##// END OF EJS Templates
cache kernel_info reply for protocol adaptation...
cache kernel_info reply for protocol adaptation WebSocket connections will not open until kernel_info is retrieved, removing a race condition waiting for the reply to indicate adaptation, which could result in a v5 message being sent to a v4 kernel. The reply is cached, so that it need not be requested on each new connection.

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base.py
93 lines | 2.9 KiB | text/x-python | PythonLexer
"""Base class for preprocessors"""
# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.
from ..utils.base import NbConvertBase
from IPython.utils.traitlets import Bool
class Preprocessor(NbConvertBase):
""" A configurable preprocessor
Inherit from this class if you wish to have configurability for your
preprocessor.
Any configurable traitlets this class exposed will be configurable in
profiles using c.SubClassName.attribute = value
you can overwrite :meth:`preprocess_cell` to apply a transformation
independently on each cell or :meth:`preprocess` if you prefer your own
logic. See corresponding docstring for informations.
Disabled by default and can be enabled via the config by
'c.YourPreprocessorName.enabled = True'
"""
enabled = Bool(False, config=True)
def __init__(self, **kw):
"""
Public constructor
Parameters
----------
config : Config
Configuration file structure
**kw : misc
Additional arguments
"""
super(Preprocessor, self).__init__(**kw)
def __call__(self, nb, resources):
if self.enabled:
self.log.debug("Applying preprocessor: %s", self.__class__.__name__)
return self.preprocess(nb,resources)
else:
return nb, resources
def preprocess(self, nb, resources):
"""
Preprocessing to apply on each notebook.
Must return modified nb, resources.
If you wish to apply your preprocessing to each cell, you might want
to override preprocess_cell method instead.
Parameters
----------
nb : NotebookNode
Notebook being converted
resources : dictionary
Additional resources used in the conversion process. Allows
preprocessors to pass variables into the Jinja engine.
"""
for worksheet in nb.worksheets:
for index, cell in enumerate(worksheet.cells):
worksheet.cells[index], resources = self.preprocess_cell(cell, resources, index)
return nb, resources
def preprocess_cell(self, cell, resources, index):
"""
Override if you want to apply some preprocessing to each cell.
Must return modified cell and resource dictionary.
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
"""
raise NotImplementedError('should be implemented by subclass')
return cell, resources