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