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@@ -32,19 +32,10 b''
32 "cell_type": "markdown",
32 "cell_type": "markdown",
33 "metadata": {},
33 "metadata": {},
34 "source": [
34 "source": [
35 "<pre style='background-color:#FDD'> Warning, Do use 1.0 or 1.x branch and not master naming have changed.</pre>\n",
36 "\n",
37 "<pre style='background-color:#FDD'> Warning, NbConvert is a Tech-Preview, API will change within the next 6 month.</pre>"
38 ]
39 },
40 {
41 "cell_type": "markdown",
42 "metadata": {},
43 "source": [
44 "Credit, Jonathan Freder (@jdfreder on github)\n",
35 "Credit, Jonathan Freder (@jdfreder on github)\n",
45 "\n",
36 "\n",
46 "<center>\n",
37 "<center>\n",
47 " ![nbca](files/nbconvert_arch.png)\n",
38 " ![nbca](images/nbconvert_arch.png)\n",
48 "</center>"
39 "</center>"
49 ]
40 ]
50 },
41 },
@@ -84,7 +75,7 b''
84 "source": [
75 "source": [
85 "import requests\n",
76 "import requests\n",
86 "response = requests.get('http://jakevdp.github.com/downloads/notebooks/XKCD_plots.ipynb')\n",
77 "response = requests.get('http://jakevdp.github.com/downloads/notebooks/XKCD_plots.ipynb')\n",
87 "response.content[0:60]+'...'"
78 "response.text[0:60]+'...'"
88 ]
79 ]
89 },
80 },
90 {
81 {
@@ -113,10 +104,9 b''
113 {
104 {
114 "data": {
105 "data": {
115 "text/plain": [
106 "text/plain": [
116 "{u'cell_type': u'heading',\n",
107 "{'cell_type': 'markdown',\n",
117 " u'level': 1,\n",
108 " 'metadata': {},\n",
118 " u'metadata': {},\n",
109 " 'source': '# XKCD plots in Matplotlib'}"
119 " u'source': u'XKCD plots in Matplotlib'}"
120 ]
110 ]
121 },
111 },
122 "execution_count": 2,
112 "execution_count": 2,
@@ -125,9 +115,9 b''
125 }
115 }
126 ],
116 ],
127 "source": [
117 "source": [
128 "from IPython.nbformat import current as nbformat\n",
118 "from IPython import nbformat\n",
129 "jake_notebook = nbformat.reads_json(response.content)\n",
119 "jake_notebook = nbformat.reads(response.text, as_version=4)\n",
130 "jake_notebook.worksheets[0].cells[0]"
120 "jake_notebook.cells[0]"
131 ]
121 ]
132 },
122 },
133 {
123 {
@@ -155,34 +145,23 b''
155 },
145 },
156 "outputs": [],
146 "outputs": [],
157 "source": [
147 "source": [
158 "import IPython.nbconvert"
159 ]
160 },
161 {
162 "cell_type": "code",
163 "execution_count": 4,
164 "metadata": {
165 "collapsed": false
166 },
167 "outputs": [],
168 "source": [
169 "from IPython.config import Config\n",
148 "from IPython.config import Config\n",
170 "from IPython.nbconvert import HTMLExporter\n",
149 "from IPython.nbconvert import HTMLExporter\n",
171 "\n",
150 "\n",
172 "## I use `basic` here to have less boilerplate and headers in the HTML.\n",
151 "## I use `basic` here to have less boilerplate and headers in the HTML.\n",
173 "## we'll see later how to pass config to exporters.\n",
152 "## we'll see later how to pass config to exporters.\n",
174 "exportHtml = HTMLExporter(config=Config({'HTMLExporter':{'default_template':'basic'}}))"
153 "html_exporter = HTMLExporter(config=Config({'HTMLExporter':{'default_template':'basic'}}))"
175 ]
154 ]
176 },
155 },
177 {
156 {
178 "cell_type": "code",
157 "cell_type": "code",
179 "execution_count": 5,
158 "execution_count": 4,
180 "metadata": {
159 "metadata": {
181 "collapsed": false
160 "collapsed": false
182 },
161 },
183 "outputs": [],
162 "outputs": [],
184 "source": [
163 "source": [
185 "(body, resources) = exportHtml.from_notebook_node(jake_notebook)"
164 "(body, resources) = html_exporter.from_notebook_node(jake_notebook)"
186 ]
165 ]
187 },
166 },
188 {
167 {
@@ -199,7 +178,7 b''
199 },
178 },
200 {
179 {
201 "cell_type": "code",
180 "cell_type": "code",
202 "execution_count": 6,
181 "execution_count": 5,
203 "metadata": {
182 "metadata": {
204 "collapsed": false
183 "collapsed": false
205 },
184 },
@@ -208,22 +187,22 b''
208 "name": "stdout",
187 "name": "stdout",
209 "output_type": "stream",
188 "output_type": "stream",
210 "text": [
189 "text": [
211 "['inlining', 'output_extension', 'metadata']\n",
190 "['raw_mimetypes', 'inlining', 'metadata', 'output_extension']\n",
212 "defaultdict(None, {'name': 'Notebook'})\n",
191 "defaultdict(None, {'name': 'Notebook'})\n",
213 "html\n"
192 ".html\n"
214 ]
193 ]
215 }
194 }
216 ],
195 ],
217 "source": [
196 "source": [
218 "print resources.keys()\n",
197 "print([key for key in resources ])\n",
219 "print resources['metadata']\n",
198 "print(resources['metadata'])\n",
220 "print resources['output_extension']\n",
199 "print(resources['output_extension'])\n",
221 "# print resources['inlining'] # too lng to be shown"
200 "# print resources['inlining'] # too lng to be shown"
222 ]
201 ]
223 },
202 },
224 {
203 {
225 "cell_type": "code",
204 "cell_type": "code",
226 "execution_count": 7,
205 "execution_count": 6,
227 "metadata": {
206 "metadata": {
228 "collapsed": false
207 "collapsed": false
229 },
208 },
@@ -232,20 +211,32 b''
232 "name": "stdout",
211 "name": "stdout",
233 "output_type": "stream",
212 "output_type": "stream",
234 "text": [
213 "text": [
214 "<!DOCTYPE html>\n",
215 "<html>\n",
216 "<head>\n",
235 "\n",
217 "\n",
236 "<div class=\"text_cell_render border-box-sizing rendered_html\">\n",
218 "<meta charset=\"utf-8\" />\n",
237 "<h1 id=\"XKCD-plots-in-Matplotlib\">XKCD plots in Matplotlib<a class=\"anchor-link\" href=\"#XKCD-plots-in-Matplotlib\">&#182;</a></h1>\n",
219 "<title>Notebook</title>\n",
238 "</div>\n",
220 "\n",
221 "<script src=\"https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js\"></script>\n",
222 "<script src=\"https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js\"></script>\n",
239 "\n",
223 "\n",
240 "<div class=\"text_cell_render border-box-sizing rendered_html\">\n",
224 "<style type=\"text/css\">\n",
241 "<p>This notebook originally appeared as a blog post at <a href=\"http://jakevdp.github.com/blog/2012/10/07/xkcd-style-plots-in-matplotli...\n"
225 " /*!\n",
226 "*\n",
227 "* Twitter Bootstrap\n",
228 "*\n",
229 "*/\n",
230 "/*! normalize.css v3.0.2 | MIT License | git.io/normalize */\n",
231 "html {\n",
232 " fon...\n"
242 ]
233 ]
243 }
234 }
244 ],
235 ],
245 "source": [
236 "source": [
246 "# Part of the body, here the first Heading\n",
237 "# Part of the body, here the first Heading\n",
247 "start = body.index('<h1 id', )\n",
238 "start = body.index('<h1 id', )\n",
248 "print body[:400]+'...'"
239 "print(body[:400]+'...')"
249 ]
240 ]
250 },
241 },
251 {
242 {
@@ -271,7 +262,7 b''
271 },
262 },
272 {
263 {
273 "cell_type": "code",
264 "cell_type": "code",
274 "execution_count": 8,
265 "execution_count": 7,
275 "metadata": {
266 "metadata": {
276 "collapsed": false
267 "collapsed": false
277 },
268 },
@@ -279,14 +270,14 b''
279 "source": [
270 "source": [
280 "from IPython.nbconvert import RSTExporter\n",
271 "from IPython.nbconvert import RSTExporter\n",
281 "\n",
272 "\n",
282 "rst_export = RSTExporter()\n",
273 "rst_exporter = RSTExporter()\n",
283 "\n",
274 "\n",
284 "(body,resources) = rst_export.from_notebook_node(jake_notebook)"
275 "(body,resources) = rst_exporter.from_notebook_node(jake_notebook)"
285 ]
276 ]
286 },
277 },
287 {
278 {
288 "cell_type": "code",
279 "cell_type": "code",
289 "execution_count": 9,
280 "execution_count": 8,
290 "metadata": {
281 "metadata": {
291 "collapsed": false
282 "collapsed": false
292 },
283 },
@@ -299,20 +290,23 b''
299 "XKCD plots in Matplotlib\n",
290 "XKCD plots in Matplotlib\n",
300 "========================\n",
291 "========================\n",
301 "\n",
292 "\n",
302 "\n",
303 "This notebook originally appeared as a blog post at `Pythonic\n",
293 "This notebook originally appeared as a blog post at `Pythonic\n",
304 "Perambulations <http://jakevdp.github.com/blog/2012/10/07/xkcd-style-plots-in-matplotlib/>`_\n",
294 "Perambulations <http://jakevdp.github.com/blog/2012/10/07/xkcd-style-plots-in-matplotlib/>`__\n",
305 "by Jake Vanderplas.\n",
295 "by Jake Vanderplas.\n",
306 "\n",
296 "\n",
307 " *Update: the matplotlib pull request has been merged! See* `*This\n",
297 ".. raw:: html\n",
308 "post* <http://jakevdp.github.io/blog/2013/07/10/XKCD-plots-in-matplotlib/>`_\n",
298 "\n",
299 " <!-- PELICAN_BEGIN_SUMMARY -->\n",
300 "\n",
301 "*Update: the matplotlib pull request has been merged! See* `*This\n",
302 "post* <http://jakevdp.github.io/blog/2013/07/10/XKCD-plots-in-matplotlib/>`__\n",
309 "*for a description of the XKCD functionality now built-in to\n",
303 "*for a description of the XKCD functionality now built-in to\n",
310 "matplotlib!*\n",
304 "matplotlib!*\n",
311 "\n",
305 "\n",
312 "One of the problems I've had with typical matplotlib figures is that\n",
306 "One of the problems I've had with typical matplotlib figures is that\n",
313 "everything in them is so precise, so perfect. For an example of what I\n",
307 "everything in them is so precise, so perfect. For an example of what I\n",
314 "mean, take a look at this figure:\n",
308 "mean, take a look at this figure:\n",
315 "In[1]:\n",
309 "\n",
316 ".. code:: python\n",
310 ".. code:: python\n",
317 "\n",
311 "\n",
318 " from IPython.display import Image\n",
312 " from IPython.display import Image\n",
@@ -320,41 +314,37 b''
320 "\n",
314 "\n",
321 "\n",
315 "\n",
322 "\n",
316 "\n",
323 "\n",
324 "\n",
325 ".. image:: output_3_0.png\n",
317 ".. image:: output_3_0.png\n",
326 "\n",
318 "\n",
327 "\n",
319 "\n",
328 "\n",
320 "\n",
329 "Sometimes when showing schematic plots, this is the type of figure I\n",
321 "Sometimes when showing schematic plots, this is the type of figure I\n",
330 "want to display. But drawing it by hand is a pain: I'd rather just use\n",
322 "want to display. But drawing it by hand is a pain: I'd rather just use\n",
331 "matplotlib. The problem is, matplotlib is a bit...\n",
323 "matpl...\n",
332 "[.....]\n",
324 "[.....]\n",
333 "owing schematic plots, this is the type of figure I\n",
325 "mage:: output_3_0.png\n",
326 "\n",
327 "\n",
328 "\n",
329 "Sometimes when showing schematic plots, this is the type of figure I\n",
334 "want to display. But drawing it by hand is a pain: I'd rather just use\n",
330 "want to display. But drawing it by hand is a pain: I'd rather just use\n",
335 "matplotlib. The problem is, matplotlib is a bit too precise. Attempting\n",
331 "matplotlib. The problem is, matplotlib is a bit too precise. Attempting\n",
336 "to duplicate this figure in matplotlib leads to something like this:\n",
332 "to duplicate this figure in matplotlib leads to something like this:\n",
337 "In[2]:\n",
333 "\n",
338 ".. code:: python\n",
334 ".. code:: python\n",
339 "\n",
335 "\n",
340 " Image('http://jakevdp.github.com/figures/mpl_version.png')\n",
336 " Image('http://jakevdp.github.com/figures/mpl_version.png')\n",
341 "\n",
337 "\n",
342 "\n",
338 "\n",
343 "\n",
339 "\n",
344 "\n",
340 ".. image:...\n"
345 "\n",
346 ".. image:: output_5_0.png\n",
347 "\n",
348 "\n",
349 "\n",
350 "It just doesn'...\n"
351 ]
341 ]
352 }
342 }
353 ],
343 ],
354 "source": [
344 "source": [
355 "print body[:970]+'...'\n",
345 "print(body[:970]+'...')\n",
356 "print '[.....]'\n",
346 "print('[.....]')\n",
357 "print body[800:1200]+'...'"
347 "print(body[800:1200]+'...')"
358 ]
348 ]
359 },
349 },
360 {
350 {
@@ -381,7 +371,7 b''
381 },
371 },
382 {
372 {
383 "cell_type": "code",
373 "cell_type": "code",
384 "execution_count": 10,
374 "execution_count": 9,
385 "metadata": {
375 "metadata": {
386 "collapsed": false
376 "collapsed": false
387 },
377 },
@@ -389,28 +379,20 b''
389 {
379 {
390 "data": {
380 "data": {
391 "text/plain": [
381 "text/plain": [
392 "[u'output_13_1.text',\n",
382 "['output_5_0.png',\n",
393 " u'output_18_0.text',\n",
383 " 'output_16_0.png',\n",
394 " u'output_3_0.text',\n",
384 " 'output_13_1.png',\n",
395 " u'output_18_1.png',\n",
385 " 'output_18_1.png',\n",
396 " u'output_12_0.text',\n",
386 " 'output_3_0.png']"
397 " u'output_5_0.text',\n",
398 " u'output_5_0.png',\n",
399 " u'output_13_1.png',\n",
400 " u'output_16_0.text',\n",
401 " u'output_13_0.text',\n",
402 " u'output_18_1.text',\n",
403 " u'output_3_0.png',\n",
404 " u'output_16_0.png']"
405 ]
387 ]
406 },
388 },
407 "execution_count": 10,
389 "execution_count": 9,
408 "metadata": {},
390 "metadata": {},
409 "output_type": "execute_result"
391 "output_type": "execute_result"
410 }
392 }
411 ],
393 ],
412 "source": [
394 "source": [
413 "resources['outputs'].keys()"
395 "list(resources['outputs'])"
414 ]
396 ]
415 },
397 },
416 {
398 {
@@ -428,7 +410,7 b''
428 },
410 },
429 {
411 {
430 "cell_type": "code",
412 "cell_type": "code",
431 "execution_count": 11,
413 "execution_count": 10,
432 "metadata": {
414 "metadata": {
433 "collapsed": false
415 "collapsed": false
434 },
416 },
@@ -934,10 +916,10 b''
934 "RU5ErkJggg==\n"
916 "RU5ErkJggg==\n"
935 ],
917 ],
936 "text/plain": [
918 "text/plain": [
937 "<IPython.core.display.Image at 0x10d2bbf90>"
919 "<IPython.core.display.Image object>"
938 ]
920 ]
939 },
921 },
940 "execution_count": 11,
922 "execution_count": 10,
941 "metadata": {},
923 "metadata": {},
942 "output_type": "execute_result"
924 "output_type": "execute_result"
943 }
925 }
@@ -987,7 +969,7 b''
987 "\n",
969 "\n",
988 " - Get the notebook data and other required files. (you are responsible for that)\n",
970 " - Get the notebook data and other required files. (you are responsible for that)\n",
989 " - Feed them to the exporter that will\n",
971 " - Feed them to the exporter that will\n",
990 " - sequentially feed the data to a number of `Transformers`. Transformer only act on the **structure**\n",
972 " - sequentially feed the data to a number of `Preprocessors`. Preprocessor only act on the **structure**\n",
991 " of the notebook, and have access to it all. \n",
973 " of the notebook, and have access to it all. \n",
992 " - feed the notebook through the jinja templating engine\n",
974 " - feed the notebook through the jinja templating engine\n",
993 " - the use templates are configurable.\n",
975 " - the use templates are configurable.\n",
@@ -1000,20 +982,20 b''
1000 "cell_type": "markdown",
982 "cell_type": "markdown",
1001 "metadata": {},
983 "metadata": {},
1002 "source": [
984 "source": [
1003 "Here we'll be interested in the `Transformers`. Each `Transformer` is applied successively and in order on the notebook before going through the conversion process.\n",
985 "Here we'll be interested in the `Preprocessors`. Each `Preprocessor` is applied successively and in order on the notebook before going through the conversion process.\n",
1004 "\n",
986 "\n",
1005 "We provide some transformer that do some modification on the notebook structure by default.\n",
987 "We provide some preprocessor that do some modification on the notebook structure by default.\n",
1006 "One of them, the `ExtractOutputTransformer` is responsible for crawling notebook,\n",
988 "One of them, the `ExtractOutputPreprocessor` is responsible for crawling notebook,\n",
1007 "finding all the figures, and put them into the resources directory, as well as choosing the key\n",
989 "finding all the figures, and put them into the resources directory, as well as choosing the key\n",
1008 "(`filename_xx_y.extension`) that can replace the figure in the template.\n",
990 "(`filename_xx_y.extension`) that can replace the figure in the template.\n",
1009 "\n",
991 "\n",
1010 "\n",
992 "\n",
1011 "The `ExtractOutputTransformer` is special in the fact that it **should** be availlable on all `Exporter`s, but is just inactive by default on some exporter."
993 "The `ExtractOutputPreprocessor` is special in the fact that it **should** be availlable on all `Exporter`s, but is just inactive by default on some exporter."
1012 ]
994 ]
1013 },
995 },
1014 {
996 {
1015 "cell_type": "code",
997 "cell_type": "code",
1016 "execution_count": 12,
998 "execution_count": 11,
1017 "metadata": {
999 "metadata": {
1018 "collapsed": false
1000 "collapsed": false
1019 },
1001 },
@@ -1021,23 +1003,25 b''
1021 {
1003 {
1022 "data": {
1004 "data": {
1023 "text/plain": [
1005 "text/plain": [
1024 "[<function IPython.nbconvert.transformers.coalescestreams.wrappedfunc>,\n",
1006 "[<function IPython.nbconvert.preprocessors.coalescestreams.cell_preprocessor.<locals>.wrappedfunc>,\n",
1025 " <IPython.nbconvert.transformers.svg2pdf.SVG2PDFTransformer at 0x10d2a7490>,\n",
1007 " <IPython.nbconvert.preprocessors.svg2pdf.SVG2PDFPreprocessor at 0x107d1a630>,\n",
1026 " <IPython.nbconvert.transformers.extractoutput.ExtractOutputTransformer at 0x10d2a7ad0>,\n",
1008 " <IPython.nbconvert.preprocessors.extractoutput.ExtractOutputPreprocessor at 0x107d1a748>,\n",
1027 " <IPython.nbconvert.transformers.csshtmlheader.CSSHTMLHeaderTransformer at 0x10d2a7b50>,\n",
1009 " <IPython.nbconvert.preprocessors.csshtmlheader.CSSHTMLHeaderPreprocessor at 0x107d1aba8>,\n",
1028 " <IPython.nbconvert.transformers.revealhelp.RevealHelpTransformer at 0x10d29dd90>,\n",
1010 " <IPython.nbconvert.preprocessors.revealhelp.RevealHelpPreprocessor at 0x107d1a710>,\n",
1029 " <IPython.nbconvert.transformers.latex.LatexTransformer at 0x10d29db50>,\n",
1011 " <IPython.nbconvert.preprocessors.latex.LatexPreprocessor at 0x107daa860>,\n",
1030 " <IPython.nbconvert.transformers.sphinx.SphinxTransformer at 0x10d2a7b90>]"
1012 " <IPython.nbconvert.preprocessors.clearoutput.ClearOutputPreprocessor at 0x107db7080>,\n",
1013 " <IPython.nbconvert.preprocessors.execute.ExecutePreprocessor at 0x107db7160>,\n",
1014 " <IPython.nbconvert.preprocessors.highlightmagics.HighlightMagicsPreprocessor at 0x107db7048>]"
1031 ]
1015 ]
1032 },
1016 },
1033 "execution_count": 12,
1017 "execution_count": 11,
1034 "metadata": {},
1018 "metadata": {},
1035 "output_type": "execute_result"
1019 "output_type": "execute_result"
1036 }
1020 }
1037 ],
1021 ],
1038 "source": [
1022 "source": [
1039 "# second transformer shoudl be Instance of ExtractFigureTransformer\n",
1023 "# 3rd one should be <ExtractOutputPreprocessor>\n",
1040 "exportHtml._transformers # 3rd one shouel be <ExtractOutputTransformer>"
1024 "html_exporter._preprocessors"
1041 ]
1025 ]
1042 },
1026 },
1043 {
1027 {
@@ -1047,14 +1031,14 b''
1047 "To enable it we will use IPython configuration/Traitlets system. If you are have already set some IPython configuration options, \n",
1031 "To enable it we will use IPython configuration/Traitlets system. If you are have already set some IPython configuration options, \n",
1048 "this will look pretty familiar to you. Configuration option are always of the form:\n",
1032 "this will look pretty familiar to you. Configuration option are always of the form:\n",
1049 "\n",
1033 "\n",
1050 " ClassName.attribute_name = value\n",
1034 " ClassName.attribute_name = value\n",
1051 " \n",
1035 " \n",
1052 "A few ways exist to create such config, like reading a config file in your profile, but you can also do it programatically usign a dictionary. Let's create such a config object, and see the difference if we pass it to our `HtmlExporter`"
1036 "A few ways exist to create such config, like reading a config file in your profile, but you can also do it programatically usign a dictionary. Let's create such a config object, and see the difference if we pass it to our `HTMLExporter`"
1053 ]
1037 ]
1054 },
1038 },
1055 {
1039 {
1056 "cell_type": "code",
1040 "cell_type": "code",
1057 "execution_count": 13,
1041 "execution_count": 12,
1058 "metadata": {
1042 "metadata": {
1059 "collapsed": false
1043 "collapsed": false
1060 },
1044 },
@@ -1064,31 +1048,23 b''
1064 "output_type": "stream",
1048 "output_type": "stream",
1065 "text": [
1049 "text": [
1066 "resources without the \"figures\" key :\n",
1050 "resources without the \"figures\" key :\n",
1067 "['inlining', 'output_extension', 'metadata']\n",
1051 "['raw_mimetypes', 'inlining', 'metadata', 'output_extension']\n",
1068 "\n",
1052 "\n",
1069 "Here we have one more field \n",
1053 "Here we have one more field\n",
1070 "['outputs', 'inlining', 'output_extension', 'metadata']\n"
1054 "['outputs', 'raw_mimetypes', 'inlining', 'metadata', 'output_extension']\n"
1071 ]
1055 ]
1072 },
1056 },
1073 {
1057 {
1074 "data": {
1058 "data": {
1075 "text/plain": [
1059 "text/plain": [
1076 "[u'output_13_1.text',\n",
1060 "['output_5_0.png',\n",
1077 " u'output_18_0.text',\n",
1061 " 'output_16_0.png',\n",
1078 " u'output_3_0.text',\n",
1062 " 'output_13_1.png',\n",
1079 " u'output_18_1.png',\n",
1063 " 'output_18_1.png',\n",
1080 " u'output_12_0.text',\n",
1064 " 'output_3_0.png']"
1081 " u'output_5_0.text',\n",
1082 " u'output_5_0.png',\n",
1083 " u'output_13_1.png',\n",
1084 " u'output_16_0.text',\n",
1085 " u'output_13_0.text',\n",
1086 " u'output_18_1.text',\n",
1087 " u'output_3_0.png',\n",
1088 " u'output_16_0.png']"
1089 ]
1065 ]
1090 },
1066 },
1091 "execution_count": 13,
1067 "execution_count": 12,
1092 "metadata": {},
1068 "metadata": {},
1093 "output_type": "execute_result"
1069 "output_type": "execute_result"
1094 }
1070 }
@@ -1097,22 +1073,22 b''
1097 "from IPython.config import Config\n",
1073 "from IPython.config import Config\n",
1098 "\n",
1074 "\n",
1099 "c = Config({\n",
1075 "c = Config({\n",
1100 " 'ExtractOutputTransformer':{'enabled':True}\n",
1076 " 'ExtractOutputPreprocessor':{'enabled':True}\n",
1101 " })\n",
1077 " })\n",
1102 "\n",
1078 "\n",
1103 "exportHtml = HTMLExporter()\n",
1079 "exportHTML = HTMLExporter()\n",
1104 "exportHtml_and_figs = HTMLExporter(config=c)\n",
1080 "exportHTML_and_figs = HTMLExporter(config=c)\n",
1105 "\n",
1081 "\n",
1106 "(_, resources) = exportHtml.from_notebook_node(jake_notebook)\n",
1082 "(_, resources) = exportHTML.from_notebook_node(jake_notebook)\n",
1107 "(_, resources_with_fig) = exportHtml_and_figs.from_notebook_node(jake_notebook)\n",
1083 "(_, resources_with_fig) = exportHTML_and_figs.from_notebook_node(jake_notebook)\n",
1108 "\n",
1084 "\n",
1109 "print 'resources without the \"figures\" key :'\n",
1085 "print('resources without the \"figures\" key :')\n",
1110 "print resources.keys()\n",
1086 "print(list(resources))\n",
1111 "\n",
1087 "\n",
1112 "print ''\n",
1088 "print('')\n",
1113 "print 'Here we have one more field '\n",
1089 "print('Here we have one more field')\n",
1114 "print resources_with_fig.keys()\n",
1090 "print(list(resources_with_fig))\n",
1115 "resources_with_fig['outputs'].keys() "
1091 "list(resources_with_fig['outputs'])"
1116 ]
1092 ]
1117 },
1093 },
1118 {
1094 {
@@ -1126,27 +1102,27 b''
1126 "cell_type": "markdown",
1102 "cell_type": "markdown",
1127 "metadata": {},
1103 "metadata": {},
1128 "source": [
1104 "source": [
1129 "#### Custom transformer"
1105 "#### Custom Preprocessor"
1130 ]
1106 ]
1131 },
1107 },
1132 {
1108 {
1133 "cell_type": "markdown",
1109 "cell_type": "markdown",
1134 "metadata": {},
1110 "metadata": {},
1135 "source": [
1111 "source": [
1136 "Of course you can imagine many transformation that you would like to apply to a notebook. This is one of the reason we provide a way to register your own transformers that will be applied to the notebook after the default ones.\n",
1112 "Of course you can imagine many transformation that you would like to apply to a notebook. This is one of the reason we provide a way to register your own preprocessors that will be applied to the notebook after the default ones.\n",
1137 "\n",
1113 "\n",
1138 "To do so you'll have to pass an ordered list of `Transformer`s to the Exporter constructor. \n",
1114 "To do so you'll have to pass an ordered list of `Preprocessor`s to the Exporter constructor. \n",
1139 "\n",
1115 "\n",
1140 "But what is an transformer ? Transformer can be either *decorated function* for dead-simple `Transformer`s that apply\n",
1116 "But what is an preprocessor ? Preprocessor can be either *decorated function* for dead-simple `Preprocessor`s that apply\n",
1141 "independently to each cell, for more advance transformation that support configurability You have to inherit from\n",
1117 "independently to each cell, for more advance transformation that support configurability You have to inherit from\n",
1142 "`Transformer` and define a `call` method as we'll see below.\n",
1118 "`Preprocessor` and define a `call` method as we'll see below.\n",
1143 "\n",
1119 "\n",
1144 "All transforers have a magic attribute that allows it to be activated/disactivate from the config dict."
1120 "All transforers have a magic attribute that allows it to be activated/disactivate from the config dict."
1145 ]
1121 ]
1146 },
1122 },
1147 {
1123 {
1148 "cell_type": "code",
1124 "cell_type": "code",
1149 "execution_count": 14,
1125 "execution_count": 13,
1150 "metadata": {
1126 "metadata": {
1151 "collapsed": false
1127 "collapsed": false
1152 },
1128 },
@@ -1157,27 +1133,29 b''
1157 "text": [
1133 "text": [
1158 "Four relevant docstring\n",
1134 "Four relevant docstring\n",
1159 "=============================\n",
1135 "=============================\n",
1160 " A configurable transformer\n",
1136 " A configurable preprocessor\n",
1161 "\n",
1137 "\n",
1162 " Inherit from this class if you wish to have configurability for your\n",
1138 " Inherit from this class if you wish to have configurability for your\n",
1163 " transformer.\n",
1139 " preprocessor.\n",
1164 "\n",
1140 "\n",
1165 " Any configurable traitlets this class exposed will be configurable in profiles\n",
1141 " Any configurable traitlets this class exposed will be configurable in\n",
1166 " using c.SubClassName.atribute=value\n",
1142 " profiles using c.SubClassName.attribute = value\n",
1167 "\n",
1143 "\n",
1168 " you can overwrite transform_cell to apply a transformation independently on each cell\n",
1144 " you can overwrite :meth:`preprocess_cell` to apply a transformation\n",
1169 " or __call__ if you prefer your own logic. See corresponding docstring for informations.\n",
1145 " independently on each cell or :meth:`preprocess` if you prefer your own\n",
1146 " logic. See corresponding docstring for informations.\n",
1170 "\n",
1147 "\n",
1171 " Disabled by default and can be enabled via the config by\n",
1148 " Disabled by default and can be enabled via the config by\n",
1172 " 'c.YourTransformerName.enabled = True'\n",
1149 " 'c.YourPreprocessorName.enabled = True'\n",
1173 " \n",
1150 " \n",
1174 "=============================\n",
1151 "=============================\n",
1175 "\n",
1152 "\n",
1176 " Transformation to apply on each notebook.\n",
1153 " Preprocessing to apply on each notebook.\n",
1177 " \n",
1154 " \n",
1178 " You should return modified nb, resources.\n",
1155 " Must return modified nb, resources.\n",
1179 " If you wish to apply your transform on each cell, you might want to \n",
1156 " \n",
1180 " overwrite transform_cell method instead.\n",
1157 " If you wish to apply your preprocessing to each cell, you might want\n",
1158 " to override preprocess_cell method instead.\n",
1181 " \n",
1159 " \n",
1182 " Parameters\n",
1160 " Parameters\n",
1183 " ----------\n",
1161 " ----------\n",
@@ -1185,12 +1163,12 b''
1185 " Notebook being converted\n",
1163 " Notebook being converted\n",
1186 " resources : dictionary\n",
1164 " resources : dictionary\n",
1187 " Additional resources used in the conversion process. Allows\n",
1165 " Additional resources used in the conversion process. Allows\n",
1188 " transformers to pass variables into the Jinja engine.\n",
1166 " preprocessors to pass variables into the Jinja engine.\n",
1189 " \n",
1167 " \n",
1190 "=============================\n",
1168 "=============================\n",
1191 "\n",
1169 "\n",
1192 " Overwrite if you want to apply a transformation on each cell. You \n",
1170 " Override if you want to apply some preprocessing to each cell.\n",
1193 " should return modified cell and resource dictionary.\n",
1171 " Must return modified cell and resource dictionary.\n",
1194 " \n",
1172 " \n",
1195 " Parameters\n",
1173 " Parameters\n",
1196 " ----------\n",
1174 " ----------\n",
@@ -1198,7 +1176,7 b''
1198 " Notebook cell being processed\n",
1176 " Notebook cell being processed\n",
1199 " resources : dictionary\n",
1177 " resources : dictionary\n",
1200 " Additional resources used in the conversion process. Allows\n",
1178 " Additional resources used in the conversion process. Allows\n",
1201 " transformers to pass variables into the Jinja engine.\n",
1179 " preprocessors to pass variables into the Jinja engine.\n",
1202 " index : int\n",
1180 " index : int\n",
1203 " Index of the cell being processed\n",
1181 " Index of the cell being processed\n",
1204 " \n",
1182 " \n",
@@ -1207,16 +1185,16 b''
1207 }
1185 }
1208 ],
1186 ],
1209 "source": [
1187 "source": [
1210 "from IPython.nbconvert.transformers import Transformer\n",
1188 "from IPython.nbconvert.preprocessors import Preprocessor\n",
1211 "import IPython.config\n",
1189 "import IPython.config\n",
1212 "print \"Four relevant docstring\"\n",
1190 "print(\"Four relevant docstring\")\n",
1213 "print '============================='\n",
1191 "print('=============================')\n",
1214 "print Transformer.__doc__\n",
1192 "print(Preprocessor.__doc__)\n",
1215 "print '============================='\n",
1193 "print('=============================')\n",
1216 "print Transformer.call.__doc__\n",
1194 "print(Preprocessor.preprocess.__doc__)\n",
1217 "print '============================='\n",
1195 "print('=============================')\n",
1218 "print Transformer.transform_cell.__doc__\n",
1196 "print(Preprocessor.preprocess_cell.__doc__)\n",
1219 "print '============================='"
1197 "print('=============================')"
1220 ]
1198 ]
1221 },
1199 },
1222 {
1200 {
@@ -1224,7 +1202,7 b''
1224 "metadata": {},
1202 "metadata": {},
1225 "source": [
1203 "source": [
1226 "***\n",
1204 "***\n",
1227 "We don't provide convenient method to be aplied on each worksheet as the **data structure** for worksheet will be removed. (not the worksheet functionnality, which is still on it's way)\n",
1205 "We don't provide convenient method to be aplied on each worksheet as the **data structure** for worksheet will be removed. (not the worksheet functionality, which is still on it's way)\n",
1228 "***"
1206 "***"
1229 ]
1207 ]
1230 },
1208 },
@@ -1239,14 +1217,14 b''
1239 "cell_type": "markdown",
1217 "cell_type": "markdown",
1240 "metadata": {},
1218 "metadata": {},
1241 "source": [
1219 "source": [
1242 "I'll now demonstrate a specific example [requested](https://github.com/ipython/nbconvert/pull/137#issuecomment-18658235) while nbconvert 2 was beeing developped. The ability to exclude cell from the conversion process based on their index. \n",
1220 "I'll now demonstrate a specific example [requested](https://github.com/ipython/nbconvert/pull/137#issuecomment-18658235) while nbconvert 2 was being developed. The ability to exclude cell from the conversion process based on their index. \n",
1243 "\n",
1221 "\n",
1244 "I'll let you imagin how to inject cell, if what you just want is to happend static content at the beginning/end of a notebook, plese refer to templating section, it will be much easier and cleaner."
1222 "I'll let you imagin how to inject cell, if what you just want is to happend static content at the beginning/end of a notebook, plese refer to templating section, it will be much easier and cleaner."
1245 ]
1223 ]
1246 },
1224 },
1247 {
1225 {
1248 "cell_type": "code",
1226 "cell_type": "code",
1249 "execution_count": 15,
1227 "execution_count": 14,
1250 "metadata": {
1228 "metadata": {
1251 "collapsed": false
1229 "collapsed": false
1252 },
1230 },
@@ -1257,71 +1235,66 b''
1257 },
1235 },
1258 {
1236 {
1259 "cell_type": "code",
1237 "cell_type": "code",
1260 "execution_count": 16,
1238 "execution_count": 15,
1261 "metadata": {
1239 "metadata": {
1262 "collapsed": false
1240 "collapsed": false
1263 },
1241 },
1264 "outputs": [],
1242 "outputs": [],
1265 "source": [
1243 "source": [
1266 "class PelicanSubCell(Transformer):\n",
1244 "class PelicanSubCell(Preprocessor):\n",
1267 " \"\"\"A Pelican specific transformer to remove somme of the cells of a notebook\"\"\"\n",
1245 " \"\"\"A Pelican specific preprocessor to remove somme of the cells of a notebook\"\"\"\n",
1268 " \n",
1246 " \n",
1269 " # I could also read the cells from nbc.metadata.pelican is someone wrote a JS extension\n",
1247 " # I could also read the cells from nbc.metadata.pelican is someone wrote a JS extension\n",
1270 " # But I'll stay with configurable value. \n",
1248 " # But I'll stay with configurable value. \n",
1271 " start = Integer(0, config=True, help=\"first cell of notebook to be converted\")\n",
1249 " start = Integer(0, config=True, help=\"first cell of notebook to be converted\")\n",
1272 " end = Integer(-1, config=True, help=\"last cell of notebook to be converted\")\n",
1250 " end = Integer(-1, config=True, help=\"last cell of notebook to be converted\")\n",
1273 " \n",
1251 " \n",
1274 " def call(self, nb, resources):\n",
1252 " def preprocess(self, nb, resources):\n",
1275 "\n",
1253 "\n",
1276 " #nbc = deepcopy(nb)\n",
1254 " #nbc = deepcopy(nb)\n",
1277 " nbc = nb\n",
1255 " nbc = nb\n",
1278 " # don't print in real transformer !!!\n",
1256 " # don't print in real preprocessor !!!\n",
1279 " print \"I'll keep only cells from \", self.start, \"to \", self.end, \"\\n\\n\"\n",
1257 " print(\"I'll keep only cells from \", self.start, \"to \", self.end, \"\\n\\n\")\n",
1280 " for worksheet in nbc.worksheets :\n",
1258 " nbc.cells = nb.cells[self.start:self.end] \n",
1281 " cells = worksheet.cells[:]\n",
1282 " worksheet.cells = cells[self.start:self.end] \n",
1283 " return nbc, resources"
1259 " return nbc, resources"
1284 ]
1260 ]
1285 },
1261 },
1286 {
1262 {
1287 "cell_type": "code",
1263 "cell_type": "code",
1288 "execution_count": 17,
1264 "execution_count": 16,
1289 "metadata": {
1265 "metadata": {
1290 "collapsed": false
1266 "collapsed": false
1291 },
1267 },
1292 "outputs": [],
1268 "outputs": [],
1293 "source": [
1269 "source": [
1294 "# I create this on the fly, but this could be loaded from a DB, and config object support merging...\n",
1270 "# I create this on the fly, but this could be loaded from a DB, and config object support merging...\n",
1295 "c = Config({\n",
1271 "c = Config()\n",
1296 " 'PelicanSubCell':{\n",
1272 "c.PelicanSubCell.enabled = True\n",
1297 " 'enabled':True,\n",
1273 "c.PelicanSubCell.start = 4\n",
1298 " 'start':4,\n",
1274 "c.PelicanSubCell.end = 6"
1299 " 'end':6,\n",
1300 " }\n",
1301 " })"
1302 ]
1275 ]
1303 },
1276 },
1304 {
1277 {
1305 "cell_type": "markdown",
1278 "cell_type": "markdown",
1306 "metadata": {},
1279 "metadata": {},
1307 "source": [
1280 "source": [
1308 "I'm creating a pelican exporter that take `PelicanSubCell` extra transformers and a `config` object as parameter. This might seem redundant, but with configuration system you'll see that one can register an inactive transformer on all exporters and activate it at will form its config files and command line. "
1281 "I'm creating a pelican exporter that take `PelicanSubCell` extra preprocessors and a `config` object as parameter. This might seem redundant, but with configuration system you'll see that one can register an inactive preprocessor on all exporters and activate it at will form its config files and command line. "
1309 ]
1282 ]
1310 },
1283 },
1311 {
1284 {
1312 "cell_type": "code",
1285 "cell_type": "code",
1313 "execution_count": 18,
1286 "execution_count": 17,
1314 "metadata": {
1287 "metadata": {
1315 "collapsed": false
1288 "collapsed": false
1316 },
1289 },
1317 "outputs": [],
1290 "outputs": [],
1318 "source": [
1291 "source": [
1319 "pelican = RSTExporter(transformers=[PelicanSubCell], config=c)"
1292 "pelican = RSTExporter(preprocessors=[PelicanSubCell], config=c)"
1320 ]
1293 ]
1321 },
1294 },
1322 {
1295 {
1323 "cell_type": "code",
1296 "cell_type": "code",
1324 "execution_count": 19,
1297 "execution_count": 18,
1325 "metadata": {
1298 "metadata": {
1326 "collapsed": false
1299 "collapsed": false
1327 },
1300 },
@@ -1338,15 +1311,13 b''
1338 "want to display. But drawing it by hand is a pain: I'd rather just use\n",
1311 "want to display. But drawing it by hand is a pain: I'd rather just use\n",
1339 "matplotlib. The problem is, matplotlib is a bit too precise. Attempting\n",
1312 "matplotlib. The problem is, matplotlib is a bit too precise. Attempting\n",
1340 "to duplicate this figure in matplotlib leads to something like this:\n",
1313 "to duplicate this figure in matplotlib leads to something like this:\n",
1341 "In[2]:\n",
1314 "\n",
1342 ".. code:: python\n",
1315 ".. code:: python\n",
1343 "\n",
1316 "\n",
1344 " Image('http://jakevdp.github.com/figures/mpl_version.png')\n",
1317 " Image('http://jakevdp.github.com/figures/mpl_version.png')\n",
1345 "\n",
1318 "\n",
1346 "\n",
1319 "\n",
1347 "\n",
1320 "\n",
1348 "\n",
1349 "\n",
1350 ".. image:: output_5_0.png\n",
1321 ".. image:: output_5_0.png\n",
1351 "\n",
1322 "\n",
1352 "\n",
1323 "\n",
@@ -1355,80 +1326,7 b''
1355 }
1326 }
1356 ],
1327 ],
1357 "source": [
1328 "source": [
1358 "print pelican.from_notebook_node(jake_notebook)[0]"
1329 "print(pelican.from_notebook_node(jake_notebook)[0])"
1359 ]
1360 },
1361 {
1362 "cell_type": "markdown",
1363 "metadata": {},
1364 "source": [
1365 "### Programatic example of extending templates / cutom filters"
1366 ]
1367 },
1368 {
1369 "cell_type": "code",
1370 "execution_count": 20,
1371 "metadata": {
1372 "collapsed": false
1373 },
1374 "outputs": [],
1375 "source": [
1376 "from IPython.nbconvert.filters.highlight import _pygment_highlight\n",
1377 "from pygments.formatters import HtmlFormatter\n",
1378 "\n",
1379 "from IPython.nbconvert.exporters import HTMLExporter\n",
1380 "from IPython.config import Config\n",
1381 "\n",
1382 "from IPython.nbformat import current as nbformat"
1383 ]
1384 },
1385 {
1386 "cell_type": "markdown",
1387 "metadata": {},
1388 "source": [
1389 "Here we define a dustom 'highlight' filter that apply a custom class to code in css. We register this filter with a already existing name, so it will replace the default one."
1390 ]
1391 },
1392 {
1393 "cell_type": "code",
1394 "execution_count": 21,
1395 "metadata": {
1396 "collapsed": false
1397 },
1398 "outputs": [],
1399 "source": [
1400 "def my_highlight(source, language='ipython'):\n",
1401 " formatter = HtmlFormatter(cssclass='highlight-ipynb')\n",
1402 " return _pygment_highlight(source, formatter, language)\n",
1403 " \n",
1404 "c = Config({'CSSHtmlHeaderTransformer':\n",
1405 " {'enabled':False, 'highlight_class':'highlight-ipynb'}})\n",
1406 "\n",
1407 "exportHtml = HTMLExporter( config=c , filters={'highlight2html': my_highlight} )\n",
1408 "(body,resources) = exportHtml.from_notebook_node(jake_notebook)"
1409 ]
1410 },
1411 {
1412 "cell_type": "code",
1413 "execution_count": 22,
1414 "metadata": {
1415 "collapsed": false
1416 },
1417 "outputs": [
1418 {
1419 "data": {
1420 "text/plain": [
1421 "u'<div class=\"highlight-ipynb\"><pre><span class=\"kn\">from</span>'"
1422 ]
1423 },
1424 "execution_count": 22,
1425 "metadata": {},
1426 "output_type": "execute_result"
1427 }
1428 ],
1429 "source": [
1430 "i = body.index('highlight-ipynb')\n",
1431 "body[i-12:i+50]"
1432 ]
1330 ]
1433 },
1331 },
1434 {
1332 {
@@ -1440,7 +1338,7 b''
1440 },
1338 },
1441 {
1339 {
1442 "cell_type": "code",
1340 "cell_type": "code",
1443 "execution_count": 23,
1341 "execution_count": 19,
1444 "metadata": {
1342 "metadata": {
1445 "collapsed": false
1343 "collapsed": false
1446 },
1344 },
@@ -1449,7 +1347,7 b''
1449 "name": "stdout",
1347 "name": "stdout",
1450 "output_type": "stream",
1348 "output_type": "stream",
1451 "text": [
1349 "text": [
1452 "<p>This post was written entirely in an IPython Notebook: the notebook file is available for download <a href=\"http://jakevdp.github.com/downloads/notebooks/XKCD_plots.ipynb\">here</a>. For more information on blogging with notebooks in octopress, see my <a href=\"http://jakevdp.github.com/blog/2012/10/04/blogging-with-ipython/\">previous post</a> on the subject.</p>\n",
1350 "</div>\n",
1453 "</div>\n",
1351 "</div>\n",
1454 "FOOOOOOOOTEEEEER\n",
1352 "FOOOOOOOOTEEEEER\n",
1455 "\n"
1353 "\n"
@@ -1459,9 +1357,9 b''
1459 "source": [
1357 "source": [
1460 "from jinja2 import DictLoader\n",
1358 "from jinja2 import DictLoader\n",
1461 "\n",
1359 "\n",
1462 "dl = DictLoader({'html_full.tpl': \n",
1360 "dl = DictLoader({'full.tpl': \n",
1463 "\"\"\"\n",
1361 "\"\"\"\n",
1464 "{%- extends 'html_basic.tpl' -%} \n",
1362 "{%- extends 'basic.tpl' -%} \n",
1465 "\n",
1363 "\n",
1466 "{% block footer %}\n",
1364 "{% block footer %}\n",
1467 "FOOOOOOOOTEEEEER\n",
1365 "FOOOOOOOOTEEEEER\n",
@@ -1469,10 +1367,10 b''
1469 "\"\"\"})\n",
1367 "\"\"\"})\n",
1470 "\n",
1368 "\n",
1471 "\n",
1369 "\n",
1472 "exportHtml = HTMLExporter( config=None , filters={'highlight': my_highlight}, extra_loaders=[dl] )\n",
1370 "exportHTML = HTMLExporter(extra_loaders=[dl])\n",
1473 "(body,resources) = exportHtml.from_notebook_node(jake_notebook)\n",
1371 "(body,resources) = exportHTML.from_notebook_node(jake_notebook)\n",
1474 "for l in body.split('\\n')[-4:]:\n",
1372 "for l in body.split('\\n')[-4:]:\n",
1475 " print l"
1373 " print(l)"
1476 ]
1374 ]
1477 },
1375 },
1478 {
1376 {
@@ -1501,7 +1399,7 b''
1501 "metadata": {},
1399 "metadata": {},
1502 "source": [
1400 "source": [
1503 "<center>\n",
1401 "<center>\n",
1504 "<blockquote class=\"twitter-tweet\"><p>As <a href=\"https://twitter.com/Mbussonn\">@Mbussonn</a> requested... easieeeeer! Deploy your Nikola site with just a click in the IPython notebook! <a href=\"http://t.co/860sJunZvj\">http://t.co/860sJunZvj</a> cc <a href=\"https://twitter.com/ralsina\">@ralsina</a></p>&mdash; Dami\u00e1n Avila (@damian_avila) <a href=\"https://twitter.com/damian_avila/statuses/370306057828335616\">August 21, 2013</a></blockquote>\n",
1402 "<blockquote class=\"twitter-tweet\"><p>As <a href=\"https://twitter.com/Mbussonn\">@Mbussonn</a> requested... easieeeeer! Deploy your Nikola site with just a click in the IPython notebook! <a href=\"http://t.co/860sJunZvj\">http://t.co/860sJunZvj</a> cc <a href=\"https://twitter.com/ralsina\">@ralsina</a></p>&mdash; DamiΓ‘n Avila (@damian_avila) <a href=\"https://twitter.com/damian_avila/statuses/370306057828335616\">August 21, 2013</a></blockquote>\n",
1505 "</center>"
1403 "</center>"
1506 ]
1404 ]
1507 },
1405 },
@@ -1525,18 +1423,26 b''
1525 "source": [
1423 "source": [
1526 "Jinja blocks use `{% %}`by default which does not play nicely with $\\LaTeX$, hence thoses are replaced by `((* *))` in latex templates."
1424 "Jinja blocks use `{% %}`by default which does not play nicely with $\\LaTeX$, hence thoses are replaced by `((* *))` in latex templates."
1527 ]
1425 ]
1528 },
1529 {
1530 "cell_type": "code",
1531 "execution_count": null,
1532 "metadata": {
1533 "collapsed": false
1534 },
1535 "outputs": [],
1536 "source": []
1537 }
1426 }
1538 ],
1427 ],
1539 "metadata": {},
1428 "metadata": {
1429 "kernelspec": {
1430 "display_name": "Python 3",
1431 "name": "python3"
1432 },
1433 "language_info": {
1434 "codemirror_mode": {
1435 "name": "ipython",
1436 "version": 3
1437 },
1438 "file_extension": ".py",
1439 "mimetype": "text/x-python",
1440 "name": "python",
1441 "nbconvert_exporter": "python",
1442 "pygments_lexer": "ipython3",
1443 "version": "3.4.2"
1444 }
1445 },
1540 "nbformat": 4,
1446 "nbformat": 4,
1541 "nbformat_minor": 0
1447 "nbformat_minor": 0
1542 } No newline at end of file
1448 }
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