upstream/ipython Commit - r20278:8f4dcac7

add kernel metadata to example notebooks

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r20278:8f4dcac7

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examples/Customization/Index.ipynb

0 +20 -2

              {
               "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": [
                  "# Customization"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "IPython has rich APIs for customization. Many behaviors of the different IPython applications can be configured using command line arguments or configuration files. IPython's core syntax and command line features can also be customized through input filters, custom magic commands, etc."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "## Tutorials"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Coming soon."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "## Examples"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Coming soon."
                 ]
                },
                {
                 "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='appconfig.py' target='_blank'>appconfig.py</a><br>"
                    ],
                    "text/plain": [
                     "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/Customization/appconfig.py"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  }
                 ],
                 "source": [
                  "%run ../utils/list_pyfiles.ipy"
                 ]
                }
               ],
-              "metadata": {},
+              "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
-             }
  No newline at end of file
+             }

examples/Embedding/Index.ipynb

0 +20 -2

              {
               "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": [
                  "# Embedding IPython Into Other Applications"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "The architecture of IPython is built with reusable components. These components include:\n",
                  "\n",
                  "* The configuration system for processing command line arguments and configuration files\n",
                  "* The IPython `InteractiveShell` object that provides the core interactive features across the entire code base\n",
                  "* The IPython kernel, which provides the capabilities of the `InteractiveShell` object over a ZeroMQ/JSON based message protocol to various frontends\n",
                  "* The IPython frontends (Notebook, Qt Console, Console, Terminal)\n",
                  "\n",
                  "These components can be embedded into other applications."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "## Tutorials"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Coming soon."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "## Examples"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Coming soon."
                 ]
                },
                {
                 "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='embed_class_long.py' target='_blank'>embed_class_long.py</a><br>"
                    ],
                    "text/plain": [
                     "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/Embedding/embed_class_long.py"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  },
                  {
                   "data": {
                    "text/html": [
                     "<a href='embed_class_short.py' target='_blank'>embed_class_short.py</a><br>"
                    ],
                    "text/plain": [
                     "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/Embedding/embed_class_short.py"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  },
                  {
                   "data": {
                    "text/html": [
                     "<a href='embed_function.py' target='_blank'>embed_function.py</a><br>"
                    ],
                    "text/plain": [
                     "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/Embedding/embed_function.py"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  },
                  {
                   "data": {
                    "text/html": [
                     "<a href='inprocess_qtconsole.py' target='_blank'>inprocess_qtconsole.py</a><br>"
                    ],
                    "text/plain": [
                     "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/Embedding/inprocess_qtconsole.py"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  },
                  {
                   "data": {
                    "text/html": [
                     "<a href='inprocess_terminal.py' target='_blank'>inprocess_terminal.py</a><br>"
                    ],
                    "text/plain": [
                     "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/Embedding/inprocess_terminal.py"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  },
                  {
                   "data": {
                    "text/html": [
                     "<a href='internal_ipkernel.py' target='_blank'>internal_ipkernel.py</a><br>"
                    ],
                    "text/plain": [
                     "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/Embedding/internal_ipkernel.py"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  },
                  {
                   "data": {
                    "text/html": [
                     "<a href='ipkernel_qtapp.py' target='_blank'>ipkernel_qtapp.py</a><br>"
                    ],
                    "text/plain": [
                     "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/Embedding/ipkernel_qtapp.py"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  },
                  {
                   "data": {
                    "text/html": [
                     "<a href='ipkernel_wxapp.py' target='_blank'>ipkernel_wxapp.py</a><br>"
                    ],
                    "text/plain": [
                     "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/Embedding/ipkernel_wxapp.py"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  }
                 ],
                 "source": [
                  "%run ../utils/list_pyfiles.ipy"
                 ]
                }
               ],
-              "metadata": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Animations Using clear_output.ipynb

0 +20 -2

              {
               "cells": [
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "# 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": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Background Jobs.ipynb

0 +20 -2

              {
               "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",
                  "        sys.stdout.flush()\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,
                 "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,
                   "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,
                 "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",
                    "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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "{'args': (), 'interval': 4, 'kwargs': {}}"
                    ]
                   },
                   "execution_count": 12,
                   "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,
                 "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,
                 "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[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[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",
                  "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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "Traceback for: <BackgroundJob #4: <function diefunc at 0x314f668>>\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[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[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",
                    "\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[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[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,
                 "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,
                 "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,
                 "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": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Beyond Plain Python.ipynb

0 +24 -6

              {
               "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\""
                 ]
                },
                {
                 "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\u2019re dealing with. Simply type `object_name.<TAB>` to view the object\u2019s attributes. Besides Python objects and keywords, tab completion also works on file and directory names."
+                 "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,
                 "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   :', ___"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 13,
                 "metadata": {
                  "collapsed": false,
                  "slideshow": {
                   "slide_type": "-"
                  }
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "u'_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]'"
                    ]
                   },
                   "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]'"
                    ]
                   },
                   "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"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 17,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "   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"
                   ]
                  }
                 ],
                 "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"
                   ]
                  }
                 ],
                 "source": [
                  "files = !ls\n",
                  "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"
                   ]
                  }
                 ],
                 "source": [
                  "!echo $files"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 21,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "BACKGROUNDJOBS.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,
                 "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",
                    "--\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"
                   ]
                  }
                 ],
                 "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 '--'"
                 ]
                },
                {
                 "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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "%magic"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Line vs cell magics:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 29,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "10000000 loops, best of 3: 190 ns per loop\n"
                   ]
                  }
                 ],
                 "source": [
                  "%timeit range(10)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 30,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "1000000 loops, best of 3: 888 ns per loop\n"
                   ]
                  }
                 ],
                 "source": [
                  "%%timeit\n",
                  "range(10)\n",
                  "range(100)"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Line magics can be used even inside code blocks:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 31,
                 "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 \u00b5s per loop\n",
-                   " size: 3001000000 loops, best of 3: 1.74 \u00b5s per loop\n",
-                   " size: 400100000 loops, best of 3: 2.72 \u00b5s 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"
                   ]
                  }
                 ],
                 "source": [
                  "for i in range(5):\n",
                  "    size = i*100\n",
                  "    print 'size:',size, \n",
                  "    %timeit 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,
                 "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"
                   ]
                  }
                 ],
                 "source": [
                  "%%bash\n",
                  "echo \"My shell is:\" $SHELL\n",
                  "echo \"My memory status is:\"\n",
                  "free"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Another interesting cell magic: create any file you want locally from the notebook:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 33,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "Writing 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,
                 "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,
                 "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",
                      "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",
                      "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",
                      "store": "StoreMagics",
                      "sx": "OSMagics",
                      "system": "OSMagics",
                      "tb": "ExecutionMagics",
                      "time": "ExecutionMagics",
                      "timeit": "ExecutionMagics",
                      "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",
                     "\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,
                   "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,
                 "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",
                  "...     a, b = b, a+b"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 37,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "0 1 2 3 4 5 6 7 8 9\n"
                   ]
                  }
                 ],
                 "source": [
                  "In [1]: for i in range(10):\n",
                  "   ...:     print i,\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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "Writing 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,
                 "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;31mZeroDivisionError\u001b[0m: float division by zero"
                   ]
                  }
                 ],
                 "source": [
                  "import mod\n",
                  "mod.g(0)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 40,
                 "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",
                    "\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,
                 "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;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,
                 "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,
                 "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,
                 "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,
                 "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;31mZeroDivisionError\u001b[0m: float division by zero"
                   ]
                  }
                 ],
                 "source": [
                  "mod.g(0)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 38,
                 "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[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[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",
                    "\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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "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"
                 ]
                },
                {
                 "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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "%matplotlib inline"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 47,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "import numpy as np\n",
                  "import matplotlib.pyplot as plt"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 48,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
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                    ],
                    "text/plain": [
                     "<matplotlib.figure.Figure at 0x3436950>"
                    ]
                   },
                   "metadata": {},
                   "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,
                 "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",
                    "}\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",
                    "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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "%qtconsole"
                 ]
                }
               ],
-              "metadata": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Capturing Output.ipynb

0 +20 -2

              {
               "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,
                 "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,
                 "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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "%%capture captured\n",
                  "print('hi, stdout')\n",
                  "print('hi, stderr', file=sys.stderr)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 12,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "<IPython.utils.capture.CapturedIO at 0x1076c9310>"
                    ]
                   },
                   "execution_count": 12,
                   "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,
                 "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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "'hi, stdout\\n'"
                    ]
                   },
                   "execution_count": 14,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "captured.stdout"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 15,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "'hi, stderr\\n'"
                    ]
                   },
                   "execution_count": 15,
                   "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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "%matplotlib inline\n",
                  "import matplotlib.pyplot as plt\n",
                  "import numpy as np"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 17,
                 "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,
                 "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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                     "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,
                 "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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "'hi, stdout\\n'"
                    ]
                   },
                   "execution_count": 20,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "cap.stdout"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 21,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "''"
                    ]
                   },
                   "execution_count": 21,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "cap.stderr"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 22,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "[]"
                    ]
                   },
                   "execution_count": 22,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "cap.outputs"
                 ]
                }
               ],
-              "metadata": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Cell Magics.ipynb

0 +20 -2

              {
               "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",
                  "\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",
                      "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",
                      "cd": "OSMagics",
                      "clear": "KernelMagics",
                      "colors": "BasicMagics",
                      "config": "ConfigMagics",
                      "connect_info": "KernelMagics",
                      "debug": "ExecutionMagics",
                      "dhist": "OSMagics",
                      "dirs": "OSMagics",
                      "doctest_mode": "KernelMagics",
                      "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",
                      "less": "KernelMagics",
                      "load": "CodeMagics",
                      "load_ext": "ExtensionMagics",
                      "loadpy": "CodeMagics",
                      "logoff": "LoggingMagics",
                      "logon": "LoggingMagics",
                      "logstart": "LoggingMagics",
                      "logstate": "LoggingMagics",
                      "logstop": "LoggingMagics",
                      "lsmagic": "BasicMagics",
                      "macro": "ExecutionMagics",
                      "magic": "BasicMagics",
                      "man": "KernelMagics",
                      "matplotlib": "PylabMagics",
                      "more": "KernelMagics",
                      "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",
                      "run": "ExecutionMagics",
                      "save": "CodeMagics",
                      "sc": "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",
                     "\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",
                     "\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"
                   ]
                  }
                 ],
                 "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"
                   ]
                  }
                 ],
                 "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"
                   ]
                  }
                 ],
                 "source": [
                  "%%script python\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"
                   ]
                  }
                 ],
                 "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"
                   ]
                  }
                 ],
                 "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,
                 "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,
                 "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,
                 "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,
                 "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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "<open file '<fdopen>', mode 'rb' at 0x112cd55d0>"
                    ]
                   },
                   "execution_count": 34,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "ruby_lines"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 35,
                 "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())"
                 ]
                }
               ],
-              "metadata": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Custom Display Logic.ipynb

0 +20 -2

              {
               "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_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$' % (self.mean,\n",
                  "                                                                 self.std, self.size)"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Create an instance of the Gaussian distribution and return it to display the default representation:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 4,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
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                     "8aCig033t/0D4Cbgj5L1Pwb+DLi8Q/3qFb7m8vcWYBdwLOH1u5Uw0tTcVUnxmm01yC9o4T4/BOp/\n",
                     "0uW4pE1Tpf3b3kK2D00Fja/DZUz9pqjsdiXXzwB3EcpXBnnrxgmDuTFgKfD0bHdod2mlvm62Hngf\n",
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                     "bkIN8iXCJ8rX6m67lrCjaSvwS53vWvS+QJjmtYXwnztr7UxNeSBbfk4kzPx5GHgM/55Z3QH8D7CX\n",
                     "kJuXEWYA3UfB0w8lSZIkSZIkSZIkSZIkSZIkSZIktcn/A4eK9UXawRDUAAAAAElFTkSuQmCC\n"
                    ],
                    "text/latex": [
                     "$\\mathcal{N}(\\mu=2, \\sigma=1),\\ N=1000$"
                    ],
                    "text/plain": [
                     "<__main__.Gaussian at 0x106e7ae10>"
                    ]
                   },
                   "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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                     "fnMJ8p8CnqxbfyppkyR10FyC3KGOClBlcPBXePnlZ5g3z331EoQ5Ra06Bxgh1MgB1gH7gRvqttkO\n",
                     "nDSH55CkfrQDeF0nnmggebLlwKHAw7izU5KicxHwPcLIe13BfZEkSZIE8B7gceBV4MyG29YRDh7a\n",
                     "Cryjw/3qBSOE2UGbk8uFM26t6XggW752Ao8QXpPfLbYr0fk8MA48Wtc2BGwEtgEbgMUF9ItTgBXA\n",
                     "/UwN8tMIdfRDCHX17XiKgKyuAz5SdCciN5/w2ltOeC26b2fufkAIH2X3VmAlU4P8RuBjyfI1wPWz\n",
                     "PUg7gnQr4ZOk0cXAHYSjNHYS3kxnt+H5e52HKs6NB7K1h6/L1nwTaDxyahUwmiyPAqtne5BOjoh/\n",
                     "klAWqPEAotZcDWwBbqWgr1yR80C2/FWB+4CHgCsK7ksvGCaUW0iuh2e7Q6unsd0ILGnSfi1wT4bH\n",
                     "8aCig033t/0D4Cbgj5L1Pwb+DLi8Q/3qFb7m8vcWYBdwLOH1u5Uw0tTcVUnxmm01yC9o4T4/BOp/\n",
                     "0uW4pE1Tpf3b3kK2D00Fja/DZUz9pqjsdiXXzwB3EcpXBnnrxgmDuTFgKfD0bHdod2mlvm62Hngf\n",
                     "4eChE4GTcQ93Vkvrlt/N1B0kSuchwmtvOeG1+F7Ca1OtORJYmCwvIMxG83U5N+uBNcnyGuDuIjrx\n",
                     "bkIN8iXCJ8rX6m67lrCjaSvwS53vWvS+QJjmtYXwnztr7UxNeSBbfk4kzPx5GHgM/55Z3QH8D7CX\n",
                     "kJuXEWYA3UfB0w8lSZIkSZIkSZIkSZIkSZIkSZIktcn/A4eK9UXawRDUAAAAAElFTkSuQmCC\n"
                    ],
                    "text/latex": [
                     "$\\mathcal{N}(\\mu=2, \\sigma=1),\\ N=1000$"
                    ],
                    "text/plain": [
                     "<__main__.Gaussian at 0x106e7ae10>"
                    ]
                   },
                   "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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                     "kJuXEWYA3UfB0w8lSZIkSZIkSZIkSZIkSZIkSZIktcn/A4eK9UXawRDUAAAAAElFTkSuQmCC\n"
                    ]
                   },
                   "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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                     "Zpl0W9y9wCWEh54WAm/Du+v1mpeavpDymzCa2mOE624B4Tq8mHBdKpuZwKxk+ihCDzivycbdC6xK\n",
                     "plcBd3ewLGUuJLRrHiD85flm6mfXEm5obQN+of1F63m3E7qdbSH8D5+0LU5V+fBd8ywk9DjaDDyN\n",
                     "5zOLdcD3gFcJuflBQu+jB+jCrpCSJEmSJEmSJEmSJEmSJEmSJEmS+tD/AzUxDUJku6WfAAAAAElF\n",
                     "TkSuQmCC\n"
                    ],
                    "text/latex": [
                     "$\\mathcal{N}(\\mu=0, \\sigma=2),\\ N=2000$"
                    ],
                    "text/plain": [
                     "<__main__.Gaussian at 0x106e9ce90>"
                    ]
                   },
                   "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": {
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                     "/ftfQXGqt1nGl3WoycpfKhFYm2++8efZb01Kc/gBSYqQ4S5JETLcJSlChrskRchwl6QIGe6SFCHD\n",
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                     "plcBd3ewLGUuJLRrHiD85flm6mfXEm5obQN+of1F63m3E7qdbSH8D5+0LU5V+fBd8ywk9DjaDDyN\n",
                     "5zOLdcD3gFcJuflBQu+jB+jCrpCSJEmSJEmSJEmSJEmSJEmSJEmS+tD/AzUxDUJku6WfAAAAAElF\n",
                     "TkSuQmCC\n"
                    ]
                   },
                   "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.])"
                    ]
                   },
                   "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",
                    "           text/markdown : MarkdownFormatter\n",
                    "              text/latex : LatexFormatter\n",
                    "        application/json : JSONFormatter\n",
                    "         application/pdf : PDFFormatter\n"
                   ]
                  }
                 ],
                 "source": [
                  "ip = get_ipython()\n",
                  "for mime, formatter in ip.display_formatter.formatters.items():\n",
                  "    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",
                    "    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",
                    "    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,
                 "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,
                 "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.])"
                    ]
                   },
                   "execution_count": 19,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "p"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 20,
                 "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.])"
                    ]
                   },
                   "execution_count": 20,
                   "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,
                 "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",
                  "        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,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/html": [
                     "<div id=\"e75b8189-92cb-4cbb-9996-bb8ad5ff1b4e\" 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",
                     "          console.log(line);\n",
                     "          $.plot(\"#e75b8189-92cb-4cbb-9996-bb8ad5ff1b4e\", [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": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Index.ipynb

0 +20 -2

              {
               "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"
                    ]
                   },
                   "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"
                    ]
                   },
                   "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": [
                     "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": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Old Custom Display Logic.ipynb

0 +23 -5

              {
               "cells": [
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "# Defining Custom Display Logic for Your Own Objects"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "## Overview"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "In Python, objects can declare their textual representation using the `__repr__` method.  IPython expands on this idea and allows objects to declare other, richer representations including:\n",
                  "\n",
                  "* HTML\n",
                  "* JSON\n",
                  "* PNG\n",
                  "* JPEG\n",
                  "* SVG\n",
                  "* LaTeX\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_`.\n",
                  "2. Registering a display function for a particular type.\n",
                  "\n",
                  "In this Notebook we show how both approaches work."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Before we get started, we will import the various display functions for displaying the different formats we will create."
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 1,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "from IPython.display import display\n",
                  "from IPython.display import (\n",
                  "    display_html, display_jpeg, display_png,\n",
                  "    display_javascript, display_svg, display_latex\n",
                  ")"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "## Implementing special display methods"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "The main idea of the first approach is that you have to implement special display methods, 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_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": [
                  "### Model Citizen: pandas"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "A prominent example of a package that has IPython-aware rich representations of its objects is [pandas](http://pandas.pydata.org/).\n",
                  "\n",
                  "A pandas DataFrame has a rich HTML table representation,\n",
                  "using `_repr_html_`.\n"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 2,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "import io\n",
                  "import pandas"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 3,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "Writing data.csv\n"
                   ]
                  }
                 ],
                 "source": [
                  "%%writefile data.csv\n",
                  "Date,Open,High,Low,Close,Volume,Adj Close\n",
                  "2012-06-01,569.16,590.00,548.50,584.00,14077000,581.50\n",
                  "2012-05-01,584.90,596.76,522.18,577.73,18827900,575.26\n",
                  "2012-04-02,601.83,644.00,555.00,583.98,28759100,581.48\n",
                  "2012-03-01,548.17,621.45,516.22,599.55,26486000,596.99\n",
                  "2012-02-01,458.41,547.61,453.98,542.44,22001000,540.12\n",
                  "2012-01-03,409.40,458.24,409.00,456.48,12949100,454.53\n"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 4,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "         Date    Open    High     Low   Close    Volume  Adj Close\n",
                     "0  2012-06-01  569.16  590.00  548.50  584.00  14077000     581.50\n",
                     "1  2012-05-01  584.90  596.76  522.18  577.73  18827900     575.26\n",
                     "2  2012-04-02  601.83  644.00  555.00  583.98  28759100     581.48\n",
                     "3  2012-03-01  548.17  621.45  516.22  599.55  26486000     596.99\n",
                     "4  2012-02-01  458.41  547.61  453.98  542.44  22001000     540.12\n",
                     "5  2012-01-03  409.40  458.24  409.00  456.48  12949100     454.53"
                    ]
                   },
                   "execution_count": 4,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "df = pandas.read_csv(\"data.csv\")\n",
                  "pandas.set_option('display.notebook_repr_html', False)\n",
                  "df"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "rich HTML can be activated via `pandas.set_option`."
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 5,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/html": [
                     "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
                     "<table border=\"1\" class=\"dataframe\">\n",
                     "  <thead>\n",
                     "    <tr style=\"text-align: right;\">\n",
                     "      <th></th>\n",
                     "      <th>Date</th>\n",
                     "      <th>Open</th>\n",
                     "      <th>High</th>\n",
                     "      <th>Low</th>\n",
                     "      <th>Close</th>\n",
                     "      <th>Volume</th>\n",
                     "      <th>Adj Close</th>\n",
                     "    </tr>\n",
                     "  </thead>\n",
                     "  <tbody>\n",
                     "    <tr>\n",
                     "      <th>0</th>\n",
                     "      <td> 2012-06-01</td>\n",
                     "      <td> 569.16</td>\n",
                     "      <td> 590.00</td>\n",
                     "      <td> 548.50</td>\n",
                     "      <td> 584.00</td>\n",
                     "      <td> 14077000</td>\n",
                     "      <td> 581.50</td>\n",
                     "    </tr>\n",
                     "    <tr>\n",
                     "      <th>1</th>\n",
                     "      <td> 2012-05-01</td>\n",
                     "      <td> 584.90</td>\n",
                     "      <td> 596.76</td>\n",
                     "      <td> 522.18</td>\n",
                     "      <td> 577.73</td>\n",
                     "      <td> 18827900</td>\n",
                     "      <td> 575.26</td>\n",
                     "    </tr>\n",
                     "    <tr>\n",
                     "      <th>2</th>\n",
                     "      <td> 2012-04-02</td>\n",
                     "      <td> 601.83</td>\n",
                     "      <td> 644.00</td>\n",
                     "      <td> 555.00</td>\n",
                     "      <td> 583.98</td>\n",
                     "      <td> 28759100</td>\n",
                     "      <td> 581.48</td>\n",
                     "    </tr>\n",
                     "    <tr>\n",
                     "      <th>3</th>\n",
                     "      <td> 2012-03-01</td>\n",
                     "      <td> 548.17</td>\n",
                     "      <td> 621.45</td>\n",
                     "      <td> 516.22</td>\n",
                     "      <td> 599.55</td>\n",
                     "      <td> 26486000</td>\n",
                     "      <td> 596.99</td>\n",
                     "    </tr>\n",
                     "    <tr>\n",
                     "      <th>4</th>\n",
                     "      <td> 2012-02-01</td>\n",
                     "      <td> 458.41</td>\n",
                     "      <td> 547.61</td>\n",
                     "      <td> 453.98</td>\n",
                     "      <td> 542.44</td>\n",
                     "      <td> 22001000</td>\n",
                     "      <td> 540.12</td>\n",
                     "    </tr>\n",
                     "    <tr>\n",
                     "      <th>5</th>\n",
                     "      <td> 2012-01-03</td>\n",
                     "      <td> 409.40</td>\n",
                     "      <td> 458.24</td>\n",
                     "      <td> 409.00</td>\n",
                     "      <td> 456.48</td>\n",
                     "      <td> 12949100</td>\n",
                     "      <td> 454.53</td>\n",
                     "    </tr>\n",
                     "  </tbody>\n",
                     "</table>\n",
                     "</div>"
                    ],
                    "text/plain": [
                     "         Date    Open    High     Low   Close    Volume  Adj Close\n",
                     "0  2012-06-01  569.16  590.00  548.50  584.00  14077000     581.50\n",
                     "1  2012-05-01  584.90  596.76  522.18  577.73  18827900     575.26\n",
                     "2  2012-04-02  601.83  644.00  555.00  583.98  28759100     581.48\n",
                     "3  2012-03-01  548.17  621.45  516.22  599.55  26486000     596.99\n",
                     "4  2012-02-01  458.41  547.61  453.98  542.44  22001000     540.12\n",
                     "5  2012-01-03  409.40  458.24  409.00  456.48  12949100     454.53"
                    ]
                   },
                   "execution_count": 5,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "pandas.set_option('display.notebook_repr_html', True)\n",
                  "df"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 6,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
                    "<table border=\"1\" class=\"dataframe\">\n",
                    "  <thead>\n",
                    "    <tr style=\"text-align: right;\">\n",
                    "      <th></th>\n",
                    "      <th>Date</th>\n",
                    "      <th>Open</th>\n",
                    "      <th>High</th>\n",
                    "      <th>Low</th>\n",
                    "      <th>Close</th>\n",
                    "      <th>Volume</th>\n",
                    "      <th>Adj Close</th>\n",
                    "    </tr>\n",
                    "  </thead>\n",
                    "  <tbody>\n",
                    "    <tr>\n",
                    "      <th>0</th>\n",
                    "      <td> 2012-06-01</td>\n",
                    "      <td> 569.16</td>\n",
                    "      <td> 590.00</td>\n"
                   ]
                  }
                 ],
                 "source": [
                  "lines = df._repr_html_().splitlines()\n",
                  "print \"\\n\".join(lines[:20])"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "### Exercise"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Write a simple `Circle` Python class.  Don't even worry about properties such as radius, position, colors, etc. To help you out use the following representations (remember to wrap them in Python strings):\n",
                  "\n",
                  "For HTML:\n",
                  "\n",
                  "    &#x25CB;\n",
                  "\n",
                  "For SVG:\n",
                  "\n",
                  "    <svg width=\"100px\" height=\"100px\">\n",
                  "        <circle cx=\"50\" cy=\"50\" r=\"20\" stroke=\"black\" stroke-width=\"1\" fill=\"white\"/>\n",
                  "    </svg>\n",
                  "\n",
                  "For LaTeX (wrap with `$` and use a raw Python string):\n",
                  "\n",
                  "    \\bigcirc\n",
                  "\n",
                  "After you write the class, create an instance and then use `display_html`, `display_svg` and `display_latex` to display those representations.\n",
                  "\n",
                  "Tips : you can slightly tweek the representation to know from which `_repr_*_` method it came from. \n",
                  "For example in my solution the svg representation is blue, and the HTML one show \"`HTML`\" between brackets."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "### Solution"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Here is my simple `MyCircle` class:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 8,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "%load soln/mycircle.py"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Now create an instance and use the display methods:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 11,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "c = MyCircle()"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 12,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/html": [
                     "&#x25CB; (<b>html</b>)"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  }
                 ],
                 "source": [
                  "display_html(c)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 13,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "image/svg+xml": [
                     "<svg width=\"100px\" height=\"100px\">\n",
                     "           <circle cx=\"50\" cy=\"50\" r=\"20\" stroke=\"black\" stroke-width=\"1\" fill=\"blue\"/>\n",
                     "        </svg>"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  }
                 ],
                 "source": [
                  "display_svg(c)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 14,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/latex": [
                     "$\\bigcirc \\LaTeX$"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  }
                 ],
                 "source": [
                  "display_latex(c)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 15,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "application/javascript": [
                     "alert('I am a circle!');"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  }
                 ],
                 "source": [
                  "display_javascript(c)"
                 ]
                },
                {
                 "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 example.  But in practice, we often need to work with existing code we can't modify.  We now illustrate how to add these kinds of extended display capabilities to existing objects. To continue with our example above, we will add a PNG representation to our `Circle` class using Matplotlib."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "### Model citizen: sympy"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "[SymPy](http://sympy.org) is another model citizen that defines rich representations of its object.\n",
                  "Unlike pandas above, sympy registers display formatters via IPython's display formatter API, rather than declaring `_repr_mime_` methods."
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 16,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "from sympy import Rational, pi, exp, I, symbols\n",
                  "x, y, z = symbols(\"x y z\")"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 17,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "3*pi/2 + exp(I*x)/(x**2 + y)"
                    ]
                   },
                   "execution_count": 17,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "r = Rational(3,2)*pi + exp(I*x) / (x**2 + y)\n",
                  "r"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "SymPy provides an `init_printing` function that sets up advanced $\\LaTeX$\n",
                  "representations of its objects."
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 18,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "image/png": [
                     "iVBORw0KGgoAAAANSUhEUgAAAFAAAAAlCAYAAADV/m7fAAAABHNCSVQICAgIfAhkiAAAA9xJREFU\n",
                     "aIHt2l2IVVUUwPHfzDQ4hc1UFpaVTvoiKNoHaTCmU/lQaERR9mGUZBSkUVEQvcR9CSKIoCgoom5F\n",
                     "BX2T+RD6EBQVZI1BBoVSFA0JUkNiiX1MD+uc5szkOPfjnHvvyP3DwF4z96y1Zp+91l577Uubuuho\n",
                     "tgMNYikG8TU+wwosxs9YjTvwWy2Kj8mMV2IeZiTGythem78txwjmYitOxHs4G7vwthonbyL7cHMy\n",
                     "vga/4/g8FLcAx+FVnIVesXDeRScW1KM4uwIH8V0yHkV3PYpbjFnifzsDt2J3Il+Mg9hTq+LJcuAr\n",
                     "Ynk/VKviJtKJe3AIv2I2Hi3SWJZzcR8O4LGijBbM0yKynsCbOKkZTtyGzzGzAbaWGJ9K6mEh/hC5\n",
                     "fD1uETmvcC7AXpFkU0dGcXUDbJfRn5Oua7EjJ10VkYbwXyLnDSfyfPyJnY10Jge+FZtCSofYNAqr\n",
                     "d9PQ2YHnsBn/iEJzrditsvTiGVyBnkl0jmIVPszb2QoYEnnvLvyCY7El8akQqnkzHaLoHMKnuEpU\n",
                     "9d/jbjwldr6D+Fi8iEooo5ToOaq5CZdl5NfRlYy31KG3LL8c2HCq2f1ezIxPSJ79W1T5p+Tp1HSi\n",
                     "1vJhPT5JxgvFRE7FC+JQP5G5WCbCfyIbRTnV8oxO8TORnTg/Ga/BN3XYLqsshKfysSk/6QqsZjNJ\n",
                     "uzZfJHKvWEU9xpcQeTOVj53YJHZeeKRAX8YZrZZ7sc1Y2A6LyVudl1M1sgbviIlbjvMaYTQ7gcvF\n",
                     "IbwkJmjlJM8sxbMZeQg/qO1l5MkCXJ+M9+DMRhqfiYcz8jrRDzy9AbbL8iljZhjrX76POTnorJgl\n",
                     "ovBNm4u9Ikmua4Dtx3FqjvouxAM56quIDhHCaaJeJCbwnEY7Uid9eLDZTsBLCmxCFsgm0UnvVt2m\n",
                     "tjlPJzaKnWy63djdIC6H9olO9OIqni3l5cRaMYFEadKfl+KcGMAG0S2/EbfjLdF+q4fSJL/vElee\n",
                     "z4vTEpwsczrKlh6rxP3BVpHUL8VpdTqWJ73i2FjGB7hTtO/3i4qhCK4UTZPsYroIP6YfSMN0Pr70\n",
                     "/xZ+n5zuTHOgR1QKh0TJNWJ86VUps0X7LZuiVuCjjLxfXKj1JfJuMYEH8GQiT9c7I0QIpWfxviN9\n",
                     "sEJKR/jbdXgjI+8Sl29o/umhGi4XJ6V+sUEMiVW0oWC7c4zdG/cn8n9XHV2HeaBVGRD16SxxXbBM\n",
                     "1KmvidCqh0GRVw/HXvFNjW7xAofxcp32jjrur/Bz20St2aZCFuEnkSoG8JWxdhmmVwg3g04xefNw\n",
                     "ifjCwUhTPWrTpk2bFuJflVvSLV1580UAAAAASUVORK5CYII=\n"
                    ],
                    "text/latex": [
                     "$$\\frac{3}{2} \\pi + \\frac{e^{\\mathbf{\\imath} x}}{x^{2} + y}$$"
                    ],
                    "text/plain": [
-                    "        \u2148\u22c5x \n",
-                    "3\u22c5\u03c0    \u212f    \n",
-                    "\u2500\u2500\u2500 + \u2500\u2500\u2500\u2500\u2500\u2500\n",
+                    "        ⅈ⋅x \n",
+                    "3⋅π    ℯ    \n",
+                    "─── + ──────\n",
                     " 2     2    \n",
                     "      x  + y"
                    ]
                   },
                   "execution_count": 18,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "from sympy.interactive.printing import init_printing\n",
                  "init_printing()\n",
                  "r"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "To add a display method to an existing class, we must use IPython's display formatter API.  Here we show all of the available formatters:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 6,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "               text/html : HTMLFormatter\n",
                    "              image/jpeg : JPEGFormatter\n",
                    "           image/svg+xml : SVGFormatter\n",
                    "               image/png : PNGFormatter\n",
                    "  application/javascript : JavascriptFormatter\n",
                    "              text/latex : LatexFormatter\n",
                    "        application/json : JSONFormatter\n",
                    "              text/plain : PlainTextFormatter\n"
                   ]
                  }
                 ],
                 "source": [
                  "ip = get_ipython()\n",
                  "for mime, formatter in ip.display_formatter.formatters.items():\n",
                  "    print '%24s : %s' % (mime, formatter.__class__.__name__)\n"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Let's grab the PNG formatter:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 20,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "png_f = ip.display_formatter.formatters['image/png']"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "We will use the `for_type` method to register our display function."
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 21,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "png_f.for_type?"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "As the docstring describes, we need to define a function the takes the object as a parameter and returns the raw PNG data."
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 22,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "%matplotlib inline\n",
                  "import matplotlib.pyplot as plt"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 23,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
                    "text/plain": [
                     "<r Circle with r=1 at (0, 0)>"
                    ]
                   },
                   "execution_count": 23,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "class AnotherCircle(object):\n",
                  "    def __init__(self, radius=1, center=(0,0), color='r'):\n",
                  "        self.radius = radius\n",
                  "        self.center = center\n",
                  "        self.color = color\n",
                  "    \n",
                  "    def __repr__(self):\n",
                  "        return \"<%s Circle with r=%s at %s>\" % (\n",
                  "                    self.color,\n",
                  "                    self.radius,\n",
                  "                    self.center,\n",
                  "                )\n",
                  "    \n",
                  "c = AnotherCircle()\n",
                  "c"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 24,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "from IPython.core.pylabtools import print_figure\n",
                  "\n",
                  "def png_circle(circle):\n",
                  "    \"\"\"Render AnotherCircle to png data using matplotlib\"\"\"\n",
                  "    fig, ax = plt.subplots()\n",
                  "    patch = plt.Circle(circle.center,\n",
                  "                       radius=circle.radius,\n",
                  "                       fc=circle.color,\n",
                  "                       )\n",
                  "    ax.add_patch(patch)\n",
                  "    plt.axis('scaled')\n",
                  "    data = print_figure(fig, 'png')\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"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 27,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "'\\x89PNG\\r\\n\\x1a\\n\\x00\\x00'\n"
                   ]
                  }
                 ],
                 "source": [
                  "c = AnotherCircle()\n",
                  "print repr(png_circle(c)[:10])"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Now we register the display function for the type:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 28,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "png_f.for_type(AnotherCircle, png_circle)"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Now all `Circle` instances have PNG representations!"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 29,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
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                     "AJCcnAyNRoPKykr079/fIVl/ydb944r9eDXdyeDq/dhTUtiv3SGl/Xph+qLOZqIApLVvr5YVkNa+\n",
                     "BYDU1FScPXsW9fX1l00P1ZP9KplrHJf65XlBk8l08Q926fQlAGyavsSRrjb+pVkBIDc3F+3t7QCA\n",
                     "wsJCWCwWp94F0lU+Ke3H7mQFXL8fr+bSn1Gp7ddfulJWQBr7tb29HUuXLkVBQQHmzJlz2S81qe1b\n",
                     "W7MC4vdtfX09cnJyLv73//777xEaGoqgoCC796tknhzfsGEDduzYgZMnTyIyMhJxcXGYPn06AEhu\n",
                     "+pKuxv9l1rfffhvFxcVQKBRQqVR47LHHkJCQICSf1PZjd7KK2I+/dKWfUSnuV1uzSmG/Xmn6ounT\n",
                     "p2PTpk2X5RW9b7uTVfS+ra+vR0ZGBsrKyuDv7w+dTocpU6YgJibG7p9ZyRQHERG5B0meqiIiIuli\n",
                     "cRARUbewOIiIqFtYHERE1C0sDiIi6hYWBxERdQuLg4iIuoXFQURE3fL/AR8SQcFGS9m7AAAAAElF\n",
                     "TkSuQmCC\n"
                    ],
                    "text/plain": [
                     "<g Circle with r=2 at (1, 0)>"
                    ]
                   },
                   "execution_count": 29,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "c2 = AnotherCircle(radius=2, center=(1,0), color='g')\n",
                  "c2"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 30,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
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                     "TkSuQmCC\n"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  }
                 ],
                 "source": [
                  "display_png(c2)"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "## return the object"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": null,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "# for demonstration purpose, I do the same with a circle that has no _repr_javascript method\n",
                  "class MyNoJSCircle(MyCircle):\n",
                  "    \n",
                  "    def _repr_javascript_(self):\n",
                  "        return\n",
                  "\n",
                  "cNoJS = MyNoJSCircle()"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Of course you can now still return the object, and this will use compute all the representations, store them in the notebook and show you the appropriate one."
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": null,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "cNoJS"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Or just use `display(object)` if you are in a middle of a loop"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": null,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "for i in range(3):\n",
                  "    display(cNoJS)"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Advantage of using `display()` versus `display_*()` is that all representation will be stored in the notebook document and notebook file, they are then availlable for other frontends or post-processing tool like `nbconvert`."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "Let's compare `display()` vs `display_html()` for our circle in the Notebook Web-app and we'll see later the difference in nbconvert."
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": null,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "print \"I should see a nice html circle in web-app, but\"\n",
                  "print \"nothing if the format I'm viewing the notebook in\"\n",
                  "print \"does not support html\"\n",
                  "display_html(cNoJS)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": null,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "print \"Whatever the format I will see a representation\"\n",
                  "print \"of my circle\"\n",
                  "display(cNoJS)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": null,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "print \"Same if I return the object\"\n",
                  "cNoJS"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": null,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "print \"But not if I print it\"\n",
                  "print cNoJS"
                 ]
                }
               ],
-              "metadata": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Plotting in the Notebook.ipynb

0 +20 -2

              {
               "cells": [
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "# Plotting with Matplotlib"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "IPython works with the [Matplotlib](http://matplotlib.org/) plotting library, which integrates Matplotlib with IPython's display system and event loop handling."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "## matplotlib mode"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "To make plots using Matplotlib, you must first enable IPython's matplotlib mode.\n",
                  "\n",
                  "To do this, run the `%matplotlib` magic command to enable plotting in the current Notebook.\n",
                  "\n",
                  "This magic takes an optional argument that specifies which Matplotlib backend should be used.  Most of the time, in the Notebook, you will want to use the `inline` backend, which will embed plots inside the Notebook:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 1,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "%matplotlib inline"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "You can also use Matplotlib GUI backends in the Notebook, such as the Qt backend (`%matplotlib qt`). This will use Matplotlib's interactive Qt UI in a floating window to the side of your browser. Of course, this only works if your browser is running on the same system as the Notebook Server.  You can always call the `display` function to paste figures into the Notebook document."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "## Making a simple plot"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "With matplotlib enabled, plotting should just work."
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 2,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "import matplotlib.pyplot as plt\n",
                  "import numpy as np"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 3,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
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                     "kL6BgYHBKIIhfQMDA4NRBEP6BgYGBqMI/x+3ghdT1LKwsgAAAABJRU5ErkJggg==\n"
                    ],
                    "text/plain": [
                     "<matplotlib.figure.Figure at 0x1084796d0>"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  }
                 ],
                 "source": [
                  "x = np.linspace(0, 3*np.pi, 500)\n",
                  "plt.plot(x, np.sin(x**2))\n",
                  "plt.title('A simple chirp');"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "These images can be resized by dragging the handle in the lower right corner.  Double clicking will return them to their original size."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "One thing to be aware of is that by default, the `Figure` object is cleared at the end of each cell, so you will need to issue all plotting commands for a single figure in a single cell."
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "## Loading Matplotlib demos with %load"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "IPython's `%load` magic can be used to load any Matplotlib demo by its URL:"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 4,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "%load http://matplotlib.org/mpl_examples/showcase/integral_demo.py"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 5,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "data": {
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                     "iISh/weZPyRnS1m/IAAAAABJRU5ErkJggg==\n"
                    ],
                    "text/plain": [
                     "<matplotlib.figure.Figure at 0x10848fb10>"
                    ]
                   },
                   "metadata": {},
                   "output_type": "display_data"
                  }
                 ],
                 "source": [
                  "\"\"\"\n",
                  "Plot demonstrating the integral as the area under a curve.\n",
                  "\n",
                  "Although this is a simple example, it demonstrates some important tweaks:\n",
                  "\n",
                  "    * A simple line plot with custom color and line width.\n",
                  "    * A shaded region created using a Polygon patch.\n",
                  "    * A text label with mathtext rendering.\n",
                  "    * figtext calls to label the x- and y-axes.\n",
                  "    * Use of axis spines to hide the top and right spines.\n",
                  "    * Custom tick placement and labels.\n",
                  "\"\"\"\n",
                  "import numpy as np\n",
                  "import matplotlib.pyplot as plt\n",
                  "from matplotlib.patches import Polygon\n",
                  "\n",
                  "\n",
                  "def func(x):\n",
                  "    return (x - 3) * (x - 5) * (x - 7) + 85\n",
                  "\n",
                  "\n",
                  "a, b = 2, 9 # integral limits\n",
                  "x = np.linspace(0, 10)\n",
                  "y = func(x)\n",
                  "\n",
                  "fig, ax = plt.subplots()\n",
                  "plt.plot(x, y, 'r', linewidth=2)\n",
                  "plt.ylim(ymin=0)\n",
                  "\n",
                  "# Make the shaded region\n",
                  "ix = np.linspace(a, b)\n",
                  "iy = func(ix)\n",
                  "verts = [(a, 0)] + list(zip(ix, iy)) + [(b, 0)]\n",
                  "poly = Polygon(verts, facecolor='0.9', edgecolor='0.5')\n",
                  "ax.add_patch(poly)\n",
                  "\n",
                  "plt.text(0.5 * (a + b), 30, r\"$\\int_a^b f(x)\\mathrm{d}x$\",\n",
                  "         horizontalalignment='center', fontsize=20)\n",
                  "\n",
                  "plt.figtext(0.9, 0.05, '$x$')\n",
                  "plt.figtext(0.1, 0.9, '$y$')\n",
                  "\n",
                  "ax.spines['right'].set_visible(False)\n",
                  "ax.spines['top'].set_visible(False)\n",
                  "ax.xaxis.set_ticks_position('bottom')\n",
                  "\n",
                  "ax.set_xticks((a, b))\n",
                  "ax.set_xticklabels(('$a$', '$b$'))\n",
                  "ax.set_yticks([])\n",
                  "\n",
                  "plt.show()\n"
                 ]
                }
               ],
-              "metadata": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Raw Input in the Notebook.ipynb

0 +20 -2

              {
               "cells": [
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "# Using `raw_input` and `%debug` in the Notebook"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "The Notebook has added support for `raw_input` and `%debug`, as of 1.0."
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 1,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [],
                 "source": [
                  "# Python 3 compat\n",
                  "import sys\n",
                  "if sys.version_info[0] >= 3:\n",
                  "    raw_input = input"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 2,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "What is your name? Sir Robin\n"
                   ]
                  },
                  {
                   "data": {
                    "text/plain": [
                     "'Sir Robin'"
                    ]
                   },
                   "execution_count": 2,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "name = raw_input(\"What is your name? \")\n",
                  "name"
                 ]
                },
                {
                 "cell_type": "markdown",
                 "metadata": {},
                 "source": [
                  "**Python 2-only**: the eval input works as well (`input` is just `eval(raw_input(prompt))`)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 3,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "How many fingers? 4\n"
                   ]
                  },
                  {
                   "data": {
                    "text/plain": [
                     "(4, int)"
                    ]
                   },
                   "execution_count": 3,
                   "metadata": {},
                   "output_type": "execute_result"
                  }
                 ],
                 "source": [
                  "fingers = input(\"How many fingers? \")\n",
                  "fingers, type(fingers)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 4,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "ename": "ZeroDivisionError",
                   "evalue": "integer division or modulo 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-4-a5097cc0c0c5>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      2\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m/\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[0mdiv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\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<ipython-input-4-a5097cc0c0c5>\u001b[0m in \u001b[0;36mdiv\u001b[1;34m(x, y)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdiv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\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----> 2\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m/\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mdiv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\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[1;31mZeroDivisionError\u001b[0m: integer division or modulo by zero"
                   ]
                  }
                 ],
                 "source": [
                  "def div(x, y):\n",
                  "    return x/y\n",
                  "\n",
                  "div(1,0)"
                 ]
                },
                {
                 "cell_type": "code",
                 "execution_count": 5,
                 "metadata": {
                  "collapsed": false
                 },
                 "outputs": [
                  {
                   "name": "stdout",
                   "output_type": "stream",
                   "text": [
                    "> \u001b[1;32m<ipython-input-4-a5097cc0c0c5>\u001b[0m(2)\u001b[0;36mdiv\u001b[1;34m()\u001b[0m\n",
                    "\u001b[1;32m      1 \u001b[1;33m\u001b[1;32mdef\u001b[0m \u001b[0mdiv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\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----> 2 \u001b[1;33m    \u001b[1;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m/\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
                    "\u001b[0m\u001b[1;32m      3 \u001b[1;33m\u001b[1;33m\u001b[0m\u001b[0m\n",
                    "\u001b[0m\n",
                    "ipdb> x\n",
                    "1\n",
                    "ipdb> y\n",
                    "0\n",
                    "ipdb> exit\n"
                   ]
                  }
                 ],
                 "source": [
                  "%debug"
                 ]
                }
               ],
-              "metadata": {},
+              "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
-             }
  No newline at end of file
+             }

examples/IPython Kernel/Rich Output.ipynb

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