Merge pull request #179 from Carreau/global-configurable

Restaure Global configurable

nbconvert.py

@@ -1,215 +1,217 b''
 #!/usr/bin/env python
 """NBConvert is a utility for conversion of IPYNB files.
 
 Commandline interface for the NBConvert conversion utility.  Read the
 readme.rst for usage information
 """
 #-----------------------------------------------------------------------------
 #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
 #-----------------------------------------------------------------------------
 
 #Stdlib imports
 from __future__ import print_function
 import sys
 import io
 import os
 
 #From IPython
 #All the stuff needed for the configurable things
 from IPython.config.application import Application
 from IPython.utils.traitlets import (Bool)
 
 #Local imports
 from nbconvert.exporters.export import export_by_name
 from nbconvert.exporters.exporter import Exporter
 from nbconvert.transformers import extractfigure
+from nbconvert.utils.config import GlobalConfigurable
 
 #-----------------------------------------------------------------------------
 #Globals and constants
 #-----------------------------------------------------------------------------
 
 #'Keys in resources' user prompt.
 KEYS_PROMPT_HEAD = "====================== Keys in Resources =================================="
 KEYS_PROMPT_BODY = """
 ===========================================================================
 You are responsible for writting these files into the appropriate 
 directorie(s) if need be.  If you do not want to see this message, enable
 the 'write' (boolean) flag of the converter.
 ===========================================================================
 """
 
 #-----------------------------------------------------------------------------
 #Classes and functions
 #-----------------------------------------------------------------------------
 
 class NbConvertApp(Application):
     """Application used to convert to and from notebook file type (*.ipynb)"""
 
     stdout = Bool(
         False, config=True,
         help="""Whether to print the converted IPYNB file to stdout
         use full do diff files without actually writing a new file"""
         )
 
     write = Bool(
         True, config=True,
         help="""Should the converted notebook file be written to disk
         along with potential extracted resources."""
         )
 
     aliases = {
              'stdout':'NbConvertApp.stdout',
              'write':'NbConvertApp.write',
              }
 
     flags = {}
 
     flags['stdout'] = (
         {'NbConvertApp' : {'stdout' : True}},
     """Print converted file to stdout, equivalent to --stdout=True
     """
     )
 
     flags['no-write'] = (
         {'NbConvertApp' : {'write' : True}},
     """Do not write to disk, eauivalent to --write=False
     """
     )
 
 
     def __init__(self, **kwargs):
         """Public constructor"""
 
         #Call base class
         super(NbConvertApp, self).__init__(**kwargs)
 
         #Register class here to have help with help all
         self.classes.insert(0, Exporter)
+        self.classes.insert(0, GlobalConfigurable)
 
 
     def start(self, argv=None):
         """Entrypoint of NbConvert application.
         
         Parameters
         ----------
         argv : list
             Commandline arguments
         """
         
         #Parse the commandline options.
         self.parse_command_line(argv)
 
         #Call base
         super(NbConvertApp, self).start()
 
         #The last arguments in list will be used by nbconvert
         if len(self.extra_args) is not 3:
             print( "Wrong number of arguments, use --help flag for usage", file=sys.stderr)
             sys.exit(-1)
         export_type = (self.extra_args)[1]
         ipynb_file = (self.extra_args)[2]
         
         #Export
         return_value = export_by_name(export_type, ipynb_file)
         if return_value is None:
             print("Error: '%s' template not found." % export_type)
             return
         else:
             (output, resources, exporter) = return_value 
         
         #TODO: Allow user to set output directory and file. 
         destination_filename = None
         destination_directory = None
         if self.write:
                 
             #Get the file name without the '.ipynb' (6 chars) extension and then
             #remove any addition periods and spaces. The resulting name will
             #be used to create the directory that the files will be exported
             #into.
             out_root = ipynb_file[:-6].replace('.', '_').replace(' ', '_')
             destination_filename = os.path.join(out_root+'.'+exporter.file_extension)
             
             destination_directory = out_root+'_files'
             if not os.path.exists(destination_directory):
                 os.mkdir(destination_directory)
                 
         #Write the results
         if self.stdout or not (destination_filename is None and destination_directory is None):
             self._write_results(output, resources, destination_filename, destination_directory)
 
 
     def _write_results(self, output, resources, destination_filename=None, destination_directory=None):
         """Output the conversion results to the console and/or filesystem
         
         Parameters
         ----------
         output : str
             Output of conversion
         resources : dictionary
             Additional input/output used by the transformers.  For
             example, the ExtractFigure transformer outputs the
             figures it extracts into this dictionary.  This method
             relies on the figures being in this dictionary when
             attempting to write the figures to the file system.
         destination_filename : str, Optional
             Filename to write output into.  If None, output is not 
             written to a file.
         destination_directory : str, Optional 
             Directory to write notebook data (i.e. figures) to.  If
             None, figures are not written to the file system.
         """
         
         if self.stdout:
             print(output.encode('utf-8'))
 
         #Write file output from conversion.
         if not destination_filename is None:
             with io.open(destination_filename, 'w') as f:
                 f.write(output)
 
         #Get the key names used by the extract figure transformer
         figures_key = extractfigure.FIGURES_KEY
         binary_key = extractfigure.BINARY_KEY
         text_key = extractfigure.TEXT_KEY
         
         #Output any associate figures into the same "root" directory.
         binkeys = resources.get(figures_key, {}).get(binary_key,{}).keys()
         textkeys = resources.get(figures_key, {}).get(text_key,{}).keys()
         if binkeys or textkeys :
             if not destination_directory is None:
                 for key in binkeys:
                     with io.open(os.path.join(destination_directory, key), 'wb') as f:
                         f.write(resources[figures_key][binary_key][key])
                 for key in textkeys:
                     with io.open(os.path.join(destination_directory, key), 'w') as f:
                         f.write(resources[figures_key][text_key][key])
 
             #Figures that weren't exported which will need to be created by the
             #user.  Tell the user what figures these are.
             if self.stdout:
                 print(KEYS_PROMPT_HEAD, file=sys.stderr)
                 print(resources[figures_key].keys(), file=sys.stderr)
                 print(KEYS_PROMPT_BODY , file=sys.stderr)
 
 #-----------------------------------------------------------------------------
 #Script main
 #-----------------------------------------------------------------------------
 
 def main():
     """Application entry point"""
 
     app = NbConvertApp.instance()
     app.description = __doc__
     app.start(argv=sys.argv)
 
 #Check to see if python is calling this file directly.
 if __name__ == '__main__':
     main()

nbconvert/filters/datatypefilter.py

@@ -1,31 +1,33 b''
 """Filter used to select the first preferred output format available.
 
 The filter contained in the file allows the converter templates to select
 the output format that is most valuable to the active export format.  The
 value of the different formats is set via 
 GlobalConfigurable.display_data_priority
 """
 #-----------------------------------------------------------------------------
 # 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.
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # Classes and functions
 #-----------------------------------------------------------------------------
 
-class DataTypeFilter(object):
+from ..utils.config import GlobalConfigurable
+
+class DataTypeFilter(GlobalConfigurable):
     """ Returns the preferred display format """
 
     display_data_priority = ['html', 'pdf', 'svg', 'latex', 'png', 'jpg', 'jpeg' , 'text']
 
     def __call__(self, output):
         """ Return the first available format in the priority """
 
         for fmt in self.display_data_priority:
             if fmt in output:
                 return [fmt]
-        return []
  No newline at end of file
+        return []

nbconvert/transformers/base.py

@@ -1,101 +1,102 b''
 """
 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 __future__ import print_function, absolute_import
 
 from IPython.config.configurable import Configurable
+from ..utils.config import GlobalConfigurable
 
 #-----------------------------------------------------------------------------
 # Classes and Functions
 #-----------------------------------------------------------------------------
 
-class ConfigurableTransformer(Configurable):
+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 cell_transform to apply a transformation independently on each cell
     or __call__ if you prefer your own logic. See orresponding docstring for informations.
     """
     
     def __init__(self, config=None, **kw):
         """
         Public constructor
         
         Parameters
         ----------
         config : Config
             Configuration file structure
         **kw : misc
             Additional arguments
         """
         
         super(ConfigurableTransformer, self).__init__(config=config, **kw)
 
        
     def __call__(self, nb, resources):
         return self.call(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 cell_transform 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.cell_transform(cell, resources, index)
             return nb, resources
         except NotImplementedError:
             raise NotImplementedError('should be implemented by subclass')
 
 
     def cell_transform(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