Source code for docutils.transforms

# $Id: __init__.py 6433 2010-09-28 08:21:25Z milde $
# Authors: David Goodger <goodger@python.org>; Ueli Schlaepfer
# Copyright: This module has been placed in the public domain.

"""
This package contains modules for standard tree transforms available
to Docutils components. Tree transforms serve a variety of purposes:

- To tie up certain syntax-specific "loose ends" that remain after the
  initial parsing of the input plaintext. These transforms are used to
  supplement a limited syntax.

- To automate the internal linking of the document tree (hyperlink
  references, footnote references, etc.).

- To extract useful information from the document tree. These
  transforms may be used to construct (for example) indexes and tables
  of contents.

Each transform is an optional step that a Docutils component may
choose to perform on the parsed document.
"""

__docformat__ = 'reStructuredText'


from docutils import languages, ApplicationError, TransformSpec


[docs]class TransformError(ApplicationError): pass
[docs]class Transform: """ Docutils transform component abstract base class. """ default_priority = None """Numerical priority of this transform, 0 through 999 (override).""" def __init__(self, document, startnode=None): """ Initial setup for in-place document transforms. """ self.document = document """The document tree to transform.""" self.startnode = startnode """Node from which to begin the transform. For many transforms which apply to the document as a whole, `startnode` is not set (i.e. its value is `None`).""" self.language = languages.get_language( document.settings.language_code, document.reporter) """Language module local to this document."""
[docs] def apply(self, **kwargs): """Override to apply the transform to the document tree.""" raise NotImplementedError('subclass must override this method')
[docs]class Transformer(TransformSpec): """ Stores transforms (`Transform` classes) and applies them to document trees. Also keeps track of components by component type name. """ def __init__(self, document): self.transforms = [] """List of transforms to apply. Each item is a 3-tuple: ``(priority string, transform class, pending node or None)``.""" self.unknown_reference_resolvers = [] """List of hook functions which assist in resolving references""" self.document = document """The `nodes.document` object this Transformer is attached to.""" self.applied = [] """Transforms already applied, in order.""" self.sorted = 0 """Boolean: is `self.tranforms` sorted?""" self.components = {} """Mapping of component type name to component object. Set by `self.populate_from_components()`.""" self.serialno = 0 """Internal serial number to keep track of the add order of transforms."""
[docs] def add_transform(self, transform_class, priority=None, **kwargs): """ Store a single transform. Use `priority` to override the default. `kwargs` is a dictionary whose contents are passed as keyword arguments to the `apply` method of the transform. This can be used to pass application-specific data to the transform instance. """ if priority is None: priority = transform_class.default_priority priority_string = self.get_priority_string(priority) self.transforms.append( (priority_string, transform_class, None, kwargs)) self.sorted = 0
[docs] def add_transforms(self, transform_list): """Store multiple transforms, with default priorities.""" for transform_class in transform_list: priority_string = self.get_priority_string( transform_class.default_priority) self.transforms.append( (priority_string, transform_class, None, {})) self.sorted = 0
[docs] def add_pending(self, pending, priority=None): """Store a transform with an associated `pending` node.""" transform_class = pending.transform if priority is None: priority = transform_class.default_priority priority_string = self.get_priority_string(priority) self.transforms.append( (priority_string, transform_class, pending, {})) self.sorted = 0
[docs] def get_priority_string(self, priority): """ Return a string, `priority` combined with `self.serialno`. This ensures FIFO order on transforms with identical priority. """ self.serialno += 1 return '%03d-%03d' % (priority, self.serialno)
[docs] def populate_from_components(self, components): """ Store each component's default transforms, with default priorities. Also, store components by type name in a mapping for later lookup. """ for component in components: if component is None: continue self.add_transforms(component.get_transforms()) self.components[component.component_type] = component self.sorted = 0 # Set up all of the reference resolvers for this transformer. Each # component of this transformer is able to register its own helper # functions to help resolve references. unknown_reference_resolvers = [] for i in components: unknown_reference_resolvers.extend(i.unknown_reference_resolvers) decorated_list = [(f.priority, f) for f in unknown_reference_resolvers] decorated_list.sort() self.unknown_reference_resolvers.extend([f[1] for f in decorated_list])
[docs] def apply_transforms(self): """Apply all of the stored transforms, in priority order.""" self.document.reporter.attach_observer( self.document.note_transform_message) while self.transforms: if not self.sorted: # Unsorted initially, and whenever a transform is added. self.transforms.sort() self.transforms.reverse() self.sorted = 1 priority, transform_class, pending, kwargs = self.transforms.pop() transform = transform_class(self.document, startnode=pending) transform.apply(**kwargs) self.applied.append((priority, transform_class, pending, kwargs))