regenerate example notebooks to remove transformed output

docs/examples/notebooks/00_notebook_tour.ipynb

@@ -40,7 +40,7 b''
        "output_type": "pyout", 
        "prompt_number": 1, 
        "text": [
-        "u'/home/fperez/ipython/ipython/docs/examples/notebooks'"
+        "u'/home/fperez/ipython/ipython/docs/examples/notebooks'"
        ]
       }
      ], 
@@ -157,7 +157,7 b''
        "output_type": "stream", 
        "stream": "stderr", 
        "text": [
-        "ERROR: File `non_existent_file.py` not found."
+        "ERROR: File `non_existent_file.py` not found."
        ]
       }
      ], 
@@ -178,9 +178,9 b''
        "evalue": "integer division or modulo by zero", 
        "output_type": "pyerr", 
        "traceback": [
-        "<span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">ZeroDivisionError</span>                         Traceback (most recent call last)", 
-        "<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/notebooks/&lt;ipython-input-7-dc39888fd1d2&gt;</span> in <span class=\"ansicyan\">&lt;module&gt;</span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\">      1</span> x <span class=\"ansiyellow\">=</span> <span class=\"ansicyan\">1</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">      2</span> y <span class=\"ansiyellow\">=</span> <span class=\"ansicyan\">4</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">----&gt; 3</span><span class=\"ansiyellow\"> </span>z <span class=\"ansiyellow\">=</span> y<span class=\"ansiyellow\">/</span><span class=\"ansiyellow\">(</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">-</span>x<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n", 
-        "<span class=\"ansired\">ZeroDivisionError</span>: integer division or modulo by zero"
+        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)", 
+        "\u001b[0;32m/home/fperez/ipython/ipython/docs/examples/notebooks/<ipython-input-7-dc39888fd1d2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mz\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", 
+        "\u001b[0;31mZeroDivisionError\u001b[0m: integer division or modulo by zero"
        ]
       }
      ], 
@@ -915,8 +915,7 b''
      "collapsed": true, 
      "input": [], 
      "language": "python", 
-     "outputs": [], 
-     "prompt_number": "&nbsp;"
+     "outputs": []
     }
    ]
   }

docs/examples/notebooks/01_notebook_introduction.ipynb

@@ -43,13 +43,13 b''
      "outputs": [
       {
        "output_type": "pyout", 
-       "prompt_number": 4, 
+       "prompt_number": 1, 
        "text": [
-        "'This is the new IPython notebook'"
+        "'This is the new IPython notebook'"
        ]
       }
      ], 
-     "prompt_number": 4
+     "prompt_number": 1
     }, 
     {
      "cell_type": "markdown", 
@@ -82,7 +82,7 b''
        ]
       }
      ], 
-     "prompt_number": 3
+     "prompt_number": 2
     }, 
     {
      "cell_type": "markdown", 
@@ -113,7 +113,7 b''
        ]
       }
      ], 
-     "prompt_number": 11
+     "prompt_number": 3
     }, 
     {
      "cell_type": "markdown", 
@@ -237,8 +237,7 b''
       "list("
      ], 
      "language": "python", 
-     "outputs": [], 
-     "prompt_number": " "
+     "outputs": []
     }, 
     {
      "cell_type": "markdown", 
@@ -277,25 +276,25 b''
        "stream": "stdout", 
        "text": [
         "{", 
-        "  "stdin_port": 39725, ", 
-        "  "ip": "127.0.0.1", ", 
-        "  "hb_port": 52883, ", 
-        "  "key": "e7b658da-b60b-42f6-b6b0-5098f5d2e533", ", 
-        "  "shell_port": 51742, ", 
-        "  "iopub_port": 41869", 
+        "  \"stdin_port\": 53970, ", 
+        "  \"ip\": \"127.0.0.1\", ", 
+        "  \"hb_port\": 53971, ", 
+        "  \"key\": \"30daac61-6b73-4bae-a7d9-9dca538794d5\", ", 
+        "  \"shell_port\": 53968, ", 
+        "  \"iopub_port\": 53969", 
         "}", 
         "", 
         "Paste the above JSON into a file, and connect with:", 
-        "    $> ipython <app> --existing <file>", 
+        "    $> ipython <app> --existing <file>", 
         "or, if you are local, you can connect with just:", 
-        "    $&gt; ipython &lt;app&gt; --existing kernel-faac4917-d0e0-467a-8467-d3c4d86a3ecc.json ", 
+        "    $> ipython <app> --existing kernel-dd85d1cc-c335-44f4-bed8-f1a2173a819a.json ", 
         "or even just:", 
-        "    $&gt; ipython &lt;app&gt; --existing ", 
+        "    $> ipython <app> --existing ", 
         "if this is the most recent IPython session you have started."
        ]
       }
      ], 
-     "prompt_number": 8
+     "prompt_number": 4
     }, 
     {
      "cell_type": "markdown", 
@@ -361,14 +360,14 b''
        "text": [
         "", 
         "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].", 
-        "For more information, type &apos;help(pylab)&apos;."
+        "For more information, type 'help(pylab)'."
        ]
       }, 
       {
        "output_type": "pyout", 
-       "prompt_number": 12, 
+       "prompt_number": 5, 
        "text": [
-        "[&lt;matplotlib.lines.Line2D at 0x43a2890&gt;]"
+        "[<matplotlib.lines.Line2D at 0x11165bcd0>]"
        ]
       }, 
       {
@@ -376,7 +375,7 b''
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KENI/dkzdg4/aoskrBQ+Ya9OYpuCp/w5kB1k7O0nQMmkFr0Lwfgp+dJTc1GgKm/szBwYI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\n"
       }
      ], 
-     "prompt_number": 12
+     "prompt_number": 5
     }, 
     {
      "cell_type": "markdown", 
@@ -412,10 +411,9 b''
      "collapsed": true, 
      "input": [], 
      "language": "python", 
-     "outputs": [], 
-     "prompt_number": "&nbsp;"
+     "outputs": []
     }
    ]
   }
  ]
-}
+}
  No newline at end of file

docs/examples/notebooks/formatting.ipynb

@@ -117,7 +117,7 b''
      "collapsed": true, 
      "input": [], 
      "language": "python", 
-     "outputs": [], 
+     "outputs": [],
      "prompt_number": " "
     }
    ]

docs/examples/notebooks/sympy.ipynb

@@ -40,7 +40,7 b''
        "text": [
         "", 
         "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].", 
-        "For more information, type 'help(pylab)'."
+        "For more information, type 'help(pylab)'."
        ]
       }
      ], 
@@ -123,7 +123,7 b''
        "output_type": "pyout", 
        "prompt_number": 6, 
        "text": [
-        "Add(Symbol('x'), Mul(Integer(2), Symbol('y')))"
+        "Add(Symbol('x'), Mul(Integer(2), Symbol('y')))"
        ]
       }
      ], 
@@ -317,10 +317,11 b''
         "", 
         "  b              ", 
         " ___             ", 
-        " \\  `            ", 
-        "  \\   \u239b n      2\u239e", 
-        "  /   \u239d2  + 6\u22c5n \u23a0", 
-        " /__,            ", 
+        " \u2572               ",
+        "  \u2572   \u239b n      2\u239e",
+        "  \u2571   \u239d2  + 6\u22c5n \u23a0",
+        " \u2571               ",
+        " \u203e\u203e\u203e             ",
         "n = a            "
        ]
       }

docs/examples/notebooks/trapezoid_rule.ipynb

@@ -110,8 +110,7 b''
      "collapsed": true, 
      "input": [], 
      "language": "python", 
-     "outputs": [], 
-     "prompt_number": " "
+     "outputs": []
     }
    ]
   }

docs/examples/parallel/helloworld.ipynb

@@ -1,65 +1,92 b''
 {
-    "nbformat": 2, 
-    "metadata": {
-        "name": "helloworld"
+ "metadata": {
+  "name": "helloworld"
+ }, 
+ "nbformat": 2, 
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "markdown", 
+     "source": [
+      "# Distributed hello world", 
+      "", 
+      "Originally by Ken Kinder (ken at kenkinder dom com)"
+     ]
     }, 
-    "worksheets": [
-        {
-            "cells": [
-                {
-                    "source": "# Distributed hello world\n\nOriginally by Ken Kinder (ken at kenkinder dom com)", 
-                    "cell_type": "markdown"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 3, 
-                    "input": "from IPython.parallel import Client"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 4, 
-                    "input": "rc = Client()\nview = rc.load_balanced_view()"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 5, 
-                    "input": "def sleep_and_echo(t, msg):\n    import time\n    time.sleep(t)\n    return msg"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 6, 
-                    "input": "world = view.apply_async(sleep_and_echo, 3, 'World!')\nhello = view.apply_async(sleep_and_echo, 2, 'Hello')\n"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [
-                        {
-                            "output_type": "stream", 
-                            "text": "Submitted tasks: ['9e533683-d54e-4588-929e-984dd3eb6dc4'] ['90395f15-723f-44df-a743-a5d88cdeb6a0']\nHello"
-                        }, 
-                        {
-                            "output_type": "stream", 
-                            "text": "World!"
-                        }
-                    ], 
-                    "collapsed": false, 
-                    "prompt_number": 7, 
-                    "input": "print \"Submitted tasks:\", hello.msg_ids, world.msg_ids\nprint hello.get(), world.get()"
-                }
-            ]
-        }
-    ]
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [
+      "from IPython.parallel import Client"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 1
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [
+      "rc = Client()", 
+      "view = rc.load_balanced_view()"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 2
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [
+      "def sleep_and_echo(t, msg):", 
+      "    import time", 
+      "    time.sleep(t)", 
+      "    return msg"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 3
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [
+      "world = view.apply_async(sleep_and_echo, 3, 'World!')", 
+      "hello = view.apply_async(sleep_and_echo, 2, 'Hello')"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 4
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": false, 
+     "input": [
+      "print \"Submitted tasks:\", hello.msg_ids, world.msg_ids", 
+      "print hello.get(), world.get()"
+     ], 
+     "language": "python", 
+     "outputs": [
+      {
+       "output_type": "stream", 
+       "stream": "stdout", 
+       "text": [
+        "Submitted tasks: ['dd1052e0-aa75-4b25-9d35-ecbdaf6e3ed7'] ['1b46aa21-20d1-459c-bc36-2d8d03336f74']", 
+        "Hello"
+       ]
+      }, 
+      {
+       "output_type": "stream", 
+       "stream": "stdout", 
+       "text": [
+        " World!"
+       ]
+      }
+     ], 
+     "prompt_number": 5
+    }
+   ]
+  }
+ ]
 }
  No newline at end of file

docs/examples/parallel/parallel_mpi.ipynb

@@ -1,139 +1,224 b''
 {
-    "worksheets": [
-        {
-            "cells": [
-                {
-                    "source": "# Simple usage of a set of MPI engines\n\nThis example assumes you've started a cluster of N engines (4 in this example) as part\nof an MPI world.  \n\nOur documentation describes [how to create an MPI profile](http://ipython.org/ipython-doc/dev/parallel/parallel_process.html#using-ipcluster-in-mpiexec-mpirun-mode)\nand explains [basic MPI usage of the IPython cluster](http://ipython.org/ipython-doc/dev/parallel/parallel_mpi.html).\n\n\nFor the simplest possible way to start 4 engines that belong to the same MPI world, \nyou can run this in a terminal or antoher notebook:\n\n<pre>\nipcluster start --engines=MPIExecEngineSetLauncher -n 4\n</pre>\n\nNote: to run the above in a notebook, use a *new* notebook and prepend the command with `!`, but do not run\nit in *this* notebook, as this command will block until you shut down the cluster.  To stop the cluster, use \nthe 'Interrupt' button on the left, which is the equivalent of sending `Ctrl-C` to the kernel.\n\nOnce the cluster is running, we can connect to it and open a view into it:", 
-                    "cell_type": "markdown"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 21, 
-                    "input": "from IPython.parallel import Client\nc = Client()\nview = c[:]"
-                }, 
-                {
-                    "source": "Let's define a simple function that ", 
-                    "cell_type": "markdown"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 22, 
-                    "input": "@view.remote(block=True)\ndef mpi_rank():\n    from mpi4py import MPI\n    comm = MPI.COMM_WORLD\n    return comm.Get_rank()"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [
-                        {
-                            "output_type": "pyout", 
-                            "prompt_number": 23, 
-                            "text": "[3, 0, 2, 1]"
-                        }
-                    ], 
-                    "collapsed": false, 
-                    "prompt_number": 23, 
-                    "input": "mpi_rank()"
-                }, 
-                {
-                    "source": "For interactive convenience, we load the parallel magic extensions and make this view\nthe active one for the automatic parallelism magics.\n\nThis is not necessary and in production codes likely won't be used, as the engines will \nload their own MPI codes separately.  But it makes it easy to illustrate everything from\nwithin a single notebook here.", 
-                    "cell_type": "markdown"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 4, 
-                    "input": "%load_ext parallelmagic\nview.activate()"
-                }, 
-                {
-                    "source": "Use the autopx magic to make the rest of this cell execute on the engines instead\nof locally", 
-                    "cell_type": "markdown"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 24, 
-                    "input": "view.block = True"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [
-                        {
-                            "output_type": "stream", 
-                            "stream": "stdout", 
-                            "text": "%autopx enabled\n\n"
-                        }
-                    ], 
-                    "collapsed": false, 
-                    "prompt_number": 32, 
-                    "input": "%autopx"
-                }, 
-                {
-                    "source": "With autopx enabled, the next cell will actually execute *entirely on each engine*:", 
-                    "cell_type": "markdown"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 29, 
-                    "input": "from mpi4py import MPI\n\ncomm = MPI.COMM_WORLD\nsize = comm.Get_size()\nrank = comm.Get_rank()\n\nif rank == 0:\n   data = [(i+1)**2 for i in range(size)]\nelse:\n   data = None\ndata = comm.scatter(data, root=0)\n\nassert data == (rank+1)**2, 'data=%s, rank=%s' % (data, rank)"
-                }, 
-                {
-                    "source": "Though the assertion at the end of the previous block validated the code, we can now \npull the 'data' variable from all the nodes for local inspection.\nFirst, don't forget to toggle off `autopx` mode so code runs again in the notebook:\n", 
-                    "cell_type": "markdown"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [
-                        {
-                            "output_type": "stream", 
-                            "stream": "stdout", 
-                            "text": "%autopx disabled\n\n"
-                        }
-                    ], 
-                    "collapsed": false, 
-                    "prompt_number": 33, 
-                    "input": "%autopx"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [
-                        {
-                            "output_type": "pyout", 
-                            "prompt_number": 34, 
-                            "text": "[16, 1, 9, 4]"
-                        }
-                    ], 
-                    "collapsed": false, 
-                    "prompt_number": 34, 
-                    "input": "view['data']"
-                }, 
-                {
-                    "input": "", 
-                    "cell_type": "code", 
-                    "collapsed": true, 
-                    "language": "python", 
-                    "outputs": []
-                }
-            ]
-        }
-    ], 
-    "metadata": {
-        "name": "parallel_mpi"
+ "metadata": {
+  "name": "parallel_mpi"
+ }, 
+ "nbformat": 2, 
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "markdown", 
+     "source": [
+      "# Simple usage of a set of MPI engines", 
+      "", 
+      "This example assumes you've started a cluster of N engines (4 in this example) as part", 
+      "of an MPI world.  ", 
+      "", 
+      "Our documentation describes [how to create an MPI profile](http://ipython.org/ipython-doc/dev/parallel/parallel_process.html#using-ipcluster-in-mpiexec-mpirun-mode)", 
+      "and explains [basic MPI usage of the IPython cluster](http://ipython.org/ipython-doc/dev/parallel/parallel_mpi.html).", 
+      "", 
+      "", 
+      "For the simplest possible way to start 4 engines that belong to the same MPI world, ", 
+      "you can run this in a terminal or antoher notebook:", 
+      "", 
+      "<pre>", 
+      "ipcluster start --engines=MPI -n 4", 
+      "</pre>", 
+      "", 
+      "Note: to run the above in a notebook, use a *new* notebook and prepend the command with `!`, but do not run", 
+      "it in *this* notebook, as this command will block until you shut down the cluster.  To stop the cluster, use ", 
+      "the 'Interrupt' button on the left, which is the equivalent of sending `Ctrl-C` to the kernel.", 
+      "", 
+      "Once the cluster is running, we can connect to it and open a view into it:"
+     ]
     }, 
-    "nbformat": 2
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [
+      "from IPython.parallel import Client", 
+      "c = Client()", 
+      "view = c[:]"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 21
+    }, 
+    {
+     "cell_type": "markdown", 
+     "source": [
+      "Let's define a simple function that gets the MPI rank from each engine."
+     ]
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [
+      "@view.remote(block=True)", 
+      "def mpi_rank():", 
+      "    from mpi4py import MPI", 
+      "    comm = MPI.COMM_WORLD", 
+      "    return comm.Get_rank()"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 22
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": false, 
+     "input": [
+      "mpi_rank()"
+     ], 
+     "language": "python", 
+     "outputs": [
+      {
+       "output_type": "pyout", 
+       "prompt_number": 23, 
+       "text": [
+        "[3, 0, 2, 1]"
+       ]
+      }
+     ], 
+     "prompt_number": 23
+    }, 
+    {
+     "cell_type": "markdown", 
+     "source": [
+      "For interactive convenience, we load the parallel magic extensions and make this view", 
+      "the active one for the automatic parallelism magics.", 
+      "", 
+      "This is not necessary and in production codes likely won't be used, as the engines will ", 
+      "load their own MPI codes separately.  But it makes it easy to illustrate everything from", 
+      "within a single notebook here."
+     ]
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [
+      "%load_ext parallelmagic", 
+      "view.activate()"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 4
+    }, 
+    {
+     "cell_type": "markdown", 
+     "source": [
+      "Use the autopx magic to make the rest of this cell execute on the engines instead", 
+      "of locally"
+     ]
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [
+      "view.block = True"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 24
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": false, 
+     "input": [
+      "%autopx"
+     ], 
+     "language": "python", 
+     "outputs": [
+      {
+       "output_type": "stream", 
+       "stream": "stdout", 
+       "text": [
+        "%autopx enabled"
+       ]
+      }
+     ], 
+     "prompt_number": 32
+    }, 
+    {
+     "cell_type": "markdown", 
+     "source": [
+      "With autopx enabled, the next cell will actually execute *entirely on each engine*:"
+     ]
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [
+      "from mpi4py import MPI", 
+      "", 
+      "comm = MPI.COMM_WORLD", 
+      "size = comm.Get_size()", 
+      "rank = comm.Get_rank()", 
+      "", 
+      "if rank == 0:", 
+      "   data = [(i+1)**2 for i in range(size)]", 
+      "else:", 
+      "   data = None", 
+      "data = comm.scatter(data, root=0)", 
+      "", 
+      "assert data == (rank+1)**2, 'data=%s, rank=%s' % (data, rank)"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 29
+    }, 
+    {
+     "cell_type": "markdown", 
+     "source": [
+      "Though the assertion at the end of the previous block validated the code, we can now ", 
+      "pull the 'data' variable from all the nodes for local inspection.", 
+      "First, don't forget to toggle off `autopx` mode so code runs again in the notebook:"
+     ]
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": false, 
+     "input": [
+      "%autopx"
+     ], 
+     "language": "python", 
+     "outputs": [
+      {
+       "output_type": "stream", 
+       "stream": "stdout", 
+       "text": [
+        "%autopx disabled"
+       ]
+      }
+     ], 
+     "prompt_number": 33
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": false, 
+     "input": [
+      "view['data']"
+     ], 
+     "language": "python", 
+     "outputs": [
+      {
+       "output_type": "pyout", 
+       "prompt_number": 34, 
+       "text": [
+        "[16, 1, 9, 4]"
+       ]
+      }
+     ], 
+     "prompt_number": 34
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [], 
+     "language": "python", 
+     "outputs": []
+    }
+   ]
+  }
+ ]
 }
  No newline at end of file

docs/examples/parallel/taskmap.ipynb

@@ -1,71 +1,109 b''
 {
-    "nbformat": 2, 
-    "metadata": {
-        "name": "taskmap"
+ "metadata": {
+  "name": "taskmap"
+ }, 
+ "nbformat": 2, 
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "markdown", 
+     "source": [
+      "# Load balanced map and parallel function decorator"
+     ]
     }, 
-    "worksheets": [
-        {
-            "cells": [
-                {
-                    "source": "# Load balanced map and parallel function decorator", 
-                    "cell_type": "markdown"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 4, 
-                    "input": "from IPython.parallel import Client"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 5, 
-                    "input": "rc = Client()\nv = rc.load_balanced_view()"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [
-                        {
-                            "output_type": "stream", 
-                            "text": "Simple, default map:  [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
-                        }
-                    ], 
-                    "collapsed": false, 
-                    "prompt_number": 6, 
-                    "input": "result = v.map(lambda x: 2*x, range(10))\nprint \"Simple, default map: \", list(result)"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [
-                        {
-                            "output_type": "stream", 
-                            "text": "Submitted tasks, got ids:  ['2a25ff3f-f0d0-4428-909a-3fe808ca61f9', 'edd42168-fac2-4b3f-a696-ce61b37aa71d', '8a548908-7812-44e6-a8b1-68e941bee608', '26435a77-fe86-49b6-b59f-de864d59c99f', '6750c7b4-2168-49ec-bcc4-feb1e17c5e53', '117240d1-5dfc-4783-948f-e9523b2b2f6a', '6de16d46-f2e2-49bd-8180-e43d1d875529', '3d372b84-0c68-4315-92c8-a080c68478b7', '43acedae-e35c-4a17-87f0-9e5e672500f7', 'eb71dd1f-9500-4375-875d-c2c42999848c']\nUsing a mapper:  [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
-                        }
-                    ], 
-                    "collapsed": false, 
-                    "prompt_number": 7, 
-                    "input": "ar = v.map_async(lambda x: 2*x, range(10))\nprint \"Submitted tasks, got ids: \", ar.msg_ids\nresult = ar.get()\nprint \"Using a mapper: \", result"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [
-                        {
-                            "output_type": "stream", 
-                            "text": "Using a parallel function:  [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
-                        }
-                    ], 
-                    "collapsed": false, 
-                    "prompt_number": 8, 
-                    "input": "@v.parallel(block=True)\ndef f(x): return 2*x\n\nresult = f.map(range(10))\nprint \"Using a parallel function: \", result"
-                }
-            ]
-        }
-    ]
+    {
+     "cell_type": "code", 
+     "collapsed": true, 
+     "input": [
+      "from IPython.parallel import Client"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 1
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": false, 
+     "input": [
+      "rc = Client()", 
+      "v = rc.load_balanced_view()"
+     ], 
+     "language": "python", 
+     "outputs": [], 
+     "prompt_number": 3
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": false, 
+     "input": [
+      "result = v.map(lambda x: 2*x, range(10))", 
+      "print \"Simple, default map: \", list(result)"
+     ], 
+     "language": "python", 
+     "outputs": [
+      {
+       "output_type": "stream", 
+       "stream": "stdout", 
+       "text": [
+        "Simple, default map:  "
+       ]
+      }, 
+      {
+       "output_type": "stream", 
+       "stream": "stdout", 
+       "text": [
+        "[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
+       ]
+      }
+     ], 
+     "prompt_number": 4
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": false, 
+     "input": [
+      "ar = v.map_async(lambda x: 2*x, range(10))", 
+      "print \"Submitted tasks, got ids: \", ar.msg_ids", 
+      "result = ar.get()", 
+      "print \"Using a mapper: \", result"
+     ], 
+     "language": "python", 
+     "outputs": [
+      {
+       "output_type": "stream", 
+       "stream": "stdout", 
+       "text": [
+        "Submitted tasks, got ids:  ['5100a4c7-73a4-4832-aa91-e774f6f3ede8', 'd0cae1cf-2b32-4092-9eb7-f17b43fb3849', 'e08d3ee2-f221-47fe-9556-ed938e692030', '065585e4-cdf9-4240-a5fe-e44b2ae5d023', 'd2162f23-68e5-4318-ba1e-e34fd03a72ac', '5b3b835f-2099-4a70-9896-d1aa810c77e6', 'e2c2a823-bd44-4f91-8db3-c154d0d86e56', '991e0c25-f98a-44b5-9d9e-889d4180b9a5', '4ad41221-28bd-482f-a300-97c404648161', '5b730eb3-e0bb-4cdd-b228-c3b8d158828a']", 
+        "Using a mapper:  [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
+       ]
+      }
+     ], 
+     "prompt_number": 5
+    }, 
+    {
+     "cell_type": "code", 
+     "collapsed": false, 
+     "input": [
+      "@v.parallel(block=True)", 
+      "def f(x): return 2*x", 
+      "", 
+      "result = f.map(range(10))", 
+      "print \"Using a parallel function: \", result"
+     ], 
+     "language": "python", 
+     "outputs": [
+      {
+       "output_type": "stream", 
+       "stream": "stdout", 
+       "text": [
+        "Using a parallel function:  [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
+       ]
+      }
+     ], 
+     "prompt_number": 6
+    }
+   ]
+  }
+ ]
 }
  No newline at end of file