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"""A preprocessor that extracts all of the outputs from the
notebook file. The extracted outputs are returned in the 'resources' dictionary.
# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.
from binascii import a2b_base64
import sys
import os
import json
from mimetypes import guess_extension
from traitlets import Unicode, Set
from .base import Preprocessor
if sys.version_info < (3,):
text_type = basestring
text_type = str
def guess_extension_without_jpe(mimetype):
This function fixes a problem with '.jpe' extensions
of jpeg images which are then not recognised by latex.
For any other case, the function works in the same way
as mimetypes.guess_extension
ext = guess_extension(mimetype)
if ext==".jpe":
return ext
class ExtractOutputPreprocessor(Preprocessor):
Extracts all of the outputs from the notebook file. The extracted
outputs are returned in the 'resources' dictionary.
output_filename_template = Unicode(
extract_output_types = Set(
{'image/png', 'image/jpeg', 'image/svg+xml', 'application/pdf'}
def preprocess_cell(self, cell, resources, cell_index):
Apply a transformation on each cell,
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.
cell_index : int
Index of the cell being processed (see
#Get the unique key from the resource dict if it exists. If it does not
#exist, use 'output' as the default. Also, get files directory if it
#has been specified
unique_key = resources.get('unique_key', 'output')
output_files_dir = resources.get('output_files_dir', None)
#Make sure outputs key exists
if not isinstance(resources['outputs'], dict):
resources['outputs'] = {}
#Loop through all of the outputs in the cell
for index, out in enumerate(cell.get('outputs', [])):
if out.output_type not in {'display_data', 'execute_result'}:
#Get the output in data formats that the template needs extracted
for mime_type in self.extract_output_types:
if mime_type in
data =[mime_type]
if (
not isinstance(data, text_type)
or mime_type == 'application/json'
# Data is either JSON-like and was parsed into a Python
# object according to the spec, or data is for sure
# JSON. In the latter case we want to go extra sure that
# we enclose a scalar string value into extra quotes by
# serializing it properly.
data = json.dumps(data)
#Binary files are base64-encoded, SVG is already XML
if mime_type in {'image/png', 'image/jpeg', 'application/pdf'}:
# data is b64-encoded as text (str, unicode),
# we want the original bytes
data = a2b_base64(data)
elif sys.platform == 'win32':
data = data.replace('\n', '\r\n').encode("UTF-8")
data = data.encode("UTF-8")
ext = guess_extension_without_jpe(mime_type)
if ext is None:
ext = '.' + mime_type.rsplit('/')[-1]
if out.metadata.get('filename', ''):
filename = out.metadata['filename']
if not filename.endswith(ext):
filename = self.output_filename_template.format(
# On the cell, make the figure available via
# cell.outputs[i].metadata.filenames['mime/type']
# where
# cell.outputs[i].data['mime/type'] contains the data
if output_files_dir is not None:
filename = os.path.join(output_files_dir, filename)
out.metadata.setdefault('filenames', {})
out.metadata['filenames'][mime_type] = filename
if filename in resources['outputs']:
raise ValueError(
"Your outputs have filename metadata associated "
"with them. Nbconvert saves these outputs to "
"external files using this filename metadata. "
"Filenames need to be unique across the notebook, "
"or images will be overwritten. The filename {} is "
"associated with more than one output. The second "
"output associated with this filename is in cell "
"{}.".format(filename, cell_index)
#In the resources, make the figure available via
# resources['outputs']['filename'] = data
resources['outputs'][filename] = data
return cell, resources