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# $Id: __init__.py 9320 2023-01-17 15:40:15Z 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):
    """
    Store "transforms" and apply them to the document tree.

    Collect lists of `Transform` instances and "unknown_reference_resolvers"
    from Docutils components (`TransformSpec` instances).
    Apply collected "transforms" to the document tree.

    Also keeps track of components by component type name.

    https://docutils.sourceforge.io/docs/peps/pep-0258.html#transformer
    """

    def __init__(self, document):
        self.transforms = []
        """List of transforms to apply.  Each item is a 4-tuple:
        ``(priority string, transform class, pending node or None, kwargs)``.
        """

        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 = False
        """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 = False

    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 = False

    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 = False

    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 and reference resolvers

        Transforms are stored with default priorities for later sorting.
        "Unknown reference resolvers" are sorted and stored.
        Components that don't inherit from `TransformSpec` are ignored.

        Also, store components by type name in a mapping for later lookup.
        """
        resolvers = []
        for component in components:
            if not isinstance(component, TransformSpec):
                continue
            self.add_transforms(component.get_transforms())
            self.components[component.component_type] = component
            resolvers.extend(component.unknown_reference_resolvers)
        self.sorted = False  # sort transform list in self.apply_transforms()

        # Sort and add helper functions to help resolve unknown references.
        def keyfun(f):
            return f.priority
        resolvers.sort(key=keyfun)
        self.unknown_reference_resolvers += resolvers

    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
                # (transforms may add other transforms).
                self.transforms.sort(reverse=True)
                self.sorted = True
            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))

Filemanager

Name Type Size Permission Actions
__pycache__ Folder 0755
__init__.py File 6.71 KB 0644
components.py File 2.1 KB 0644
frontmatter.py File 20.87 KB 0644
misc.py File 4.76 KB 0644
parts.py File 6.75 KB 0644
peps.py File 10.85 KB 0644
references.py File 35.96 KB 0644
universal.py File 12.25 KB 0644
writer_aux.py File 2.99 KB 0644