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"""Module containing a preprocessor that extracts all of the outputs from the
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notebook file. The extracted outputs are returned in the 'resources' dictionary.
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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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# Imports
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#-----------------------------------------------------------------------------
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import base64
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import sys
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import os
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from IPython.utils.traitlets import Unicode, Set
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from .base import Preprocessor
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from IPython.utils import py3compat
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#-----------------------------------------------------------------------------
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# Classes
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#-----------------------------------------------------------------------------
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class ExtractOutputPreprocessor(Preprocessor):
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"""
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Extracts all of the outputs from the notebook file. The extracted
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outputs are returned in the 'resources' dictionary.
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"""
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output_filename_template = Unicode(
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"{unique_key}_{cell_index}_{index}.{extension}", config=True)
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extract_output_types = Set({'png', 'jpg', 'svg', 'pdf'}, config=True)
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def preprocess_cell(self, cell, resources, cell_index):
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"""
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Apply a transformation on each cell,
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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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preprocessors to pass variables into the Jinja engine.
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cell_index : int
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Index of the cell being processed (see base.py)
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"""
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#Get the unique key from the resource dict if it exists. If it does not
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#exist, use 'output' as the default. Also, get files directory if it
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#has been specified
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unique_key = resources.get('unique_key', 'output')
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output_files_dir = resources.get('output_files_dir', None)
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#Make sure outputs key exists
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if not isinstance(resources['outputs'], dict):
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resources['outputs'] = {}
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#Loop through all of the outputs in the cell
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for index, out in enumerate(cell.get('outputs', [])):
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#Get the output in data formats that the template needs extracted
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for out_type in self.extract_output_types:
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if out.hasattr(out_type):
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data = out[out_type]
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#Binary files are base64-encoded, SVG is already XML
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if out_type in ('png', 'jpg', 'jpeg', 'pdf'):
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# data is b64-encoded as text (str, unicode)
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# decodestring only accepts bytes
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data = py3compat.cast_bytes(data)
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data = base64.decodestring(data)
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elif sys.platform == 'win32':
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data = data.replace('\n', '\r\n').encode("UTF-8")
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else:
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data = data.encode("UTF-8")
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#Build an output name
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filename = self.output_filename_template.format(
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unique_key=unique_key,
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cell_index=cell_index,
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index=index,
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extension=out_type)
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#On the cell, make the figure available via
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# cell.outputs[i].svg_filename ... etc (svg in example)
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# Where
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# cell.outputs[i].svg contains the data
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if output_files_dir is not None:
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filename = os.path.join(output_files_dir, filename)
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out[out_type + '_filename'] = filename
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#In the resources, make the figure available via
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# resources['outputs']['filename'] = data
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resources['outputs'][filename] = data
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return cell, resources
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