FIX, coalescestreams incorrect nesting.

IPython/nbconvert/preprocessors/coalescestreams.py

@@ -1,75 +1,75 b''
 """Module that allows latex output notebooks to be conditioned before
 they are converted.  Exposes a decorator (@cell_preprocessor) in
 addition to the coalesce_streams pre-proccessor.
 """
 #-----------------------------------------------------------------------------
 # Copyright (c) 2013, the IPython Development Team.
 #
 # Distributed under the terms of the Modified BSD License.
 #
 # The full license is in the file COPYING.txt, distributed with this software.
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # Functions
 #-----------------------------------------------------------------------------
 
 def cell_preprocessor(function):
     """
     Wrap a function to be executed on all cells of a notebook
     
     Wrapped Parameters
     ----------
     cell : NotebookNode cell
         Notebook cell being processed
     resources : dictionary
         Additional resources used in the conversion process.  Allows
         preprocessors to pass variables into the Jinja engine.
     index : int
         Index of the cell being processed
     """
     
     def wrappedfunc(nb, resources):
         for worksheet in nb.worksheets :
             for index, cell in enumerate(worksheet.cells):
                 worksheet.cells[index], resources = function(cell, resources, index)
         return nb, resources
     return wrappedfunc
 
 
 @cell_preprocessor
 def coalesce_streams(cell, resources, index):
     """
     Merge consecutive sequences of stream output into single stream
     to prevent extra newlines inserted at flush calls
     
     Parameters
     ----------
     cell : NotebookNode cell
         Notebook cell being processed
     resources : dictionary
         Additional resources used in the conversion process.  Allows
         transformers to pass variables into the Jinja engine.
     index : int
         Index of the cell being processed
     """
     
     outputs = cell.get('outputs', [])
     if not outputs:
         return cell, resources
     
     last = outputs[0]
     new_outputs = [last]
     
     for output in outputs[1:]:
         if (output.output_type == 'stream' and
             last.output_type == 'stream' and
             last.stream == output.stream
         ):
             last.text += output.text
         else:
             new_outputs.append(output)
-        last = output
+            last = output
 
     cell.outputs = new_outputs
     return cell, resources