Updating a few example notebooks to v3.

examples/lib/BackgroundJobs.ipynb

@@ -1,193 +1,381 b''
 {
+ "metadata": {
+  "name": "BackgroundJobs"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
     "worksheets": [
         {
             "cells": [
                 {
-                    "source": "# Simple interactive bacgkround jobs with IPython\n\nWe start by loading the `backgroundjobs` library and defining a few trivial functions to illustrate things with.", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "# Simple interactive bacgkround jobs with IPython\n",
+      "\n",
+      "We start by loading the `backgroundjobs` library and defining a few trivial functions to illustrate things with."
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "from IPython.lib import backgroundjobs as bg\n",
+      "\n",
+      "import sys\n",
+      "import time\n",
+      "\n",
+      "def sleepfunc(interval=2, *a, **kw):\n",
+      "    args = dict(interval=interval,\n",
+      "                args=a,\n",
+      "                kwargs=kw)\n",
+      "    time.sleep(interval)\n",
+      "    return args\n",
+      "\n",
+      "def diefunc(interval=2, *a, **kw):\n",
+      "    time.sleep(interval)\n",
+      "    raise Exception(\"Dead job with interval %s\" % interval)\n",
+      "\n",
+      "def printfunc(interval=1, reps=5):\n",
+      "    for n in range(reps):\n",
+      "        time.sleep(interval)\n",
+      "        print 'In the background...', n\n",
+      "        sys.stdout.flush()\n",
+      "    print 'All done!'\n",
+      "    sys.stdout.flush()"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": false, 
-                    "prompt_number": 35, 
-                    "input": "from IPython.lib import backgroundjobs as bg\n\nimport sys\nimport time\n\ndef sleepfunc(interval=2, *a, **kw):\n    args = dict(interval=interval,\n                args=a,\n                kwargs=kw)\n    time.sleep(interval)\n    return args\n\ndef diefunc(interval=2, *a, **kw):\n    time.sleep(interval)\n    raise Exception(\"Dead job with interval %s\" % interval)\n\ndef printfunc(interval=1, reps=5):\n    for n in range(reps):\n        time.sleep(interval)\n        print 'In the background...', n\n        sys.stdout.flush()\n    print 'All done!'\n    sys.stdout.flush()"
+     "prompt_number": 35
                 }, 
                 {
-                    "source": "Now, we can create a job manager (called simply `jobs`) and use it to submit new jobs.\n<br>\nRun the cell below and wait a few seconds for the whole thing to finish, until you see the \"All done!\" printout.", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Now, we can create a job manager (called simply `jobs`) and use it to submit new jobs.\n",
+      "<br>\n",
+      "Run the cell below and wait a few seconds for the whole thing to finish, until you see the \"All done!\" printout."
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "jobs = bg.BackgroundJobManager()\n",
+      "\n",
+      "# Start a few jobs, the first one will have ID # 0\n",
+      "jobs.new(sleepfunc, 4)\n",
+      "jobs.new(sleepfunc, kw={'reps':2})\n",
+      "jobs.new('printfunc(1,3)')\n",
+      "\n",
+      "# This makes a couple of jobs which will die.  Let's keep a reference to\n",
+      "# them for easier traceback reporting later\n",
+      "diejob1 = jobs.new(diefunc, 1)\n",
+      "diejob2 = jobs.new(diefunc, 2)"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "Starting job # 0 in a separate thread.\nStarting job # 2 in a separate thread.\nStarting job # 3 in a separate thread.\nStarting job # 4 in a separate thread.\nStarting job # 5 in a separate thread.\n"
+       "text": [
+        "Starting job # 0 in a separate thread.\n",
+        "Starting job # 2 in a separate thread.\n",
+        "Starting job # 3 in a separate thread.\n",
+        "Starting job # 4 in a separate thread.\n",
+        "Starting job # 5 in a separate thread.\n"
+       ]
                         }, 
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "In the background... 0\n"
+       "text": [
+        "In the background... 0\n"
+       ]
                         }, 
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "In the background... 1\n"
+       "text": [
+        "In the background... 1\n"
+       ]
                         }, 
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "In the background... 2\n"
+       "text": [
+        "In the background... 2\n"
+       ]
                         }, 
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "All done!\n"
+       "text": [
+        "All done!\n"
+       ]
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 36, 
-                    "input": "jobs = bg.BackgroundJobManager()\n\n# Start a few jobs, the first one will have ID # 0\njobs.new(sleepfunc, 4)\njobs.new(sleepfunc, kw={'reps':2})\njobs.new('printfunc(1,3)')\n\n# This makes a couple of jobs which will die.  Let's keep a reference to\n# them for easier traceback reporting later\ndiejob1 = jobs.new(diefunc, 1)\ndiejob2 = jobs.new(diefunc, 2)"
+     "prompt_number": 36
                 }, 
                 {
-                    "source": "You can check the status of your jobs at any time:", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "You can check the status of your jobs at any time:"
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "jobs.status()"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "Completed jobs:\n0 : &lt;function sleepfunc at 0x30e1578&gt;\n2 : &lt;function sleepfunc at 0x30e1578&gt;\n3 : printfunc(1,3)\n\nDead jobs:\n4 : &lt;function diefunc at 0x304d488&gt;\n5 : &lt;function diefunc at 0x304d488&gt;\n\n"
+       "text": [
+        "Completed jobs:\n",
+        "0 : &lt;function sleepfunc at 0x30e1578&gt;\n",
+        "2 : &lt;function sleepfunc at 0x30e1578&gt;\n",
+        "3 : printfunc(1,3)\n",
+        "\n",
+        "Dead jobs:\n",
+        "4 : &lt;function diefunc at 0x304d488&gt;\n",
+        "5 : &lt;function diefunc at 0x304d488&gt;\n",
+        "\n"
+       ]
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 37, 
-                    "input": "jobs.status()"
+     "prompt_number": 37
                 }, 
                 {
-                    "source": "For any completed job, you can get its result easily:", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "For any completed job, you can get its result easily:"
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "jobs[0].result\n",
+      "j0 = jobs[0]\n",
+      "j0.join?"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": false, 
-                    "prompt_number": 43, 
-                    "input": "jobs[0].result\nj0 = jobs[0]\nj0.join?"
+     "prompt_number": 43
                 }, 
                 {
-                    "source": "You can get the traceback of any dead job.  Run the line\nbelow again interactively until it prints a traceback (check the status\nof the job):\n", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "You can get the traceback of any dead job.  Run the line\n",
+      "below again interactively until it prints a traceback (check the status\n",
+      "of the job):\n"
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "print \"Status of diejob1:\", diejob1.status\n",
+      "diejob1.traceback()  # jobs.traceback(4) would also work here, with the job number"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "Status of diejob1: Dead (Exception), call jobs.traceback() for details\n<span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">Exception</span>                                 Traceback (most recent call last)\n<span class=\"ansigreen\">/home/fperez/usr/lib/python2.6/site-packages/IPython/lib/backgroundjobs.py</span> in <span class=\"ansicyan\">call</span><span class=\"ansiblue\">(self)</span>\n<span class=\"ansigreen\">    462</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">    463</span>     <span class=\"ansigreen\">def</span> call<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">--&gt; 464</span><span class=\"ansiyellow\">         </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>func<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>self<span class=\"ansiyellow\">.</span>args<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>self<span class=\"ansiyellow\">.</span>kwargs<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/lib/&lt;ipython-input-15-54795a097787&gt;</span> in <span class=\"ansicyan\">diefunc</span><span class=\"ansiblue\">(interval, *a, **kw)</span>\n<span class=\"ansigreen\">     14</span> <span class=\"ansigreen\">def</span> diefunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">2</span><span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">     15</span>     time<span class=\"ansiyellow\">.</span>sleep<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">---&gt; 16</span><span class=\"ansiyellow\">     </span><span class=\"ansigreen\">raise</span> Exception<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">&quot;Dead job with interval %s&quot;</span> <span class=\"ansiyellow\">%</span> interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">     17</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">     18</span> <span class=\"ansigreen\">def</span> printfunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">,</span> reps<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">5</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansired\">Exception</span>: Dead job with interval 1\n"
+       "text": [
+        "Status of diejob1: Dead (Exception), call jobs.traceback() for details\n",
+        "<span class=\"ansired\">---------------------------------------------------------------------------</span>\n",
+        "<span class=\"ansired\">Exception</span>                                 Traceback (most recent call last)\n",
+        "<span class=\"ansigreen\">/home/fperez/usr/lib/python2.6/site-packages/IPython/lib/backgroundjobs.py</span> in <span class=\"ansicyan\">call</span><span class=\"ansiblue\">(self)</span>\n",
+        "<span class=\"ansigreen\">    462</span> <span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">    463</span>     <span class=\"ansigreen\">def</span> call<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">--&gt; 464</span><span class=\"ansiyellow\">         </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>func<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>self<span class=\"ansiyellow\">.</span>args<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>self<span class=\"ansiyellow\">.</span>kwargs<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n",
+        "\n",
+        "<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/lib/&lt;ipython-input-15-54795a097787&gt;</span> in <span class=\"ansicyan\">diefunc</span><span class=\"ansiblue\">(interval, *a, **kw)</span>\n",
+        "<span class=\"ansigreen\">     14</span> <span class=\"ansigreen\">def</span> diefunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">2</span><span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">     15</span>     time<span class=\"ansiyellow\">.</span>sleep<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">---&gt; 16</span><span class=\"ansiyellow\">     </span><span class=\"ansigreen\">raise</span> Exception<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">&quot;Dead job with interval %s&quot;</span> <span class=\"ansiyellow\">%</span> interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">     17</span> <span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">     18</span> <span class=\"ansigreen\">def</span> printfunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">,</span> reps<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">5</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n",
+        "\n",
+        "<span class=\"ansired\">Exception</span>: Dead job with interval 1\n"
+       ]
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 34, 
-                    "input": "print \"Status of diejob1:\", diejob1.status\ndiejob1.traceback()  # jobs.traceback(4) would also work here, with the job number"
+     "prompt_number": 34
                 }, 
                 {
-                    "source": "This will print all tracebacks for all dead jobs:", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "This will print all tracebacks for all dead jobs:"
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "jobs.traceback()"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "Traceback for: &lt;BackgroundJob #4: &lt;function diefunc at 0x30df758&gt;&gt;\n<span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">Exception</span>                                 Traceback (most recent call last)\n<span class=\"ansigreen\">/home/fperez/usr/lib/python2.6/site-packages/IPython/lib/backgroundjobs.py</span> in <span class=\"ansicyan\">call</span><span class=\"ansiblue\">(self)</span>\n<span class=\"ansigreen\">    462</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">    463</span>     <span class=\"ansigreen\">def</span> call<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">--&gt; 464</span><span class=\"ansiyellow\">         </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>func<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>self<span class=\"ansiyellow\">.</span>args<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>self<span class=\"ansiyellow\">.</span>kwargs<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/lib/&lt;ipython-input-15-54795a097787&gt;</span> in <span class=\"ansicyan\">diefunc</span><span class=\"ansiblue\">(interval, *a, **kw)</span>\n<span class=\"ansigreen\">     14</span> <span class=\"ansigreen\">def</span> diefunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">2</span><span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">     15</span>     time<span class=\"ansiyellow\">.</span>sleep<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">---&gt; 16</span><span class=\"ansiyellow\">     </span><span class=\"ansigreen\">raise</span> Exception<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">&quot;Dead job with interval %s&quot;</span> <span class=\"ansiyellow\">%</span> interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">     17</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">     18</span> <span class=\"ansigreen\">def</span> printfunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">,</span> reps<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">5</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansired\">Exception</span>: Dead job with interval 1\n\nTraceback for: &lt;BackgroundJob #5: &lt;function diefunc at 0x30df758&gt;&gt;\n<span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">Exception</span>                                 Traceback (most recent call last)\n<span class=\"ansigreen\">/home/fperez/usr/lib/python2.6/site-packages/IPython/lib/backgroundjobs.py</span> in <span class=\"ansicyan\">call</span><span class=\"ansiblue\">(self)</span>\n<span class=\"ansigreen\">    462</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">    463</span>     <span class=\"ansigreen\">def</span> call<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">--&gt; 464</span><span class=\"ansiyellow\">         </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>func<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>self<span class=\"ansiyellow\">.</span>args<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>self<span class=\"ansiyellow\">.</span>kwargs<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/lib/&lt;ipython-input-15-54795a097787&gt;</span> in <span class=\"ansicyan\">diefunc</span><span class=\"ansiblue\">(interval, *a, **kw)</span>\n<span class=\"ansigreen\">     14</span> <span class=\"ansigreen\">def</span> diefunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">2</span><span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">     15</span>     time<span class=\"ansiyellow\">.</span>sleep<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">---&gt; 16</span><span class=\"ansiyellow\">     </span><span class=\"ansigreen\">raise</span> Exception<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">&quot;Dead job with interval %s&quot;</span> <span class=\"ansiyellow\">%</span> interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">     17</span> <span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">     18</span> <span class=\"ansigreen\">def</span> printfunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">,</span> reps<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">5</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n\n<span class=\"ansired\">Exception</span>: Dead job with interval 2\n\n"
+       "text": [
+        "Traceback for: &lt;BackgroundJob #4: &lt;function diefunc at 0x30df758&gt;&gt;\n",
+        "<span class=\"ansired\">---------------------------------------------------------------------------</span>\n",
+        "<span class=\"ansired\">Exception</span>                                 Traceback (most recent call last)\n",
+        "<span class=\"ansigreen\">/home/fperez/usr/lib/python2.6/site-packages/IPython/lib/backgroundjobs.py</span> in <span class=\"ansicyan\">call</span><span class=\"ansiblue\">(self)</span>\n",
+        "<span class=\"ansigreen\">    462</span> <span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">    463</span>     <span class=\"ansigreen\">def</span> call<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">--&gt; 464</span><span class=\"ansiyellow\">         </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>func<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>self<span class=\"ansiyellow\">.</span>args<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>self<span class=\"ansiyellow\">.</span>kwargs<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n",
+        "\n",
+        "<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/lib/&lt;ipython-input-15-54795a097787&gt;</span> in <span class=\"ansicyan\">diefunc</span><span class=\"ansiblue\">(interval, *a, **kw)</span>\n",
+        "<span class=\"ansigreen\">     14</span> <span class=\"ansigreen\">def</span> diefunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">2</span><span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">     15</span>     time<span class=\"ansiyellow\">.</span>sleep<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">---&gt; 16</span><span class=\"ansiyellow\">     </span><span class=\"ansigreen\">raise</span> Exception<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">&quot;Dead job with interval %s&quot;</span> <span class=\"ansiyellow\">%</span> interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">     17</span> <span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">     18</span> <span class=\"ansigreen\">def</span> printfunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">,</span> reps<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">5</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n",
+        "\n",
+        "<span class=\"ansired\">Exception</span>: Dead job with interval 1\n",
+        "\n",
+        "Traceback for: &lt;BackgroundJob #5: &lt;function diefunc at 0x30df758&gt;&gt;\n",
+        "<span class=\"ansired\">---------------------------------------------------------------------------</span>\n",
+        "<span class=\"ansired\">Exception</span>                                 Traceback (most recent call last)\n",
+        "<span class=\"ansigreen\">/home/fperez/usr/lib/python2.6/site-packages/IPython/lib/backgroundjobs.py</span> in <span class=\"ansicyan\">call</span><span class=\"ansiblue\">(self)</span>\n",
+        "<span class=\"ansigreen\">    462</span> <span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">    463</span>     <span class=\"ansigreen\">def</span> call<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">--&gt; 464</span><span class=\"ansiyellow\">         </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>func<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>self<span class=\"ansiyellow\">.</span>args<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>self<span class=\"ansiyellow\">.</span>kwargs<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n",
+        "\n",
+        "<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/lib/&lt;ipython-input-15-54795a097787&gt;</span> in <span class=\"ansicyan\">diefunc</span><span class=\"ansiblue\">(interval, *a, **kw)</span>\n",
+        "<span class=\"ansigreen\">     14</span> <span class=\"ansigreen\">def</span> diefunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">2</span><span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">     15</span>     time<span class=\"ansiyellow\">.</span>sleep<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">---&gt; 16</span><span class=\"ansiyellow\">     </span><span class=\"ansigreen\">raise</span> Exception<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">&quot;Dead job with interval %s&quot;</span> <span class=\"ansiyellow\">%</span> interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">     17</span> <span class=\"ansiyellow\"></span>\n",
+        "<span class=\"ansigreen\">     18</span> <span class=\"ansigreen\">def</span> printfunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">,</span> reps<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">5</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n",
+        "\n",
+        "<span class=\"ansired\">Exception</span>: Dead job with interval 2\n",
+        "\n"
+       ]
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 33, 
-                    "input": "jobs.traceback()"
+     "prompt_number": 33
                 }, 
                 {
-                    "source": "The job manager can be flushed of all completed jobs at any time:", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "The job manager can be flushed of all completed jobs at any time:"
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "jobs.flush()"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "No jobs to flush.\n"
+       "text": [
+        "No jobs to flush.\n"
+       ]
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 25, 
-                    "input": "jobs.flush()"
+     "prompt_number": 25
                 }, 
                 {
-                    "source": "After that, the status is simply empty:", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "After that, the status is simply empty:"
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": true,
+     "input": [
+      "jobs.status()"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 27, 
-                    "input": "jobs.status()"
+     "prompt_number": 27
                 }, 
                 {
-                    "source": "It's easy to wait on a job:", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "It's easy to wait on a job:"
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "j = jobs.new(sleepfunc, 2)\n",
+      "print \"Will wait for j now...\"\n",
+      "sys.stdout.flush()\n",
+      "j.join()\n",
+      "print \"Result from j:\"\n",
+      "j.result"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "Starting job # 7 in a separate thread.\nWill wait for j now...\n"
+       "text": [
+        "Starting job # 7 in a separate thread.\n",
+        "Will wait for j now...\n"
+       ]
                         }, 
                         {
                             "output_type": "stream", 
                             "stream": "stdout", 
-                            "text": "Result from j:\n"
+       "text": [
+        "Result from j:\n"
+       ]
                         }, 
                         {
                             "output_type": "pyout", 
                             "prompt_number": 46, 
-                            "text": "{&apos;args&apos;: (), &apos;interval&apos;: 2, &apos;kwargs&apos;: {}}"
+       "text": [
+        "{&apos;args&apos;: (), &apos;interval&apos;: 2, &apos;kwargs&apos;: {}}"
+       ]
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 46, 
-                    "input": "j = jobs.new(sleepfunc, 2)\nprint \"Will wait for j now...\"\nsys.stdout.flush()\nj.join()\nprint \"Result from j:\"\nj.result"
+     "prompt_number": 46
                 }, 
                 {
-                    "input": "", 
                     "cell_type": "code", 
                     "collapsed": true, 
+     "input": [],
                     "language": "python", 
+     "metadata": {},
                     "outputs": []
                 }
-            ]
-        }
     ], 
-    "metadata": {
-        "name": "BackgroundJobs"
-    }, 
-    "nbformat": 2
+   "metadata": {}
+  }
+ ]
 }
  No newline at end of file

examples/parallel/rmt/rmt.ipynb

@@ -1,228 +1,308 b''
 {
-    "nbformat": 2, 
     "metadata": {
         "name": "rmt"
     }, 
+ "nbformat": 3,
+ "nbformat_minor": 0,
     "worksheets": [
         {
             "cells": [
                 {
-                    "source": "# Eigenvalue distribution of Gaussian orthogonal random matrices", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "# Eigenvalue distribution of Gaussian orthogonal random matrices"
+     ]
                 }, 
                 {
-                    "source": "The eigenvalues of random matrices obey certain statistical laws. Here we construct random matrices \nfrom the Gaussian Orthogonal Ensemble (GOE), find their eigenvalues and then investigate the nearest\nneighbor eigenvalue distribution $\\rho(s)$.", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "The eigenvalues of random matrices obey certain statistical laws. Here we construct random matrices \n",
+      "from the Gaussian Orthogonal Ensemble (GOE), find their eigenvalues and then investigate the nearest\n",
+      "neighbor eigenvalue distribution $\\rho(s)$."
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "from rmtkernel import ensemble_diffs, normalize_diffs, GOE\n",
+      "import numpy as np\n",
+      "from IPython.parallel import Client"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": false, 
-                    "prompt_number": 1, 
-                    "input": "from rmtkernel import ensemble_diffs, normalize_diffs, GOE\nimport numpy as np\nfrom IPython.parallel import Client"
+     "prompt_number": 1
                 }, 
                 {
-                    "source": "## Wigner's nearest neighbor eigenvalue distribution", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "## Wigner's nearest neighbor eigenvalue distribution"
+     ]
                 }, 
                 {
-                    "source": "The Wigner distribution gives the theoretical result for the nearest neighbor eigenvalue distribution\nfor the GOE:\n\n$$\\rho(s) = \\frac{\\pi s}{2} \\exp(-\\pi s^2/4)$$", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "The Wigner distribution gives the theoretical result for the nearest neighbor eigenvalue distribution\n",
+      "for the GOE:\n",
+      "\n",
+      "$$\\rho(s) = \\frac{\\pi s}{2} \\exp(-\\pi s^2/4)$$"
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": true,
+     "input": [
+      "def wigner_dist(s):\n",
+      "    \"\"\"Returns (s, rho(s)) for the Wigner GOE distribution.\"\"\"\n",
+      "    return (np.pi*s/2.0) * np.exp(-np.pi*s**2/4.)"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 2, 
-                    "input": "def wigner_dist(s):\n    \"\"\"Returns (s, rho(s)) for the Wigner GOE distribution.\"\"\"\n    return (np.pi*s/2.0) * np.exp(-np.pi*s**2/4.)"
+     "prompt_number": 2
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": true,
+     "input": [
+      "def generate_wigner_data():\n",
+      "    s = np.linspace(0.0,4.0,400)\n",
+      "    rhos = wigner_dist(s)\n",
+      "    return s, rhos"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 3, 
-                    "input": "def generate_wigner_data():\n    s = np.linspace(0.0,4.0,400)\n    rhos = wigner_dist(s)\n    return s, rhos"
+     "prompt_number": 3
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "s, rhos = generate_wigner_data()"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": false, 
-                    "prompt_number": 4, 
-                    "input": "s, rhos = generate_wigner_data()"
+     "prompt_number": 4
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "plot(s, rhos)\n",
+      "xlabel('Normalized level spacing s')\n",
+      "ylabel('Probability $\\rho(s)$')"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [
                         {
                             "output_type": "pyout", 
                             "prompt_number": 17, 
-                            "text": "<matplotlib.text.Text at 0x3828790>"
+       "text": [
+        "<matplotlib.text.Text at 0x3828790>"
+       ]
                         }, 
                         {
                             "output_type": "display_data", 
                             "png": 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oUeqcDCkYQljOrILx8ssvs2DBAlq1asWMGTOIc/Kps1Iwai83N5gxQ33KcIGH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\nSUVORK5CYII=\n"
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 17, 
-                    "input": "plot(s, rhos)\nxlabel('Normalized level spacing s')\nylabel('Probability $\\rho(s)$')"
+     "prompt_number": 17
                 }, 
                 {
-                    "source": "## Serial calculation of nearest neighbor eigenvalue distribution", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "## Serial calculation of nearest neighbor eigenvalue distribution"
+     ]
                 }, 
                 {
-                    "source": "In this section we numerically construct and diagonalize a large number of GOE random matrices\nand compute the nerest neighbor eigenvalue distribution. This comptation is done on a single core.", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "In this section we numerically construct and diagonalize a large number of GOE random matrices\n",
+      "and compute the nerest neighbor eigenvalue distribution. This comptation is done on a single core."
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": true,
+     "input": [
+      "def serial_diffs(num, N):\n",
+      "    \"\"\"Compute the nearest neighbor distribution for num NxX matrices.\"\"\"\n",
+      "    diffs = ensemble_diffs(num, N)\n",
+      "    normalized_diffs = normalize_diffs(diffs)\n",
+      "    return normalized_diffs"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 6, 
-                    "input": "def serial_diffs(num, N):\n    \"\"\"Compute the nearest neighbor distribution for num NxX matrices.\"\"\"\n    diffs = ensemble_diffs(num, N)\n    normalized_diffs = normalize_diffs(diffs)\n    return normalized_diffs"
+     "prompt_number": 6
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": true,
+     "input": [
+      "serial_nmats = 1000\n",
+      "serial_matsize = 50"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 7, 
-                    "input": "serial_nmats = 1000\nserial_matsize = 50"
+     "prompt_number": 7
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "%timeit -r1 -n1 serial_diffs(serial_nmats, serial_matsize)"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [
                         {
                             "output_type": "stream", 
-                            "text": "1 loops, best of 1: 1.19 s per loop"
+       "stream": "stdout",
+       "text": [
+        "1 loops, best of 1: 1.19 s per loop"
+       ]
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 8, 
-                    "input": "%timeit -r1 -n1 serial_diffs(serial_nmats, serial_matsize)"
+     "prompt_number": 8
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "serial_diffs = serial_diffs(serial_nmats, serial_matsize)"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": false, 
-                    "prompt_number": 9, 
-                    "input": "serial_diffs = serial_diffs(serial_nmats, serial_matsize)"
+     "prompt_number": 9
                 }, 
                 {
-                    "source": "The numerical computation agrees with the predictions of Wigner, but it would be nice to get more\nstatistics. For that we will do a parallel computation.", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "The numerical computation agrees with the predictions of Wigner, but it would be nice to get more\n",
+      "statistics. For that we will do a parallel computation."
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": false,
+     "input": [
+      "hist_data = hist(serial_diffs, bins=30, normed=True)\n",
+      "plot(s, rhos)\n",
+      "xlabel('Normalized level spacing s')\n",
+      "ylabel('Probability $P(s)$')"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [
                         {
                             "output_type": "pyout", 
                             "prompt_number": 10, 
-                            "text": "<matplotlib.text.Text at 0x3475bd0>"
+       "text": [
+        "<matplotlib.text.Text at 0x3475bd0>"
+       ]
                         }, 
                         {
                             "output_type": "display_data", 
                             "png": 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CWKxqWTAyczM5EH8Af2d/raMIU0lpDXtfhSeeB12+1mmEsEjVsmDsu7SPjk06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\nrkJggg==\n"
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 10, 
-                    "input": "hist_data = hist(serial_diffs, bins=30, normed=True)\nplot(s, rhos)\nxlabel('Normalized level spacing s')\nylabel('Probability $P(s)$')"
+     "prompt_number": 10
                 }, 
                 {
-                    "source": "## Parallel calculation of nearest neighbor eigenvalue distribution", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "## Parallel calculation of nearest neighbor eigenvalue distribution"
+     ]
                 }, 
                 {
-                    "source": "Here we perform a parallel computation, where each process constructs and diagonalizes a subset of\nthe overall set of random matrices.", 
-                    "cell_type": "markdown"
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Here we perform a parallel computation, where each process constructs and diagonalizes a subset of\n",
+      "the overall set of random matrices."
+     ]
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": true,
+     "input": [
+      "def parallel_diffs(rc, num, N):\n",
+      "    nengines = len(rc.targets)\n",
+      "    num_per_engine = num/nengines\n",
+      "    print \"Running with\", num_per_engine, \"per engine.\"\n",
+      "    ar = rc.apply_async(ensemble_diffs, num_per_engine, N)\n",
+      "    diffs = np.array(ar.get()).flatten()\n",
+      "    normalized_diffs = normalize_diffs(diffs)\n",
+      "    return normalized_diffs"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 11, 
-                    "input": "def parallel_diffs(rc, num, N):\n    nengines = len(rc.targets)\n    num_per_engine = num/nengines\n    print \"Running with\", num_per_engine, \"per engine.\"\n    ar = rc.apply_async(ensemble_diffs, num_per_engine, N)\n    diffs = np.array(ar.get()).flatten()\n    normalized_diffs = normalize_diffs(diffs)\n    return normalized_diffs"
+     "prompt_number": 11
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": true,
+     "input": [
+      "client = Client()\n",
+      "view = client[:]\n",
+      "view.run('rmtkernel.py')\n",
+      "view.block = False"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 12, 
-                    "input": "client = Client()\nview = client[:]\nview.run('rmtkernel.py')\nview.block = False"
+     "prompt_number": 12
                 }, 
                 {
                     "cell_type": "code", 
+     "collapsed": true,
+     "input": [
+      "parallel_nmats = 40*serial_nmats\n",
+      "parallel_matsize = 50"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [], 
-                    "collapsed": true, 
-                    "prompt_number": 13, 
-                    "input": "parallel_nmats = 40*serial_nmats\nparallel_matsize = 50"
+     "prompt_number": 13
                 }, 
                 {
                     "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [
-                        {
-                            "output_type": "stream", 
-                            "text": "Running with 10000 per engine.\n1 loops, best of 1: 14 s per loop"
-                        }, 
-                        {
-                            "output_type": "stream"
-                        }
-                    ], 
                     "collapsed": false, 
-                    "prompt_number": 14, 
-                    "input": "%timeit -r1 -n1 parallel_diffs(view, parallel_nmats, parallel_matsize)"
-                }, 
-                {
-                    "cell_type": "code", 
+     "input": [
+      "%timeit -r1 -n1 parallel_diffs(view, parallel_nmats, parallel_matsize)"
+     ],
                     "language": "python", 
+     "metadata": {},
                     "outputs": [
                         {
                             "output_type": "stream", 
-                            "text": "Running with 10000 per engine."
+       "stream": "stdout",
+       "text": [
+        "Running with 10000 per engine.\n",
+        "1 loops, best of 1: 14 s per loop"
+       ]
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 15, 
-                    "input": "pdiffs = parallel_diffs(view, parallel_nmats, parallel_matsize)"
-                }, 
-                {
-                    "source": "Again, the agreement with the Wigner distribution is excellent, but now we have better\nstatistics.", 
-                    "cell_type": "markdown"
-                }, 
-                {
-                    "cell_type": "code", 
-                    "language": "python", 
-                    "outputs": [
-                        {
-                            "output_type": "pyout", 
-                            "prompt_number": 16, 
-                            "text": "<matplotlib.text.Text at 0x376c950>"
-                        }, 
-                        {
-                            "output_type": "display_data", 
-                            "png": 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uXX4vD3d9mIe7mU54O90eBoCmEJ52hfj18Pu9lfZpLz9DIZxFVT87VbkOw1rspWBcuHaB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\nYgzjDehT9fgt8mPlwZWy+q2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P8+bNGTZsWJnbJDw8nJkzZ/Lee+9RUFBAnTp1Kv2ZCMdh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\n"
+     "prompt_number": 14
                         }
                     ], 
-                    "collapsed": false, 
-                    "prompt_number": 16, 
-                    "input": "hist_data = hist(pdiffs, bins=30, normed=True)\nplot(s, rhos)\nxlabel('Normalized level spacing s')\nylabel('Probability $P(s)$')"
-                }
-            ]
+   "metadata": {}
         }
     ]
 }
  No newline at end of file

examples/tests/heartbeat/gilsleep.ipynb

@@ -2,17 +2,19 b''
  "metadata": {
   "name": "gilsleep"
  }, 
- "nbformat": 2, 
+ "nbformat": 3,
+ "nbformat_minor": 0,
  "worksheets": [
   {
    "cells": [
     {
      "cell_type": "markdown", 
+     "metadata": {},
      "source": [
-      "Holding the GIL for too long could disrupt the heartbeat due to non-copying sends.", 
-      "", 
-      "The following cell repeatedly calls a function that holds the GIL for five seconds.", 
-      "", 
+      "Holding the GIL for too long could disrupt the heartbeat due to non-copying sends.\n",
+      "\n",
+      "The following cell repeatedly calls a function that holds the GIL for five seconds.\n",
+      "\n",
       "The heartbeat will fail after a few iterations prior to fixing Issue [#1260](https://github.com/ipython/ipython/issues/1260)."
      ]
     }, 
@@ -20,25 +22,26 b''
      "cell_type": "code", 
      "collapsed": false, 
      "input": [
-      "import sys", 
-      "import time", 
-      "", 
-      "from cython import inline", 
-      "", 
-      "def gilsleep(t):", 
-      "    \"\"\"gil-holding sleep with cython.inline\"\"\"", 
-      "    code = '\\n'.join([", 
-      "        'from posix cimport unistd',", 
-      "        'unistd.sleep(t)',", 
-      "    ])", 
-      "    while True:", 
-      "        inline(code, quiet=True, t=t)", 
-      "        print time.time()", 
-      "        sys.stdout.flush() # this is important", 
-      "", 
+      "import sys\n",
+      "import time\n",
+      "\n",
+      "from cython import inline\n",
+      "\n",
+      "def gilsleep(t):\n",
+      "    \"\"\"gil-holding sleep with cython.inline\"\"\"\n",
+      "    code = '\\n'.join([\n",
+      "        'from posix cimport unistd',\n",
+      "        'unistd.sleep(t)',\n",
+      "    ])\n",
+      "    while True:\n",
+      "        inline(code, quiet=True, t=t)\n",
+      "        print time.time()\n",
+      "        sys.stdout.flush() # this is important\n",
+      "\n",
       "gilsleep(5)"
      ], 
      "language": "python", 
+     "metadata": {},
      "outputs": [], 
      "prompt_number": 1
     }, 
@@ -47,10 +50,12 b''
      "collapsed": true, 
      "input": [], 
      "language": "python", 
+     "metadata": {},
      "outputs": [], 
      "prompt_number": " "
     }
-   ]
+   ],
+   "metadata": {}
   }
  ]
 }
  No newline at end of file