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# $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
class TransformError(ApplicationError): pass
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."""
def apply(self, **kwargs):
"""Override to apply the transform to the document tree."""
raise NotImplementedError('subclass must override this method')
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."""
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
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
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
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)
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])
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))