will crash a Linux or Mac system; equivalent calls can be made on Windows\n",
      "dll = 'dylib' if sys.platform == 'darwin' else 'so.6'\n",
      "libc = CDLL(\"libc.%s\" % dll) \n",
      "libc.time(-1)  # BOOM!!"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "All of the goodness of IPython works"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here are two system aliases:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pwd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "u'/Users/bgranger/Documents/Computation/IPython/code/ipython/examples/notebooks'"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ls"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "01_notebook_introduction.ipynb        Octave Magic.ipynb\r\n",
        "Animations Using clear_output.ipynb   PyLab and Matplotlib.ipynb\r\n",
        "Basic Output.ipynb                    R Magics.ipynb\r\n",
        "Custom Display Logic.ipynb            Running Code.ipynb\r\n",
        "Cython Magics.ipynb                   Script Magics.ipynb\r\n",
        "Data Publication API.ipynb            SymPy Examples.ipynb\r\n",
        "Display System.ipynb                  Trapezoid Rule.ipynb\r\n",
        "JS Progress Bar.ipynb                 Typesetting Math Using MathJax.ipynb\r\n",
        "Local Files.ipynb                     animation.m4v\r\n",
        "Markdown Cells.ipynb                  python-logo.svg\r\n",
        "Notebook Tour.ipynb\r\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Any command line program can be run using `!` with string interpolation from Python variables:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "message = 'The IPython notebook is great!'\n",
      "# note: the echo command does not run on Windows, it's a unix command.\n",
      "!echo $message"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Tab completion works:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy\n",
      "numpy.random."
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Shift-Tab on selection, or after `(` brings up a tooltip with the docstring:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "numpy.random.rand("
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Adding `?` opens the docstring in the pager below:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "magic?"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Exceptions are formatted nicely:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = 1\n",
      "y = 4\n",
      "z = y/(1-x)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "ZeroDivisionError",
       "evalue": "integer division or modulo by zero",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-15-dc39888fd1d2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mz\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;31mZeroDivisionError\u001b[0m: integer division or modulo by zero"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Working with external code"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There are a number of ways of getting external code into code cells."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Pasting code with `>>>` prompts works as expected:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      ">>> the_world_is_flat = 1\n",
      ">>> if the_world_is_flat:\n",
      "...     print(\"Be careful not to fall off!\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Be careful not to fall off!\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The `%load` magic lets you load code from URLs or local files:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%load?"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%load http://matplotlib.org/mpl_examples/showcase/integral_demo.py"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\"\"\"\n",
      "Plot demonstrating the integral as the area under a curve.\n",
      "\n",
      "Although this is a simple example, it demonstrates some important tweaks:\n",
      "\n",
      "    * A simple line plot with custom color and line width.\n",
      "    * A shaded region created using a Polygon patch.\n",
      "    * A text label with mathtext rendering.\n",
      "    * figtext calls to label the x- and y-axes.\n",
      "    * Use of axis spines to hide the top and right spines.\n",
      "    * Custom tick placement and labels.\n",
      "\"\"\"\n",
      "import numpy as np\n",
      "import matplotlib.pyplot as plt\n",
      "from matplotlib.patches import Polygon\n",
      "\n",
      "\n",
      "def func(x):\n",
      "    return (x - 3) * (x - 5) * (x - 7) + 85\n",
      "\n",
      "\n",
      "a, b = 2, 9 # integral limits\n",
      "x = np.linspace(0, 10)\n",
      "y = func(x)\n",
      "\n",
      "fig, ax = plt.subplots()\n",
      "plt.plot(x, y, 'r', linewidth=2)\n",
      "plt.ylim(ymin=0)\n",
      "\n",
      "# Make the shaded region\n",
      "ix = np.linspace(a, b)\n",
      "iy = func(ix)\n",
      "verts = [(a, 0)] + list(zip(ix, iy)) + [(b, 0)]\n",
      "poly = Polygon(verts, facecolor='0.9', edgecolor='0.5')\n",
      "ax.add_patch(poly)\n",
      "\n",
      "plt.text(0.5 * (a + b), 30, r\"$\\int_a^b f(x)\\mathrm{d}x$\",\n",
      "         horizontalalignment='center', fontsize=20)\n",
      "\n",
      "plt.figtext(0.9, 0.05, '$x$')\n",
      "plt.figtext(0.1, 0.9, '$y$')\n",
      "\n",
      "ax.spines['right'].set_visible(False)\n",
      "ax.spines['top'].set_visible(False)\n",
      "ax.xaxis.set_ticks_position('bottom')\n",
      "\n",
      "ax.set_xticks((a, b))\n",
      "ax.set_xticklabels(('$a$', '$b$'))\n",
      "ax.set_yticks([])\n",
      "\n",
      "plt.show()\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {
        "png": {
         "height": 401,
         "width": 596
        }
       },
       "output_type": "display_data",
       "png": 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GqjSNtilToulXv8qMe/be2yf5UXeUVAAAADBGladPj5bvfS8z69t991g8a1ZE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\n9ttvwdcKJ++//74k6c4777Q5CQAAOBlKKhSNz6fEfv1kZGQER2ZSktK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       "text": [
        "<matplotlib.figure.Figure at 0x1078d7e10>"
       ]
      }
     ],
     "prompt_number": 3
    }
   ],
   "metadata": {}
  }
 ]
}