Removed ActivatableTransformer and moved enabled key into base.

IPython/nbconvert/transformers/__init__.py

@@ -1,12 +1,11
 # Class base Transformers
-from .activatable import ActivatableTransformer
 from .base import ConfigurableTransformer
 from .convertfigures import ConvertFiguresTransformer
 from .svg2pdf import Svg2PdfTransformer
 from .extractfigure import ExtractFigureTransformer
 from .revealhelp import RevealHelpTransformer
 from .latex import LatexTransformer
 from .sphinx import SphinxTransformer
 
 # decorated function Transformers
 from .coalescestreams import coalesce_streams

IPython/nbconvert/transformers/base.py

@@ -1,101 +1,109
 """
 Module that re-groups transformer that would be applied to ipynb files
 before going through the templating machinery.
 
 It exposes a convenient class to inherit from to access configurability.
 """
 #-----------------------------------------------------------------------------
 # 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 ..utils.config import GlobalConfigurable
+from IPython.utils.traitlets import Bool
 
 #-----------------------------------------------------------------------------
 # Classes and Functions
 #-----------------------------------------------------------------------------
 
 class ConfigurableTransformer(GlobalConfigurable):
     """ A configurable transformer
 
     Inherit from this class if you wish to have configurability for your
     transformer.
 
     Any configurable traitlets this class exposed will be configurable in profiles
     using c.SubClassName.atribute=value
 
     you can overwrite transform_cell to apply a transformation independently on each cell
     or __call__ if you prefer your own logic. See corresponding docstring for informations.
+
+    Disabled by default and can be enabled via the config by
+        'c.YourTransformerName.enabled = True'
     """
     
     enabled = Bool(False, config=True)
 
     def __init__(self, **kw):
         """
         Public constructor
         
         Parameters
         ----------
         config : Config
             Configuration file structure
         **kw : misc
             Additional arguments
         """
         
         super(ConfigurableTransformer, self).__init__(**kw)
 
        
     def __call__(self, nb, resources):
+        if self.enabled:
         return self.call(nb,resources)
+        else:
+            return nb, resources
+
 
     def call(self, nb, resources):
         """
         Transformation to apply on each notebook.
         
         You should return modified nb, resources.
         If you wish to apply your transform on each cell, you might want to 
         overwrite transform_cell method instead.
         
         Parameters
         ----------
         nb : NotebookNode
             Notebook being converted
         resources : dictionary
             Additional resources used in the conversion process.  Allows
             transformers to pass variables into the Jinja engine.
         """
         try :
             for worksheet in nb.worksheets :
                 for index, cell in enumerate(worksheet.cells):
                     worksheet.cells[index], resources = self.transform_cell(cell, resources, index)
             return nb, resources
         except NotImplementedError:
             raise NotImplementedError('should be implemented by subclass')
 
 
     def transform_cell(self, cell, resources, index):
         """
         Overwrite if you want to apply a transformation on each cell.  You 
         should return modified cell and resource dictionary.
         
         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
         """
 
         raise NotImplementedError('should be implemented by subclass')
         return cell, resources
 

IPython/nbconvert/transformers/convertfigures.py

@@ -1,77 +1,77
 """Module containing a transformer that converts outputs in the notebook from 
 one format to another.
 """
 #-----------------------------------------------------------------------------
 # 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.
 #-----------------------------------------------------------------------------
 
 #TODO: Come after extract
 
 #-----------------------------------------------------------------------------
 # Imports
 #-----------------------------------------------------------------------------
 
-from .activatable import ActivatableTransformer
+from .base import ConfigurableTransformer
 
 #-----------------------------------------------------------------------------
 # Classes
 #-----------------------------------------------------------------------------
 
-class ConvertFiguresTransformer(ActivatableTransformer):
+class ConvertFiguresTransformer(ConfigurableTransformer):
     """
     Converts all of the outputs in a notebook from one format to another.
     """
 
 
     def __init__(self, from_formats, to_format, **kw):
         """
         Public constructor
         
         Parameters
         ----------
         from_formats : list [of string]
             Formats that the converter can convert from
         to_format : string
             Format that the converter converts to
         config : Config
             Configuration file structure
         **kw : misc
             Additional arguments
         """
         super(ConvertFiguresTransformer, self).__init__(**kw)
 
         #TODO: Configurable, singular
         self._from_formats = from_formats
         self._to_format = to_format
 
 
     def convert_figure(self, data_format, data):
         raise NotImplementedError()
 
 
     def transform_cell(self, cell, resources, cell_index):
         """
         Apply a transformation on each cell,
         
         See base.py
         """
 
         #Loop through all of the datatypes of the outputs in the cell.
         for index, cell_out in enumerate(cell.get('outputs', [])):
             for data_type, data in cell_out.items():
                 self._convert_figure(cell_out, data_type, data)
         return cell, resources
 
 
     def _convert_figure(self, cell_out, data_type, data):
         """
         Convert a figure and output the results to the cell output
         """
 
         if not self._to_format in cell_out:
             if data_type in self._from_formats:
                 cell_out[self._to_format] = self.convert_figure(data_type, data)

IPython/nbconvert/transformers/csshtmlheader.py

@@ -1,106 +1,106
 """Module that pre-processes the notebook for export to HTML.
 """
 #-----------------------------------------------------------------------------
 # 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
 #-----------------------------------------------------------------------------
 
 import os
 import io
 
 from pygments.formatters import HtmlFormatter
         
 from IPython.utils import path
 
-from .activatable import ActivatableTransformer
+from .base import ConfigurableTransformer
 
 from IPython.utils.traitlets import Unicode
         
 #-----------------------------------------------------------------------------
 # Classes and functions
 #-----------------------------------------------------------------------------
 
-class CSSHTMLHeaderTransformer(ActivatableTransformer):
+class CSSHTMLHeaderTransformer(ConfigurableTransformer):
     """
     Transformer used to pre-process notebook for HTML output.  Adds IPython notebook
     front-end CSS and Pygments CSS to HTML output.
     """
 
     header = []
 
     highlight_class = Unicode('.highlight', config=True,
                               help="CSS highlight class identifier")
 
     def __init__(self, config=None, **kw):
         """
         Public constructor
         
         Parameters
         ----------
         config : Config
             Configuration file structure
         **kw : misc
             Additional arguments
         """
         
         super(CSSHTMLHeaderTransformer, self).__init__(config=config, **kw)
 
         if self.enabled :
             self._regen_header()
 
 
     def __call__(self, nb, resources):
         """Fetch and add CSS to the resource dictionary
 
         Fetch CSS from IPython and Pygments to add at the beginning
         of the html files.  Add this css in resources in the 
         "inlining.css" key
         
         Parameters
         ----------
         nb : NotebookNode
             Notebook being converted
         resources : dictionary
             Additional resources used in the conversion process.  Allows
             transformers to pass variables into the Jinja engine.
         """
         
         resources['inlining'] = {}
         resources['inlining']['css'] = self.header
         
         return nb, resources
 
 
     def _regen_header(self):
         """ 
         Fills self.header with lines of CSS extracted from IPython 
         and Pygments.
         """
         
         #Clear existing header.
         header = []
         
         #Construct path to IPy CSS
         sheet_filename = os.path.join(path.get_ipython_package_dir(), 
             'html', 'static', 'style', 'style.min.css')
         
         #Load style CSS file.
         with io.open(sheet_filename, encoding='utf-8') as file:
             file_text = file.read()
             header.append(file_text)
 
         #Add pygments CSS
         formatter = HtmlFormatter()
         pygments_css = formatter.get_style_defs(self.highlight_class)
         header.append(pygments_css)
 
         #Set header        
         self.header = header
 

IPython/nbconvert/transformers/extractfigure.py

@@ -1,91 +1,91
 """Module containing a transformer that extracts all of the figures from the
 notebook file.  The extracted figures are returned in the 'resources' dictionary.
 """
 #-----------------------------------------------------------------------------
 # 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
 #-----------------------------------------------------------------------------
 
 import sys
 from IPython.utils.traitlets import Dict, Unicode
-from .activatable import ActivatableTransformer
+from .base import ConfigurableTransformer
 
 #-----------------------------------------------------------------------------
 # Classes
 #-----------------------------------------------------------------------------
 
-class ExtractFigureTransformer(ActivatableTransformer):
+class ExtractFigureTransformer(ConfigurableTransformer):
     """
     Extracts all of the figures from the notebook file.  The extracted 
     figures are returned in the 'resources' dictionary.
     """
 
 
     figure_filename_template = Unicode(
         "{unique_key}_{cell_index}_{index}.{extension}", config=True)
 
 
     def transform_cell(self, cell, resources, cell_index):
         """
         Apply a transformation on each cell,
         
         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.
         cell_index : int
             Index of the cell being processed (see base.py)
         """
 
         #Get the unique key from the resource dict if it exists.  If it does not 
         #exist, use 'figure' as the default.
         unique_key = resources.get('unique_key', 'figure')
         
         #Make sure figures key exists
         if not 'figures' in resources:
             resources['figures'] = {}
             
         #Loop through all of the outputs in the cell
         for index, out in enumerate(cell.get('outputs', [])):
 
             #Get the output in data formats that the template is interested in.
             for out_type in self.display_data_priority:
                 if out.hasattr(out_type):
                     data = out[out_type]
 
                     #Binary files are base64-encoded, SVG is already XML
                     if out_type in ('png', 'jpg', 'pdf'):
                         data = data.decode('base64')
                     elif sys.platform == 'win32':
                         data = data.replace('\n', '\r\n').encode("UTF-8")
                     else:
                         data = data.encode("UTF-8")
                     
                     #Build a figure name
                     figure_name = self.figure_filename_template.format( 
                                     unique_key=unique_key,
                                     cell_index=cell_index,
                                     index=index,
                                     extension=out_type)
 
                     #On the cell, make the figure available via 
                     #   cell.outputs[i].svg_filename  ... etc (svg in example)
                     # Where
                     #   cell.outputs[i].svg  contains the data
                     out[out_type + '_filename'] = figure_name
 
                     #In the resources, make the figure available via
                     #   resources['figures']['filename'] = data
                     resources['figures'][figure_name] = data
 
         return cell, resources

IPython/nbconvert/transformers/latex.py

@@ -1,53 +1,53
 """Module that allows latex output notebooks to be conditioned before
 they are converted.
 """
 #-----------------------------------------------------------------------------
 # 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
 
 # Our own imports
 # Needed to override transformer
-from .activatable import (ActivatableTransformer)
+from .base import (ConfigurableTransformer)
 from IPython.nbconvert import filters
 
 #-----------------------------------------------------------------------------
 # Classes
 #-----------------------------------------------------------------------------
 
-class LatexTransformer(ActivatableTransformer):
+class LatexTransformer(ConfigurableTransformer):
     """
     Converter for latex destined documents.
     """
 
     def transform_cell(self, cell, resources, index):
         """
         Apply a transformation on each cell,
         
         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
             Modified index of the cell being processed (see base.py)
         """
         
         #If the cell is a markdown cell, preprocess the ampersands used to
         #remove the space between them and their contents.  Latex will complain
         #if spaces exist between the ampersands and the math content.  
         #See filters.latex.rm_math_space for more information.
         if hasattr(cell, "source") and cell.cell_type == "markdown":
             cell.source = filters.rm_math_space(cell.source)
         return cell, resources

IPython/nbconvert/transformers/sphinx.py

@@ -1,264 +1,264
 """Module that allows custom Sphinx parameters to be set on the notebook and
 on the 'other' object passed into Jinja.  Called prior to Jinja conversion
 process.
 """
 #-----------------------------------------------------------------------------
 # 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
 # Used to find Sphinx package location
 import sphinx
 import os.path
 
 # Used to set the default date to today's date 
 from datetime import date 
 
 # Third-party imports
 # Needed for Pygments latex definitions.
 from pygments.formatters import LatexFormatter
 
 # Our own imports
 # Configurable traitlets
 from IPython.utils.traitlets import Unicode, Bool
 
 # Needed to override transformer
-from .activatable import (ActivatableTransformer) #TODO
+from .base import (ConfigurableTransformer)
 
 from IPython.nbconvert.utils import console  
 
 #-----------------------------------------------------------------------------
 # Classes and functions
 #-----------------------------------------------------------------------------
 
-class SphinxTransformer(ActivatableTransformer):
+class SphinxTransformer(ConfigurableTransformer):
     """
     Sphinx utility transformer.
 
     This transformer is used to set variables needed by the latex to build
     Sphinx stylized templates.
     """
     
     interactive = Bool(False, config=True, help="""
         Allows you to define whether or not the Sphinx exporter will prompt
         you for input during the conversion process.  If this is set to false,
         the author, version, release, date, and chapter_style traits should
         be set.
         """)
     
     author = Unicode("Unknown Author", config=True, help="Author name")
     
     version = Unicode("", config=True, help="""
         Version number
         You can leave this blank if you do not want to render a version number.
         Example: "1.0.0"
         """)
     
     release = Unicode("", config=True, help="""
         Release name
         You can leave this blank if you do not want to render a release name.
         Example: "Rough Draft"
         """)
     
     publish_date = Unicode("", config=True, help="""
         Publish date
         This is the date to render on the document as the publish date.
         Leave this blank to default to todays date.  
         Example: "June 12, 1990"
         """)
     
     chapter_style = Unicode("Bjarne", config=True, help="""
         Sphinx chapter style
         This is the style to use for the chapter headers in the document.
         You may choose one of the following:
             "Bjarne"    (default)
             "Lenny"
             "Glenn"
             "Conny"
             "Rejne"
             "Sonny"    (used for international documents)
         """)
     
     output_style = Unicode("notebook", config=True, help="""
         Nbconvert Ipython
         notebook input/output formatting style.
         You may choose one of the following:
             "simple     (recommended for long code segments)"
             "notebook"  (default)
         """)
     
     center_output = Bool(False, config=True, help="""
         Optional attempt to center all output.  If this is false, no additional
         formatting is applied.
         """)
     
     use_headers = Bool(True, config=True, help="""
         Whether not a header should be added to the document.
         """)
     
     #Allow the user to override the title of the notebook (useful for
     #fancy document titles that the file system doesn't support.)
     overridetitle = Unicode("", config=True, help="")
 
     
     def call(self, nb, resources):
         """
         Sphinx transformation to apply on each notebook.
         
         Parameters
         ----------
         nb : NotebookNode
             Notebook being converted
         resources : dictionary
             Additional resources used in the conversion process.  Allows
             transformers to pass variables into the Jinja engine.
         """
          
         # TODO: Add versatile method of additional notebook metadata.  Include
         #       handling of multiple files.  For now use a temporay namespace,
         #       '_draft' to signify that this needs to change.
         if not "sphinx" in resources:
             resources["sphinx"] = {}
 
         if self.interactive:
             
             # Prompt the user for additional meta data that doesn't exist currently
             # but would be usefull for Sphinx.
             resources["sphinx"]["author"] = self._prompt_author()
             resources["sphinx"]["version"] = self._prompt_version()
             resources["sphinx"]["release"] = self._prompt_release()
             resources["sphinx"]["date"] = self._prompt_date()
             
             # Prompt the user for the document style.
             resources["sphinx"]["chapterstyle"] = self._prompt_chapter_title_style()
             resources["sphinx"]["outputstyle"] = self._prompt_output_style()
             
             # Small options
             resources["sphinx"]["centeroutput"] = console.prompt_boolean("Do you want to center the output? (false)", False)
             resources["sphinx"]["header"] = console.prompt_boolean("Should a Sphinx document header be used? (true)", True)
         else:
             
             # Try to use the traitlets.
             resources["sphinx"]["author"] = self.author
             resources["sphinx"]["version"] = self.version
             resources["sphinx"]["release"] = self.release
             
             # Use todays date if none is provided.
             if self.publish_date:
                 resources["sphinx"]["date"] = self.publish_date
             elif len(resources['metadata']['modified_date'].strip()) == 0:
                 resources["sphinx"]["date"] = date.today().strftime("%B %-d, %Y")
             else:
                 resources["sphinx"]["date"] = resources['metadata']['modified_date']
             
             # Sphinx traitlets.
             resources["sphinx"]["chapterstyle"] = self.chapter_style
             resources["sphinx"]["outputstyle"] = self.output_style
             resources["sphinx"]["centeroutput"] = self.center_output
             resources["sphinx"]["header"] = self.use_headers
             
         # Find and pass in the path to the Sphinx dependencies.
         resources["sphinx"]["texinputs"] = os.path.realpath(os.path.join(sphinx.__file__, "..", "texinputs"))
         
         # Generate Pygments definitions for Latex 
         resources["sphinx"]["pygment_definitions"] = self._generate_pygments_latex_def()
         
         if not (self.overridetitle == None or len(self.overridetitle.strip()) == 0):
             resources['metadata']['name'] = self.overridetitle
         
         # End
         return nb, resources 
     
     
     def _generate_pygments_latex_def(self):
         """
         Generate the pygments latex definitions that allows pygments
         to work in latex.
         """
         
         return LatexFormatter().get_style_defs()       
     
     
     def _prompt_author(self):
         """
         Prompt the user to input an Author name
         """
         return  console.input("Author name: ")
     
     
     def _prompt_version(self):
         """
         prompt the user to enter a version number
         """
         return  console.input("Version (ie ""1.0.0""): ")
     
     
     def _prompt_release(self):
         """
         Prompt the user to input a release name
         """
         
         return  console.input("Release Name (ie ""Rough draft""): ")
     
     
     def _prompt_date(self, resources):
         """
         Prompt the user to enter a date
         """
         
         if resources['metadata']['modified_date']:
             default_date = resources['metadata']['modified_date']
         else:
             default_date = date.today().strftime("%B %-d, %Y")
             
         user_date = console.input("Date (deafults to \"" + default_date + "\"): ")
         if len(user_date.strip()) == 0:
             user_date = default_date
         return user_date
     
     
     def _prompt_output_style(self):
         """
         Prompts the user to pick an IPython output style.
         """
         
         # Dictionary of available output styles
         styles = {1: "simple",
                   2: "notebook"}
         
         #Append comments to the menu when displaying it to the user.
         comments = {1: "(recommended for long code segments)",
                     2: "(default)"}
         
         return console.prompt_dictionary(styles, default_style=2, menu_comments=comments)
     
     
     def _prompt_chapter_title_style(self):
         """
         Prompts the user to pick a Sphinx chapter style
         """
         
         # Dictionary of available Sphinx styles
         styles = {1: "Bjarne",
                   2: "Lenny",
                   3: "Glenn",
                   4: "Conny",
                   5: "Rejne",
                   6: "Sonny"}
         
         #Append comments to the menu when displaying it to the user.
         comments = {1: "(default)",
                     6: "(for international documents)"}
         
         return console.prompt_dictionary(styles, menu_comments=comments)