Backport PR #8132: Only split lines on text output

rather than all mime-types, which includes b64 output.

This doesn't change how files are read, so it is still valid for any mime-type data to be split on disk. It just changes which mime-types IPython.nbformat splits on write.

/cc @shoyer who reported the issue on twitter

IPython/nbconvert/exporters/tests/files/notebook2.ipynb

@@ -1,262 +1,178
 {
  "cells": [
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# NumPy and Matplotlib examples"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "First import NumPy and Matplotlib:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "\n",
       "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.kernel.zmq.pylab.backend_inline].\n",
       "For more information, type 'help(pylab)'.\n"
      ]
     }
    ],
    "source": [
     "%pylab inline"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "import numpy as np"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Now we show some very basic examples of how they can be used."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "a = np.random.uniform(size=(100,100))"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "(100, 100)"
       ]
      },
      "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "a.shape"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "evs = np.linalg.eigvals(a)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "(100,)"
       ]
      },
      "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "evs.shape"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Here is a cell that has both text and PNG output:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "(array([95,  4,  0,  0,  0,  0,  0,  0,  0,  1]),\n",
        " array([ -2.93566063,   2.35937011,   7.65440086,  12.9494316 ,\n",
        "        18.24446235,  23.53949309,  28.83452384,  34.12955458,\n",
        "        39.42458533,  44.71961607,  50.01464682]),\n",
        " <a list of 10 Patch objects>)"
       ]
      },
      "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
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+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXgAAAD9CAYAAAC2l2x5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text/plain": [
        "<matplotlib.figure.Figure at 0x108c8f1d0>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "hist(evs.real)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": []
   }
  ],
  "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 0
-}
  No newline at end of file
+}

IPython/nbconvert/exporters/tests/test_notebook.py

@@ -1,39 +1,39
 """Tests for notebook.py"""
 
 # Copyright (c) IPython Development Team.
 # Distributed under the terms of the Modified BSD License.
 
 import json
 
 from .base import ExportersTestsBase
 from ..notebook import NotebookExporter
 
 from IPython.nbformat import validate
 from IPython.testing.tools import assert_big_text_equal
 
 class TestNotebookExporter(ExportersTestsBase):
     """Contains test functions for notebook.py"""
 
     exporter_class = NotebookExporter
 
     def test_export(self):
         """
         Does the NotebookExporter return the file unchanged?
         """
         with open(self._get_notebook()) as f:
             file_contents = f.read()
         (output, resources) = self.exporter_class().from_filename(self._get_notebook())
         assert len(output) > 0
-        assert_big_text_equal(output, file_contents)
+        assert_big_text_equal(output.strip(), file_contents.strip())
 
     def test_downgrade_3(self):
         exporter = self.exporter_class(nbformat_version=3)
         (output, resources) = exporter.from_filename(self._get_notebook())
         nb = json.loads(output)
         validate(nb)
 
     def test_downgrade_2(self):
         exporter = self.exporter_class(nbformat_version=2)
         (output, resources) = exporter.from_filename(self._get_notebook())
         nb = json.loads(output)
         self.assertEqual(nb['nbformat'], 2)

IPython/nbformat/v4/rwbase.py

@@ -1,96 +1,102
 """Base classes and utilities for readers and writers."""
 
 # Copyright (c) IPython Development Team.
 # Distributed under the terms of the Modified BSD License.
 
 from IPython.utils.py3compat import string_types, cast_unicode_py2
 
 
 def rejoin_lines(nb):
     """rejoin multiline text into strings
 
     For reversing effects of ``split_lines(nb)``.
 
     This only rejoins lines that have been split, so if text objects were not split
     they will pass through unchanged.
 
     Used when reading JSON files that may have been passed through split_lines.
     """
     for cell in nb.cells:
         if 'source' in cell and isinstance(cell.source, list):
             cell.source = ''.join(cell.source)
         if cell.get('cell_type', None) == 'code':
             for output in cell.get('outputs', []):
                 output_type = output.get('output_type', '')
                 if output_type in {'execute_result', 'display_data'}:
                     for key, value in output.get('data', {}).items():
                         if key != 'application/json' and isinstance(value, list):
                             output.data[key] = ''.join(value)
                 elif output_type:
                     if isinstance(output.get('text', ''), list):
                         output.text = ''.join(output.text)
     return nb
 
+_non_text_split_mimes = {
+    'application/javascript',
+    'image/svg+xml',
+}
 
 def split_lines(nb):
     """split likely multiline text into lists of strings
 
     For file output more friendly to line-based VCS. ``rejoin_lines(nb)`` will
     reverse the effects of ``split_lines(nb)``.
 
     Used when writing JSON files.
     """
     for cell in nb.cells:
         source = cell.get('source', None)
         if isinstance(source, string_types):
             cell['source'] = source.splitlines(True)
 
         if cell.cell_type == 'code':
             for output in cell.outputs:
                 if output.output_type in {'execute_result', 'display_data'}:
                     for key, value in output.data.items():
-                        if key != 'application/json' and isinstance(value, string_types):
+                        if isinstance(value, string_types) and (
+                            key.startswith('text/') or key in _non_text_split_mimes
+                        ):
                             output.data[key] = value.splitlines(True)
                 elif output.output_type == 'stream':
                     if isinstance(output.text, string_types):
                         output.text = output.text.splitlines(True)
     return nb
 
 
 def strip_transient(nb):
     """Strip transient values that shouldn't be stored in files.
 
     This should be called in *both* read and write.
     """
     nb.metadata.pop('orig_nbformat', None)
     nb.metadata.pop('orig_nbformat_minor', None)
     nb.metadata.pop('signature', None)
     for cell in nb.cells:
         cell.metadata.pop('trusted', None)
     return nb
 
 
 class NotebookReader(object):
     """A class for reading notebooks."""
 
     def reads(self, s, **kwargs):
         """Read a notebook from a string."""
         raise NotImplementedError("loads must be implemented in a subclass")
 
     def read(self, fp, **kwargs):
         """Read a notebook from a file like object"""
         nbs = cast_unicode_py2(fp.read())
         return self.reads(nbs, **kwargs)
 
 
 class NotebookWriter(object):
     """A class for writing notebooks."""
 
     def writes(self, nb, **kwargs):
         """Write a notebook to a string."""
         raise NotImplementedError("loads must be implemented in a subclass")
 
     def write(self, nb, fp, **kwargs):
         """Write a notebook to a file like object"""
         nbs = cast_unicode_py2(self.writes(nb, **kwargs))
         return fp.write(nbs)