remove signatures from example notebook metadata

examples/Customization/Index.ipynb

@@ -1,103 +1,101 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "<img src=\"../images/ipython_logo.png\">"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Back to the main [Index](../Index.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# 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": {
-  "signature": "sha256:de8cb1aff3da9097ba3fc7afab4327fc589f2bb1c154feeeb5ed97c87e37486f"
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 0
 }
  No newline at end of file

examples/Embedding/Index.ipynb

@@ -1,194 +1,192 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "<img src=\"../images/ipython_logo.png\">"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Back to the main [Index](../Index.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# 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": {
-  "signature": "sha256:627cdf03b8de558c9344f9d1e8f0beeb2448e37e492d676e6db7b07d33251a2b"
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 0
 }
  No newline at end of file

examples/IPython Kernel/Beyond Plain Python.ipynb

@@ -1,1807 +1,1805 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "# IPython: beyond plain Python"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "When executing code in IPython, all valid Python syntax works as-is, but IPython provides a number of features designed to make the interactive experience more fluid and efficient."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
     }
    },
    "source": [
     "## First things first: running code, getting help"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "In the notebook, to run a cell of code, hit `Shift-Enter`. This executes the cell and puts the cursor in the next cell below, or makes a new one if you are at the end.  Alternately, you can use:\n",
     "    \n",
     "- `Alt-Enter` to force the creation of a new cell unconditionally (useful when inserting new content in the middle of an existing notebook).\n",
     "- `Control-Enter` executes the cell and keeps the cursor in the same cell, useful for quick experimentation of snippets that you don't need to keep permanently."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Hi\n"
      ]
     }
    ],
    "source": [
     "print \"Hi\""
    ]
   },
   {
    "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."
    ]
   },
   {
    "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",
       "\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": {
-  "signature": "sha256:31071a05d0ecd75ed72fe3f0de0ad447a6f85cffe382c26efa5e68db1fee54ee"
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 0
 }
  No newline at end of file

examples/IPython Kernel/Capturing Output.ipynb

@@ -1,489 +1,487 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Capturing Output With <tt>%%capture</tt>"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "IPython has a [cell magic](Cell Magics.ipynb), `%%capture`, which captures the stdout/stderr of a cell. With this magic you can discard these streams or store them in a variable."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 9,
    "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"
      ]
     },
     {
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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": {
-  "signature": "sha256:df6354daf203e842bc040989d149760382d8ceec769160e4efe8cde9dfcb9107"
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 0
 }
  No newline at end of file

examples/IPython Kernel/Custom Display Logic.ipynb

@@ -1,1325 +1,1323 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Custom Display Logic"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Overview"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "As described in the [Rich Output](Rich Output.ipynb) tutorial, the IPython display system can display rich representations of objects in the following formats:\n",
     "\n",
     "* JavaScript\n",
     "* HTML\n",
     "* PNG\n",
     "* JPEG\n",
     "* SVG\n",
     "* LaTeX\n",
     "* PDF\n",
     "\n",
     "This Notebook shows how you can add custom display logic to your own classes, so that they can be displayed using these rich representations. There are two ways of accomplishing this:\n",
     "\n",
     "1. Implementing special display methods such as `_repr_html_` when you define your class.\n",
     "2. Registering a display function for a particular existing class.\n",
     "\n",
     "This Notebook describes and illustrates both approaches."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Import the IPython display functions."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "from IPython.display import (\n",
     "    display, display_html, display_png, display_svg\n",
     ")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Parts of this notebook need the matplotlib inline backend:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Special display methods"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The main idea of the first approach is that you have to implement special display methods when you define your class, one for each representation you want to use. Here is a list of the names of the special methods and the values they must return:\n",
     "\n",
     "* `_repr_html_`: return raw HTML as a string\n",
     "* `_repr_json_`: return raw JSON as a string\n",
     "* `_repr_jpeg_`: return raw JPEG data\n",
     "* `_repr_png_`: return raw PNG data\n",
     "* `_repr_svg_`: return raw SVG data as a string\n",
     "* `_repr_latex_`: return LaTeX commands in a string surrounded by \"$\"."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "As an illustration, we build a class that holds data generated by sampling a Gaussian distribution with given mean and standard deviation. Here is the definition of the `Gaussian` class, which has a custom PNG and LaTeX representation."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "from IPython.core.pylabtools import print_figure\n",
     "from IPython.display import Image, SVG, Math\n",
     "\n",
     "class Gaussian(object):\n",
     "    \"\"\"A simple object holding data sampled from a Gaussian distribution.\n",
     "    \"\"\"\n",
     "    def __init__(self, mean=0.0, std=1, size=1000):\n",
     "        self.data = np.random.normal(mean, std, size)\n",
     "        self.mean = mean\n",
     "        self.std = std\n",
     "        self.size = size\n",
     "        # For caching plots that may be expensive to compute\n",
     "        self._png_data = None\n",
     "        \n",
     "    def _figure_data(self, format):\n",
     "        fig, ax = plt.subplots()\n",
     "        ax.hist(self.data, bins=50)\n",
     "        ax.set_title(self._repr_latex_())\n",
     "        ax.set_xlim(-10.0,10.0)\n",
     "        data = print_figure(fig, format)\n",
     "        # We MUST close the figure, otherwise IPython's display machinery\n",
     "        # will pick it up and send it as output, resulting in a double display\n",
     "        plt.close(fig)\n",
     "        return data\n",
     "        \n",
     "    def _repr_png_(self):\n",
     "        if self._png_data is None:\n",
     "            self._png_data = self._figure_data('png')\n",
     "        return self._png_data\n",
     "    \n",
     "    def _repr_latex_(self):\n",
     "        return r'$\\mathcal{N}(\\mu=%.2g, \\sigma=%.2g),\\ N=%d$' % (self.mean,\n",
     "                                                                 self.std, self.size)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Create an instance of the Gaussian distribution and return it to display the default representation:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
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        "Cryjw/3qBSOE2UGbk8uFM26t6XggW752Ao8QXpPfLbYr0fk8MA48Wtc2BGwEtgEbgMUF9ItTgBXA\n",
        "/UwN8tMIdfRDCHX17XiKgKyuAz5SdCciN5/w2ltOeC26b2fufkAIH2X3VmAlU4P8RuBjyfI1wPWz\n",
        "PUg7gnQr4ZOk0cXAHYSjNHYS3kxnt+H5e52HKs6NB7K1h6/L1nwTaDxyahUwmiyPAqtne5BOjoh/\n",
        "klAWqPEAotZcDWwBbqWgr1yR80C2/FWB+4CHgCsK7ksvGCaUW0iuh2e7Q6unsd0ILGnSfi1wT4bH\n",
        "8aCig033t/0D4Cbgj5L1Pwb+DLi8Q/3qFb7m8vcWYBdwLOH1u5Uw0tTcVUnxmm01yC9o4T4/BOp/\n",
        "0uW4pE1Tpf3b3kK2D00Fja/DZUz9pqjsdiXXzwB3EcpXBnnrxgmDuTFgKfD0bHdod2mlvm62Hngf\n",
        "4eChE4GTcQ93Vkvrlt/N1B0kSuchwmtvOeG1+F7Ca1OtORJYmCwvIMxG83U5N+uBNcnyGuDuIjrx\n",
        "bkIN8iXCJ8rX6m67lrCjaSvwS53vWvS+QJjmtYXwnztr7UxNeSBbfk4kzPx5GHgM/55Z3QH8D7CX\n",
        "kJuXEWYA3UfB0w8lSZIkSZIkSZIkSZIkSZIkSZIktcn/A4eK9UXawRDUAAAAAElFTkSuQmCC\n"
       ],
       "text/latex": [
        "$\\mathcal{N}(\\mu=2, \\sigma=1),\\ N=1000$"
       ],
       "text/plain": [
        "<__main__.Gaussian at 0x106e7ae10>"
       ]
      },
      "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "x = Gaussian(2.0, 1.0)\n",
     "x"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "You can also pass the object to the `display` function to display the default representation:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
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        "Cryjw/3qBSOE2UGbk8uFM26t6XggW752Ao8QXpPfLbYr0fk8MA48Wtc2BGwEtgEbgMUF9ItTgBXA\n",
        "/UwN8tMIdfRDCHX17XiKgKyuAz5SdCciN5/w2ltOeC26b2fufkAIH2X3VmAlU4P8RuBjyfI1wPWz\n",
        "PUg7gnQr4ZOk0cXAHYSjNHYS3kxnt+H5e52HKs6NB7K1h6/L1nwTaDxyahUwmiyPAqtne5BOjoh/\n",
        "klAWqPEAotZcDWwBbqWgr1yR80C2/FWB+4CHgCsK7ksvGCaUW0iuh2e7Q6unsd0ILGnSfi1wT4bH\n",
        "8aCig033t/0D4Cbgj5L1Pwb+DLi8Q/3qFb7m8vcWYBdwLOH1u5Uw0tTcVUnxmm01yC9o4T4/BOp/\n",
        "0uW4pE1Tpf3b3kK2D00Fja/DZUz9pqjsdiXXzwB3EcpXBnnrxgmDuTFgKfD0bHdod2mlvm62Hngf\n",
        "4eChE4GTcQ93Vkvrlt/N1B0kSuchwmtvOeG1+F7Ca1OtORJYmCwvIMxG83U5N+uBNcnyGuDuIjrx\n",
        "bkIN8iXCJ8rX6m67lrCjaSvwS53vWvS+QJjmtYXwnztr7UxNeSBbfk4kzPx5GHgM/55Z3QH8D7CX\n",
        "kJuXEWYA3UfB0w8lSZIkSZIkSZIkSZIkSZIkSZIktcn/A4eK9UXawRDUAAAAAElFTkSuQmCC\n"
       ],
       "text/latex": [
        "$\\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": {
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       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "display_png(x)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "<div class=\"alert alert-success\">\n",
     "It is important to note a subtle different between <code>display</code> and <code>display_png</code>. The former computes <em>all</em> representations of the object, and lets the notebook UI decide which to display. The later only computes the PNG representation.\n",
     "</div>"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Create a new Gaussian with different parameters:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
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        "DeGhp23A+W0uVwyGCfc2nkg+yztamt7kw3fNtQt4knA9PtLZovSk24AR4KnUsiFgI7Ad2ADM7kC5\n",
        "qjoRWAw8SHm4LyG0zU8ntNXvwAHN6nU98JudLkQPm0a47hYQrkPvFTXuPwhhpGzOBE6hPNxvAj6V\n",
        "TF8D3DjZDtoZotsIf3EqXQCsAw4S/trvIDwMpfpE3U2gxdIP3x1k7OE7NcZrMrvvAJXDw64A1ibT\n",
        "a4GVk+2gG2rIx1HeXXI34WEo1edjwBbgy3TR17UeUe3hO6/BxhSBBwhP6V3Z4bLEYg6hqYbk3zmT\n",
        "rdzsfu4bgblVll8L3FfHfnwYaryJzu11wM3A7yXzvw98DriiTeWKgddb8/0s8H3gTYRrdxuhNqrm\n",
        "mHJUtmaH+3kZtql88OmEZJnK1Xpub6W+P6Sq7eE71ef7yb8vAXcRmr4M98aMECp4e4B5wIuTrdyp\n",
        "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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      },
      "metadata": {},
      "output_type": "display_data"
     },
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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": {
-  "signature": "sha256:86c779d5798c4a68bda7e71c8ef320cb7ba9d7e3d0f1bc4b828ee65f617a5ae3"
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 0
 }
  No newline at end of file

examples/IPython Kernel/Index.ipynb

@@ -1,168 +1,166 b''
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "<img src=\"../images/ipython_logo.png\">"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Back to the main [Index](../Index.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# IPython Kernel"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "IPython provides extensions to the Python programming language that make working interactively convenient and efficient. These extensions are implemented in the IPython Kernel and are available in all of the IPython Frontends (Notebook, Terminal, Console and Qt Console) when running this kernel."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Tutorials"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "* [Cell Magics](Cell Magics.ipynb)\n",
     "* [Script Magics](Script Magics.ipynb)\n",
     "* [Rich Output](Rich Output.ipynb)\n",
     "* [Custom Display Logic](Custom Display Logic.ipynb)\n",
     "* [Plotting in the Notebook](Plotting in the Notebook.ipynb)\n",
     "* [Capturing Output](Capturing Output.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Examples"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "* [Background Jobs](Background Jobs.ipynb)\n",
     "* [Trapezoid Rule](Trapezoid Rule.ipynb)\n",
     "* [SymPy](SymPy.ipynb)\n",
     "* [Raw Input in the Notebook](Raw Input in the Notebook.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Non-notebook examples"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "This directory also contains examples that are regular Python (`.py`) files."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/html": [
        "<a href='example-demo.py' target='_blank'>example-demo.py</a><br>"
       ],
       "text/plain": [
        "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/IPython Kernel/example-demo.py"
       ]
      },
      "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": {
-  "signature": "sha256:ee769d05a7e195e4b8546ef9a866ef03e59bff2f0fcba499d168c06b516aa79a"
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 0
 }
  No newline at end of file

examples/IPython Kernel/Plotting in the Notebook.ipynb

@@ -1,740 +1,738 b''
 {
  "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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       ],
       "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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       ],
       "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": {
-  "signature": "sha256:74dbf5caa25c937be70dfe2ab509783a01f4a2044850d7044e729300a8c3644d"
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 0
 }
  No newline at end of file

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

@@ -1,158 +1,156 b''
 {
  "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": {
-  "signature": "sha256:ac5c21534f3dd013c78d4d201527f3ed4dea5b6fad4116b8d23c67ba107e48c3"
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 0
 }
  No newline at end of file