Renamed preprocessors to transformers to maintain consistency

nbconvert/api/exporter.py

@@ -1,316 +1,315 b''
 """This module defines Exporter, a highly configurable converter
 that uses Jinja2 to export notebook files into different formats.
 """
 
 #-----------------------------------------------------------------------------
 # Copyright (c) 2013, the IPython Development Team.
 #
 # Distributed under the terms of the Modified BSD License.
 #
 # The full license is in the file COPYING.txt, distributed with this software.
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # Imports
 #-----------------------------------------------------------------------------
 
 from __future__ import print_function, absolute_import
 
 # Stdlib imports
 import io
 import os
 import inspect
 
 # IPython imports
 from IPython.config.configurable import Configurable
 from IPython.nbformat import current as nbformat
 from IPython.utils.traitlets import MetaHasTraits, Unicode, List, Bool
 from IPython.utils.text import indent
 
 # other libs/dependencies
 from jinja2 import Environment, FileSystemLoader
 from markdown import markdown
 
 # local import
 import nbconvert.filters.strings
 import nbconvert.filters.markdown
 import nbconvert.filters.latex
 import nbconvert.filters.datatypefilter
 import nbconvert.filters.highlight
 import nbconvert.filters.ansi
 
 import nbconvert.transformers.extractfigure
 import nbconvert.transformers.coalescestreams
 
 #-----------------------------------------------------------------------------
 # Globals and constants
 #-----------------------------------------------------------------------------
 
 #Jinja2 extensions to load.
 JINJA_EXTENSIONS = ['jinja2.ext.loopcontrols']
 
 #-----------------------------------------------------------------------------
 # Class
 #-----------------------------------------------------------------------------
 
 class Exporter(Configurable):
     """
     Exports notebooks into other file formats.  Uses Jinja 2 templating engine
     to output new formats.  Inherit from this class if you are creating a new
     template type along with new filters/transformers.  If the filters/
     transformers provided by default suffice, there is no need to inherit from
     this class.  Instead, override the template_file and file_extension
     traits via a config file.
     """
     
     template_file = Unicode(
             '', config=True,
             help="Name of the template file to use")
 
     file_extension = Unicode(
         'txt', config=True, 
         help="Extension of the file that should be written to disk"
         )
 
     template_path = Unicode(
         "/../templates/", config=True,
         help="Path where the template files are located.")
 
     template_skeleton_path = Unicode(
         "/../templates/skeleton/", config=True,
         help="Path where the template skeleton files are located.") 
 
     #Jinja block definitions
     jinja_comment_block_start = Unicode("", config=True)
     jinja_comment_block_end = Unicode("", config=True)
     jinja_variable_block_start = Unicode("", config=True)
     jinja_variable_block_end = Unicode("", config=True)
     jinja_logic_block_start = Unicode("", config=True)
     jinja_logic_block_end = Unicode("", config=True)
     
     #Extension that the template files use.    
     template_extension = Unicode(".tpl", config=True)
 
     #Processors that process the input data prior to the export, set in the 
     #constructor for this class.
-    preprocessors = [] 
+    transformers = [] 
 
     
     def __init__(self, transformers=None, filters=None, config=None, **kw):
         """
         Public constructor
     
         Parameters
         ----------
         transformers : list[of transformer]
             Custom transformers to apply to the notebook prior to engaging
             the Jinja template engine.  Any transformers specified here 
             will override existing transformers if a naming conflict
             occurs.
         filters : list[of filter]
             Custom filters to make accessible to the Jinja templates.  Any
             filters specified here will override existing filters if a
             naming conflict occurs.
         config : config
             User configuration instance.
         """
         
         #Call the base class constructor
         super(Exporter, self).__init__(config=config, **kw)
 
         #Standard environment
         self._init_environment()
 
         #Add transformers
         self._register_transformers()
 
         #Add filters to the Jinja2 environment
         self._register_filters()
 
         #Load user transformers.  Overwrite existing transformers if need be.
         if not transformers is None:        
             for transformer in transformers:
                 self.register_transformer(transformer)
                 
         #Load user filters.  Overwrite existing filters if need be.
         if not filters is None:
             for key, user_filter in filters.iteritems():
                 if issubclass(user_filter, MetaHasTraits):
                     self.environment.filters[key] = user_filter(config=config)
                 else:
                     self.environment.filters[key] = user_filter
     
     
     def from_notebook_node(self, nb):
         """
         Convert a notebook from a notebook node instance.
     
         Parameters
         ----------
         nb : Notebook node
         """
         
         nb, resources = self._preprocess(nb)
         
         #Load the template file.
         self.template = self.environment.get_template(self.template_file+self.template_extension)
         
         return self.template.render(nb=nb, resources=resources), resources
 
 
     def from_filename(self, filename):
         """
         Convert a notebook from a notebook file.
     
         Parameters
         ----------
         filename : str
             Full filename of the notebook file to open and convert.
         """
         
         with io.open(filename) as f:
             return self.from_notebook_node(nbformat.read(f, 'json'))
 
 
     def from_file(self, file_stream):
         """
         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, 'json'))
 
 
     def register_transformer(self, transformer):
         """
         Register a transformer.
         Transformers are classes that act upon the notebook before it is
         passed into the Jinja templating engine.  Transformers are also
         capable of passing additional information to the Jinja
         templating engine.
     
         Parameters
         ----------
         transformer : transformer
         """
         
         if inspect.isfunction(transformer):
-            self.preprocessors.append(transformer)
+            self.transformers.append(transformer)
             return transformer
         elif isinstance(transformer, MetaHasTraits):
             transformer_instance = transformer(config=self.config)
-            self.preprocessors.append(transformer_instance)
+            self.transformers.append(transformer_instance)
             return transformer_instance
         else:
             transformer_instance = transformer()
-            self.preprocessors.append(transformer_instance)
+            self.transformers.append(transformer_instance)
             return transformer_instance
 
 
     def register_filter(self, name, filter):
         """
         Register a filter.
         A filter is a function that accepts and acts on one string.  
         The filters are accesible within the Jinja templating engine.
     
         Parameters
         ----------
         name : str
             name to give the filter in the Jinja engine
         filter : filter
         """
-        
         if inspect.isfunction(filter):
             self.environment.filters[name] = filter
         elif isinstance(filter, MetaHasTraits):
             self.environment.filters[name] = filter(config=self.config)
         else:
             self.environment.filters[name] = filter()
         return self.environment.filters[name]
 
     
     def _register_transformers(self):
         """
         Register all of the transformers needed for this exporter.
         """
-        
+         
         self.register_transformer(nbconvert.transformers.coalescestreams.coalesce_streams)
         
         #Remember the figure extraction transformer so it can be enabled and
         #disabled easily later.
         self.extract_figure_transformer = self.register_transformer(nbconvert.transformers.extractfigure.ExtractFigureTransformer)
         
         
     def _register_filters(self):
         """
         Register all of the filters required for the exporter.
         """
         
         self.register_filter('indent', indent)
         self.register_filter('markdown', markdown)
         self.register_filter('ansi2html', nbconvert.filters.ansi.ansi2html)
         self.register_filter('filter_data_type', nbconvert.filters.datatypefilter.DataTypeFilter)
         self.register_filter('get_lines', nbconvert.filters.strings.get_lines)
         self.register_filter('highlight', nbconvert.filters.highlight.highlight)
         self.register_filter('highlight2html', nbconvert.filters.highlight.highlight) 
         self.register_filter('highlight2latex', nbconvert.filters.highlight.highlight2latex)
         self.register_filter('markdown2latex', nbconvert.filters.markdown.markdown2latex)
         self.register_filter('markdown2rst', nbconvert.filters.markdown.markdown2rst)
         self.register_filter('pycomment', nbconvert.filters.strings.python_comment)
         self.register_filter('rm_ansi', nbconvert.filters.ansi.remove_ansi)
         self.register_filter('rm_dollars', nbconvert.filters.strings.strip_dollars)
         self.register_filter('rm_fake', nbconvert.filters.strings.rm_fake)
         self.register_filter('rm_math_space', nbconvert.filters.latex.rm_math_space)
         self.register_filter('wrap', nbconvert.filters.strings.wrap)
         
         
     def _init_environment(self):
         """
         Create the Jinja templating environment.
         """
         
         self.environment = Environment(
             loader=FileSystemLoader([
                 os.path.dirname(os.path.realpath(__file__)) + self.template_path,
                 os.path.dirname(os.path.realpath(__file__)) + self.template_skeleton_path,
                 ]),
             extensions=JINJA_EXTENSIONS
             )
         
         #Set special Jinja2 syntax that will not conflict with latex.
         if self.jinja_logic_block_start:
             self.environment.block_start_string = self.jinja_logic_block_start
         if self.jinja_logic_block_end:
             self.environment.block_end_string = self.jinja_logic_block_end
         if self.jinja_variable_block_start:
             self.environment.variable_start_string = self.jinja_variable_block_start
         if self.jinja_variable_block_end:
             self.environment.variable_end_string = self.jinja_variable_block_end
         if self.jinja_comment_block_start:
             self.environment.comment_start_string = self.jinja_comment_block_start
         if self.jinja_comment_block_end:
             self.environment.comment_end_string = self.jinja_comment_block_end
 
 
     def _preprocess(self, nb):
         """
         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.
         """
         
-        #Dict of 'resources' that can be filled by the preprocessors.
+        #Dict of 'resources' that can be filled by the transformers.
         resources = {}
 
         #Run each transformer on the notebook.  Carry the output along
         #to each transformer
-        for transformer in self.preprocessors:
+        for transformer in self.transformers:
             nb, resources = transformer(nb, resources)
         return nb, resources