diff env/lib/python3.9/site-packages/docutils/transforms/__init__.py @ 0:4f3585e2f14b draft default tip

"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"

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+++ b/env/lib/python3.9/site-packages/docutils/transforms/__init__.py	Mon Mar 22 18:12:50 2021 +0000
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+# $Id: __init__.py 8358 2019-08-26 16:45:09Z milde $
+# Authors: David Goodger <[e-mail]>; 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(object):
+
+    """
+    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 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 = 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 = sorted((f.priority, f) for f in unknown_reference_resolvers)
+        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))