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+# $Id: __init__.py 9502 2023-12-14 22:39:08Z 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))
+        self.document.reporter.detach_observer(
+            self.document.note_transform_message)