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"""Preprocessor for merging consecutive stream outputs for easier handling."""
# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.
import re
import functools
from traitlets.log import get_logger
def cell_preprocessor(function):
"""
Wrap a function to be executed on all cells of a notebook
The wrapped function should have these 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
"""
@functools.wraps(function)
def wrappedfunc(nb, resources):
get_logger().debug(
"Applying preprocessor: %s", function.__name__
)
for index, cell in enumerate(nb.cells):
nb.cells[index], resources = function(cell, resources, index)
return nb, resources
return wrappedfunc
cr_pat = re.compile(r'.*\r(?=[^\n])')
@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.name == output.name
):
last.text += output.text
else:
new_outputs.append(output)
last = output
# process \r characters
for output in new_outputs:
if output.output_type == 'stream' and '\r' in output.text:
output.text = cr_pat.sub('', output.text)
cell.outputs = new_outputs
return cell, resources