pass on IPython Kernel example notebooks

- Python 3 fixes
- add `%matplotlib notebook` to plotting example
- various copy-editing

examples/IPython Kernel/Animations Using clear_output.ipynb

@@ -1,1359 +1,1359 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Simple animations Using clear_output"
+    "# Simple Animations Using clear_output"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Sometimes you want to clear the output area in the middle of a calculation.  This can be useful for doing simple animations. In terminals, there is the carriage-return (`'\\r'`) for overwriting a single line, but the notebook frontend can clear the whole output area, not just a single line.\n",
     "\n",
     "To clear output in the Notebook you can use the `clear_output()` function.  If you are clearing the output every frame of an animation, calling `clear_output()` will create noticeable flickering.  You can use `clear_output(wait=True)` to add the *clear_output* call to a queue.  When data becomes available to replace the existing output, the *clear_output* will be called immediately before the new data is added.  This avoids the flickering by not rendering the cleared output to the screen."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Simple example"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Here we show our progress iterating through a list:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": true
    },
    "outputs": [],
    "source": [
     "import sys\n",
     "import time"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "9\n"
      ]
     }
    ],
    "source": [
     "from IPython.display import display, clear_output\n",
     "for i in range(10):\n",
     "    time.sleep(0.25)\n",
     "    clear_output(wait=True)\n",
     "    print(i)\n",
     "    sys.stdout.flush()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## AsyncResult.wait_interactive"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The AsyncResult object has a special `wait_interactive()` method, which prints its progress interactively,\n",
     "so you can watch as your parallel computation completes.\n",
     "\n",
     "**This example assumes you have an IPython cluster running, which you can start from the [cluster panel](/#clusters)**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       " 100/100 tasks finished after    6 s\n",
       "done\n"
      ]
     }
    ],
    "source": [
     "from IPython import parallel\n",
     "rc = parallel.Client()\n",
     "view = rc.load_balanced_view()\n",
     "\n",
     "amr = view.map_async(time.sleep, [0.5]*100)\n",
     "\n",
     "amr.wait_interactive()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Matplotlib example"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "You can also use `clear_output()` to clear figures and plots."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
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        "msn/AbPOyGwnPY5DAAAAAElFTkSuQmCC\n"
       ],
       "text/plain": [
        "<matplotlib.figure.Figure at 0x10f01b310>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "from scipy.special import jn\n",
     "x = np.linspace(0,5)\n",
     "f, ax = plt.subplots()\n",
     "ax.set_title(\"Bessel functions\")\n",
     "\n",
     "for n in range(1,10):\n",
     "    time.sleep(1)\n",
     "    ax.plot(x, jn(x,n))\n",
     "    clear_output(wait=True)\n",
     "    display(f)\n",
     "\n",
     "# close the figure at the end, so we don't get a duplicate\n",
     "# of the last plot\n",
     "plt.close()"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
     "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.4.2"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
 }

examples/IPython Kernel/Background Jobs.ipynb

@@ -1,404 +1,404 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Simple interactive bacgkround jobs with IPython\n",
     "\n",
     "We start by loading the `backgroundjobs` library and defining a few trivial functions to illustrate things with."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "from IPython.lib import backgroundjobs as bg\n",
     "\n",
     "import sys\n",
     "import time\n",
     "\n",
     "def sleepfunc(interval=2, *a, **kw):\n",
     "    args = dict(interval=interval,\n",
     "                args=a,\n",
     "                kwargs=kw)\n",
     "    time.sleep(interval)\n",
     "    return args\n",
     "\n",
     "def diefunc(interval=2, *a, **kw):\n",
     "    time.sleep(interval)\n",
     "    raise Exception(\"Dead job with interval %s\" % interval)\n",
     "\n",
     "def printfunc(interval=1, reps=5):\n",
     "    for n in range(reps):\n",
     "        time.sleep(interval)\n",
-    "        print 'In the background...', n\n",
+    "        print('In the background... %i' % n)\n",
     "        sys.stdout.flush()\n",
-    "    print 'All done!'\n",
+    "    print('All done!')\n",
     "    sys.stdout.flush()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Now, we can create a job manager (called simply `jobs`) and use it to submit new jobs.\n",
     "\n",
     "Run the cell below, it will show when the jobs start. Wait a few seconds until you see the 'all done' completion message:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Starting job # 0 in a separate thread.\n",
       "Starting job # 2 in a separate thread.\n",
       "Starting job # 3 in a separate thread.\n"
      ]
     },
     {
      "data": {
       "text/plain": [
        "<BackgroundJob #3: printfunc(1,3)>"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "In the background... 0\n",
       "In the background... 1\n",
       "In the background... 2\n",
       "All done!\n"
      ]
     }
    ],
    "source": [
     "jobs = bg.BackgroundJobManager()\n",
     "\n",
     "# Start a few jobs, the first one will have ID # 0\n",
     "jobs.new(sleepfunc, 4)\n",
     "jobs.new(sleepfunc, kw={'reps':2})\n",
     "jobs.new('printfunc(1,3)')"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "You can check the status of your jobs at any time:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Completed jobs:\n",
-      "0 : <function sleepfunc at 0x314f848>\n",
-      "2 : <function sleepfunc at 0x314f848>\n",
+      "0 : <function sleepfunc at 0x10521f2f0>\n",
+      "2 : <function sleepfunc at 0x10521f2f0>\n",
       "3 : printfunc(1,3)\n",
       "\n"
      ]
     }
    ],
    "source": [
     "jobs.status()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "For any completed job, you can get its result easily:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "{'args': (), 'interval': 4, 'kwargs': {}}"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "jobs[0].result"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Errors and tracebacks"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The jobs manager tries to help you with debugging:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Starting job # 4 in a separate thread.\n",
       "Starting job # 5 in a separate thread.\n"
      ]
     }
    ],
    "source": [
     "# This makes a couple of jobs which will die.  Let's keep a reference to\n",
     "# them for easier traceback reporting later\n",
     "diejob1 = jobs.new(diefunc, 1)\n",
     "diejob2 = jobs.new(diefunc, 2)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "You can get the traceback of any dead job.  Run the line\n",
     "below again interactively until it prints a traceback (check the status\n",
     "of the job):\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Status of diejob1: Dead (Exception), call jobs.traceback() for details\n",
       "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n",
       "\u001b[1;31mException\u001b[0m                                 Traceback (most recent call last)\n",
-      "\u001b[1;32m/home/fperez/usr/opt/virtualenv/ipython-0.13.2/lib/python2.7/site-packages/IPython/lib/backgroundjobs.pyc\u001b[0m in \u001b[0;36mcall\u001b[1;34m(self)\u001b[0m\n",
-      "\u001b[0;32m    482\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m    483\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mcall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m--> 484\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m/Users/minrk/dev/ip/mine/IPython/lib/backgroundjobs.py\u001b[0m in \u001b[0;36mcall\u001b[1;34m(self)\u001b[0m\n",
+      "\u001b[0;32m    489\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m    490\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mcall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m--> 491\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0m\n",
-      "\u001b[1;32m<ipython-input-1-fbbbd0d2a1c3>\u001b[0m in \u001b[0;36mdiefunc\u001b[1;34m(interval, *a, **kw)\u001b[0m\n",
+      "\u001b[1;32m<ipython-input-1-169e49434ce0>\u001b[0m in \u001b[0;36mdiefunc\u001b[1;34m(interval, *a, **kw)\u001b[0m\n",
       "\u001b[0;32m     13\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdiefunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0;32m     14\u001b[0m     \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;32m---> 15\u001b[1;33m     \u001b[1;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Dead job with interval %s\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0minterval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0m\u001b[0;32m     16\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0;32m     17\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mprintfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreps\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\n",
       "\u001b[1;31mException\u001b[0m: Dead job with interval 1\n"
      ]
     }
    ],
    "source": [
-    "print \"Status of diejob1:\", diejob1.status\n",
+    "print(\"Status of diejob1: %s\" % diejob1.status)\n",
     "diejob1.traceback()  # jobs.traceback(4) would also work here, with the job number"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "This will print all tracebacks for all dead jobs:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Traceback for: <BackgroundJob #4: <function diefunc at 0x314f668>>\n",
+      "Traceback for: <BackgroundJob #4: <function diefunc at 0x10521f7b8>>\n",
       "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n",
       "\u001b[1;31mException\u001b[0m                                 Traceback (most recent call last)\n",
-      "\u001b[1;32m/home/fperez/usr/opt/virtualenv/ipython-0.13.2/lib/python2.7/site-packages/IPython/lib/backgroundjobs.pyc\u001b[0m in \u001b[0;36mcall\u001b[1;34m(self)\u001b[0m\n",
-      "\u001b[0;32m    482\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m    483\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mcall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m--> 484\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m/Users/minrk/dev/ip/mine/IPython/lib/backgroundjobs.py\u001b[0m in \u001b[0;36mcall\u001b[1;34m(self)\u001b[0m\n",
+      "\u001b[0;32m    489\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m    490\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mcall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m--> 491\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0m\n",
-      "\u001b[1;32m<ipython-input-1-fbbbd0d2a1c3>\u001b[0m in \u001b[0;36mdiefunc\u001b[1;34m(interval, *a, **kw)\u001b[0m\n",
+      "\u001b[1;32m<ipython-input-1-169e49434ce0>\u001b[0m in \u001b[0;36mdiefunc\u001b[1;34m(interval, *a, **kw)\u001b[0m\n",
       "\u001b[0;32m     13\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdiefunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0;32m     14\u001b[0m     \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;32m---> 15\u001b[1;33m     \u001b[1;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Dead job with interval %s\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0minterval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0m\u001b[0;32m     16\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0;32m     17\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mprintfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreps\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\n",
       "\u001b[1;31mException\u001b[0m: Dead job with interval 1\n",
       "\n",
-      "Traceback for: <BackgroundJob #5: <function diefunc at 0x314f668>>\n",
+      "Traceback for: <BackgroundJob #5: <function diefunc at 0x10521f7b8>>\n",
       "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n",
       "\u001b[1;31mException\u001b[0m                                 Traceback (most recent call last)\n",
-      "\u001b[1;32m/home/fperez/usr/opt/virtualenv/ipython-0.13.2/lib/python2.7/site-packages/IPython/lib/backgroundjobs.pyc\u001b[0m in \u001b[0;36mcall\u001b[1;34m(self)\u001b[0m\n",
-      "\u001b[0;32m    482\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m    483\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mcall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m--> 484\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m/Users/minrk/dev/ip/mine/IPython/lib/backgroundjobs.py\u001b[0m in \u001b[0;36mcall\u001b[1;34m(self)\u001b[0m\n",
+      "\u001b[0;32m    489\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m    490\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mcall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m--> 491\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0m\n",
-      "\u001b[1;32m<ipython-input-1-fbbbd0d2a1c3>\u001b[0m in \u001b[0;36mdiefunc\u001b[1;34m(interval, *a, **kw)\u001b[0m\n",
+      "\u001b[1;32m<ipython-input-1-169e49434ce0>\u001b[0m in \u001b[0;36mdiefunc\u001b[1;34m(interval, *a, **kw)\u001b[0m\n",
       "\u001b[0;32m     13\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdiefunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0;32m     14\u001b[0m     \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;32m---> 15\u001b[1;33m     \u001b[1;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Dead job with interval %s\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0minterval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0m\u001b[0;32m     16\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0;32m     17\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mprintfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreps\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\n",
       "\u001b[1;31mException\u001b[0m: Dead job with interval 2\n",
       "\n"
      ]
     }
    ],
    "source": [
     "jobs.traceback()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The job manager can be flushed of all completed jobs at any time:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Flushing 3 Completed jobs.\n",
       "Flushing 2 Dead jobs.\n"
      ]
     }
    ],
    "source": [
     "jobs.flush()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "After that, the status is simply empty:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 9,
    "metadata": {
     "collapsed": true
    },
    "outputs": [],
    "source": [
     "jobs.status()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Jobs have a `.join` method that lets you wait on their thread for completion:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Starting job # 0 in a separate thread.\n"
      ]
     }
    ],
    "source": [
     "j = jobs.new(sleepfunc, 2)\n",
     "j.join?"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Exercise\n",
     "\n",
     "1. Start a new job that calls `sleepfunc` with a 5-second wait\n",
     "2. Print a short message that indicates you are waiting (note: you'll need to flush stdout to see that print output appear).\n",
     "3. Wait on the job and then print its result."
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
     "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.4.2"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
 }

examples/IPython Kernel/Beyond Plain Python.ipynb

@@ -1,1823 +1,2523 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "# IPython: beyond plain Python"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "When executing code in IPython, all valid Python syntax works as-is, but IPython provides a number of features designed to make the interactive experience more fluid and efficient."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "## First things first: running code, getting help"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "In the notebook, to run a cell of code, hit `Shift-Enter`. This executes the cell and puts the cursor in the next cell below, or makes a new one if you are at the end.  Alternately, you can use:\n",
     "    \n",
     "- `Alt-Enter` to force the creation of a new cell unconditionally (useful when inserting new content in the middle of an existing notebook).\n",
     "- `Control-Enter` executes the cell and keeps the cursor in the same cell, useful for quick experimentation of snippets that you don't need to keep permanently."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Hi\n"
      ]
     }
    ],
    "source": [
-    "print \"Hi\""
+    "print(\"Hi\")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "Getting help:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "?"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "Typing `object_name?` will print all sorts of details about any object, including docstrings, function definition lines (for call arguments) and constructor details for classes."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "import collections\n",
     "collections.namedtuple?"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "collections.Counter??"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "*int*?"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "An IPython quick reference card:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%quickref"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "## Tab completion"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Tab completion, especially for attributes, is a convenient way to explore the structure of any object you’re dealing with. Simply type `object_name.<TAB>` to view the object’s attributes. Besides Python objects and keywords, tab completion also works on file and directory names."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "collections."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "## The interactive workflow: input, output, history"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "12"
       ]
      },
      "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "2+10"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "22"
       ]
      },
      "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "_+10"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "You can suppress the storage and rendering of output if you append `;` to the last cell (this comes in handy when plotting with matplotlib, for example):"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "10+20;"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "22"
       ]
      },
      "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "_"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "The output is stored in `_N` and `Out[N]` variables:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "True"
       ]
      },
      "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "_10 == Out[10]"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "And the last three have shorthands for convenience:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "last output: True\n",
       "next one   : 22\n",
       "and next   : 22\n"
      ]
     }
    ],
    "source": [
-    "print 'last output:', _\n",
-    "print 'next one   :', __\n",
-    "print 'and next   :', ___"
+    "from __future__ import print_function\n",
+    "\n",
+    "print('last output:', _)\n",
+    "print('next one   :', __)\n",
+    "print('and next   :', ___)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
     "collapsed": false,
     "slideshow": {
      "slide_type": "-"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "u'_10 == Out[10]'"
+       "'_10 == Out[10]'"
       ]
      },
      "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "In[11]"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "u'In[11]'"
+       "'In[11]'"
       ]
      },
      "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "_i"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "u'In[11]'"
+       "'In[11]'"
       ]
      },
      "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "_ii"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
     "collapsed": false,
     "slideshow": {
      "slide_type": "subslide"
     }
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "last input: _ii\n",
       "next one  : _i\n",
       "and next  : In[11]\n"
      ]
     }
    ],
    "source": [
-    "print 'last input:', _i\n",
-    "print 'next one  :', _ii\n",
-    "print 'and next  :', _iii"
+    "print('last input:', _i)\n",
+    "print('next one  :', _ii)\n",
+    "print('and next  :', _iii)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "   1: print \"Hi\"\n",
+      "   1: print(\"Hi\")\n",
       "   2: ?\n",
       "   3:\n",
       "import collections\n",
       "collections.namedtuple?\n",
       "   4: collections.Counter??\n",
       "   5: *int*?\n"
      ]
     }
    ],
    "source": [
     "%history -n 1-5"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "subslide"
     }
    },
    "source": [
     "**Exercise**\n",
     "\n",
     "Write the last 10 lines of history to a file named `log.py`."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "## Accessing the underlying operating system"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/home/fperez/ipython/tutorial/notebooks\r\n"
+      "/Users/minrk/dev/ip/mine/examples/IPython Kernel\r\n"
      ]
     }
    ],
    "source": [
     "!pwd"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 19,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "My current directory's files:\n",
-      "['BackgroundJobs.ipynb', 'Custom Display Logic.ipynb', 'Customizing IPython - Condensed.ipynb', 'Customizing IPython - Config.ipynb', 'Customizing IPython - Extensions.ipynb', 'Customizing IPython - Magics.ipynb', 'data', 'figs', 'flare.json', 'Index.ipynb', 'Interactive Widgets.ipynb', 'IPython - beyond plain Python.ipynb', 'kernel-embedding', 'Markdown Cells.ipynb', 'myscript.py', 'nbconvert_arch.png', 'NbConvert from command line.ipynb', 'NbConvert Python library.ipynb', 'Notebook and javascript extension.ipynb', 'Notebook Basics.ipynb', 'Overview of IPython.parallel.ipynb', 'parallel', 'Rich Display System.ipynb', 'Running a Secure Public Notebook.ipynb', 'Running Code.ipynb', 'Sample.ipynb', 'soln', 'Terminal usage.ipynb', 'text_analysis.py', 'Typesetting Math Using MathJax.ipynb']\n"
+      "['Animations Using clear_output.ipynb', 'Background Jobs.ipynb', 'Beyond Plain Python.ipynb', 'Capturing Output.ipynb', 'Cell Magics.ipynb', 'Custom Display Logic.ipynb', 'Index.ipynb', 'Old Custom Display Logic.ipynb', 'Plotting in the Notebook.ipynb', 'Raw Input in the Notebook.ipynb', 'Rich Output.ipynb', 'Script Magics.ipynb', 'SymPy.ipynb', 'Terminal Usage.ipynb', 'Third Party Rich Output.ipynb', 'Trapezoid Rule.ipynb', 'Working With External Code.ipynb', '__pycache__', 'data', 'example-demo.py', 'gui', 'ipython-completion.bash', 'ipython-get-history.py', 'ipython-qtconsole.desktop', 'ipython.desktop', 'mod.py', 'test.txt']\n"
      ]
     }
    ],
    "source": [
     "files = !ls\n",
-    "print \"My current directory's files:\"\n",
-    "print files"
+    "print(\"My current directory's files:\")\n",
+    "print(files)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 20,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[BackgroundJobs.ipynb, Custom Display Logic.ipynb, Customizing IPython - Condensed.ipynb, Customizing IPython - Config.ipynb, Customizing IPython - Extensions.ipynb, Customizing IPython - Magics.ipynb, data, figs, flare.json, Index.ipynb, Interactive Widgets.ipynb, IPython - beyond plain Python.ipynb, kernel-embedding, Markdown Cells.ipynb, myscript.py, nbconvert_arch.png, NbConvert from command line.ipynb, NbConvert Python library.ipynb, Notebook and javascript extension.ipynb, Notebook Basics.ipynb, Overview of IPython.parallel.ipynb, parallel, Rich Display System.ipynb, Running a Secure Public Notebook.ipynb, Running Code.ipynb, Sample.ipynb, soln, Terminal usage.ipynb, text_analysis.py, Typesetting Math Using MathJax.ipynb]\r\n"
+      "[Animations Using clear_output.ipynb, Background Jobs.ipynb, Beyond Plain Python.ipynb, Capturing Output.ipynb, Cell Magics.ipynb, Custom Display Logic.ipynb, Index.ipynb, Old Custom Display Logic.ipynb, Plotting in the Notebook.ipynb, Raw Input in the Notebook.ipynb, Rich Output.ipynb, Script Magics.ipynb, SymPy.ipynb, Terminal Usage.ipynb, Third Party Rich Output.ipynb, Trapezoid Rule.ipynb, Working With External Code.ipynb, __pycache__, data, example-demo.py, gui, ipython-completion.bash, ipython-get-history.py, ipython-qtconsole.desktop, ipython.desktop, mod.py, test.txt]\r\n"
      ]
     }
    ],
    "source": [
     "!echo $files"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 21,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "BACKGROUNDJOBS.IPYNB\r\n"
+      "ANIMATIONS USING CLEAR_OUTPUT.IPYNB\r\n"
      ]
     }
    ],
    "source": [
     "!echo {files[0].upper()}"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Note that all this is available even in multiline blocks:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 22,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "00 - BackgroundJobs\r\n",
-      "01 - Custom Display Logic\r\n",
-      "02 - Customizing IPython - Condensed\r\n",
-      "03 - Customizing IPython - Config\r\n",
-      "04 - Customizing IPython - Extensions\r\n",
-      "05 - Customizing IPython - Magics\r\n",
+      "00 - Animations Using clear_output\n",
+      "01 - Background Jobs\n",
+      "02 - Beyond Plain Python\n",
+      "03 - Capturing Output\n",
+      "04 - Cell Magics\n",
+      "05 - Custom Display Logic\n",
+      "06 - Index\n",
+      "07 - Old Custom Display Logic\n",
+      "08 - Plotting in the Notebook\n",
+      "09 - Raw Input in the Notebook\n",
+      "10 - Rich Output\n",
+      "11 - Script Magics\n",
+      "12 - SymPy\n",
+      "13 - Terminal Usage\n",
+      "14 - Third Party Rich Output\n",
+      "15 - Trapezoid Rule\n",
+      "16 - Working With External Code\n",
       "--\n",
       "--\n",
       "--\n",
-      "09 - Index\r\n",
-      "10 - Interactive Widgets\r\n",
-      "11 - IPython - beyond plain Python\r\n",
       "--\n",
-      "13 - Markdown Cells\r\n",
       "--\n",
       "--\n",
-      "16 - NbConvert from command line\r\n",
-      "17 - NbConvert Python library\r\n",
-      "18 - Notebook and javascript extension\r\n",
-      "19 - Notebook Basics\r\n",
-      "20 - Overview of IPython.parallel\r\n",
       "--\n",
-      "22 - Rich Display System\r\n",
-      "23 - Running a Secure Public Notebook\r\n",
-      "24 - Running Code\r\n",
-      "25 - Sample\r\n",
       "--\n",
-      "27 - Terminal usage\r\n",
       "--\n",
-      "29 - Typesetting Math Using MathJax\r\n"
+      "--\n"
      ]
     }
    ],
    "source": [
     "import os\n",
     "for i,f in enumerate(files):\n",
     "    if f.endswith('ipynb'):\n",
     "        !echo {\"%02d\" % i} - \"{os.path.splitext(f)[0]}\"\n",
     "    else:\n",
-    "        print '--'"
+    "        print('--')"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Beyond Python: magic functions"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The IPyhton 'magic' functions are a set of commands, invoked by prepending one or two `%` signs to their name, that live in a namespace separate from your normal Python variables and provide a more command-like interface.  They take flags with `--` and arguments without quotes, parentheses or commas. The motivation behind this system is two-fold:\n",
     "    \n",
     "- To provide an orthogonal namespace for controlling IPython itself and exposing other system-oriented functionality.\n",
     "\n",
     "- To expose a calling mode that requires minimal verbosity and typing while working interactively.  Thus the inspiration taken from the classic Unix shell style for commands."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 23,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%magic"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Line vs cell magics:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 24,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "10000000 loops, best of 3: 190 ns per loop\n"
+      "10000 loops, best of 3: 19.3 µs per loop\n"
      ]
     }
    ],
    "source": [
-    "%timeit range(10)"
+    "%timeit list(range(1000))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 25,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1000000 loops, best of 3: 888 ns per loop\n"
+      "100000 loops, best of 3: 2.78 µs per loop\n"
      ]
     }
    ],
    "source": [
     "%%timeit\n",
-    "range(10)\n",
-    "range(100)"
+    "list(range(10))\n",
+    "list(range(100))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Line magics can be used even inside code blocks:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 26,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "size: 010000000 loops, best of 3: 129 ns per loop\n",
-      " size: 1001000000 loops, best of 3: 649 ns per loop\n",
-      " size: 2001000000 loops, best of 3: 1.09 µs per loop\n",
-      " size: 3001000000 loops, best of 3: 1.74 µs per loop\n",
-      " size: 400100000 loops, best of 3: 2.72 µs per loop\n",
-      "\n"
+      "size: 100 100000 loops, best of 3: 1.86 µs per loop\n",
+      "size: 200 100000 loops, best of 3: 2.49 µs per loop\n",
+      "size: 300 100000 loops, best of 3: 4.04 µs per loop\n",
+      "size: 400 100000 loops, best of 3: 6.21 µs per loop\n"
      ]
     }
    ],
    "source": [
-    "for i in range(5):\n",
+    "for i in range(1, 5):\n",
     "    size = i*100\n",
-    "    print 'size:',size, \n",
-    "    %timeit range(size)"
+    "    print('size:', size, end=' ')\n",
+    "    %timeit list(range(size))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Magics can do anything they want with their input, so it doesn't have to be valid Python:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 27,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "My shell is: /bin/bash\n",
-      "My memory status is:\n",
-      "             total       used       free     shared    buffers     cached\n",
-      "Mem:       7870888    6389328    1481560          0     662860    2505172\n",
-      "-/+ buffers/cache:    3221296    4649592\n",
-      "Swap:      3905532       4852    3900680\n"
+      "My shell is: /usr/local/bin/bash\n",
+      "My disk usage is:\n",
+      "Filesystem      Size   Used  Avail Capacity  iused   ifree %iused  Mounted on\n",
+      "/dev/disk1     233Gi  216Gi   16Gi    94% 56788108 4190706   93%   /\n",
+      "devfs          190Ki  190Ki    0Bi   100%      656       0  100%   /dev\n",
+      "map -hosts       0Bi    0Bi    0Bi   100%        0       0  100%   /net\n",
+      "map auto_home    0Bi    0Bi    0Bi   100%        0       0  100%   /home\n"
      ]
     }
    ],
    "source": [
     "%%bash\n",
     "echo \"My shell is:\" $SHELL\n",
-    "echo \"My memory status is:\"\n",
-    "free"
+    "echo \"My disk usage is:\"\n",
+    "df -h"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Another interesting cell magic: create any file you want locally from the notebook:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 28,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Writing test.txt\n"
+      "Overwriting test.txt\n"
      ]
     }
    ],
    "source": [
     "%%writefile test.txt\n",
     "This is a test file!\n",
     "It can contain anything I want...\n",
     "\n",
     "And more..."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 29,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "This is a test file!\r\n",
       "It can contain anything I want...\r\n",
       "\r\n",
       "And more..."
      ]
     }
    ],
    "source": [
     "!cat test.txt"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Let's see what other magics are currently defined in the system:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 30,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "application/json": {
        "cell": {
         "!": "OSMagics",
         "HTML": "Other",
         "SVG": "Other",
         "bash": "Other",
         "capture": "ExecutionMagics",
         "debug": "ExecutionMagics",
         "file": "Other",
         "html": "DisplayMagics",
         "javascript": "DisplayMagics",
         "latex": "DisplayMagics",
         "perl": "Other",
         "prun": "ExecutionMagics",
         "pypy": "Other",
         "python": "Other",
         "python2": "Other",
         "python3": "Other",
         "ruby": "Other",
         "script": "ScriptMagics",
         "sh": "Other",
         "svg": "DisplayMagics",
         "sx": "OSMagics",
         "system": "OSMagics",
         "time": "ExecutionMagics",
         "timeit": "ExecutionMagics",
         "writefile": "OSMagics"
        },
        "line": {
         "alias": "OSMagics",
         "alias_magic": "BasicMagics",
         "autocall": "AutoMagics",
         "automagic": "AutoMagics",
         "autosave": "KernelMagics",
         "bookmark": "OSMagics",
         "cat": "Other",
         "cd": "OSMagics",
-        "cl": "Other",
         "clear": "KernelMagics",
-        "clk": "Other",
         "colors": "BasicMagics",
         "config": "ConfigMagics",
         "connect_info": "KernelMagics",
         "cp": "Other",
-        "d": "Other",
-        "dd": "Other",
         "debug": "ExecutionMagics",
         "dhist": "OSMagics",
         "dirs": "OSMagics",
-        "dl": "Other",
-        "doctest_mode": "KernelMagics",
-        "dx": "Other",
+        "doctest_mode": "BasicMagics",
         "ed": "Other",
         "edit": "KernelMagics",
         "env": "OSMagics",
         "gui": "BasicMagics",
         "hist": "Other",
         "history": "HistoryMagics",
         "install_default_config": "DeprecatedMagics",
         "install_ext": "ExtensionMagics",
         "install_profiles": "DeprecatedMagics",
         "killbgscripts": "ScriptMagics",
         "ldir": "Other",
         "less": "KernelMagics",
         "lf": "Other",
         "lk": "Other",
         "ll": "Other",
         "load": "CodeMagics",
         "load_ext": "ExtensionMagics",
         "loadpy": "CodeMagics",
         "logoff": "LoggingMagics",
         "logon": "LoggingMagics",
         "logstart": "LoggingMagics",
         "logstate": "LoggingMagics",
         "logstop": "LoggingMagics",
         "ls": "Other",
         "lsmagic": "BasicMagics",
         "lx": "Other",
         "macro": "ExecutionMagics",
         "magic": "BasicMagics",
         "man": "KernelMagics",
         "matplotlib": "PylabMagics",
         "mkdir": "Other",
         "more": "KernelMagics",
         "mv": "Other",
+        "namespace": "Other",
         "notebook": "BasicMagics",
         "page": "BasicMagics",
         "pastebin": "CodeMagics",
         "pdb": "ExecutionMagics",
         "pdef": "NamespaceMagics",
         "pdoc": "NamespaceMagics",
         "pfile": "NamespaceMagics",
         "pinfo": "NamespaceMagics",
         "pinfo2": "NamespaceMagics",
         "popd": "OSMagics",
         "pprint": "BasicMagics",
         "precision": "BasicMagics",
         "profile": "BasicMagics",
         "prun": "ExecutionMagics",
         "psearch": "NamespaceMagics",
         "psource": "NamespaceMagics",
         "pushd": "OSMagics",
         "pwd": "OSMagics",
         "pycat": "OSMagics",
         "pylab": "PylabMagics",
         "qtconsole": "KernelMagics",
         "quickref": "BasicMagics",
         "recall": "HistoryMagics",
         "rehashx": "OSMagics",
         "reload_ext": "ExtensionMagics",
         "rep": "Other",
         "rerun": "HistoryMagics",
         "reset": "NamespaceMagics",
         "reset_selective": "NamespaceMagics",
         "rm": "Other",
         "rmdir": "Other",
         "run": "ExecutionMagics",
         "save": "CodeMagics",
         "sc": "OSMagics",
+        "set_env": "OSMagics",
         "store": "StoreMagics",
         "sx": "OSMagics",
         "system": "OSMagics",
         "tb": "ExecutionMagics",
+        "tic": "TimerMagics",
         "time": "ExecutionMagics",
         "timeit": "ExecutionMagics",
+        "toc": "TimerMagics",
         "unalias": "OSMagics",
         "unload_ext": "ExtensionMagics",
         "who": "NamespaceMagics",
         "who_ls": "NamespaceMagics",
         "whos": "NamespaceMagics",
         "xdel": "NamespaceMagics",
         "xmode": "BasicMagics"
        }
       },
       "text/plain": [
        "Available line magics:\n",
-       "%alias  %alias_magic  %autocall  %automagic  %autosave  %bookmark  %cat  %cd  %cl  %clear  %clk  %colors  %config  %connect_info  %cp  %d  %dd  %debug  %dhist  %dirs  %dl  %doctest_mode  %dx  %ed  %edit  %env  %gui  %hist  %history  %install_default_config  %install_ext  %install_profiles  %killbgscripts  %ldir  %less  %lf  %lk  %ll  %load  %load_ext  %loadpy  %logoff  %logon  %logstart  %logstate  %logstop  %ls  %lsmagic  %lx  %macro  %magic  %man  %matplotlib  %mkdir  %more  %mv  %notebook  %page  %pastebin  %pdb  %pdef  %pdoc  %pfile  %pinfo  %pinfo2  %popd  %pprint  %precision  %profile  %prun  %psearch  %psource  %pushd  %pwd  %pycat  %pylab  %qtconsole  %quickref  %recall  %rehashx  %reload_ext  %rep  %rerun  %reset  %reset_selective  %rm  %rmdir  %run  %save  %sc  %store  %sx  %system  %tb  %time  %timeit  %unalias  %unload_ext  %who  %who_ls  %whos  %xdel  %xmode\n",
+       "%alias  %alias_magic  %autocall  %automagic  %autosave  %bookmark  %cat  %cd  %clear  %colors  %config  %connect_info  %cp  %debug  %dhist  %dirs  %doctest_mode  %ed  %edit  %env  %gui  %hist  %history  %install_default_config  %install_ext  %install_profiles  %killbgscripts  %ldir  %less  %lf  %lk  %ll  %load  %load_ext  %loadpy  %logoff  %logon  %logstart  %logstate  %logstop  %ls  %lsmagic  %lx  %macro  %magic  %man  %matplotlib  %mkdir  %more  %mv  %namespace  %notebook  %page  %pastebin  %pdb  %pdef  %pdoc  %pfile  %pinfo  %pinfo2  %popd  %pprint  %precision  %profile  %prun  %psearch  %psource  %pushd  %pwd  %pycat  %pylab  %qtconsole  %quickref  %recall  %rehashx  %reload_ext  %rep  %rerun  %reset  %reset_selective  %rm  %rmdir  %run  %save  %sc  %set_env  %store  %sx  %system  %tb  %tic  %time  %timeit  %toc  %unalias  %unload_ext  %who  %who_ls  %whos  %xdel  %xmode\n",
        "\n",
        "Available cell magics:\n",
        "%%!  %%HTML  %%SVG  %%bash  %%capture  %%debug  %%file  %%html  %%javascript  %%latex  %%perl  %%prun  %%pypy  %%python  %%python2  %%python3  %%ruby  %%script  %%sh  %%svg  %%sx  %%system  %%time  %%timeit  %%writefile\n",
        "\n",
        "Automagic is ON, % prefix IS NOT needed for line magics."
       ]
      },
-     "execution_count": 35,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "%lsmagic"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Running normal Python code: execution and errors"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Not only can you input normal Python code, you can even paste straight from a Python or IPython shell session:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 31,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "1\n",
       "1\n",
       "2\n",
       "3\n",
       "5\n",
       "8\n"
      ]
     }
    ],
    "source": [
     ">>> # Fibonacci series:\n",
     "... # the sum of two elements defines the next\n",
     "... a, b = 0, 1\n",
     ">>> while b < 10:\n",
-    "...     print b\n",
+    "...     print(b)\n",
     "...     a, b = b, a+b"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 1 2 3 4 5 6 7 8 9\n"
+      "0 1 2 3 4 5 6 7 8 9 "
      ]
     }
    ],
    "source": [
     "In [1]: for i in range(10):\n",
-    "   ...:     print i,\n",
+    "   ...:     print(i, end=' ')\n",
     "   ...:     "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "And when your code produces errors, you can control how they are displayed with the `%xmode` magic:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 33,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Writing mod.py\n"
+      "Overwriting mod.py\n"
      ]
     }
    ],
    "source": [
     "%%writefile mod.py\n",
     "\n",
     "def f(x):\n",
     "    return 1.0/(x-1)\n",
     "\n",
     "def g(y):\n",
     "    return f(y+1)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Now let's call the function `g` with an argument that would produce an error:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 34,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "ename": "ZeroDivisionError",
      "evalue": "float division by zero",
      "output_type": "error",
      "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-39-a54c5799f57e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mmod\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mmod\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m/home/fperez/ipython/tutorial/notebooks/mod.py\u001b[0m in \u001b[0;36mg\u001b[1;34m(y)\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m/home/fperez/ipython/tutorial/notebooks/mod.py\u001b[0m in \u001b[0;36mf\u001b[1;34m(x)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-40-a54c5799f57e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mmod\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mmod\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m in \u001b[0;36mg\u001b[1;34m(y)\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m in \u001b[0;36mf\u001b[1;34m(x)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mZeroDivisionError\u001b[0m: float division by zero"
      ]
     }
    ],
    "source": [
     "import mod\n",
     "mod.g(0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 35,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Exception reporting mode: Plain\n"
      ]
     },
     {
      "ename": "ZeroDivisionError",
      "evalue": "float division by zero",
      "output_type": "error",
      "traceback": [
       "Traceback \u001b[1;36m(most recent call last)\u001b[0m:\n",
-      "  File \u001b[0;32m\"<ipython-input-40-5a5bcec1553f>\"\u001b[0m, line \u001b[0;32m2\u001b[0m, in \u001b[0;35m<module>\u001b[0m\n    mod.g(0)\n",
-      "  File \u001b[0;32m\"mod.py\"\u001b[0m, line \u001b[0;32m6\u001b[0m, in \u001b[0;35mg\u001b[0m\n    return f(y+1)\n",
-      "\u001b[1;36m  File \u001b[1;32m\"mod.py\"\u001b[1;36m, line \u001b[1;32m3\u001b[1;36m, in \u001b[1;35mf\u001b[1;36m\u001b[0m\n\u001b[1;33m    return 1.0/(x-1)\u001b[0m\n",
+      "  File \u001b[0;32m\"<ipython-input-41-8932f4bf53fa>\"\u001b[0m, line \u001b[0;32m2\u001b[0m, in \u001b[0;35m<module>\u001b[0m\n    mod.g(0)\n",
+      "  File \u001b[0;32m\"/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\"\u001b[0m, line \u001b[0;32m6\u001b[0m, in \u001b[0;35mg\u001b[0m\n    return f(y+1)\n",
+      "\u001b[1;36m  File \u001b[1;32m\"/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\"\u001b[1;36m, line \u001b[1;32m3\u001b[1;36m, in \u001b[1;35mf\u001b[1;36m\u001b[0m\n\u001b[1;33m    return 1.0/(x-1)\u001b[0m\n",
       "\u001b[1;31mZeroDivisionError\u001b[0m\u001b[1;31m:\u001b[0m float division by zero\n"
      ]
     }
    ],
    "source": [
     "%xmode plain\n",
     "mod.g(0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 36,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Exception reporting mode: Verbose\n"
      ]
     },
     {
      "ename": "ZeroDivisionError",
      "evalue": "float division by zero",
      "output_type": "error",
      "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-41-81967cfaa0c3>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'xmode verbose'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mmod\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m        \u001b[1;36mglobal\u001b[0m \u001b[0;36mmod.g\u001b[0m \u001b[1;34m= <function g at 0x237fc08>\u001b[0m\n",
-      "\u001b[1;32m/home/fperez/ipython/tutorial/notebooks/mod.py\u001b[0m in \u001b[0;36mg\u001b[1;34m(y=0)\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m        \u001b[1;36mglobal\u001b[0m \u001b[0;36mf\u001b[0m \u001b[1;34m= <function f at 0x2367c08>\u001b[0m\u001b[1;34m\n        \u001b[0m\u001b[0;36my\u001b[0m \u001b[1;34m= 0\u001b[0m\n",
-      "\u001b[1;32m/home/fperez/ipython/tutorial/notebooks/mod.py\u001b[0m in \u001b[0;36mf\u001b[1;34m(x=1)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m        \u001b[0;36mx\u001b[0m \u001b[1;34m= 1\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-42-539f73e80e01>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'xmode verbose'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mmod\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m        \u001b[1;36mglobal\u001b[0m \u001b[0;36mmod.g\u001b[0m \u001b[1;34m= <function g at 0x105887d08>\u001b[0m\n",
+      "\u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m in \u001b[0;36mg\u001b[1;34m(y=0)\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m        \u001b[1;36mglobal\u001b[0m \u001b[0;36mf\u001b[0m \u001b[1;34m= <function f at 0x105887d90>\u001b[0m\u001b[1;34m\n        \u001b[0m\u001b[0;36my\u001b[0m \u001b[1;34m= 0\u001b[0m\n",
+      "\u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m in \u001b[0;36mf\u001b[1;34m(x=1)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m        \u001b[0;36mx\u001b[0m \u001b[1;34m= 1\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mZeroDivisionError\u001b[0m: float division by zero"
      ]
     }
    ],
    "source": [
     "%xmode verbose\n",
     "mod.g(0)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The default `%xmode` is \"context\", which shows additional context but not all local variables.  Let's restore that one for the rest of our session."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 37,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Exception reporting mode: Context\n"
      ]
     }
    ],
    "source": [
     "%xmode context"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Running code in other languages with special `%%` magics"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 38,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "July"
      ]
     }
    ],
    "source": [
     "%%perl\n",
     "@months = (\"July\", \"August\", \"September\");\n",
     "print $months[0];"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 39,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Hello World!\n"
      ]
     }
    ],
    "source": [
     "%%ruby\n",
     "name = \"world\"\n",
     "puts \"Hello #{name.capitalize}!\""
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Exercise"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Write a cell that executes in Bash and prints your current working directory as well as the date.\n",
-    "\n",
-    "Apologies to Windows users who may not have Bash available, not sure how to obtain the equivalent result with `cmd.exe` or Powershell."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "%load soln/bash-script"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
     "## Raw Input in the notebook"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Since 1.0 the IPython notebook web application support `raw_input` which for example allow us to invoke the `%debug` magic in the notebook:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "ename": "ZeroDivisionError",
      "evalue": "float division by zero",
      "output_type": "error",
      "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-45-5e708f13c839>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mmod\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m/home/fperez/ipython/tutorial/notebooks/mod.py\u001b[0m in \u001b[0;36mg\u001b[1;34m(y)\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m/home/fperez/ipython/tutorial/notebooks/mod.py\u001b[0m in \u001b[0;36mf\u001b[1;34m(x)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-46-5e708f13c839>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mmod\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m in \u001b[0;36mg\u001b[1;34m(y)\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m in \u001b[0;36mf\u001b[1;34m(x)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[1;31mZeroDivisionError\u001b[0m: float division by zero"
      ]
     }
    ],
    "source": [
     "mod.g(0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 41,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "> \u001b[0;32m/Users/bussonniermatthias/ipython-in-depth/notebooks/mod.py\u001b[0m(3)\u001b[0;36mf\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;32m      2 \u001b[0;31m\u001b[0;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0m\u001b[0;32m----> 3 \u001b[0;31m    \u001b[0;32mreturn\u001b[0m \u001b[0;36m1.0\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0m\u001b[0;32m      4 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "> \u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m(3)\u001b[0;36mf\u001b[1;34m()\u001b[0m\n",
+      "\u001b[1;32m      2 \u001b[1;33m\u001b[1;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\u001b[1;32m----> 3 \u001b[1;33m    \u001b[1;32mreturn\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\u001b[1;32m      4 \u001b[1;33m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0m\n",
-      "ipdb> x\n",
-      "1\n",
       "ipdb> up\n",
-      "> \u001b[0;32m/Users/bussonniermatthias/ipython-in-depth/notebooks/mod.py\u001b[0m(6)\u001b[0;36mg\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;32m      4 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0m\u001b[0;32m      5 \u001b[0;31m\u001b[0;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0m\u001b[0;32m----> 6 \u001b[0;31m    \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "> \u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m(6)\u001b[0;36mg\u001b[1;34m()\u001b[0m\n",
+      "\u001b[1;32m      4 \u001b[1;33m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\u001b[1;32m      5 \u001b[1;33m\u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\u001b[1;32m----> 6 \u001b[1;33m    \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0m\n",
-      "ipdb> y\n",
-      "0\n",
-      "ipdb> up\n",
-      "> \u001b[0;32m<ipython-input-37-5e708f13c839>\u001b[0m(1)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;32m----> 1 \u001b[0;31m\u001b[0mmod\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "ipdb> down\n",
+      "> \u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m(3)\u001b[0;36mf\u001b[1;34m()\u001b[0m\n",
+      "\u001b[1;32m      2 \u001b[1;33m\u001b[1;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\u001b[1;32m----> 3 \u001b[1;33m    \u001b[1;32mreturn\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\u001b[1;32m      4 \u001b[1;33m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\n",
+      "ipdb> bt\n",
+      "  \u001b[1;32m<ipython-input-46-5e708f13c839>\u001b[0m(1)\u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n",
+      "\u001b[1;32m----> 1 \u001b[1;33m\u001b[0mmod\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\n",
+      "  \u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m(6)\u001b[0;36mg\u001b[1;34m()\u001b[0m\n",
+      "\u001b[0;32m      2 \u001b[0m\u001b[1;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m      3 \u001b[0m    \u001b[1;32mreturn\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m      4 \u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m      5 \u001b[0m\u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m----> 6 \u001b[1;33m    \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\n",
+      "> \u001b[1;32m/Users/minrk/dev/ip/mine/examples/IPython Kernel/mod.py\u001b[0m(3)\u001b[0;36mf\u001b[1;34m()\u001b[0m\n",
+      "\u001b[1;32m      1 \u001b[1;33m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\u001b[1;32m      2 \u001b[1;33m\u001b[1;32mdef\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\u001b[1;32m----> 3 \u001b[1;33m    \u001b[1;32mreturn\u001b[0m \u001b[1;36m1.0\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\u001b[1;32m      4 \u001b[1;33m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[0m\u001b[1;32m      5 \u001b[1;33m\u001b[1;32mdef\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
       "\u001b[0m\n",
       "ipdb> exit\n"
      ]
     }
    ],
    "source": [
     "%debug"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Don't foget to exit your debugging session. Raw input can of course be use to ask for user input:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 42,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Are you enjoying this tutorial ?Yes !\n",
-      "enjoy is : Yes !\n"
+      "Are you enjoying this tutorial? yes\n",
+      "enjoy is: yes\n"
      ]
     }
    ],
    "source": [
-    "enjoy = raw_input('Are you enjoying this tutorial ?')\n",
-    "print 'enjoy is :', enjoy"
+    "enjoy = input('Are you enjoying this tutorial? ')\n",
+    "print('enjoy is:', enjoy)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Plotting in the notebook"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "This magic configures matplotlib to render its figures inline:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 43,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%matplotlib inline"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 44,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "import numpy as np\n",
     "import matplotlib.pyplot as plt"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 45,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
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+       "NnPy9WQz184Enp+mqbPXVAf/9qp0aZp+FDgLuJrszaP3AKcAv5ym6StqXJrmWJqm24EzgLeTvUn0\n",
+       "L8BfkFUCPiJN00trXJ7a4bnAncA7i7rgqn37/LstSZIkSZKkZmp75ZUkSZIkSZIazPBKkiRJkiRJ\n",
+       "jWV4JUmSJEmSpMYyvJIkSZIkSVJjGV5JkiRJkiSpsQyvJEmSJEmS1FiGV5IkSZIkSWoswytJkiRJ\n",
+       "kiQ1luGVJEmSJEmSGsvwSpIkSZIkSY1leCVJkiRJkqTGMrySJEmSJElSYxleSZIkSZIkqbEMryRJ\n",
+       "kiRJktRYhleSJEmSJElqLMMrSZIkSZIkNZbhlSRJkiRJkhrL8EqSJEmSJEmNZXglSZIkSZKkxvr/\n",
+       "gUJ07DcuELgAAAAASUVORK5CYII=\n"
       ],
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x3436950>"
+       "<matplotlib.figure.Figure at 0x106c2a9b0>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "image/png": {
+       "height": 392,
+       "width": 599
+      }
+     },
      "output_type": "display_data"
     }
    ],
    "source": [
     "x = np.linspace(0, 2*np.pi, 300)\n",
     "y = np.sin(x**2)\n",
     "plt.plot(x, y)\n",
     "plt.title(\"A little chirp\")\n",
     "fig = plt.gcf()  # let's keep the figure object around for later..."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## The IPython kernel/client model"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "{\n",
-      "  \"stdin_port\": 50023, \n",
-      "  \"ip\": \"127.0.0.1\", \n",
-      "  \"control_port\": 50024, \n",
-      "  \"hb_port\": 50025, \n",
-      "  \"signature_scheme\": \"hmac-sha256\", \n",
-      "  \"key\": \"b54b8859-d64d-48bb-814a-909f9beb3316\", \n",
-      "  \"shell_port\": 50021, \n",
-      "  \"transport\": \"tcp\", \n",
-      "  \"iopub_port\": 50022\n",
+      "  \"stdin_port\": 62401,\n",
+      "  \"key\": \"64c935a7-64e8-4ab7-ab22-6e0f3ff84e02\",\n",
+      "  \"hb_port\": 62403,\n",
+      "  \"transport\": \"tcp\",\n",
+      "  \"signature_scheme\": \"hmac-sha256\",\n",
+      "  \"shell_port\": 62399,\n",
+      "  \"control_port\": 62402,\n",
+      "  \"ip\": \"127.0.0.1\",\n",
+      "  \"iopub_port\": 62400\n",
       "}\n",
       "\n",
       "Paste the above JSON into a file, and connect with:\n",
       "    $> ipython <app> --existing <file>\n",
       "or, if you are local, you can connect with just:\n",
-      "    $> ipython <app> --existing kernel-30f00f4a-230c-4e64-bea5-0e5f6a52cb40.json \n",
+      "    $> ipython <app> --existing kernel-25383540-ce7f-4529-900a-ded0e510d5d8.json \n",
       "or even just:\n",
       "    $> ipython <app> --existing \n",
       "if this is the most recent IPython session you have started.\n"
      ]
     }
    ],
    "source": [
     "%connect_info"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "We can connect automatically a Qt Console to the currently running kernel with the `%qtconsole` magic, or by typing `ipython console --existing <kernel-UUID>` in any terminal:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 47,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%qtconsole"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
     "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.4.2"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
 }

examples/IPython Kernel/Capturing Output.ipynb

@@ -1,505 +1,505 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Capturing Output With <tt>%%capture</tt>"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "IPython has a [cell magic](Cell Magics.ipynb), `%%capture`, which captures the stdout/stderr of a cell. With this magic you can discard these streams or store them in a variable."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "from __future__ import print_function\n",
     "import sys"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "By default, `%%capture` discards these streams.  This is a simple way to suppress unwanted output."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%%capture\n",
     "print('hi, stdout')\n",
     "print('hi, stderr', file=sys.stderr)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "If you specify a name, then stdout/stderr will be stored in an object in your namespace."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%%capture captured\n",
     "print('hi, stdout')\n",
     "print('hi, stderr', file=sys.stderr)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "<IPython.utils.capture.CapturedIO at 0x1076c9310>"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "captured"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Calling the object writes the output to stdout/stderr as appropriate."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "hi, stdout\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
       "hi, stderr\n"
      ]
     }
    ],
    "source": [
     "captured()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "'hi, stdout\\n'"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "captured.stdout"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "'hi, stderr\\n'"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "captured.stderr"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "`%%capture` grabs all output types, not just stdout/stderr, so you can do plots and use IPython's display system inside `%%capture`"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%%capture wontshutup\n",
     "\n",
     "print(\"setting up X\")\n",
     "x = np.linspace(0,5,1000)\n",
     "print(\"step 2: constructing y-data\")\n",
     "y = np.sin(x)\n",
     "print(\"step 3: display info about y\")\n",
     "plt.plot(x,y)\n",
     "print(\"okay, I'm done now\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "setting up X\n",
       "step 2: constructing y-data\n",
       "step 3: display info about y\n",
       "okay, I'm done now\n"
      ]
     },
     {
      "data": {
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        "o49CvXolz33OQt+lSxd27dp11j+fOHEiPXr0OO8XDwkJKXkyEREHu+giuPZa80pJgZwcU6AzMuCV\n",
        "V8yoPzcXqlUzxyzUqAEXXGA+1+uF/fvNaZp79ph/1qCBebVqZVb8tGwJF17oo7DeUkpMTPRu2LCh\n",
        "wD9bs2aNt2vXric/njhxonfSpEkFPluvXj0voJdeeumlVzFe9erVO2+d9knrxltIcyo+Pp5t27ax\n",
        "Y8cOateuzdy5c0lNTS3w2e1OXL8kIuICJZ6MXbBgAZGRkWRkZNC9e3euu+46AL7//nu6d+8OQGho\n",
        "KCkpKXTt2pVGjRrRp08fYmNjfZNcRESKxDFHIIiIiH9Y3xmrDVWnDBo0iLCwMJoGyiEbfpKdnU2H\n",
        "Dh1o3LgxTZo04aWXXrIdyZpff/2VNm3a0KJFCxo1asQjjzxiO5J1+fn5xMXFFWlBiJtFRUXRrFkz\n",
        "4uLiuPw8ay2tjujz8/Np2LAhK1asIDw8nNatW5Oamhq07Z1Vq1ZRuXJlbr/9djZu3Gg7jjW7du1i\n",
        "165dtGjRgl9++YVWrVqxcOHCoP3v4tChQ1SsWJFjx47Rrl07nnvuOdq1a2c7ljUvvPACGzZs4MCB\n",
        "AyxevNh2HGvq1q3Lhg0bqF69+nmftTqi14aq0yUkJFCtWjXbMayrWbMmLVq0AKBy5crExsbyfVlu\n",
        "Q3SYihUrAnDkyBHy8/OL9BfbrXJyckhLS+OOO+7QabcUvhDmTFYLfUEbqnJzcy0mEqfZsWMHWVlZ\n",
        "tGnTxnYUa44fP06LFi0ICwujQ4cONGrUyHYka+6//34mT55MuXLWu87WhYSE0LlzZ+Lj45k+ffo5\n",
        "n7X63dKGKjmXX375hZtvvpkpU6ZQuXJl23GsKVeuHJ9//jk5OTl88sknQXsUwpIlS7jsssuIi4vT\n",
        "aB5IT08nKyuLpUuX8ve//51Vq1YV+qzVQh8eHk52dvbJj7Ozs4mIiLCYSJzi6NGj3HTTTdx66630\n",
        "7NnTdhxHqFKlCt27d2f9+vW2o1ixevVqFi9eTN26denXrx8fffQRt99+u+1Y1tSqVQuAP/3pT9x4\n",
        "441kZmYW+qzVQv/HDVVHjhxh7ty5JCUl2YwkDuD1ehk8eDCNGjVi5MiRtuNYtWfPHvbt2wfA4cOH\n",
        "+eCDD4iLi7Ocyo6JEyeSnZ3Nt99+y5w5c+jYsSOzZs2yHcuKQ4cOceDAAQAOHjzI8uXLz7laz2qh\n",
        "14aq0/VNJLb3AAAAlUlEQVTr14+2bduydetWIiMjmTFjhu1IVqSnpzN79mxWrlxJXFwccXFxLFu2\n",
        "zHYsK3bu3EnHjh1p0aIFbdq0oUePHnTq1Ml2LEcI5tZvXl4eCQkJJ/+7uP7667nmmmsKfV4bpkRE\n",
        "XE5T1yIiLqdCLyLicir0IiIup0IvIuJyKvQiIi6nQi8i4nIq9CIiLqdCLyLicv8PoaUAhzXYTeQA\n",
        "AAAASUVORK5CYII=\n"
       ],
       "text/plain": [
        "<matplotlib.figure.Figure at 0x10866ae90>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "wontshutup()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "And you can selectively disable capturing stdout, stderr or rich display, by passing `--no-stdout`, `--no-stderr` and `--no-display`"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
       "hello, stderr\n"
      ]
     }
    ],
    "source": [
     "%%capture cap --no-stderr\n",
     "print('hi, stdout')\n",
     "print(\"hello, stderr\", file=sys.stderr)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 12,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "'hi, stdout\\n'"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "cap.stdout"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "''"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "cap.stderr"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "[]"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "cap.outputs"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
     "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.4.2"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
 }

examples/IPython Kernel/Cell Magics.ipynb

@@ -1,717 +1,689 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Cell Magics in IPython"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "IPython has a system of commands we call 'magics' that provide effectively a mini command language that is orthogonal to the syntax of Python and is extensible by the user with new commands.  Magics are meant to be typed interactively, so they use command-line conventions, such as using whitespace for separating arguments, dashes for options and other conventions typical of a command-line environment.\n",
+    "IPython has a system of commands we call 'magics' that provide a mini command language that is orthogonal to the syntax of Python and is extensible by the user with new commands.  Magics are meant to be typed interactively, so they use command-line conventions, such as using whitespace for separating arguments, dashes for options and other conventions typical of a command-line environment.\n",
     "\n",
     "Magics come in two kinds:\n",
     "\n",
     "* Line magics: these are commands prepended by one `%` character and whose arguments only extend to the end of the current line.\n",
     "* Cell magics: these use *two* percent characters as a marker (`%%`), and they receive as argument *both* the current line where they are declared and the whole body of the cell.  Note that cell magics can *only* be used as the first line in a cell, and as a general principle they can't be 'stacked' (i.e. you can only use one cell magic per cell).  A few of them, because of how they operate, can be stacked, but that is something you will discover on a case by case basis.\n",
     "\n",
     "The `%lsmagic` magic is used to list all available magics, and it will show both line and cell magics currently defined:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "application/json": {
        "cell": {
         "!": "OSMagics",
         "HTML": "Other",
         "SVG": "Other",
         "bash": "Other",
         "capture": "ExecutionMagics",
         "debug": "ExecutionMagics",
         "file": "Other",
         "html": "DisplayMagics",
         "javascript": "DisplayMagics",
         "latex": "DisplayMagics",
         "perl": "Other",
         "prun": "ExecutionMagics",
         "pypy": "Other",
         "python": "Other",
+        "python2": "Other",
         "python3": "Other",
         "ruby": "Other",
         "script": "ScriptMagics",
         "sh": "Other",
         "svg": "DisplayMagics",
         "sx": "OSMagics",
         "system": "OSMagics",
         "time": "ExecutionMagics",
         "timeit": "ExecutionMagics",
         "writefile": "OSMagics"
        },
        "line": {
         "alias": "OSMagics",
         "alias_magic": "BasicMagics",
         "autocall": "AutoMagics",
         "automagic": "AutoMagics",
         "autosave": "KernelMagics",
         "bookmark": "OSMagics",
+        "cat": "Other",
         "cd": "OSMagics",
         "clear": "KernelMagics",
         "colors": "BasicMagics",
         "config": "ConfigMagics",
         "connect_info": "KernelMagics",
+        "cp": "Other",
         "debug": "ExecutionMagics",
         "dhist": "OSMagics",
         "dirs": "OSMagics",
-        "doctest_mode": "KernelMagics",
+        "doctest_mode": "BasicMagics",
         "ed": "Other",
         "edit": "KernelMagics",
         "env": "OSMagics",
-        "gist": "Other",
         "gui": "BasicMagics",
         "hist": "Other",
         "history": "HistoryMagics",
         "install_default_config": "DeprecatedMagics",
         "install_ext": "ExtensionMagics",
         "install_profiles": "DeprecatedMagics",
         "killbgscripts": "ScriptMagics",
+        "ldir": "Other",
         "less": "KernelMagics",
+        "lf": "Other",
+        "lk": "Other",
+        "ll": "Other",
         "load": "CodeMagics",
         "load_ext": "ExtensionMagics",
         "loadpy": "CodeMagics",
         "logoff": "LoggingMagics",
         "logon": "LoggingMagics",
         "logstart": "LoggingMagics",
         "logstate": "LoggingMagics",
         "logstop": "LoggingMagics",
+        "ls": "Other",
         "lsmagic": "BasicMagics",
+        "lx": "Other",
         "macro": "ExecutionMagics",
         "magic": "BasicMagics",
         "man": "KernelMagics",
         "matplotlib": "PylabMagics",
+        "mkdir": "Other",
         "more": "KernelMagics",
+        "mv": "Other",
         "notebook": "BasicMagics",
         "page": "BasicMagics",
         "pastebin": "CodeMagics",
         "pdb": "ExecutionMagics",
         "pdef": "NamespaceMagics",
         "pdoc": "NamespaceMagics",
         "pfile": "NamespaceMagics",
         "pinfo": "NamespaceMagics",
         "pinfo2": "NamespaceMagics",
         "popd": "OSMagics",
         "pprint": "BasicMagics",
         "precision": "BasicMagics",
         "profile": "BasicMagics",
         "prun": "ExecutionMagics",
         "psearch": "NamespaceMagics",
         "psource": "NamespaceMagics",
         "pushd": "OSMagics",
         "pwd": "OSMagics",
         "pycat": "OSMagics",
         "pylab": "PylabMagics",
         "qtconsole": "KernelMagics",
         "quickref": "BasicMagics",
         "recall": "HistoryMagics",
         "rehashx": "OSMagics",
         "reload_ext": "ExtensionMagics",
         "rep": "Other",
         "rerun": "HistoryMagics",
         "reset": "NamespaceMagics",
         "reset_selective": "NamespaceMagics",
+        "rm": "Other",
+        "rmdir": "Other",
         "run": "ExecutionMagics",
         "save": "CodeMagics",
         "sc": "OSMagics",
+        "set_env": "OSMagics",
         "store": "StoreMagics",
         "sx": "OSMagics",
         "system": "OSMagics",
         "tb": "ExecutionMagics",
-        "tic": "TimerMagics",
         "time": "ExecutionMagics",
         "timeit": "ExecutionMagics",
-        "toc": "TimerMagics",
         "unalias": "OSMagics",
         "unload_ext": "ExtensionMagics",
         "who": "NamespaceMagics",
         "who_ls": "NamespaceMagics",
         "whos": "NamespaceMagics",
         "xdel": "NamespaceMagics",
         "xmode": "BasicMagics"
        }
       },
       "text/plain": [
        "Available line magics:\n",
-       "%alias  %alias_magic  %autocall  %automagic  %autosave  %bookmark  %cd  %clear  %colors  %config  %connect_info  %debug  %dhist  %dirs  %doctest_mode  %ed  %edit  %env  %gist  %gui  %hist  %history  %install_default_config  %install_ext  %install_profiles  %killbgscripts  %less  %load  %load_ext  %loadpy  %logoff  %logon  %logstart  %logstate  %logstop  %lsmagic  %macro  %magic  %man  %matplotlib  %more  %notebook  %page  %pastebin  %pdb  %pdef  %pdoc  %pfile  %pinfo  %pinfo2  %popd  %pprint  %precision  %profile  %prun  %psearch  %psource  %pushd  %pwd  %pycat  %pylab  %qtconsole  %quickref  %recall  %rehashx  %reload_ext  %rep  %rerun  %reset  %reset_selective  %run  %save  %sc  %store  %sx  %system  %tb  %tic  %time  %timeit  %toc  %unalias  %unload_ext  %who  %who_ls  %whos  %xdel  %xmode\n",
+       "%alias  %alias_magic  %autocall  %automagic  %autosave  %bookmark  %cat  %cd  %clear  %colors  %config  %connect_info  %cp  %debug  %dhist  %dirs  %doctest_mode  %ed  %edit  %env  %gui  %hist  %history  %install_default_config  %install_ext  %install_profiles  %killbgscripts  %ldir  %less  %lf  %lk  %ll  %load  %load_ext  %loadpy  %logoff  %logon  %logstart  %logstate  %logstop  %ls  %lsmagic  %lx  %macro  %magic  %man  %matplotlib  %mkdir  %more  %mv  %notebook  %page  %pastebin  %pdb  %pdef  %pdoc  %pfile  %pinfo  %pinfo2  %popd  %pprint  %precision  %profile  %prun  %psearch  %psource  %pushd  %pwd  %pycat  %pylab  %qtconsole  %quickref  %recall  %rehashx  %reload_ext  %rep  %rerun  %reset  %reset_selective  %rm  %rmdir  %run  %save  %sc  %set_env  %store  %sx  %system  %tb  %time  %timeit  %unalias  %unload_ext  %who  %who_ls  %whos  %xdel  %xmode\n",
        "\n",
        "Available cell magics:\n",
-       "%%!  %%HTML  %%SVG  %%bash  %%capture  %%debug  %%file  %%html  %%javascript  %%latex  %%perl  %%prun  %%pypy  %%python  %%python3  %%ruby  %%script  %%sh  %%svg  %%sx  %%system  %%time  %%timeit  %%writefile\n",
+       "%%!  %%HTML  %%SVG  %%bash  %%capture  %%debug  %%file  %%html  %%javascript  %%latex  %%perl  %%prun  %%pypy  %%python  %%python2  %%python3  %%ruby  %%script  %%sh  %%svg  %%sx  %%system  %%time  %%timeit  %%writefile\n",
        "\n",
        "Automagic is ON, % prefix IS NOT needed for line magics."
       ]
      },
      "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "%lsmagic"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Since in the introductory section we already covered the most frequently used line magics, we will focus here on the cell magics, which offer a great amount of power.\n",
     "\n",
     "Let's load matplotlib and numpy so we can use numerics/plotting at will later on."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## <!--====--> Some simple cell magics"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Timing the execution of code; the 'timeit' magic exists both in line and cell form:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "100 loops, best of 3: 6.05 ms per loop\n"
+      "100 loops, best of 3: 7.06 ms per loop\n"
      ]
     }
    ],
    "source": [
     "%timeit np.linalg.eigvals(np.random.rand(100,100))"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "100 loops, best of 3: 6.07 ms per loop\n"
+      "100 loops, best of 3: 7.4 ms per loop\n"
      ]
     }
    ],
    "source": [
     "%%timeit a = np.random.rand(100, 100)\n",
     "np.linalg.eigvals(a)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The `%%capture` magic can be used to capture the stdout/err of any block of python code, either to discard it (if it's noise to you) or to store it in a variable for later use:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%%capture capt\n",
     "from __future__ import print_function\n",
     "import sys\n",
     "print('Hello stdout')\n",
     "print('and stderr', file=sys.stderr)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "('Hello stdout\\n', 'and stderr\\n')"
       ]
      },
      "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "capt.stdout, capt.stderr"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Hello stdout\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
       "and stderr\n"
      ]
     }
    ],
    "source": [
     "capt.show()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The `%%writefile` magic is a very useful tool that writes the cell contents as a named file:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Writing foo.py\n"
      ]
     }
    ],
    "source": [
     "%%writefile foo.py\n",
     "print('Hello world')"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Hello world\n"
      ]
     }
    ],
    "source": [
     "%run foo"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## <!--====--> Magics for running code under other interpreters"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "IPython has a `%%script` cell magic, which lets you run a cell in\n",
     "a subprocess of any interpreter on your system, such as: bash, ruby, perl, zsh, R, etc.\n",
     "\n",
     "It can even be a script of your own, which expects input on stdin."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "To use it, simply pass a path or shell command to the program you want to run on the `%%script` line,\n",
     "and the rest of the cell will be run by that script, and stdout/err from the subprocess are captured and displayed."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "hello from Python 2.7.2 (default, Oct 11 2012, 20:14:37) \n",
-      "[GCC 4.2.1 Compatible Apple Clang 4.0 (tags/Apple/clang-418.0.60)]\n"
+      "hello from Python 2.7.9 (default, Jan 29 2015, 06:27:40) \n",
+      "[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.56)]\n"
      ]
     }
    ],
    "source": [
-    "%%script python\n",
+    "%%script python2\n",
     "import sys\n",
     "print 'hello from Python %s' % sys.version"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "hello from Python: 3.3.1 (v3.3.1:d9893d13c628, Apr  6 2013, 11:07:11) \n",
-      "[GCC 4.2.1 (Apple Inc. build 5666) (dot 3)]\n"
+      "hello from Python: 3.4.2 |Continuum Analytics, Inc.| (default, Oct 21 2014, 17:42:20) \n",
+      "[GCC 4.2.1 (Apple Inc. build 5577)]\n"
      ]
     }
    ],
    "source": [
     "%%script python3\n",
     "import sys\n",
     "print('hello from Python: %s' % sys.version)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "IPython also creates aliases for a few common interpreters, such as bash, ruby, perl, etc.\n",
     "\n",
     "These are all equivalent to `%%script <name>`"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Hello from Ruby 1.9.3\n"
+      "Hello from Ruby 2.0.0\n"
      ]
     }
    ],
    "source": [
     "%%ruby\n",
     "puts \"Hello from Ruby #{RUBY_VERSION}\""
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "hello from /usr/local/bin/bash\n"
      ]
     }
    ],
    "source": [
     "%%bash\n",
     "echo \"hello from $BASH\""
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Exercise: write your own script that numbers input lines"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Write a file, called `lnum.py`, such that the following cell works as shown (hint: don't forget about the executable bit!): "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0: my first line\n",
-      "1: my second\n",
-      "2: more\n",
-      "---- END ----\n"
-     ]
-    }
-   ],
-   "source": [
-    "%%script ./lnum.py\n",
-    "my first line\n",
-    "my second\n",
-    "more"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
     "## Capturing output"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "You can also capture stdout/err from these subprocesses into Python variables, instead of letting them go directly to stdout/err"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "hi, stdout\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
       "hello, stderr\n"
      ]
     }
    ],
    "source": [
     "%%bash\n",
     "echo \"hi, stdout\"\n",
     "echo \"hello, stderr\" >&2\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 15,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%%bash --out output --err error\n",
     "echo \"hi, stdout\"\n",
     "echo \"hello, stderr\" >&2"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 16,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "hello, stderr\n",
       "\n",
       "hi, stdout\n",
       "\n"
      ]
     }
    ],
    "source": [
     "print(error)\n",
     "print(output)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Background Scripts"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "These scripts can be run in the background, by adding the `--bg` flag.\n",
     "\n",
     "When you do this, output is discarded unless you use the `--out/err`\n",
     "flags to store output as above."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 17,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Starting job # 0 in a separate thread.\n"
      ]
     }
    ],
    "source": [
     "%%ruby --bg --out ruby_lines\n",
     "for n in 1...10\n",
     "    sleep 1\n",
     "    puts \"line #{n}\"\n",
     "    STDOUT.flush\n",
     "end"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "When you do store output of a background thread, these are the stdout/err *pipes*,\n",
     "rather than the text of the output."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 18,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<open file '<fdopen>', mode 'rb' at 0x112cd55d0>"
+       "<_io.BufferedReader name=52>"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "ruby_lines"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 19,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "line 1\n",
       "line 2\n",
       "line 3\n",
       "line 4\n",
       "line 5\n",
       "line 6\n",
       "line 7\n",
       "line 8\n",
       "line 9\n",
       "\n"
      ]
     }
    ],
    "source": [
-    "print(ruby_lines.read())"
+    "print(ruby_lines.read().decode('utf8'))"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
     "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.4.2"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
 }

examples/IPython Kernel/Custom Display Logic.ipynb

@@ -1,1341 +1,1556 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Custom Display Logic"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Overview"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "As described in the [Rich Output](Rich Output.ipynb) tutorial, the IPython display system can display rich representations of objects in the following formats:\n",
     "\n",
     "* JavaScript\n",
     "* HTML\n",
     "* PNG\n",
     "* JPEG\n",
     "* SVG\n",
     "* LaTeX\n",
     "* PDF\n",
     "\n",
     "This Notebook shows how you can add custom display logic to your own classes, so that they can be displayed using these rich representations. There are two ways of accomplishing this:\n",
     "\n",
     "1. Implementing special display methods such as `_repr_html_` when you define your class.\n",
     "2. Registering a display function for a particular existing class.\n",
     "\n",
     "This Notebook describes and illustrates both approaches."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Import the IPython display functions."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "from IPython.display import (\n",
     "    display, display_html, display_png, display_svg\n",
     ")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Parts of this notebook need the matplotlib inline backend:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Special display methods"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The main idea of the first approach is that you have to implement special display methods when you define your class, one for each representation you want to use. Here is a list of the names of the special methods and the values they must return:\n",
     "\n",
     "* `_repr_html_`: return raw HTML as a string\n",
-    "* `_repr_json_`: return raw JSON as a string\n",
+    "* `_repr_json_`: return a JSONable dict\n",
     "* `_repr_jpeg_`: return raw JPEG data\n",
     "* `_repr_png_`: return raw PNG data\n",
     "* `_repr_svg_`: return raw SVG data as a string\n",
     "* `_repr_latex_`: return LaTeX commands in a string surrounded by \"$\"."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "As an illustration, we build a class that holds data generated by sampling a Gaussian distribution with given mean and standard deviation. Here is the definition of the `Gaussian` class, which has a custom PNG and LaTeX representation."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "from IPython.core.pylabtools import print_figure\n",
     "from IPython.display import Image, SVG, Math\n",
     "\n",
     "class Gaussian(object):\n",
     "    \"\"\"A simple object holding data sampled from a Gaussian distribution.\n",
     "    \"\"\"\n",
     "    def __init__(self, mean=0.0, std=1, size=1000):\n",
     "        self.data = np.random.normal(mean, std, size)\n",
     "        self.mean = mean\n",
     "        self.std = std\n",
     "        self.size = size\n",
     "        # For caching plots that may be expensive to compute\n",
     "        self._png_data = None\n",
     "        \n",
     "    def _figure_data(self, format):\n",
     "        fig, ax = plt.subplots()\n",
     "        ax.hist(self.data, bins=50)\n",
     "        ax.set_title(self._repr_latex_())\n",
     "        ax.set_xlim(-10.0,10.0)\n",
     "        data = print_figure(fig, format)\n",
     "        # We MUST close the figure, otherwise IPython's display machinery\n",
     "        # will pick it up and send it as output, resulting in a double display\n",
     "        plt.close(fig)\n",
     "        return data\n",
     "        \n",
     "    def _repr_png_(self):\n",
     "        if self._png_data is None:\n",
     "            self._png_data = self._figure_data('png')\n",
     "        return self._png_data\n",
     "    \n",
     "    def _repr_latex_(self):\n",
     "        return r'$\\mathcal{N}(\\mu=%.2g, \\sigma=%.2g),\\ N=%d$' % (self.mean,\n",
     "                                                                 self.std, self.size)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Create an instance of the Gaussian distribution and return it to display the default representation:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
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+       "ttZgNSZXYyarX5G5/LrJz9vkatC/P/zYtmc84xnnr2fNkAhRzJeXJtkz4xo4gfv/5mPlf//Vwa1J\n",
+       "svNzzjnyscePPbHq7rpdCwdvvHvf5y6da2sNVmNyNWay+hWZy6+b/LwtXw1qlSfT0B2iaq0/leQF\n",
+       "Gc2r+v7W2t51qwoAYM51TSyvtb4iySdaay9O8sokP7muVQEAzLne1XkvS/JbSdJaO5jkz2qtz1m3\n",
+       "qgAA5lzvcN55SR6ZaH9kfOyvTroiYK699LnnPvZZ55z90SR53qc9/WkPHzoy65IAZqIMw7Dmi2qt\n",
+       "NyV5U2vtveP2Lya5qbX2/snz7rrrrrW/OADAjFx22WVltef23om6K8k3J3lvrXVbkouXB6i1FgIA\n",
+       "sJF0zYlqrf1BktRa35HkLUl+cD2LAgCYd13DeQAAZzp75wEAdBCiAAA6CFEAAB2mtnderfUlSX43\n",
+       "yZe21j48Pva9Sb4po/D2htbam6f1/mxMtdarM1qo8OHxoe9trb1ndhUxb2w5xVrUWh9NsvR/yFtb\n",
+       "azfPsh7my/gJA29K8vbW2s211ouT3JLkWJL7k1zTWnvKyeNTCVG11s9O8m1J7k5Sxsd2JHlBa+1F\n",
+       "tdbNSe6utb6ttfb306iBDWtI8uOttd+ddSHMn8ktp2qtn5rkzUkuPcFlnNn2ttYun3URzK2bMnrK\n",
+       "wDPH7d1JrmitLdZar01yZZLbnuriqQzntdY+0Fr7tiSPZ/RHMUlemuS3x/1Hk/zXJDun8f5seD9Q\n",
+       "a31XrXX3rAth7thyirX64lrrPbXWu2qtz551McyX1to1Sd6XJLXWrUkea60tjrtvS7JrpetP6k5U\n",
+       "rfXzk/zsssMfaq1dfZzTz0vy3on20lYxnIGe6rOT5Dtba78xPufnaq0vX3ouGcSWU6zdc1trj9da\n",
+       "vzrJG5JcNeuCmFvnJnl0ov1ITpBTTipEtdb+PMlqb5M+mmT7RPvTk/zFybw/G9cqPzu/l+TLkwhR\n",
+       "LFn6f+Svx+3teXKogidprT0+/vquWuv2E53PGe1AnhyatufJoeqTnIrVeUtbv9yd5NVJUmv9lCSv\n",
+       "TGJCKE9Sa31trfUzxs2vS3LvLOth7ixtObU0IfS4W05BktRad9Zarxh///z8Q/iGT9JaO5xka631\n",
+       "gvGhq5LcudI1pyJEDUnSWnsgyR/VWv9XknuS/FRrzfbvLPd/kry51vr2JI+21vbMuB7miC2nWKP7\n",
+       "klxVa92T5Pokr5ttOcyxpfnb1ya5ffw36Hmttd9e6SLbvgAAdPCwTQCADkIUAEAHIQoAoIMQBQDQ\n",
+       "QYgCAOggRAEAdBCiAAA6CFEAAB2EKACADv8fn0xUCxJB1sMAAAAASUVORK5CYII=\n"
       ],
       "text/latex": [
        "$\\mathcal{N}(\\mu=2, \\sigma=1),\\ N=1000$"
       ],
       "text/plain": [
-       "<__main__.Gaussian at 0x106e7ae10>"
+       "<__main__.Gaussian at 0x10665a4e0>"
       ]
      },
      "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "x = Gaussian(2.0, 1.0)\n",
     "x"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "You can also pass the object to the `display` function to display the default representation:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
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+       "rLJjhuXAaU+IAjhNHDh8dMuN473ykuS6XQsHZ1kPnO4M5wEAdBCiAAA6CFEAAB3MiQI4CXsf3H/r\n",
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+       "ANBBiAIA6CBEAQB0EKIAADqYWA6wBpOr8ZL5XpHXa/JntIoPnpoQBbAGk6vxkvlekddr8me0ig+e\n",
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+       "8dCRhaX2+eecvW/nRRdePbuK4NQSogDosnjoyMIN4xV+SXL9roUZVgOn3oohqtZ6VpJfSPKFGQ39\n",
+       "/UiSDyW5JcmxJPcnuaa1Nky5TgCAuXKiOVFfkuSB1tpLkrwqyeuS7E5yRWvt0iQPJLlyuiUCAMyf\n",
+       "Fe9Etdb+NMmfjptPT/K3SUprbXF87LYkN4+/AgCcMVa1Oq/Wel6S/5DkZ5McmOh6JMl5U6gLAGCu\n",
+       "nXBiea31M5K8Mcn3Jflgku+f6N6e5NHplAbAvJlckWfPPc50K96JqrV+VpJbk7ymtfZga+1wkq21\n",
+       "1gvGp1yV5M7plgjAvFhakXfD3fsuPfqJYcus64FZOtGdqGuTPCfJr9dak9Fdp2uT3F5rPZbkvtba\n",
+       "7umWCAAwf040sfzajELTcpdMpxwAgI3Bti8AAB2EKACADrZ9AeApbdu6eccd9z60Z6ltRR78AyEK\n",
+       "gKd04PDRLTdO7I933a6Fg7OsB+aJ4TwAgA5CFABAByEKAKCDEAUA0EGIAgDoIEQBAHQQogAAOghR\n",
+       "AAAdhCgAgA6eWA6ctvY+uP/WxUNHFpLk/HPO3rfzoguvnm1FwOlEiAJOW4uHjizcMN6y5PpdCzOu\n",
+       "BjjdGM4DAOggRAEAdBCiAAA6CFEAAB1MLAdgXWzbunnHHfc+tGepbUUkpzshCoB1ceDw0S03jldD\n",
+       "JlZEcvoznAcA0EGIAgDoIEQBAHQQogAAOghRAAAdhCgAgA5CFABAByEKAKCDEAUA0EGIAgDoIEQB\n",
+       "AHQQogAAOghRAAAdhCgAgA5CFABAh82zLgBgvex9cP+ti4eOLCy1N51VdsywHOA0J0QBp43FQ0cW\n",
+       "brh736VL7et2LRycZT3A6c1wHgBAByEKAKCDEAUA0EGIAgDoIEQBAHQQogAAOghRAAAdhCgAgA5C\n",
+       "FABAByEKAKCDbV+AM8K2rZt33HHvQ3uW2vbVA07WCUNUrXVbkjcleXtr7eZa68VJbklyLMn9Sa5p\n",
+       "rQ3TLRPg5Bw4fHTLjfbVA9bRaobzbkrylon27iRXtNYuTfJAkiunURgAwDw7YYhqrV2T5H1JUmvd\n",
+       "muSx1triuPu2JLumVx4AwHxa68Tyc5M8OtF+JMl561cOAMDGsNaJ5Qfy5NC0PU8OVQBTtffB/bcu\n",
+       "HjqysNQ+/5yz9+286MKrZ1cRT2VyMr/fE6ejNYWo1trhWuvWWusFrbWHk1yV5M7plAbwyRYPHVm4\n",
+       "YWKC+PW7FmZYDSuZnMzv98TpaC0hamkF3rVJbq+1HktyX2tt9/qXBQAw31YVolprb0/y9vH39ye5\n",
+       "ZJpFAQDMO08sBwDoIEQBAHSw7QuwoU2uALOVC3AqCVHAhja5AsxWLsCpZDgPAKCDEAUA0EGIAgDo\n",
+       "IEQBAHQQogAAOghRAAAdhCgAgA5CFABAByEKAKCDEAUA0EGIAgDoIEQBAHQQogAAOghRAAAdhCgA\n",
+       "gA6bZ10AwEr2Prj/1sVDRxaW2pvOKjtmWA7AE4QoYK4tHjqycMPd+y5dal+3a+HgLOsBWGI4DwCg\n",
+       "gxAFANBBiAIA6CBEAQB0MLEcmLnlK/DOP+fsfTsvuvDq2VXEetu2dfOOO+59aM9Se6Xf8eTnwWeB\n",
+       "eSZEATO3fAXe9bsWZlgN03Dg8NEtN67ydzz5efBZYJ4ZzgMA6CBEAQB0EKIAADoIUQAAHUwsB+CU\n",
+       "m1ytt9IKvLWs6oNTTYgC4JSbXK230gq8tazqg1PNcB4AQAchCgCggxAFANBBiAIA6GBiOQAbxmpX\n",
+       "9S1nf0amQYgCYMNY7aq+5ezPyDQYzgMA6CBEAQB0EKIAADqYEwWcEmuZ2Ds5eXjTWWXHKSkQYI2E\n",
+       "KOCUWMvE3snJw9ftWjg4/eoA1s5wHgBAByEKAKCDEAUA0MGcKGDVDhw4sDXJxROHPn7uuee+d1b1\n",
+       "AMySEMXcqLW+tLW2Z9Z1sKKFO/7sb+58919/9Owk+fov2P7+Z33ksXcurbo7/1lPe/biRx//4NLJ\n",
+       "ttZgNSZXYyarX5G5/LrJz9vkatC/P/zYtmc84xnnr2fNkAhRzJeXJtkz4xo4gfv/5mPlf//Vwa1J\n",
+       "svNzzjnyscePPbHq7rpdCwdvvHvf5y6da2sNVmNyNWay+hWZy6+b/LwtXw1qlSfT0B2iaq0/leQF\n",
+       "Gc2r+v7W2t51qwoAYM51TSyvtb4iySdaay9O8sokP7muVQEAzLne1XkvS/JbSdJaO5jkz2qtz1m3\n",
+       "qgAA5lzvcN55SR6ZaH9kfOyvTroiYK699LnnPvZZ55z90SR53qc9/WkPHzoy65IAZqIMw7Dmi2qt\n",
+       "NyV5U2vtveP2Lya5qbX2/snz7rrrrrW/OADAjFx22WVltef23om6K8k3J3lvrXVbkouXB6i1FgIA\n",
+       "sJF0zYlqrf1BktRa35HkLUl+cD2LAgCYd13DeQAAZzp75wEAdBCiAAA6CFEAAB2mtnderfUlSX43\n",
+       "yZe21j48Pva9Sb4po/D2htbam6f1/mxMtdarM1qo8OHxoe9trb1ndhUxb2w5xVrUWh9NsvR/yFtb\n",
+       "azfPsh7my/gJA29K8vbW2s211ouT3JLkWJL7k1zTWnvKyeNTCVG11s9O8m1J7k5Sxsd2JHlBa+1F\n",
+       "tdbNSe6utb6ttfb306iBDWtI8uOttd+ddSHMn8ktp2qtn5rkzUkuPcFlnNn2ttYun3URzK2bMnrK\n",
+       "wDPH7d1JrmitLdZar01yZZLbnuriqQzntdY+0Fr7tiSPZ/RHMUlemuS3x/1Hk/zXJDun8f5seD9Q\n",
+       "a31XrXX3rAth7thyirX64lrrPbXWu2qtz551McyX1to1Sd6XJLXWrUkea60tjrtvS7JrpetP6k5U\n",
+       "rfXzk/zsssMfaq1dfZzTz0vy3on20lYxnIGe6rOT5Dtba78xPufnaq0vX3ouGcSWU6zdc1trj9da\n",
+       "vzrJG5JcNeuCmFvnJnl0ov1ITpBTTipEtdb+PMlqb5M+mmT7RPvTk/zFybw/G9cqPzu/l+TLkwhR\n",
+       "LFn6f+Svx+3teXKogidprT0+/vquWuv2E53PGe1AnhyatufJoeqTnIrVeUtbv9yd5NVJUmv9lCSv\n",
+       "TGJCKE9Sa31trfUzxs2vS3LvLOth7ixtObU0IfS4W05BktRad9Zarxh///z8Q/iGT9JaO5xka631\n",
+       "gvGhq5LcudI1pyJEDUnSWnsgyR/VWv9XknuS/FRrzfbvLPd/kry51vr2JI+21vbMuB7miC2nWKP7\n",
+       "klxVa92T5Pokr5ttOcyxpfnb1ya5ffw36Hmttd9e6SLbvgAAdPCwTQCADkIUAEAHIQoAoIMQBQDQ\n",
+       "QYgCAOggRAEAdBCiAAA6CFEAAB2EKACADv8fn0xUCxJB1sMAAAAASUVORK5CYII=\n"
       ],
       "text/latex": [
        "$\\mathcal{N}(\\mu=2, \\sigma=1),\\ N=1000$"
       ],
       "text/plain": [
-       "<__main__.Gaussian at 0x106e7ae10>"
+       "<__main__.Gaussian at 0x10665a4e0>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "display(x)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Use `display_png` to view the PNG representation:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "image/png": [
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-       "kO0fz9ncvZu9956z9+yefXbfr5mdPefZs7tPbnY/++z3POcsSJIkSZIkSZIkSZIkSZIkSZIkSZJ6\n",
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-       "+I8mjz3Xvi0Gfly3vhc4KtkuS7t6jKUVQXhzvwysB94B/AQh3B+o22Z+w31+DvjvZLmUrLc6iq5Z\n",
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-       "d9Z29RhH5FoE/ChZniDUeq8CngU+W7fdKw33uxD4erK8Eni0yWNnKSWUgLXAB4AXgBOY/KCo+WDS\n",
-       "p9oo87C6vrfynDD9iHwR6UOvfkB0C+ED7Qngr3Lu2w7Ct5Ca1xBG/s+nbD8maZfUI44izET5babO\n",
-       "ZDgT+D8OroePMvVr+YPATyfLHweuBFbNoT8fItSklxC+DbwtaT+ZyaC8kTAtEEJd/1NzeL6aS2k+\n",
-       "a+Uq4Bfr1uv7Ue8QwjeEejcT6v55920BUz8wtxC+PWVtV49p/Lqs/lEGvkUoCdxb174LeAOwmamj\n",
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       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "display_png(x)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-success\">\n",
     "It is important to note a subtle different between <code>display</code> and <code>display_png</code>. The former computes <em>all</em> representations of the object, and lets the notebook UI decide which to display. The later only computes the PNG representation.\n",
     "</div>"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Create a new Gaussian with different parameters:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
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+       "DHqnrk9yRynlTJL7a623tisRAGA8LGfy+vUZBKm5rjz3cmA8HDx0ZN/UyemJhdo3b+p2jbAcANaI\n",
+       "5fRYwYY3dXJ6Yu/+w7sXar9hcuLEKOsBYG2w8joAQCOCFQBAI4IVAEAjghUAQCMmr7Nhne3Jvp0X\n",
+       "nHf48ksv2TO6imBjWezvoL9/jCvBig3rbE/23Tg5McJqYONZ7O+gv3+MK0OBAACNCFYAAI0IVgAA\n",
+       "jQhWAACNmLwOC9i+bcuuO+976MB8bfYCBGA+ghUs4PipR7fetMATS/YCBGA+hgIBABrRYwXAilhs\n",
+       "OD0xpM76JFgBsCIWG05PDKmzPglWAIwV21GxlglWAIwV21Gxlpm8DgDQiGAFANCIYAUA0IhgBQDQ\n",
+       "iMnrjLWzPh10/lOfNfW505+ar80aOgC0Jlgx1s72dNANkxMnbtp/+HkLta1cZQBsRIYCAQAaEawA\n",
+       "ABoRrAAAGhGsAAAaEawAABoRrAAAGhGsAAAaEawAABoRrAAAGhGsAAAasaUNAGvO9m1bdt1530MH\n",
+       "5muzzydrmWAFwJpz/NSjW29aYB9Q+3yylhkKBABoRLACAGhEsAIAaESwAgBoRLACAGhEsAIAaMRy\n",
+       "C4zEwUNH9k2dnJ6Yr23nBecdvvzSS/aMtiJgI1rsZ1Gy+M+jc7mXjUOwYiSmTk5P7F1gTZobJydG\n",
+       "XA2wUS32syhZ/OfRudzLxmEoEACgET1WrHmLdb/b2gKYy3Y4rCbBijVvse53W1sAc9kOh9VkKBAA\n",
+       "oBE9Vqy6xbrt/+bUI9uf9rSn7RxxScAGdS7DiIvd64nBjUOwYtUt1m2f6LoHRudchhEXu9cTgxtH\n",
+       "02BVSnlbkisyGGJ8Q631YMvX59wcP378/Ic/d/r7Huv7br7287ZsOvq8S575O6OuCwDWi2bBqpTy\n",
+       "8iSP1VpfXEr58iTvT7JgLwSr4qs++ODRt//B4b8+f77GPc+/+CPPuyQLBquzLo53/lOfNfW505+a\n",
+       "r82TOMBGttgwYWJh0vWkZY/VS5K8J0lqrSdKKR8vpTyn1vqXDd+Dc/SZz58+c/j438zb9sgXHzu9\n",
+       "2L1nWxzvhsmJEzftP/y8hdqWVCjAOnK2KQ8WJl0/Wgari5IcnXX82eE5wWoN+a7nXnhq5/lP/fx8\n",
+       "bc++cOtTRl0PAKwnXd/3TV6olHJzkttrrR8dHr8jyc211k/Mvu7uu+9u84YAACNw1VVXzTs3eT4t\n",
+       "e6zuTvKaJB8tpWxPctncULXU4gAAxkmzBUJrrb+XJKWUDyX5QJI3tnptAIBx0GwoEABgo7OlDQBA\n",
+       "I4IVAEAjghUAQCMj3SuwlPKdSX4zyTfXWj8zPPf6JN+fQch7S631/aOsibWvlLIng4chPjM89fpa\n",
+       "65+uXkWsNbbTYilKKceSzPwM+WCt9ZbVrIe1Zbiywe1J7qm13lJKuSzJu5KcSfJAkutqrQtOUB9Z\n",
+       "sCqlfHWS1ybZn6QbntuV5Ipa64tKKVuS7C+l/G6tdf6lwdmo+iQ/W2v9zdUuhLXHdlosw8Fa6ytW\n",
+       "uwjWrJszWN3g6cPjW5NcXWudKqVcn+SaJLctdPPIhgJrrZ+stb42yekM/qFMku9K8t5h+6NJfifJ\n",
+       "5aOqibHy46WUPy6l3LrahbDmPGE7rSQfL6U8Z3VLYo37xlLKvaWUu0spz1rtYlhbaq3XJflYkpRS\n",
+       "tiV5pNY6NWy+LcnkYvc377EqpXxdkl+ac/rhWuueeS6/KMlHZx3PbIPDBrTQn50k/6rW+u7hNb9c\n",
+       "SnnZzLppENtpsXTPrbWeLqV8e5K3JLl2tQtizbowybFZx0dzlpzSPFjVWv88yZPtYj2WZMes42ck\n",
+       "+YvWNTEenuSfnd9K8i1JBCtmzPwc+avh8Y48MWjBE9RaTw9//eNSyo6zXc+GdjxPDFI78sSg9SVW\n",
+       "66nAmW1t9id5dZKUUp6S5JVJTDrlCUopbyqlPHN4+D1J7lvNelhzZrbTmpl0Ou92WpAkpZTLSylX\n",
+       "D7//1vxtIIcvUWs9lWRbKeXi4alrk9y12D2rFaz6JKm1PpjkD0spf5Dk3iRvq7VOr1JNrF3/K8n7\n",
+       "Syn3JDlWaz2wyvWwhthOiyW6P8m1pZQDSW5M8ubVLYc1bGY++PVJ7hj+G/Q1tdb3LnaTLW0AABqx\n",
+       "QCgAQCOCFQBAI4IVAEAjghUAQCOCFQBAI4IVAEAjghUAQCOCFQBAI4IVAEAj/x8Ld0kx4zM3zgAA\n",
+       "AABJRU5ErkJggg==\n"
       ],
       "text/latex": [
        "$\\mathcal{N}(\\mu=0, \\sigma=2),\\ N=2000$"
       ],
       "text/plain": [
-       "<__main__.Gaussian at 0x106e9ce90>"
+       "<__main__.Gaussian at 0x106ab8c18>"
       ]
      },
      "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "x2 = Gaussian(0, 2, 2000)\n",
     "x2"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "You can then compare the two Gaussians by displaying their histograms:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "image/png": [
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       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
     {
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       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "display_png(x)\n",
     "display_png(x2)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Note that like `print`, you can call any of the `display` functions multiple times in a cell."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Adding IPython display support to existing objects"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "When you are directly writing your own classes, you can adapt them for display in IPython by following the above approach.  But in practice, you often need to work with existing classes that you can't easily modify. We now illustrate how to add rich output capabilities to existing objects. We will use the NumPy polynomials and change their default representation to be a formatted LaTeX expression."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "First, consider how a NumPy polynomial object renders by default:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Polynomial([ 1.,  2.,  3.], [-10.,  10.], [-1.,  1.])"
+       "Polynomial([ 1.,  2.,  3.], [-10.,  10.], [-1,  1])"
       ]
      },
      "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "p = np.polynomial.Polynomial([1,2,3], [-10, 10])\n",
     "p"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Next, define a function that pretty-prints a polynomial as a LaTeX string:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "def poly_to_latex(p):\n",
     "    terms = ['%.2g' % p.coef[0]]\n",
     "    if len(p) > 1:\n",
     "        term = 'x'\n",
     "        c = p.coef[1]\n",
     "        if c!=1:\n",
     "            term = ('%.2g ' % c) + term\n",
     "        terms.append(term)\n",
     "    if len(p) > 2:\n",
     "        for i in range(2, len(p)):\n",
     "            term = 'x^%d' % i\n",
     "            c = p.coef[i]\n",
     "            if c!=1:\n",
     "                term = ('%.2g ' % c) + term\n",
     "            terms.append(term)\n",
     "    px = '$P(x)=%s$' % '+'.join(terms)\n",
     "    dom = r', $x \\in [%.2g,\\ %.2g]$' % tuple(p.domain)\n",
     "    return px+dom"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "This produces, on our polynomial ``p``, the following:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "'$P(x)=1+2 x+3 x^2$, $x \\\\in [-10,\\\\ 10]$'"
       ]
      },
      "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "poly_to_latex(p)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "You can render this string using the `Latex` class:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/latex": [
        "$P(x)=1+2 x+3 x^2$, $x \\in [-10,\\ 10]$"
       ],
       "text/plain": [
        "<IPython.core.display.Latex object>"
       ]
      },
      "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "from IPython.display import Latex\n",
     "Latex(poly_to_latex(p))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "However, you can configure IPython to do this automatically by registering the `Polynomial` class and the `plot_to_latex` function with an IPython display formatter. Let's look at the default formatters provided by IPython:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "              text/plain : PlainTextFormatter\n",
-      "              image/jpeg : JPEGFormatter\n",
-      "               text/html : HTMLFormatter\n",
-      "           image/svg+xml : SVGFormatter\n",
       "               image/png : PNGFormatter\n",
-      "  application/javascript : JavascriptFormatter\n",
+      "         application/pdf : PDFFormatter\n",
+      "               text/html : HTMLFormatter\n",
+      "              image/jpeg : JPEGFormatter\n",
+      "              text/plain : PlainTextFormatter\n",
       "           text/markdown : MarkdownFormatter\n",
-      "              text/latex : LatexFormatter\n",
       "        application/json : JSONFormatter\n",
-      "         application/pdf : PDFFormatter\n"
+      "  application/javascript : JavascriptFormatter\n",
+      "              text/latex : LatexFormatter\n",
+      "           image/svg+xml : SVGFormatter\n"
      ]
     }
    ],
    "source": [
     "ip = get_ipython()\n",
     "for mime, formatter in ip.display_formatter.formatters.items():\n",
-    "    print '%24s : %s' % (mime, formatter.__class__.__name__)"
+    "    print('%24s : %s' % (mime, formatter.__class__.__name__))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The `formatters` attribute is a dictionary keyed by MIME types. To define a custom LaTeX display function, you want a handle on the `text/latex` formatter:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "ip = get_ipython()\n",
     "latex_f = ip.display_formatter.formatters['text/latex']"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The formatter object has a couple of methods for registering custom display functions for existing types."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Help on method for_type in module IPython.core.formatters:\n",
       "\n",
-      "for_type(self, typ, func=None) method of IPython.core.formatters.LatexFormatter instance\n",
+      "for_type(typ, func=None) method of IPython.core.formatters.LatexFormatter instance\n",
       "    Add a format function for a given type.\n",
       "    \n",
       "    Parameters\n",
       "    -----------\n",
       "    typ : type or '__module__.__name__' string for a type\n",
       "        The class of the object that will be formatted using `func`.\n",
       "    func : callable\n",
       "        A callable for computing the format data.\n",
       "        `func` will be called with the object to be formatted,\n",
       "        and will return the raw data in this formatter's format.\n",
       "        Subclasses may use a different call signature for the\n",
       "        `func` argument.\n",
       "        \n",
       "        If `func` is None or not specified, there will be no change,\n",
       "        only returning the current value.\n",
       "    \n",
       "    Returns\n",
       "    -------\n",
       "    oldfunc : callable\n",
       "        The currently registered callable.\n",
       "        If you are registering a new formatter,\n",
       "        this will be the previous value (to enable restoring later).\n",
       "\n"
      ]
     }
    ],
    "source": [
     "help(latex_f.for_type)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Help on method for_type_by_name in module IPython.core.formatters:\n",
       "\n",
-      "for_type_by_name(self, type_module, type_name, func=None) method of IPython.core.formatters.LatexFormatter instance\n",
+      "for_type_by_name(type_module, type_name, func=None) method of IPython.core.formatters.LatexFormatter instance\n",
       "    Add a format function for a type specified by the full dotted\n",
       "    module and name of the type, rather than the type of the object.\n",
       "    \n",
       "    Parameters\n",
       "    ----------\n",
       "    type_module : str\n",
       "        The full dotted name of the module the type is defined in, like\n",
       "        ``numpy``.\n",
       "    type_name : str\n",
       "        The name of the type (the class name), like ``dtype``\n",
       "    func : callable\n",
       "        A callable for computing the format data.\n",
       "        `func` will be called with the object to be formatted,\n",
       "        and will return the raw data in this formatter's format.\n",
       "        Subclasses may use a different call signature for the\n",
       "        `func` argument.\n",
       "        \n",
       "        If `func` is None or unspecified, there will be no change,\n",
       "        only returning the current value.\n",
       "    \n",
       "    Returns\n",
       "    -------\n",
       "    oldfunc : callable\n",
       "        The currently registered callable.\n",
       "        If you are registering a new formatter,\n",
       "        this will be the previous value (to enable restoring later).\n",
       "\n"
      ]
     }
    ],
    "source": [
     "help(latex_f.for_type_by_name)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "In this case, we will use `for_type_by_name` to register `poly_to_latex` as the display function for the `Polynomial` type:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "latex_f.for_type_by_name('numpy.polynomial.polynomial',\n",
     "                                 'Polynomial', poly_to_latex)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Once the custom display function has been registered, all NumPy `Polynomial` instances will be represented by their LaTeX form instead:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/latex": [
        "$P(x)=1+2 x+3 x^2$, $x \\in [-10,\\ 10]$"
       ],
       "text/plain": [
-       "Polynomial([ 1.,  2.,  3.], [-10.,  10.], [-1.,  1.])"
+       "Polynomial([ 1.,  2.,  3.], [-10.,  10.], [-1,  1])"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "p"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/latex": [
        "$P(x)=-20+71 x+-15 x^2+x^3$, $x \\in [-1,\\ 1]$"
       ],
       "text/plain": [
-       "Polynomial([-20.,  71., -15.,   1.], [-1.,  1.], [-1.,  1.])"
+       "Polynomial([-20.,  71., -15.,   1.], [-1,  1], [-1,  1])"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "p2 = np.polynomial.Polynomial([-20, 71, -15, 1])\n",
     "p2"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## More complex display with `_ipython_display_`"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Rich output special methods and functions can only display one object or MIME type at a time. Sometimes this is not enough if you want to display multiple objects or MIME types at once. An example of this would be to use an HTML representation to put some HTML elements in the DOM and then use a JavaScript representation to add events to those elements.\n",
     "\n",
     "**IPython 2.0** recognizes another display method, `_ipython_display_`, which allows your objects to take complete control of displaying themselves. If this method is defined, IPython will call it, and make no effort to display the object using the above described `_repr_*_` methods for custom display functions. It's a way for you to say \"Back off, IPython, I can display this myself.\" Most importantly, your `_ipython_display_` method can make multiple calls to the top-level `display` functions to accomplish its goals.\n",
     "\n",
     "Here is an object that uses `display_html` and `display_javascript` to make a plot using the [Flot](http://www.flotcharts.org/) JavaScript plotting library:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 20,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "import json\n",
     "import uuid\n",
     "from IPython.display import display_javascript, display_html, display\n",
     "\n",
     "class FlotPlot(object):\n",
     "    def __init__(self, x, y):\n",
     "        self.x = x\n",
     "        self.y = y\n",
     "        self.uuid = str(uuid.uuid4())\n",
     "    \n",
     "    def _ipython_display_(self):\n",
-    "        json_data = json.dumps(zip(self.x, self.y))\n",
+    "        json_data = json.dumps(list(zip(self.x, self.y)))\n",
     "        display_html('<div id=\"{}\" style=\"height: 300px; width:80%;\"></div>'.format(self.uuid),\n",
     "            raw=True\n",
     "        )\n",
     "        display_javascript(\"\"\"\n",
     "        require([\"//cdnjs.cloudflare.com/ajax/libs/flot/0.8.2/jquery.flot.min.js\"], function() {\n",
     "          var line = JSON.parse(\"%s\");\n",
     "          console.log(line);\n",
     "          $.plot(\"#%s\", [line]);\n",
     "        });\n",
     "        \"\"\" % (json_data, self.uuid), raw=True)\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 21,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<div id=\"e75b8189-92cb-4cbb-9996-bb8ad5ff1b4e\" style=\"height: 300px; width:80%;\"></div>"
+       "<div id=\"4ad544ff-a161-4493-ba2c-f99531e317bd\" style=\"height: 300px; width:80%;\"></div>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
     {
      "data": {
       "application/javascript": [
        "\n",
        "        require([\"//cdnjs.cloudflare.com/ajax/libs/flot/0.8.2/jquery.flot.min.js\"], function() {\n",
-       "          var line = JSON.parse(\"[[0.0, 0.0], [0.20408163265306123, 0.20266793654820095], [0.40816326530612246, 0.39692414892492234], [0.61224489795918369, 0.57470604121617908], [0.81632653061224492, 0.72863478346935029], [1.0204081632653061, 0.85232156971961837], [1.2244897959183674, 0.94063278511248671], [1.4285714285714286, 0.98990307637212394], [1.6326530612244898, 0.99808748213471832], [1.8367346938775511, 0.96484630898376322], [2.0408163265306123, 0.89155923041100371], [2.2448979591836737, 0.7812680235262639], [2.4489795918367347, 0.63855032022660208], [2.6530612244897958, 0.46932961277720098], [2.8571428571428572, 0.28062939951435684], [3.0612244897959187, 0.080281674842813497], [3.2653061224489797, -0.12339813736217871], [3.4693877551020407, -0.32195631507261868], [3.6734693877551021, -0.50715170948451438], [3.8775510204081636, -0.67129779355193209], [4.0816326530612246, -0.80758169096833643], [4.2857142857142856, -0.91034694431078278], [4.4897959183673475, -0.97532828606704558], [4.6938775510204085, -0.99982866838408957], [4.8979591836734695, -0.98283120392563061], [5.1020408163265305, -0.92504137173820289], [5.3061224489795915, -0.82885773637304272], [5.5102040816326534, -0.69827239556539955], [5.7142857142857144, -0.53870528838615628], [5.9183673469387754, -0.35677924089893803], [6.1224489795918373, -0.16004508604325057], [6.3265306122448983, 0.043331733368683463], [6.5306122448979593, 0.24491007101197931], [6.7346938775510203, 0.43632342647181932], [6.9387755102040813, 0.6096271964908323], [7.1428571428571432, 0.75762841539272019], [7.3469387755102042, 0.87418429881973347], [7.5510204081632653, 0.95445719973875187], [7.7551020408163271, 0.99511539477766364], [7.9591836734693882, 0.99447136726361685], [8.1632653061224492, 0.95255184753146038], [8.3673469387755102, 0.87109670348232071], [8.5714285714285712, 0.75348672743963763], [8.7755102040816322, 0.60460331650615429], [8.979591836734695, 0.43062587038273736], [9.183673469387756, 0.23877531564403087], [9.387755102040817, 0.037014401485062368], [9.591836734693878, -0.16628279384875641], [9.795918367346939, -0.36267842882654883], [10.0, -0.54402111088936989]]\");\n",
+       "          var line = JSON.parse(\"[[0.0, 0.0], [0.20408163265306123, 0.20266793654820095], [0.40816326530612246, 0.39692414892492234], [0.6122448979591837, 0.5747060412161791], [0.8163265306122449, 0.7286347834693503], [1.0204081632653061, 0.8523215697196184], [1.2244897959183674, 0.9406327851124867], [1.4285714285714286, 0.9899030763721239], [1.6326530612244898, 0.9980874821347183], [1.836734693877551, 0.9648463089837632], [2.0408163265306123, 0.8915592304110037], [2.2448979591836737, 0.7812680235262639], [2.4489795918367347, 0.6385503202266021], [2.6530612244897958, 0.469329612777201], [2.857142857142857, 0.28062939951435684], [3.0612244897959187, 0.0802816748428135], [3.2653061224489797, -0.12339813736217871], [3.4693877551020407, -0.3219563150726187], [3.673469387755102, -0.5071517094845144], [3.8775510204081636, -0.6712977935519321], [4.081632653061225, -0.8075816909683364], [4.285714285714286, -0.9103469443107828], [4.4897959183673475, -0.9753282860670456], [4.6938775510204085, -0.9998286683840896], [4.8979591836734695, -0.9828312039256306], [5.1020408163265305, -0.9250413717382029], [5.3061224489795915, -0.8288577363730427], [5.510204081632653, -0.6982723955653996], [5.714285714285714, -0.5387052883861563], [5.918367346938775, -0.35677924089893803], [6.122448979591837, -0.16004508604325057], [6.326530612244898, 0.04333173336868346], [6.530612244897959, 0.2449100710119793], [6.73469387755102, 0.4363234264718193], [6.938775510204081, 0.6096271964908323], [7.142857142857143, 0.7576284153927202], [7.346938775510204, 0.8741842988197335], [7.551020408163265, 0.9544571997387519], [7.755102040816327, 0.9951153947776636], [7.959183673469388, 0.9944713672636168], [8.16326530612245, 0.9525518475314604], [8.36734693877551, 0.8710967034823207], [8.571428571428571, 0.7534867274396376], [8.775510204081632, 0.6046033165061543], [8.979591836734695, 0.43062587038273736], [9.183673469387756, 0.23877531564403087], [9.387755102040817, 0.03701440148506237], [9.591836734693878, -0.1662827938487564], [9.795918367346939, -0.3626784288265488], [10.0, -0.5440211108893699]]\");\n",
        "          console.log(line);\n",
-       "          $.plot(\"#e75b8189-92cb-4cbb-9996-bb8ad5ff1b4e\", [line]);\n",
+       "          $.plot(\"#4ad544ff-a161-4493-ba2c-f99531e317bd\", [line]);\n",
        "        });\n",
        "        "
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "import numpy as np\n",
     "x = np.linspace(0,10)\n",
     "y = np.sin(x)\n",
     "FlotPlot(x, np.sin(x))"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
     "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.4.2"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
 }

examples/IPython Kernel/Index.ipynb

@@ -1,184 +1,198 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "<img src=\"../images/ipython_logo.png\">"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Back to the main [Index](../Index.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# IPython Kernel"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "IPython provides extensions to the Python programming language that make working interactively convenient and efficient. These extensions are implemented in the IPython Kernel and are available in all of the IPython Frontends (Notebook, Terminal, Console and Qt Console) when running this kernel."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Tutorials"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "* [Cell Magics](Cell Magics.ipynb)\n",
     "* [Script Magics](Script Magics.ipynb)\n",
     "* [Rich Output](Rich Output.ipynb)\n",
     "* [Custom Display Logic](Custom Display Logic.ipynb)\n",
     "* [Plotting in the Notebook](Plotting in the Notebook.ipynb)\n",
     "* [Capturing Output](Capturing Output.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Examples"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "* [Background Jobs](Background Jobs.ipynb)\n",
     "* [Trapezoid Rule](Trapezoid Rule.ipynb)\n",
     "* [SymPy](SymPy.ipynb)\n",
     "* [Raw Input in the Notebook](Raw Input in the Notebook.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Non-notebook examples"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "This directory also contains examples that are regular Python (`.py`) files."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/html": [
        "<a href='example-demo.py' target='_blank'>example-demo.py</a><br>"
       ],
       "text/plain": [
-       "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/IPython Kernel/example-demo.py"
+       "/Users/minrk/dev/ip/mine/examples/IPython Kernel/example-demo.py"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
     {
      "data": {
       "text/html": [
        "<a href='ipython-get-history.py' target='_blank'>ipython-get-history.py</a><br>"
       ],
       "text/plain": [
-       "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/IPython Kernel/ipython-get-history.py"
+       "/Users/minrk/dev/ip/mine/examples/IPython Kernel/ipython-get-history.py"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "%run ../utils/list_pyfiles.ipy"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "There are also a set of examples that show how to integrate IPython with different GUI event loops:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/html": [
+       "data/<br>\n",
+       "&nbsp;&nbsp;<a href='data/flare.json' target='_blank'>flare.json</a><br>"
+      ],
+      "text/plain": [
+       "data/\n",
+       "  flare.json"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
        "gui/<br>\n",
        "&nbsp;&nbsp;<a href='gui/gui-glut.py' target='_blank'>gui-glut.py</a><br>\n",
        "&nbsp;&nbsp;<a href='gui/gui-gtk.py' target='_blank'>gui-gtk.py</a><br>\n",
        "&nbsp;&nbsp;<a href='gui/gui-gtk3.py' target='_blank'>gui-gtk3.py</a><br>\n",
        "&nbsp;&nbsp;<a href='gui/gui-pyglet.py' target='_blank'>gui-pyglet.py</a><br>\n",
        "&nbsp;&nbsp;<a href='gui/gui-qt.py' target='_blank'>gui-qt.py</a><br>\n",
        "&nbsp;&nbsp;<a href='gui/gui-tk.py' target='_blank'>gui-tk.py</a><br>\n",
        "&nbsp;&nbsp;<a href='gui/gui-wx.py' target='_blank'>gui-wx.py</a><br>"
       ],
       "text/plain": [
        "gui/\n",
        "  gui-glut.py\n",
        "  gui-gtk.py\n",
        "  gui-gtk3.py\n",
        "  gui-pyglet.py\n",
        "  gui-qt.py\n",
        "  gui-tk.py\n",
        "  gui-wx.py"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "%run ../utils/list_subdirs.ipy"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
     "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.4.2"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 0
 }