"""This module defines a base Exporter class. For Jinja template-based export, see templateexporter.py. """ from __future__ import print_function, absolute_import import io import os import copy import collections import datetime from IPython.config.configurable import LoggingConfigurable from IPython.config import Config from IPython import nbformat from IPython.utils.traitlets import MetaHasTraits, Unicode, List, TraitError from IPython.utils.importstring import import_item from IPython.utils import text, py3compat class ResourcesDict(collections.defaultdict): def __missing__(self, key): return '' class FilenameExtension(Unicode): """A trait for filename extensions.""" default_value = u'' info_text = 'a filename extension, beginning with a dot' def validate(self, obj, value): # cast to proper unicode value = super(FilenameExtension, self).validate(obj, value) # check that it starts with a dot if value and not value.startswith('.'): msg = "FileExtension trait '{}' does not begin with a dot: {!r}" raise TraitError(msg.format(self.name, value)) return value class Exporter(LoggingConfigurable): """ Class containing methods that sequentially run a list of preprocessors on a NotebookNode object and then return the modified NotebookNode object and accompanying resources dict. """ file_extension = FilenameExtension( '.txt', config=True, help="Extension of the file that should be written to disk" ) # MIME type of the result file, for HTTP response headers. # This is *not* a traitlet, because we want to be able to access it from # the class, not just on instances. output_mimetype = '' #Configurability, allows the user to easily add filters and preprocessors. preprocessors = List(config=True, help="""List of preprocessors, by name or namespace, to enable.""") _preprocessors = List() default_preprocessors = List(['jupyter_nbconvert.preprocessors.coalesce_streams', 'jupyter_nbconvert.preprocessors.SVG2PDFPreprocessor', 'jupyter_nbconvert.preprocessors.ExtractOutputPreprocessor', 'jupyter_nbconvert.preprocessors.CSSHTMLHeaderPreprocessor', 'jupyter_nbconvert.preprocessors.RevealHelpPreprocessor', 'jupyter_nbconvert.preprocessors.LatexPreprocessor', 'jupyter_nbconvert.preprocessors.ClearOutputPreprocessor', 'jupyter_nbconvert.preprocessors.ExecutePreprocessor', 'jupyter_nbconvert.preprocessors.HighlightMagicsPreprocessor'], config=True, help="""List of preprocessors available by default, by name, namespace, instance, or type.""") def __init__(self, config=None, **kw): """ Public constructor Parameters ---------- config : config User configuration instance. """ with_default_config = self.default_config if config: with_default_config.merge(config) super(Exporter, self).__init__(config=with_default_config, **kw) self._init_preprocessors() @property def default_config(self): return Config() def from_notebook_node(self, nb, resources=None, **kw): """ Convert a notebook from a notebook node instance. Parameters ---------- nb : :class:`~IPython.nbformat.NotebookNode` Notebook node (dict-like with attr-access) resources : dict Additional resources that can be accessed read/write by preprocessors and filters. **kw Ignored (?) """ nb_copy = copy.deepcopy(nb) resources = self._init_resources(resources) if 'language' in nb['metadata']: resources['language'] = nb['metadata']['language'].lower() # Preprocess nb_copy, resources = self._preprocess(nb_copy, resources) return nb_copy, resources def from_filename(self, filename, resources=None, **kw): """ Convert a notebook from a notebook file. Parameters ---------- filename : str Full filename of the notebook file to open and convert. """ # Pull the metadata from the filesystem. if resources is None: resources = ResourcesDict() if not 'metadata' in resources or resources['metadata'] == '': resources['metadata'] = ResourcesDict() path, basename = os.path.split(filename) notebook_name = basename[:basename.rfind('.')] resources['metadata']['name'] = notebook_name resources['metadata']['path'] = path modified_date = datetime.datetime.fromtimestamp(os.path.getmtime(filename)) resources['metadata']['modified_date'] = modified_date.strftime(text.date_format) with io.open(filename, encoding='utf-8') as f: return self.from_notebook_node(nbformat.read(f, as_version=4), resources=resources, **kw) def from_file(self, file_stream, resources=None, **kw): """ Convert a notebook from a notebook file. Parameters ---------- file_stream : file-like object Notebook file-like object to convert. """ return self.from_notebook_node(nbformat.read(file_stream, as_version=4), resources=resources, **kw) def register_preprocessor(self, preprocessor, enabled=False): """ Register a preprocessor. Preprocessors are classes that act upon the notebook before it is passed into the Jinja templating engine. preprocessors are also capable of passing additional information to the Jinja templating engine. Parameters ---------- preprocessor : preprocessor """ if preprocessor is None: raise TypeError('preprocessor') isclass = isinstance(preprocessor, type) constructed = not isclass # Handle preprocessor's registration based on it's type if constructed and isinstance(preprocessor, py3compat.string_types): # Preprocessor is a string, import the namespace and recursively call # this register_preprocessor method preprocessor_cls = import_item(preprocessor) return self.register_preprocessor(preprocessor_cls, enabled) if constructed and hasattr(preprocessor, '__call__'): # Preprocessor is a function, no need to construct it. # Register and return the preprocessor. if enabled: preprocessor.enabled = True self._preprocessors.append(preprocessor) return preprocessor elif isclass and isinstance(preprocessor, MetaHasTraits): # Preprocessor is configurable. Make sure to pass in new default for # the enabled flag if one was specified. self.register_preprocessor(preprocessor(parent=self), enabled) elif isclass: # Preprocessor is not configurable, construct it self.register_preprocessor(preprocessor(), enabled) else: # Preprocessor is an instance of something without a __call__ # attribute. raise TypeError('preprocessor') def _init_preprocessors(self): """ Register all of the preprocessors needed for this exporter, disabled unless specified explicitly. """ self._preprocessors = [] # Load default preprocessors (not necessarly enabled by default). for preprocessor in self.default_preprocessors: self.register_preprocessor(preprocessor) # Load user-specified preprocessors. Enable by default. for preprocessor in self.preprocessors: self.register_preprocessor(preprocessor, enabled=True) def _init_resources(self, resources): #Make sure the resources dict is of ResourcesDict type. if resources is None: resources = ResourcesDict() if not isinstance(resources, ResourcesDict): new_resources = ResourcesDict() new_resources.update(resources) resources = new_resources #Make sure the metadata extension exists in resources if 'metadata' in resources: if not isinstance(resources['metadata'], ResourcesDict): new_metadata = ResourcesDict() new_metadata.update(resources['metadata']) resources['metadata'] = new_metadata else: resources['metadata'] = ResourcesDict() if not resources['metadata']['name']: resources['metadata']['name'] = 'Notebook' #Set the output extension resources['output_extension'] = self.file_extension return resources def _preprocess(self, nb, resources): """ Preprocess the notebook before passing it into the Jinja engine. To preprocess the notebook is to apply all of the Parameters ---------- nb : notebook node notebook that is being exported. resources : a dict of additional resources that can be accessed read/write by preprocessors """ # Do a copy.deepcopy first, # we are never safe enough with what the preprocessors could do. nbc = copy.deepcopy(nb) resc = copy.deepcopy(resources) #Run each preprocessor on the notebook. Carry the output along #to each preprocessor for preprocessor in self._preprocessors: nbc, resc = preprocessor(nbc, resc) return nbc, resc