path: root/.venv/lib/python3.12/site-packages/lark/parsers/earley_forest.py

""""This module implements an SPPF implementation

This is used as the primary output mechanism for the Earley parser
in order to store complex ambiguities.

Full reference and more details is here:
http://www.bramvandersanden.com/post/2014/06/shared-packed-parse-forest/
"""

from random import randint
from math import isinf
from collections import deque
from operator import attrgetter
from importlib import import_module
from functools import partial

from ..parse_tree_builder import AmbiguousIntermediateExpander
from ..visitors import Discard
from ..lexer import Token
from ..utils import logger
from ..tree import Tree

class ForestNode(object):
    pass

class SymbolNode(ForestNode):
    """
    A Symbol Node represents a symbol (or Intermediate LR0).

    Symbol nodes are keyed by the symbol (s). For intermediate nodes
    s will be an LR0, stored as a tuple of (rule, ptr). For completed symbol
    nodes, s will be a string representing the non-terminal origin (i.e.
    the left hand side of the rule).

    The children of a Symbol or Intermediate Node will always be Packed Nodes;
    with each Packed Node child representing a single derivation of a production.

    Hence a Symbol Node with a single child is unambiguous.

    :ivar s: A Symbol, or a tuple of (rule, ptr) for an intermediate node.
    :ivar start: The index of the start of the substring matched by this
        symbol (inclusive).
    :ivar end: The index of the end of the substring matched by this
        symbol (exclusive).
    :ivar is_intermediate: True if this node is an intermediate node.
    :ivar priority: The priority of the node's symbol.
    """
    __slots__ = ('s', 'start', 'end', '_children', 'paths', 'paths_loaded', 'priority', 'is_intermediate', '_hash')
    def __init__(self, s, start, end):
        self.s = s
        self.start = start
        self.end = end
        self._children = set()
        self.paths = set()
        self.paths_loaded = False

        ### We use inf here as it can be safely negated without resorting to conditionals,
        #   unlike None or float('NaN'), and sorts appropriately.
        self.priority = float('-inf')
        self.is_intermediate = isinstance(s, tuple)
        self._hash = hash((self.s, self.start, self.end))

    def add_family(self, lr0, rule, start, left, right):
        self._children.add(PackedNode(self, lr0, rule, start, left, right))

    def add_path(self, transitive, node):
        self.paths.add((transitive, node))

    def load_paths(self):
        for transitive, node in self.paths:
            if transitive.next_titem is not None:
                vn = SymbolNode(transitive.next_titem.s, transitive.next_titem.start, self.end)
                vn.add_path(transitive.next_titem, node)
                self.add_family(transitive.reduction.rule.origin, transitive.reduction.rule, transitive.reduction.start, transitive.reduction.node, vn)
            else:
                self.add_family(transitive.reduction.rule.origin, transitive.reduction.rule, transitive.reduction.start, transitive.reduction.node, node)
        self.paths_loaded = True

    @property
    def is_ambiguous(self):
        """Returns True if this node is ambiguous."""
        return len(self.children) > 1

    @property
    def children(self):
        """Returns a list of this node's children sorted from greatest to
        least priority."""
        if not self.paths_loaded: self.load_paths()
        return sorted(self._children, key=attrgetter('sort_key'))

    def __iter__(self):
        return iter(self._children)

    def __eq__(self, other):
        if not isinstance(other, SymbolNode):
            return False
        return self is other or (type(self.s) == type(other.s) and self.s == other.s and self.start == other.start and self.end is other.end)

    def __hash__(self):
        return self._hash

    def __repr__(self):
        if self.is_intermediate:
            rule = self.s[0]
            ptr = self.s[1]
            before = ( expansion.name for expansion in rule.expansion[:ptr] )
            after = ( expansion.name for expansion in rule.expansion[ptr:] )
            symbol = "{} ::= {}* {}".format(rule.origin.name, ' '.join(before), ' '.join(after))
        else:
            symbol = self.s.name
        return "({}, {}, {}, {})".format(symbol, self.start, self.end, self.priority)

class PackedNode(ForestNode):
    """
    A Packed Node represents a single derivation in a symbol node.

    :ivar rule: The rule associated with this node.
    :ivar parent: The parent of this node.
    :ivar left: The left child of this node. ``None`` if one does not exist.
    :ivar right: The right child of this node. ``None`` if one does not exist.
    :ivar priority: The priority of this node.
    """
    __slots__ = ('parent', 's', 'rule', 'start', 'left', 'right', 'priority', '_hash')
    def __init__(self, parent, s, rule, start, left, right):
        self.parent = parent
        self.s = s
        self.start = start
        self.rule = rule
        self.left = left
        self.right = right
        self.priority = float('-inf')
        self._hash = hash((self.left, self.right))

    @property
    def is_empty(self):
        return self.left is None and self.right is None

    @property
    def sort_key(self):
        """
        Used to sort PackedNode children of SymbolNodes.
        A SymbolNode has multiple PackedNodes if it matched
        ambiguously. Hence, we use the sort order to identify
        the order in which ambiguous children should be considered.
        """
        return self.is_empty, -self.priority, self.rule.order

    @property
    def children(self):
        """Returns a list of this node's children."""
        return [x for x in [self.left, self.right] if x is not None]

    def __iter__(self):
        yield self.left
        yield self.right

    def __eq__(self, other):
        if not isinstance(other, PackedNode):
            return False
        return self is other or (self.left == other.left and self.right == other.right)

    def __hash__(self):
        return self._hash

    def __repr__(self):
        if isinstance(self.s, tuple):
            rule = self.s[0]
            ptr = self.s[1]
            before = ( expansion.name for expansion in rule.expansion[:ptr] )
            after = ( expansion.name for expansion in rule.expansion[ptr:] )
            symbol = "{} ::= {}* {}".format(rule.origin.name, ' '.join(before), ' '.join(after))
        else:
            symbol = self.s.name
        return "({}, {}, {}, {})".format(symbol, self.start, self.priority, self.rule.order)

class ForestVisitor(object):
    """
    An abstract base class for building forest visitors.

    This class performs a controllable depth-first walk of an SPPF.
    The visitor will not enter cycles and will backtrack if one is encountered.
    Subclasses are notified of cycles through the ``on_cycle`` method.

    Behavior for visit events is defined by overriding the
    ``visit*node*`` functions.

    The walk is controlled by the return values of the ``visit*node_in``
    methods. Returning a node(s) will schedule them to be visited. The visitor
    will begin to backtrack if no nodes are returned.

    :ivar single_visit: If ``True``, non-Token nodes will only be visited once.
    """

    def __init__(self, single_visit=False):
        self.single_visit = single_visit

    def visit_token_node(self, node):
        """Called when a ``Token`` is visited. ``Token`` nodes are always leaves."""
        pass

    def visit_symbol_node_in(self, node):
        """Called when a symbol node is visited. Nodes that are returned
        will be scheduled to be visited. If ``visit_intermediate_node_in``
        is not implemented, this function will be called for intermediate
        nodes as well."""
        pass

    def visit_symbol_node_out(self, node):
        """Called after all nodes returned from a corresponding ``visit_symbol_node_in``
        call have been visited. If ``visit_intermediate_node_out``
        is not implemented, this function will be called for intermediate
        nodes as well."""
        pass

    def visit_packed_node_in(self, node):
        """Called when a packed node is visited. Nodes that are returned
        will be scheduled to be visited. """
        pass

    def visit_packed_node_out(self, node):
        """Called after all nodes returned from a corresponding ``visit_packed_node_in``
        call have been visited."""
        pass

    def on_cycle(self, node, path):
        """Called when a cycle is encountered.

        :param node: The node that causes a cycle.
        :param path: The list of nodes being visited: nodes that have been
            entered but not exited. The first element is the root in a forest
            visit, and the last element is the node visited most recently.
            ``path`` should be treated as read-only.
        """
        pass

    def get_cycle_in_path(self, node, path):
        """A utility function for use in ``on_cycle`` to obtain a slice of
        ``path`` that only contains the nodes that make up the cycle."""
        index = len(path) - 1
        while id(path[index]) != id(node):
            index -= 1
        return path[index:]

    def visit(self, root):
        # Visiting is a list of IDs of all symbol/intermediate nodes currently in
        # the stack. It serves two purposes: to detect when we 'recurse' in and out
        # of a symbol/intermediate so that we can process both up and down. Also,
        # since the SPPF can have cycles it allows us to detect if we're trying
        # to recurse into a node that's already on the stack (infinite recursion).
        visiting = set()

        # set of all nodes that have been visited
        visited = set()

        # a list of nodes that are currently being visited
        # used for the `on_cycle` callback
        path = []

        # We do not use recursion here to walk the Forest due to the limited
        # stack size in python. Therefore input_stack is essentially our stack.
        input_stack = deque([root])

        # It is much faster to cache these as locals since they are called
        # many times in large parses.
        vpno = getattr(self, 'visit_packed_node_out')
        vpni = getattr(self, 'visit_packed_node_in')
        vsno = getattr(self, 'visit_symbol_node_out')
        vsni = getattr(self, 'visit_symbol_node_in')
        vino = getattr(self, 'visit_intermediate_node_out', vsno)
        vini = getattr(self, 'visit_intermediate_node_in', vsni)
        vtn = getattr(self, 'visit_token_node')
        oc = getattr(self, 'on_cycle')

        while input_stack:
            current = next(reversed(input_stack))
            try:
                next_node = next(current)
            except StopIteration:
                input_stack.pop()
                continue
            except TypeError:
                ### If the current object is not an iterator, pass through to Token/SymbolNode
                pass
            else:
                if next_node is None:
                    continue

                if id(next_node) in visiting:
                    oc(next_node, path)
                    continue

                input_stack.append(next_node)
                continue

            if not isinstance(current, ForestNode):
                vtn(current)
                input_stack.pop()
                continue

            current_id = id(current)
            if current_id in visiting:
                if isinstance(current, PackedNode):
                    vpno(current)
                elif current.is_intermediate:
                    vino(current)
                else:
                    vsno(current)
                input_stack.pop()
                path.pop()
                visiting.remove(current_id)
                visited.add(current_id)
            elif self.single_visit and current_id in visited:
                input_stack.pop()
            else:
                visiting.add(current_id)
                path.append(current)
                if isinstance(current, PackedNode):
                    next_node = vpni(current)
                elif current.is_intermediate:
                    next_node = vini(current)
                else:
                    next_node = vsni(current)
                if next_node is None:
                    continue

                if not isinstance(next_node, ForestNode) and \
                        not isinstance(next_node, Token):
                    next_node = iter(next_node)
                elif id(next_node) in visiting:
                    oc(next_node, path)
                    continue

                input_stack.append(next_node)

class ForestTransformer(ForestVisitor):
    """The base class for a bottom-up forest transformation. Most users will
    want to use ``TreeForestTransformer`` instead as it has a friendlier
    interface and covers most use cases.

    Transformations are applied via inheritance and overriding of the
    ``transform*node`` methods.

    ``transform_token_node`` receives a ``Token`` as an argument.
    All other methods receive the node that is being transformed and
    a list of the results of the transformations of that node's children.
    The return value of these methods are the resulting transformations.

    If ``Discard`` is raised in a node's transformation, no data from that node
    will be passed to its parent's transformation.
    """

    def __init__(self):
        super(ForestTransformer, self).__init__()
        # results of transformations
        self.data = dict()
        # used to track parent nodes
        self.node_stack = deque()

    def transform(self, root):
        """Perform a transformation on an SPPF."""
        self.node_stack.append('result')
        self.data['result'] = []
        self.visit(root)
        assert len(self.data['result']) <= 1
        if self.data['result']:
            return self.data['result'][0]

    def transform_symbol_node(self, node, data):
        """Transform a symbol node."""
        return node

    def transform_intermediate_node(self, node, data):
        """Transform an intermediate node."""
        return node

    def transform_packed_node(self, node, data):
        """Transform a packed node."""
        return node

    def transform_token_node(self, node):
        """Transform a ``Token``."""
        return node

    def visit_symbol_node_in(self, node):
        self.node_stack.append(id(node))
        self.data[id(node)] = []
        return node.children

    def visit_packed_node_in(self, node):
        self.node_stack.append(id(node))
        self.data[id(node)] = []
        return node.children

    def visit_token_node(self, node):
        try:
            transformed = self.transform_token_node(node)
        except Discard:
            pass
        else:
            self.data[self.node_stack[-1]].append(transformed)

    def visit_symbol_node_out(self, node):
        self.node_stack.pop()
        try:
            transformed = self.transform_symbol_node(node, self.data[id(node)])
        except Discard:
            pass
        else:
            self.data[self.node_stack[-1]].append(transformed)
        finally:
            del self.data[id(node)]

    def visit_intermediate_node_out(self, node):
        self.node_stack.pop()
        try:
            transformed = self.transform_intermediate_node(node, self.data[id(node)])
        except Discard:
            pass
        else:
            self.data[self.node_stack[-1]].append(transformed)
        finally:
            del self.data[id(node)]

    def visit_packed_node_out(self, node):
        self.node_stack.pop()
        try:
            transformed = self.transform_packed_node(node, self.data[id(node)])
        except Discard:
            pass
        else:
            self.data[self.node_stack[-1]].append(transformed)
        finally:
            del self.data[id(node)]

class ForestSumVisitor(ForestVisitor):
    """
    A visitor for prioritizing ambiguous parts of the Forest.

    This visitor is used when support for explicit priorities on
    rules is requested (whether normal, or invert). It walks the
    forest (or subsets thereof) and cascades properties upwards
    from the leaves.

    It would be ideal to do this during parsing, however this would
    require processing each Earley item multiple times. That's
    a big performance drawback; so running a forest walk is the
    lesser of two evils: there can be significantly more Earley
    items created during parsing than there are SPPF nodes in the
    final tree.
    """
    def __init__(self):
        super(ForestSumVisitor, self).__init__(single_visit=True)

    def visit_packed_node_in(self, node):
        yield node.left
        yield node.right

    def visit_symbol_node_in(self, node):
        return iter(node.children)

    def visit_packed_node_out(self, node):
        priority = node.rule.options.priority if not node.parent.is_intermediate and node.rule.options.priority else 0
        priority += getattr(node.right, 'priority', 0)
        priority += getattr(node.left, 'priority', 0)
        node.priority = priority

    def visit_symbol_node_out(self, node):
        node.priority = max(child.priority for child in node.children)

class PackedData():
    """Used in transformationss of packed nodes to distinguish the data
    that comes from the left child and the right child.
    """

    class _NoData():
        pass

    NO_DATA = _NoData()

    def __init__(self, node, data):
        self.left = self.NO_DATA
        self.right = self.NO_DATA
        if data:
            if node.left is not None:
                self.left = data[0]
                if len(data) > 1:
                    self.right = data[1]
            else:
                self.right = data[0]

class ForestToParseTree(ForestTransformer):
    """Used by the earley parser when ambiguity equals 'resolve' or
    'explicit'. Transforms an SPPF into an (ambiguous) parse tree.

    tree_class: The tree class to use for construction
    callbacks: A dictionary of rules to functions that output a tree
    prioritizer: A ``ForestVisitor`` that manipulates the priorities of
        ForestNodes
    resolve_ambiguity: If True, ambiguities will be resolved based on
        priorities. Otherwise, `_ambig` nodes will be in the resulting
        tree.
    use_cache: If True, the results of packed node transformations will be
        cached.
    """

    def __init__(self, tree_class=Tree, callbacks=dict(), prioritizer=ForestSumVisitor(), resolve_ambiguity=True, use_cache=True):
        super(ForestToParseTree, self).__init__()
        self.tree_class = tree_class
        self.callbacks = callbacks
        self.prioritizer = prioritizer
        self.resolve_ambiguity = resolve_ambiguity
        self._use_cache = use_cache
        self._cache = {}
        self._on_cycle_retreat = False
        self._cycle_node = None
        self._successful_visits = set()

    def visit(self, root):
        if self.prioritizer:
            self.prioritizer.visit(root)
        super(ForestToParseTree, self).visit(root)
        self._cache = {}

    def on_cycle(self, node, path):
        logger.debug("Cycle encountered in the SPPF at node: %s. "
                "As infinite ambiguities cannot be represented in a tree, "
                "this family of derivations will be discarded.", node)
        self._cycle_node = node
        self._on_cycle_retreat = True

    def _check_cycle(self, node):
        if self._on_cycle_retreat:
            if id(node) == id(self._cycle_node) or id(node) in self._successful_visits:
                self._cycle_node = None
                self._on_cycle_retreat = False
                return
            raise Discard()

    def _collapse_ambig(self, children):
        new_children = []
        for child in children:
            if hasattr(child, 'data') and child.data == '_ambig':
                new_children += child.children
            else:
                new_children.append(child)
        return new_children

    def _call_rule_func(self, node, data):
        # called when transforming children of symbol nodes
        # data is a list of trees or tokens that correspond to the
        # symbol's rule expansion
        return self.callbacks[node.rule](data)

    def _call_ambig_func(self, node, data):
        # called when transforming a symbol node
        # data is a list of trees where each tree's data is
        # equal to the name of the symbol or one of its aliases.
        if len(data) > 1:
            return self.tree_class('_ambig', data)
        elif data:
            return data[0]
        raise Discard()

    def transform_symbol_node(self, node, data):
        if id(node) not in self._successful_visits:
            raise Discard()
        self._check_cycle(node)
        self._successful_visits.remove(id(node))
        data = self._collapse_ambig(data)
        return self._call_ambig_func(node, data)

    def transform_intermediate_node(self, node, data):
        if id(node) not in self._successful_visits:
            raise Discard()
        self._check_cycle(node)
        self._successful_visits.remove(id(node))
        if len(data) > 1:
            children = [self.tree_class('_inter', c) for c in data]
            return self.tree_class('_iambig', children)
        return data[0]

    def transform_packed_node(self, node, data):
        self._check_cycle(node)
        if self.resolve_ambiguity and id(node.parent) in self._successful_visits:
            raise Discard()
        if self._use_cache and id(node) in self._cache:
            return self._cache[id(node)]
        children = []
        assert len(data) <= 2
        data = PackedData(node, data)
        if data.left is not PackedData.NO_DATA:
            if node.left.is_intermediate and isinstance(data.left, list):
                children += data.left
            else:
                children.append(data.left)
        if data.right is not PackedData.NO_DATA:
            children.append(data.right)
        if node.parent.is_intermediate:
            return self._cache.setdefault(id(node), children)
        return self._cache.setdefault(id(node), self._call_rule_func(node, children))

    def visit_symbol_node_in(self, node):
        super(ForestToParseTree, self).visit_symbol_node_in(node)
        if self._on_cycle_retreat:
            return
        return node.children

    def visit_packed_node_in(self, node):
        self._on_cycle_retreat = False
        to_visit = super(ForestToParseTree, self).visit_packed_node_in(node)
        if not self.resolve_ambiguity or id(node.parent) not in self._successful_visits:
            if not self._use_cache or id(node) not in self._cache:
                return to_visit

    def visit_packed_node_out(self, node):
        super(ForestToParseTree, self).visit_packed_node_out(node)
        if not self._on_cycle_retreat:
            self._successful_visits.add(id(node.parent))

def handles_ambiguity(func):
    """Decorator for methods of subclasses of ``TreeForestTransformer``.
    Denotes that the method should receive a list of transformed derivations."""
    func.handles_ambiguity = True
    return func

class TreeForestTransformer(ForestToParseTree):
    """A ``ForestTransformer`` with a tree ``Transformer``-like interface.
    By default, it will construct a tree.

    Methods provided via inheritance are called based on the rule/symbol
    names of nodes in the forest.

    Methods that act on rules will receive a list of the results of the
    transformations of the rule's children. By default, trees and tokens.

    Methods that act on tokens will receive a token.

    Alternatively, methods that act on rules may be annotated with
    ``handles_ambiguity``. In this case, the function will receive a list
    of all the transformations of all the derivations of the rule.
    By default, a list of trees where each tree.data is equal to the
    rule name or one of its aliases.

    Non-tree transformations are made possible by override of
    ``__default__``, ``__default_token__``, and ``__default_ambig__``.

    .. note::

        Tree shaping features such as inlined rules and token filtering are
        not built into the transformation. Positions are also not
        propagated.

    :param tree_class: The tree class to use for construction
    :param prioritizer: A ``ForestVisitor`` that manipulates the priorities of
        nodes in the SPPF.
    :param resolve_ambiguity: If True, ambiguities will be resolved based on
        priorities.
    :param use_cache: If True, caches the results of some transformations,
        potentially improving performance when ``resolve_ambiguity==False``.
        Only use if you know what you are doing: i.e. All transformation
        functions are pure and referentially transparent.
    """

    def __init__(self, tree_class=Tree, prioritizer=ForestSumVisitor(), resolve_ambiguity=True, use_cache=False):
        super(TreeForestTransformer, self).__init__(tree_class, dict(), prioritizer, resolve_ambiguity, use_cache)

    def __default__(self, name, data):
        """Default operation on tree (for override).

        Returns a tree with name with data as children.
        """
        return self.tree_class(name, data)

    def __default_ambig__(self, name, data):
        """Default operation on ambiguous rule (for override).

        Wraps data in an '_ambig_' node if it contains more than
        one element.
        """
        if len(data) > 1:
            return self.tree_class('_ambig', data)
        elif data:
            return data[0]
        raise Discard()

    def __default_token__(self, node):
        """Default operation on ``Token`` (for override).

        Returns ``node``.
        """
        return node

    def transform_token_node(self, node):
        return getattr(self, node.type, self.__default_token__)(node)

    def _call_rule_func(self, node, data):
        name = node.rule.alias or node.rule.options.template_source or node.rule.origin.name
        user_func = getattr(self, name, self.__default__)
        if user_func == self.__default__ or hasattr(user_func, 'handles_ambiguity'):
            user_func = partial(self.__default__, name)
        if not self.resolve_ambiguity:
            wrapper = partial(AmbiguousIntermediateExpander, self.tree_class)
            user_func = wrapper(user_func)
        return user_func(data)

    def _call_ambig_func(self, node, data):
        name = node.s.name
        user_func = getattr(self, name, self.__default_ambig__)
        if user_func == self.__default_ambig__ or not hasattr(user_func, 'handles_ambiguity'):
            user_func = partial(self.__default_ambig__, name)
        return user_func(data)

class ForestToPyDotVisitor(ForestVisitor):
    """
    A Forest visitor which writes the SPPF to a PNG.

    The SPPF can get really large, really quickly because
    of the amount of meta-data it stores, so this is probably
    only useful for trivial trees and learning how the SPPF
    is structured.
    """
    def __init__(self, rankdir="TB"):
        super(ForestToPyDotVisitor, self).__init__(single_visit=True)
        self.pydot = import_module('pydot')
        self.graph = self.pydot.Dot(graph_type='digraph', rankdir=rankdir)

    def visit(self, root, filename):
        super(ForestToPyDotVisitor, self).visit(root)
        try:
            self.graph.write_png(filename)
        except FileNotFoundError as e:
            logger.error("Could not write png: ", e)

    def visit_token_node(self, node):
        graph_node_id = str(id(node))
        graph_node_label = "\"{}\"".format(node.value.replace('"', '\\"'))
        graph_node_color = 0x808080
        graph_node_style = "\"filled,rounded\""
        graph_node_shape = "diamond"
        graph_node = self.pydot.Node(graph_node_id, style=graph_node_style, fillcolor="#{:06x}".format(graph_node_color), shape=graph_node_shape, label=graph_node_label)
        self.graph.add_node(graph_node)

    def visit_packed_node_in(self, node):
        graph_node_id = str(id(node))
        graph_node_label = repr(node)
        graph_node_color = 0x808080
        graph_node_style = "filled"
        graph_node_shape = "diamond"
        graph_node = self.pydot.Node(graph_node_id, style=graph_node_style, fillcolor="#{:06x}".format(graph_node_color), shape=graph_node_shape, label=graph_node_label)
        self.graph.add_node(graph_node)
        yield node.left
        yield node.right

    def visit_packed_node_out(self, node):
        graph_node_id = str(id(node))
        graph_node = self.graph.get_node(graph_node_id)[0]
        for child in [node.left, node.right]:
            if child is not None:
                child_graph_node_id = str(id(child))
                child_graph_node = self.graph.get_node(child_graph_node_id)[0]
                self.graph.add_edge(self.pydot.Edge(graph_node, child_graph_node))
            else:
                #### Try and be above the Python object ID range; probably impl. specific, but maybe this is okay.
                child_graph_node_id = str(randint(100000000000000000000000000000,123456789012345678901234567890))
                child_graph_node_style = "invis"
                child_graph_node = self.pydot.Node(child_graph_node_id, style=child_graph_node_style, label="None")
                child_edge_style = "invis"
                self.graph.add_node(child_graph_node)
                self.graph.add_edge(self.pydot.Edge(graph_node, child_graph_node, style=child_edge_style))

    def visit_symbol_node_in(self, node):
        graph_node_id = str(id(node))
        graph_node_label = repr(node)
        graph_node_color = 0x808080
        graph_node_style = "\"filled\""
        if node.is_intermediate:
            graph_node_shape = "ellipse"
        else:
            graph_node_shape = "rectangle"
        graph_node = self.pydot.Node(graph_node_id, style=graph_node_style, fillcolor="#{:06x}".format(graph_node_color), shape=graph_node_shape, label=graph_node_label)
        self.graph.add_node(graph_node)
        return iter(node.children)

    def visit_symbol_node_out(self, node):
        graph_node_id = str(id(node))
        graph_node = self.graph.get_node(graph_node_id)[0]
        for child in node.children:
            child_graph_node_id = str(id(child))
            child_graph_node = self.graph.get_node(child_graph_node_id)[0]
            self.graph.add_edge(self.pydot.Edge(graph_node, child_graph_node))