upstream/ipython Commit - r6674:65a259f3

Fix handling of raw cells in all converters, add stderr to test nb

Fernando Perez -

r6674:65a259f3

parent child

nbconvert.py

0 +71 -29

             from __future__ import print_function
             import codecs
+            import logging
             import os
             import pprint
             import re
                 with_preamble = True
                 user_preamble = None
                 output = str()
+                raw_as_verbatim = False
                 def __init__(self, infile):
                     self.infile = infile
                     lines.extend(self.optional_header())
                     for worksheet in self.nb.worksheets:
                         for cell in worksheet.cells:
+                            #print(cell.cell_type)  # dbg
                             conv_fn = self.dispatch(cell.cell_type)
                             lines.extend(conv_fn(cell))
                             lines.append('')
                     Returns list."""
                     raise NotImplementedError
-                def render_plaintext(self, cell):
+                def render_raw(self, cell):
-                    """convert plain text
+                    """convert a cell with raw text
                     Returns list."""
                     raise NotImplementedError
                     """Render cells of unkown type
                     Returns list."""
+                    data = pprint.pformat(cell)
+                    logging.warning('Unknown cell:\n%s' % data)
+                    return self._unknown_lines(data)
+                def _unknown_lines(self, data):
+                    """Return list of lines for an unknown cell.
+                    Parameters
+                    ----------
+                    data : str
+                      The content of the unknown data as a single string.
+                    """
                     raise NotImplementedError
                     return [cell.source]
                 @DocInherit
-                def render_plaintext(self, cell):
+                def render_raw(self, cell):
+                    if self.raw_as_verbatim:
+                        return ['::', '', indent(cell.source), '']
+                    else:
                         return [cell.source]
                 @DocInherit
                     return lines
                 @DocInherit
+                def render_pyerr(self, output):
+                    # Note: a traceback is a *list* of frames.
+                    return ['::', '', indent(remove_ansi('\n'.join(output.traceback))), '']
+                @DocInherit
                 def _img_lines(self, img_file):
                     return ['.. image:: %s' % img_file, '']
                     return lines
                 @DocInherit
-                def render_unknown(self, cell):
+                def _unknown_lines(self, data):
-                    return rst_directive('.. warning:: Unknown cell') + [repr(cell)]
+                    return rst_directive('.. warning:: Unknown cell') + [data]
             class ConverterQuickHTML(Converter):
                 extension = 'html'
+                def in_tag(self, tag, src):
+                    """Return a list of elements bracketed by the given tag"""
+                    return ['<%s>' % tag, src, '</%s>' % tag]
                 def optional_header(self):
                     # XXX: inject the IPython standard CSS into here
                     s = """<html>
                 @DocInherit
                 def render_markdown(self, cell):
-                    return ["<pre>"+cell.source+"</pre>"]
+                    return self.in_tag('pre', cell.source)
                 @DocInherit
-                def render_plaintext(self, cell):
+                def render_raw(self, cell):
-                    return ["<pre>"+cell.source+"</pre>"]
+                    if self.raw_as_verbatim:
+                        return self.in_tag('pre', cell.source)
+                    else:
+                        return [cell.source]
                 @DocInherit
                 def render_pyout(self, output):
-                    lines = ['<tr><td><tt>Out[<b>%s</b>]:</tt></td></tr>' % output.prompt_number, '<td>']
+                    lines = ['<tr><td><tt>Out[<b>%s</b>]:</tt></td></tr>' %
+                             output.prompt_number, '<td>']
                     # output is a dictionary like object with type as a key
-                    if 'latex' in output:
+                    for out_type in ('text', 'latex'):
-                        lines.append("<pre>")
+                        if out_type in output:
-                        lines.extend(indent(output.latex))
+                            lines.extend(self.in_tag('pre', indent(output[out_type])))
-                        lines.append("</pre>")
-                    if 'text' in output:
-                        lines.append("<pre>")
-                        lines.extend(indent(output.text))
-                        lines.append("</pre>")
                     return lines
                 @DocInherit
+                def render_pyerr(self, output):
+                    # Note: a traceback is a *list* of frames.
+                    return self.in_tag('pre', remove_ansi('\n'.join(output.traceback)))
+                @DocInherit
                 def _img_lines(self, img_file):
                     return ['<img src="%s">' % img_file, '']
                     return lines
+                @DocInherit
+                def _unknown_lines(self, data):
+                    return ['<h2>Warning:: Unknown cell</h2>'] + self.in_tag('pre', data)
             class ConverterLaTeX(Converter):
                 """Converts a notebook to a .tex file suitable for pdflatex.
 : r'\subparagraph',
 : r'\subparagraph'}
-                def env(self, environment, lines):
+                def in_env(self, environment, lines):
                     """Return list of environment lines for input lines
                     Parameters
                     # Cell codes first carry input code, we use lstlisting for that
                     lines = [r'\begin{codecell}']
-                    lines.extend(self.env('codeinput',
+                    lines.extend(self.in_env('codeinput',
-                                          self.env('lstlisting', cell.input)))
+                                          self.in_env('lstlisting', cell.input)))
                     outlines = []
                     for output in cell.outputs:
                     # And then output of many possible types; use a frame for all of it.
                     if outlines:
-                        lines.extend(self.env('codeoutput', outlines))
+                        lines.extend(self.in_env('codeoutput', outlines))
                     lines.append(r'\end{codecell}')
                 @DocInherit
                 def _img_lines(self, img_file):
-                    return self.env('center',
+                    return self.in_env('center',
                             [r'\includegraphics[width=3in]{%s}' % img_file, r'\par'])
                 def _svg_lines(self, img_file):
                     lines = []
                     if 'text' in output:
-                        lines.extend(self.env('verbatim', output.text.strip()))
+                        lines.extend(self.in_env('verbatim', output.text.strip()))
                     return lines
                         lines.extend(output.latex)
                     if 'text' in output:
-                        lines.extend(self.env('verbatim', output.text))
+                        lines.extend(self.in_env('verbatim', output.text))
                     return lines
                 @DocInherit
                 def render_pyerr(self, output):
                     # Note: a traceback is a *list* of frames.
-                    return self.env('traceback',
+                    return self.in_env('traceback',
-                                    self.env('verbatim',
+                                    self.in_env('verbatim',
                                              remove_ansi('\n'.join(output.traceback))))
                 @DocInherit
-                def render_unknown(self, cell):
+                def render_raw(self, cell):
-                    return self.env('verbatim', pprint.pformat(cell))
+                    if self.raw_as_verbatim:
+                        return self.in_env('verbatim', cell.source)
+                    else:
+                        return [cell.source]
+                @DocInherit
+                def _unknown_lines(self, data):
+                    return [r'{\vspace{5mm}\bf WARNING:: unknown cell:}'] + \
+                      self.in_env('verbatim', data)
             def rst2simplehtml(infile):

tests/test.ipynb

0 +65 -14

@@ -51,15 +51,12 b''
51	{	51	{
52	"cell_type": "markdown",	52	"cell_type": "markdown",
53	"source": [	53	"source": [
54	"A section heading",
55	"=================",
56	"",
57	"A bit of text, with important things:",	54	"A bit of text, with important things:",
58	"",	55	"",
59	"* and",	56	"* and",
60	"* more",	57	"* more that are boldface, as well as `verbatim`.",
61	"",	58	"",
62	"Using ~~reST links to `ipython <~~http://ipython.org~~>`_~~."	59	"Using markdown hyperlinks for [ipython](http://ipython.org)."
63	]	60	]
64	},	61	},
65	{	62	{
@@ -67,21 +64,21 b''
67	"collapsed": false,	64	"collapsed": false,
68	"input": [	65	"input": [
69	"f = figure()",	66	"f = figure()",
70	"plot([1])",	67	"plot([1,2,3])",
71	"display(f)"	68	"display(f)"
72	],	69	],
73	"language": "python",	70	"language": "python",
74	"outputs": [	71	"outputs": [
75	{	72	{
76	"output_type": "display_data",	73	"output_type": "display_data",
77	"png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAD3CAYAAAAUl4NyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABLEQAAYCkCAAAs9X/vh7DYicSaVQAAAABJRU5ErkJggg==\n",	74	"png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAD3CAYAAAAJxX+sAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nz6ixi4j4GTV2ERE/8/9mUozJaDh2nQAAAABJRU5ErkJggg==\n",
78	"text": [	75	"text": [
79	"<matplotlib.figure.Figure at 0x~~28f2750~~>"	76	"<matplotlib.figure.Figure at 0x981bccc>"
80	]	77	]
81	},	78	},
82	{	79	{
83	"output_type": "display_data",	80	"output_type": "display_data",
84	"png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAD3CAYAAAAUl4NyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABLEQAAYCkCAAAs9X/vh7DYicSaVQAAAABJRU5ErkJggg==\n"	81	"png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAD3CAYAAAAJxX+sAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAG9JJREFUeJzt3Xt0VeWZx/FvEIoDA1QuEkQEEsotIZ5ATKCACZRChaK2\noMi4GBdETBXlJlXwUmCwzKy2CEUFsWMrGuINlBIQAZETMIFcJCCEwJgwmcQaMAnlZiSEZM8fr9JG\n4OR2Tva5/D5rZQmcvc5+1l7bhx/v2ed5gyzLshAREb/RzO4CRETEvdTYRUT8jBq7iIifUWMXEfEz\nauwiIn5GjV1ExM+4bOwXLlwgJiYGh8PB4MGDWb58+VWPW7BgASEhIQwaNIijR496pFAREamboNqe\nYy8vL6dVq1ZUVFQwaNAgNm7cSK9evS6/npGRwdy5c9m0aRPbtm1j3bp1bN682eOFi4jI1dW6FNOq\nVSsAzp8/z6VLl2jZsmWN19PT05k4cSLt27dn8uTJ5ObmeqZSERGpk+a1HVBdXU1kZCQ5OTmsWLGC\nbt261Xg9IyODKVOmXP59p06dyM/PJzQ0tMZxQUFBbipZRCSw1HdAQK2JvVmzZhw8eJC8vDxWrVpF\ndnb2FSf8/kmv1cS/O1Y/jftZuHCh7TX404+up66nN/188IHFLbdYTJtmcepUwya+1PmpmB49ejB2\n7FjS09Nr/HlMTAxHjhy5/PuSkhJCQkIaVIyISKAqK4N//3d45BF49VXzc8MNDXsvl429tLSU06dP\nf3vSMrZv385dd91V45iYmBg2bNhAWVkZSUlJ9OvXr2GViIgEIMuCd9+FAQOgQwc4dAhGjWrce7pc\nYy8uLuaBBx6gqqqK4OBg5s2bR5cuXVizZg0ACQkJREdHM2zYMKKiomjfvj2JiYmNq0hqFRcXZ3cJ\nfkXX0710PeuuuNgk9GPHYMMGGDLEPe9b6+OO7hIUFEQTnUpExKtZFvzlLzB/PvzqV/D00/C9Bw4v\na0jvrPWpGBERcZ/jx+Ghh+D0adixA2691f3n0EgBEZEmUFUFK1ZAdDSMGQP79nmmqYMSu4iIxx05\nAvHx8IMfQFoa9O7t2fMpsYuIeMjFi7BkCcTGwgMPwK5dnm/qoMQuIuIRWVkmpd98M+zfD9/70r5H\nKbGLiLhReTk88QSMG2f+u3lz0zZ1UGMXEXGblBTzgWhRkfmi0f33gx1jsrQUIyLSSGfPwpNPQnIy\nrFoFd95pbz1K7CIijbBlC4SHm8cZDx+2v6mDEruISIOUlsLs2bB3L7z2GowcaXdF/6DELiJSD5YF\nb71lUnrnzmYt3ZuaOiixi4jU2d/+ZoZ25efDX/8KMTF2V3R1SuwiIrWwLPjTn8DhgMhI81y6tzZ1\nUGIXEXEpPx+mT4fz5+Hjj83cdG+nxC4ichVVVfD88yaZjxtnPiT1haYOSuwiIlc4fNiMA2jVykxh\n7NXL7orqR4ldRORbFy/C4sUwYgQ8+CDs3Ol7TR2U2EVEAMjIMCm9Z084cAC6drW7ooZTYxeRgFZe\nDs8+C+vWmY0wJk2yZ76LO2kpRkQC1q5d5gPREyfMuvp99/l+UwcldhEJQGfOwK9/DVu3wurV8POf\n212Reymxi0hASU424wCaNTMp3d+aOiixi0iAKCmBmTPNzkZvvAFxcXZX5DlK7CLi1yzLfDA6YIDZ\nyejgQf9u6qDELiJ+rKgIHn4YCgvNFnVRUXZX1DSU2EXE71RXw8svw8CBZiRAVlbgNHVQYhcRP/P5\n52Zo14UL4HRCWJjdFTU9JXYR8QuXLsHvfw9DhsDdd0NqamA2dVBiFxE/8NlnZhxAu3ZmNEBIiN0V\n2UuJXUR8VkUF/OY3MGqU+ZB0xw41dVBiFxEftXevSem9e5uhXTfdZHdF3kONXUR8ytdfw9NPw9tv\nw8qVMHGif8x3cSctxYiIz/joI/NFo1OnzDiAe+5RU78aJXYR8XqnT8Pjj5vG/vLLcMcddlfk3ZTY\nRcSrbdxoHlu8/no4dEhNvS6U2EXEK508CY89Zma7vPkm3H673RX5DiV2EfEqlgWvvw4RERAaap54\nUVOvHyV2EfEahYWQkADFxfDBBzBokN0V+SYldhGxXXU1vPSSGdo1fDhkZqqpN4YSu4jY6tgxePBB\nqKqCPXugXz+7K/J9SuwiYotLl+C//guGDoV771VTdycldhFpcgcOmHEAHTqYWek9ethdkX9RYheR\nJnPhghkHMHq0eZRx2zY1dU9QYheRJpGaalJ6WJgZsxscbHdF/kuNXUQ86vx5eOopWL8eXngBJkyw\nuyL/53IppqioiBEjRhAWFkZcXBxJSUlXHON0OmnXrh2RkZFERkby3HPPeaxYEfEt27dDeDicPWuG\ndqmpNw2Xib1FixYsX74ch8NBaWkp0dHRjB8/njZt2tQ4LjY2lk2bNnm0UBHxHadOmaFdu3bBmjUw\nZozdFQUWl4k9ODgYh8MBQMeOHQkLCyMrK+uK4yzL8kx1IuJzNmwwKb1NGzO0S0296dV5jT0vL4+c\nnByio6Nr/HlQUBBpaWk4HA5GjhzJjBkzCA0NdXuhIuLdiovh0UchJwfefdc8ny72qFNjP3fuHJMm\nTWL58uW0bt26xmsDBw6kqKiIFi1asHbtWmbNmsXmzZuv+j6LFi26/Ou4uDji4uIaXLiIeAfLgrVr\n4YknYPp0WLfOjNiVhnE6nTidzka9R5BVyzpKZWUl48aNY+zYscyePdvlm1mWRXBwMIWFhbRs2bLm\niYKCtGQj4mcKCuChh6C0FP78Z/h25VbcqCG90+Uau2VZxMfHEx4efs2mfvLkycsnTU5OJiIi4oqm\nLiL+pbraPLoYFQUjR0J6upq6N3G5FJOamkpiYiIRERFERkYCsHTpUgoLCwFISEhg/fr1rF69mubN\nmxMREcGyZcs8X7WI2CY31wztatbMfOmoTx+7K5Lvq3Upxm0n0lKMiE+rrITf/x6efx4WL4aHHzbN\nXTyrIb1T3zwVkVrt3w/TpkGXLvDpp9C9u90ViSv6+1ZErumbb2D+fLOB9OOPm12N1NS9nxK7iFzV\nnj1mLf3WW83Qrs6d7a5I6kqNXURqOHfOpPSNG+HFF+EXv7C7IqkvLcWIyGVbt5pxABcumKFdauq+\nSYldRCgrgzlzzPLLq6/CqFF2VySNocQuEsAsC955x6T0Dh3M0C41dd+nxC4SoL78EmbMgGPH4L33\nYMgQuysSd1FiFwkwlmWWWxwOGDAAsrPV1P2NErtIADl+3AztOn0aduwwjzKK/1FiFwkAVVWwYgVE\nR5uNL/btU1P3Z0rsIn7uyBGIj4cf/ADS0qB3b7srEk9TYhfxUxcvwpIlEBsLDzxg9h9VUw8MSuwi\nfigz06T0bt3MAK9u3eyuSJqSEruIHykvN1vU/fzn8OSTsHmzmnogUmMX8RMpKeYD0aIi80Wj+++H\noCC7qxI7aClGxMedPWvSeXIyrFoFd95pd0ViNyV2ER+2ZYsZB1BVZYZ2qakLKLGL+KSSEpg92zyP\n/tprZkNpke8osYv4EMuCt94yowCCg80GGGrq8n1K7CI+4m9/MxtIHz8Of/0rxMTYXZF4KyV2ES9n\nWfCnP5mhXQMHmufS1dTFFSV2ES+Wnw/Tp8P58/Dxx2YJRqQ2SuwiXqiqCpYtM8l83DjYu1dNXepO\niV3Eyxw+DNOmQevW5qmXXr3srkh8jRK7iJe4eBEWLYIRI8zyy86daurSMErsIl4gI8Ok9JAQOHAA\nuna1uyLxZWrsIjYqL4dnn4V168xGGJMmab6LNJ6WYkRssmuX+UD0xAmzrn7ffWrq4h5K7CJN7PRp\nM1p361ZYvdqM2BVxJyV2kSa0aZMZ2tWsmUnpauriCUrsIk3gq69g5kzIyoLERIiLs7si8WdK7CIe\nZFnmg9EBA+CWW8zQLjV18TQldhEPKSoyQ7sKC83c9KgouyuSQKHELuJm1dXw8stmYFdMjFl+UVOX\npqTELuJGn38ODz4IFRXgdEJYmN0VSSBSYhdxg0uX4He/gyFD4Be/gNRUNXWxjxK7SCMdPAjx8fDD\nH5rRACEhdlckgU6JXaSBKirMOICf/hQeeQR27FBTF++gxC7SAHv3mpTeu7cZ2nXTTXZXJPIPauwi\n9fD11/D00/D227ByJUycqPku4n20FCNSRx99ZL5odOqUGQdwzz1q6uKdlNhFavH3v8O8eaaxv/wy\n3HGH3RWJuKbELuLC+++boV3/8i8mpaupiy9QYhe5ipMn4bHHzAejb70Fw4fbXZFI3blM7EVFRYwY\nMYKwsDDi4uJISkq66nELFiwgJCSEQYMGcfToUY8UKtIULAtefx0iIiA01DyjrqYuvibIsizrWi+e\nOHGCEydO4HA4KC0tJTo6moMHD9KmTZvLx2RkZDB37lw2bdrEtm3bWLduHZs3b77yREFBuDiViO0K\nCyEhAYqL4dVXYdAguysSaVjvdJnYg4ODcTgcAHTs2JGwsDCysrJqHJOens7EiRNp3749kydPJjc3\nt55li9iruhpeeskM7Ro+HDIz1dTFt9V5jT0vL4+cnByio6Nr/HlGRgZTpky5/PtOnTqRn59PaGio\n+6oU8ZBjx8zQrupq2LMH+vWzuyKRxqtTYz937hyTJk1i+fLltG7dusZrlmVd8c+EoGs83Lto0aLL\nv46LiyNOOw6ITSorYdky+MMfYOFCmDHDbFcnYjen04nT6WzUe7hcYweorKxk3LhxjB07ltmzZ1/x\n+gsvvMClS5eYM2cOAKGhoeTn5195Iq2xi5fIzjbjADp2hFdegR497K5I5NrcvsZuWRbx8fGEh4df\ntakDxMTEsGHDBsrKykhKSqKf/i0rXurCBTMOYMwYs//otm1q6uKfXC7FpKamkpiYSEREBJGRkQAs\nXbqUwsJCABISEoiOjmbYsGFERUXRvn17EhMTPV+1SD2lppqUHhZm9h0NDra7IhHPqXUpxm0n0lKM\n2OD8eXjqKVi/Hl54ASZMsLsikfpx+1KMiC/bts2MAzh3zowDUFOXQKGRAuJ3Tp2CuXPNnqOvvAKj\nR9tdkUjTUmIXv7Jhg0npbdualK6mLoFIiV38QnExPPoo5OTAu+/C0KF2VyRiHyV28WmWBa+9Brfe\nCn37mmmMauoS6JTYxWcVFMBDD0FpKWzfDt+ONRIJeErs4nOqqsx+o1FR8JOfQEaGmrrIP1NiF5+S\nm2uGdjVrZr501KeP3RWJeB8ldvEJlZXw29+asbr33w8pKWrqIteixC5eb/9+mDYNunSBTz+F7t3t\nrkjEuymxi9f65huYP99sIP344/DBB2rqInWhxC5eafdus5YeGWmGdnXubHdFIr5DjV28ytmzsGAB\nbNxotqu7+267KxLxPVqKEa+xdSsMGAAVFWYcgJq6SMMosYvtyspgzhz45BN49VUYNcruikR8mxK7\n2May4J13zNCuDh3g0CE1dRF3UGIXW3z5JTzyCHz+Obz3HgwZYndFIv5DiV2alGWZ5RaHAyIizDPq\nauoi7qXELk3m+HGYPh3OnIGPPjKNXUTcT4ldPK6qClasgOho+NnPYN8+NXURT1JiF4/KyYH4eGjZ\nEvbuhR/9yO6KRPyfErt4xMWLsGQJxMXB1Kmwa5eaukhTUWIXt8vMNCn9llsgOxtuvtnuikQCixK7\nuE15Ofz61zB+vBnelZyspi5iBzV2cQun0+w7+sUX5otG//ZvEBRkd1UigUlLMdIoZ87Ak0/C5s2w\nahXceafdFYmIErs02JYtZhxAdbV5+kVNXcQ7KLFLvZWUwOzZ5nn0tWth5Ei7KxKRf6bELnVmWfDm\nm2a0bpcuZi1dTV3E+yixS5188QU8/DAUFMCmTeZbpCLinZTYxaXqanjlFbNFXVSU2UxaTV3Euymx\nyzXl5ZmhXeXl5puj4eF2VyQidaHELleoqoJly2DwYPNlo7Q0NXURX6LELjUcOmTGAfzrv0J6OoSG\n2l2RiNSXErsAZgPphQvNUy4PPQQ7d6qpi/gqJXYhPd2k9JAQOHAAuna1uyIRaQw19gD29dfw7LOQ\nlAR//CPce6/mu4j4Ay3FBKiPPza7GH31FRw+DJMmqamL+Asl9gBz+rQZrbttG6xeDePG2V2RiLib\nEnsA2bTJPLbYooVJ6WrqIv5JiT0AfPUVzJxpvjW6bh3ExtpdkYh4khK7H7MsSEw0Q7u6d4fPPlNT\nFwkESux+qqgIfvUr898tW8ycFxEJDErsfqa62nwoOnAgDBkCWVlq6iKBRondj/zP/5ihXRcvQkoK\n9O9vd0UiYgcldj9w6RL87nfw4x/DL38Jn3yipi4SyFw29mnTptG5c2cGDBhw1dedTift2rUjMjKS\nyMhInnvuOY8UKdd28CDExMCOHZCZCbNmwXXX2V2ViNjJZWOfOnUqH374ocs3iI2NJTs7m+zsbJ55\n5hm3FifXVlFhxgH89KcwYwZs3w49e9pdlYh4A5dr7MOHD6egoMDlG1iW5c56pA727jVDu/r0MUO7\nbrrJ7opExJs06sPToKAg0tLScDgcjBw5khkzZhDqYtbrokWLLv86Li6OuLi4xpw+4Jw/D888A++8\nAytXwoQJmu8i4m+cTidOp7NR7xFk1RK5CwoKGD9+PIcOHbritXPnznHdddfRokUL1q5dy8aNG9m8\nefPVTxQUpHTfCDt2mDnpt98Ozz8PHTrYXZGINIWG9M5GNfZ/ZlkWwcHBFBYW0rJlS7cUJ/D3v8Pj\nj5uNL9asgZ/9zO6KRKQpNaR3Nupxx5MnT14+YXJyMhEREVdt6tIw779vhna1amWGdqmpi0hduFxj\nnzx5MikpKZSWltKtWzcWL15MZWUlAAkJCaxfv57Vq1fTvHlzIiIiWLZsWZMU7e9OnIDHHjOzXd56\nC4YPt7siEfEltS7FuO1EWoqplWXBG2+Yeenx8fCb38D119tdlYjYqSG9UyMFvMT//R8kJMDJk7B1\nq5n1IiLSEBopYLPqanjpJTOoKzYWMjLU1EWkcZTYbXTsmFlysSzYswf69rW7IhHxB0rsNqishP/8\nTxg6FO67T01dRNxLib2JZWeblN6pk5mV3qOH3RWJiL9RYm8iFy7AU0/BmDFmAuOHH6qpi4hnKLE3\ngU8+gQcfNHuPfvYZBAfbXZGI+DM1dg86dw4WLID33oMXXzSbYIiIeJqWYjxk2zaT0MvLISdHTV1E\nmo4Su5udOgVz5pg9R195BUaPtrsiEQk0SuxutH69Gdr1wx+aoV1q6iJiByV2NyguhkcfhSNHTHP/\n8Y/trkhEApkSeyNYFvzlL3DrrdCvn3lGXU1dROymxN5A//u/ZkejU6fMRtIOh90ViYgYSuz1VFVl\n9hu97TYYNQrS09XURcS7KLHXQ26uGQfQvDmkpUHv3nZXJCJyJSX2OqishN/+1mwkPWUKOJ1q6iLi\nvZTYa/HppzBtGnTtan59yy12VyQi4poS+zV88w08+SSMHWu2qtuyRU1dRHyDEvtV7N5thnZFRsKh\nQ3DjjXZXJCJSd2rs/+TsWZg/HzZtMkO77r7b7opEROpPSzHf+uADM7SrstKMA1BTFxFfFfCJvbTU\nDO1KS4M//xl+8hO7KxIRaZyATeyWBW+/bVJ6p05mAww1dRHxBwGZ2L/8Eh5+GPLy4P33YfBguysS\nEXGfgErslgX//d9maJfDAfv3q6mLiP8JmMR+/DhMn26efNm5EyIi7K5IRMQz/D6xV1XB8uUQHQ13\n3AF796qpi4h/8+vEnpNjhnZdfz3s2we9etldkYiI5/llYr94Ef7jPyAuzsx5+fhjNXURCRx+l9gz\nM00z797d7Gh08812VyQi0rT8JrGXl8O8eTB+PDz1FCQnq6mLSGDyi8budJoPRIuLzdCuyZMhKMju\nqkRE7OHTSzFnzsATT5g5L6tWmbQuIhLofDaxJydDeLhJ5ocPq6mLiHzH5xJ7SQnMmgUZGfD66zBi\nhN0ViYh4F59J7JYFSUlmaFfXrmZol5q6iMiVfCKxf/GFGdpVUGA2wYiOtrsiERHv5dWJvboa1qwx\nW9TddpvZTFpNXUTENa9N7Hl5ZmjXN9+YxxnDwuyuSETEN3hdYr90Cf7wBzNO9847ITVVTV1EpD68\nKrF/9pkZ2tW2rXnqJSTE7opERHyPVyT2igpYuNBsTZeQAB99pKYuItJQtif2fftMSu/VCw4cMI8y\niohIw9nW2L/+Gp59Ft58E/74R7jnHs13ERFxB5dLMdOmTaNz584MGDDgmscsWLCAkJAQBg0axNGj\nR+t00p07zReNSkrMOIB771VTrw+n02l3CX5F19O9dD3t57KxT506lQ8//PCar2dkZLBnzx6ysrKY\nN28e8+bNc3my06fNI4xTp8KLL8Ibb0CHDg0rPJDpfxz30vV0L11P+7ls7MOHD+eGG2645uvp6elM\nnDiR9u3bM3nyZHJzc12eLDwcWrQwKX3s2IYVLCIirjXqqZiMjAz69+9/+fedOnUiPz//mscnJZnx\num3bNuasIiLiSqM+PLUsC8uyavxZkIvF8thYLaS7y+LFi+0uwa/oerqXrqe9GtXYY2JiOHLkCGPG\njAGgpKSEkGs8gP79vwBERMQzGrUUExMTw4YNGygrKyMpKYl+/fq5qy4REWkgl4l98uTJpKSkUFpa\nSrdu3Vi8eDGVlZUAJCQkEB0dzbBhw4iKiqJ9+/YkJiY2SdEiIuKC5UYpKSlW3759rV69elkrV668\n6jHz58+3evbsaQ0cONDKzc115+n9Tm3Xc9euXVbbtm0th8NhORwOa8mSJTZU6RumTp1q3XjjjVZ4\nePg1j9G9WTe1XUvdl/VTWFhoxcXFWf3797diY2OtdevWXfW4+tyfbm3sDofDSklJsQoKCqw+ffpY\nJSUlNV5PT0+3hg4dapWVlVlJSUnWuHHj3Hl6v1Pb9dy1a5c1fvx4m6rzLbt377b2799/zWake7Pu\naruWui/rp7i42MrOzrYsy7JKSkqsnj17WmfPnq1xTH3vT7cNATtz5gwAt99+O927d2f06NGkp6fX\nOKa+z70HsrpcT9CH0nXl7u9kBLLariXovqyP4OBgHA4HAB07diQsLIysrKwax9T3/nRbY8/MzKRv\n376Xf9+/f3/27dtX45j6PvceyOpyPYOCgkhLS8PhcDB37lxdy0bQvek+ui8bLi8vj5ycHKK/t1Vc\nfe/PJh3ba9XzuXdxbeDAgRQVFZGZmUn//v2ZNWuW3SX5LN2b7qP7smHOnTvHpEmTWL58Oa1bt67x\nWn3vT7c19ttuu63GELCcnBwGDx5c45jvnnv/jqvn3gNdXa5nmzZtaNWqFS1atCA+Pp7MzEwqKiqa\nulS/oHvTfXRf1l9lZSUTJkxgypQp3HXXXVe8Xt/7022NvV27dgDs3r2bgoICduzYQUxMzBXF6bn3\nuqnL9Tx58uTlv8WTk5OJiIigZcuWTV6rP9C96T66L+vHsizi4+MJDw9n9uzZVz2mvvenW+exr1ix\ngoSEBCorK5k5cyYdO3ZkzZo1gJ57b4jaruf69etZvXo1zZs3JyIigmXLltlcsffSdzLcp7Zrqfuy\nflJTU0lMTCQiIoLIyEgAli5dSmFhIdCw+zPI0sfXIiJ+xSv2PBUREfdRYxcR8TNq7CIifkaNXUTE\nz6ixi4j4GTV2ERE/8/9mUozJaDh2nQAAAABJRU5ErkJggg==\n"
85	}	82	}
86	],	83	],
87	"prompt_number": 1	84	"prompt_number": 1
@@ -128,7 +125,8 b''
128	"output_type": "stream",	125	"output_type": "stream",
129	"stream": "stdout",	126	"stream": "stdout",
130	"text": [	127	"text": [
131	"hello world"	128	"hello world",
		129	""
132	]	130	]
133	}	131	}
134	],	132	],
@@ -141,17 +139,70 b''
141	]	139	]
142	},	140	},
143	{	141	{
144	"cell_type": "~~plaintext~~",	142	"cell_type": "raw",
145	"source": [	143	"source": [
146	"plain text"	144	"plain text"
147	]	145	]
148	},	146	},
149	{	147	{
150	"cell_type": "code",	148	"cell_type": "code",
151	"collapsed": ~~tru~~e,	149	"collapsed": false,
152	"input": [],	150	"input": [
		151	"import sys",
		152	"m = 'A message'",
		153	"print m, 'to stdout'",
		154	"print >> sys.stderr, m, 'to stderr'",
		155	"m"
		156	],
153	"language": "python",	157	"language": "python",
154	"outputs": []	158	"outputs": [
		159	{
		160	"output_type": "stream",
		161	"stream": "stdout",
		162	"text": [
		163	"A message to stdout",
		164	""
		165	]
		166	},
		167	{
		168	"output_type": "stream",
		169	"stream": "stderr",
		170	"text": [
		171	"A message to stderr",
		172	""
		173	]
		174	},
		175	{
		176	"output_type": "pyout",
		177	"prompt_number": 5,
		178	"text": [
		179	"'A message'"
		180	]
		181	}
		182	],
		183	"prompt_number": 5
		184	},
		185	{
		186	"cell_type": "code",
		187	"collapsed": false,
		188	"input": [
		189	"# a traceback",
		190	"1/0"
		191	],
		192	"language": "python",
		193	"outputs": [
		194	{
		195	"ename": "ZeroDivisionError",
		196	"evalue": "integer division or modulo by zero",
		197	"output_type": "pyerr",
		198	"traceback": [
		199	"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mZeroDivisionError\u001b[0m Traceback (most recent call last)",
		200	"\u001b[1;32m/home/fperez/ipython/nbconvert/tests/<ipython-input-6-03412a6702b7>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;31m# a traceback\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[1;36m1\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
		201	"\u001b[1;31mZeroDivisionError\u001b[0m: integer division or modulo by zero"
		202	]
		203	}
		204	],
		205	"prompt_number": 6
155	}	206	}
156	]	207	]
157	}	208	}

General Comments 0

Write
Preview

You need to be logged in to leave comments. Login now

No TODOs yet

	Site-wide shortcuts
/	Use quick search box
g h	Goto home page
g g	Goto my private gists page
g G	Goto my public gists page
g 0-9	Goto bookmarked items from 0-9
n r	New repository page
n g	New gist page

	Repositories
g s	Goto summary page
g c	Goto changelog page
g f	Goto files page
g F	Goto files page with file search activated
g p	Goto pull requests page
g o	Goto repository settings
g O	Goto repository access permissions settings
t s	Toggle sidebar on some pages