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from functools import wraps
from .utils import smart_decorator, combine_alternatives
from .tree import Tree
from .exceptions import VisitError, GrammarError
from .lexer import Token
###{standalone
from inspect import getmembers, getmro
class Discard(Exception):
"""When raising the Discard exception in a transformer callback,
that node is discarded and won't appear in the parent.
"""
pass
# Transformers
class _Decoratable:
"Provides support for decorating methods with @v_args"
@classmethod
def _apply_decorator(cls, decorator, **kwargs):
mro = getmro(cls)
assert mro[0] is cls
libmembers = {name for _cls in mro[1:] for name, _ in getmembers(_cls)}
for name, value in getmembers(cls):
# Make sure the function isn't inherited (unless it's overwritten)
if name.startswith('_') or (name in libmembers and name not in cls.__dict__):
continue
if not callable(value):
continue
# Skip if v_args already applied (at the function level)
if hasattr(cls.__dict__[name], 'vargs_applied') or hasattr(value, 'vargs_applied'):
continue
static = isinstance(cls.__dict__[name], (staticmethod, classmethod))
setattr(cls, name, decorator(value, static=static, **kwargs))
return cls
def __class_getitem__(cls, _):
return cls
class Transformer(_Decoratable):
"""Transformers visit each node of the tree, and run the appropriate method on it according to the node's data.
Calls its methods (provided by user via inheritance) according to ``tree.data``.
The returned value replaces the old one in the structure.
They work bottom-up (or depth-first), starting with the leaves and ending at the root of the tree.
Transformers can be used to implement map & reduce patterns. Because nodes are reduced from leaf to root,
at any point the callbacks may assume the children have already been transformed (if applicable).
``Transformer`` can do anything ``Visitor`` can do, but because it reconstructs the tree,
it is slightly less efficient. It can be used to implement map or reduce patterns.
All these classes implement the transformer interface:
- ``Transformer`` - Recursively transforms the tree. This is the one you probably want.
- ``Transformer_InPlace`` - Non-recursive. Changes the tree in-place instead of returning new instances
- ``Transformer_InPlaceRecursive`` - Recursive. Changes the tree in-place instead of returning new instances
Parameters:
visit_tokens: By default, transformers only visit rules.
visit_tokens=True will tell ``Transformer`` to visit tokens
as well. This is a slightly slower alternative to lexer_callbacks
but it's easier to maintain and works for all algorithms
(even when there isn't a lexer).
"""
__visit_tokens__ = True # For backwards compatibility
def __init__(self, visit_tokens=True):
self.__visit_tokens__ = visit_tokens
def _call_userfunc(self, tree, new_children=None):
# Assumes tree is already transformed
children = new_children if new_children is not None else tree.children
try:
f = getattr(self, tree.data)
except AttributeError:
return self.__default__(tree.data, children, tree.meta)
else:
try:
wrapper = getattr(f, 'visit_wrapper', None)
if wrapper is not None:
return f.visit_wrapper(f, tree.data, children, tree.meta)
else:
return f(children)
except (GrammarError, Discard):
raise
except Exception as e:
raise VisitError(tree.data, tree, e)
def _call_userfunc_token(self, token):
try:
f = getattr(self, token.type)
except AttributeError:
return self.__default_token__(token)
else:
try:
return f(token)
except (GrammarError, Discard):
raise
except Exception as e:
raise VisitError(token.type, token, e)
def _transform_children(self, children):
for c in children:
try:
if isinstance(c, Tree):
yield self._transform_tree(c)
elif self.__visit_tokens__ and isinstance(c, Token):
yield self._call_userfunc_token(c)
else:
yield c
except Discard:
pass
def _transform_tree(self, tree):
children = list(self._transform_children(tree.children))
return self._call_userfunc(tree, children)
def transform(self, tree):
return self._transform_tree(tree)
def __mul__(self, other):
return TransformerChain(self, other)
def __default__(self, data, children, meta):
"""Default operation on tree (for override)
Function that is called on if a function with a corresponding name has not been found.
Defaults to reconstruct the Tree.
"""
return Tree(data, children, meta)
def __default_token__(self, token):
"""Default operation on token (for override)
Function that is called on if a function with a corresponding name has not been found.
Defaults to just return the argument.
"""
return token
class InlineTransformer(Transformer): # XXX Deprecated
def _call_userfunc(self, tree, new_children=None):
# Assumes tree is already transformed
children = new_children if new_children is not None else tree.children
try:
f = getattr(self, tree.data)
except AttributeError:
return self.__default__(tree.data, children, tree.meta)
else:
return f(*children)
class TransformerChain(object):
def __init__(self, *transformers):
self.transformers = transformers
def transform(self, tree):
for t in self.transformers:
tree = t.transform(tree)
return tree
def __mul__(self, other):
return TransformerChain(*self.transformers + (other,))
class Transformer_InPlace(Transformer):
"Non-recursive. Changes the tree in-place instead of returning new instances"
def _transform_tree(self, tree): # Cancel recursion
return self._call_userfunc(tree)
def transform(self, tree):
for subtree in tree.iter_subtrees():
subtree.children = list(self._transform_children(subtree.children))
return self._transform_tree(tree)
class Transformer_NonRecursive(Transformer):
"Non-recursive. Doesn't change the original tree."
def transform(self, tree):
# Tree to postfix
rev_postfix = []
q = [tree]
while q:
t = q.pop()
rev_postfix.append( t )
if isinstance(t, Tree):
q += t.children
# Postfix to tree
stack = []
for x in reversed(rev_postfix):
if isinstance(x, Tree):
size = len(x.children)
if size:
args = stack[-size:]
del stack[-size:]
else:
args = []
stack.append(self._call_userfunc(x, args))
else:
stack.append(x)
t ,= stack # We should have only one tree remaining
return t
class Transformer_InPlaceRecursive(Transformer):
"Recursive. Changes the tree in-place instead of returning new instances"
def _transform_tree(self, tree):
tree.children = list(self._transform_children(tree.children))
return self._call_userfunc(tree)
# Visitors
class VisitorBase:
def _call_userfunc(self, tree):
return getattr(self, tree.data, self.__default__)(tree)
def __default__(self, tree):
"Default operation on tree (for override)"
return tree
def __class_getitem__(cls, _):
return cls
class Visitor(VisitorBase):
"""Bottom-up visitor, non-recursive.
Visits the tree, starting with the leaves and finally the root (bottom-up)
Calls its methods (provided by user via inheritance) according to ``tree.data``
"""
def visit(self, tree):
for subtree in tree.iter_subtrees():
self._call_userfunc(subtree)
return tree
def visit_topdown(self,tree):
for subtree in tree.iter_subtrees_topdown():
self._call_userfunc(subtree)
return tree
class Visitor_Recursive(VisitorBase):
"""Bottom-up visitor, recursive.
Visits the tree, starting with the leaves and finally the root (bottom-up)
Calls its methods (provided by user via inheritance) according to ``tree.data``
"""
def visit(self, tree):
for child in tree.children:
if isinstance(child, Tree):
self.visit(child)
self._call_userfunc(tree)
return tree
def visit_topdown(self,tree):
self._call_userfunc(tree)
for child in tree.children:
if isinstance(child, Tree):
self.visit_topdown(child)
return tree
def visit_children_decor(func):
"See Interpreter"
@wraps(func)
def inner(cls, tree):
values = cls.visit_children(tree)
return func(cls, values)
return inner
class Interpreter(_Decoratable):
"""Interpreter walks the tree starting at the root.
Visits the tree, starting with the root and finally the leaves (top-down)
For each tree node, it calls its methods (provided by user via inheritance) according to ``tree.data``.
Unlike ``Transformer`` and ``Visitor``, the Interpreter doesn't automatically visit its sub-branches.
The user has to explicitly call ``visit``, ``visit_children``, or use the ``@visit_children_decor``.
This allows the user to implement branching and loops.
"""
def visit(self, tree):
f = getattr(self, tree.data)
wrapper = getattr(f, 'visit_wrapper', None)
if wrapper is not None:
return f.visit_wrapper(f, tree.data, tree.children, tree.meta)
else:
return f(tree)
def visit_children(self, tree):
return [self.visit(child) if isinstance(child, Tree) else child
for child in tree.children]
def __getattr__(self, name):
return self.__default__
def __default__(self, tree):
return self.visit_children(tree)
# Decorators
def _apply_decorator(obj, decorator, **kwargs):
try:
_apply = obj._apply_decorator
except AttributeError:
return decorator(obj, **kwargs)
else:
return _apply(decorator, **kwargs)
def _inline_args__func(func):
@wraps(func)
def create_decorator(_f, with_self):
if with_self:
def f(self, children):
return _f(self, *children)
else:
def f(self, children):
return _f(*children)
return f
return smart_decorator(func, create_decorator)
def inline_args(obj): # XXX Deprecated
return _apply_decorator(obj, _inline_args__func)
def _visitor_args_func_dec(func, visit_wrapper=None, static=False):
def create_decorator(_f, with_self):
if with_self:
def f(self, *args, **kwargs):
return _f(self, *args, **kwargs)
else:
def f(self, *args, **kwargs):
return _f(*args, **kwargs)
return f
if static:
f = wraps(func)(create_decorator(func, False))
else:
f = smart_decorator(func, create_decorator)
f.vargs_applied = True
f.visit_wrapper = visit_wrapper
return f
def _vargs_inline(f, data, children, meta):
return f(*children)
def _vargs_meta_inline(f, data, children, meta):
return f(meta, *children)
def _vargs_meta(f, data, children, meta):
return f(children, meta) # TODO swap these for consistency? Backwards incompatible!
def _vargs_tree(f, data, children, meta):
return f(Tree(data, children, meta))
def v_args(inline=False, meta=False, tree=False, wrapper=None):
"""A convenience decorator factory for modifying the behavior of user-supplied visitor methods.
By default, callback methods of transformers/visitors accept one argument - a list of the node's children.
``v_args`` can modify this behavior. When used on a transformer/visitor class definition,
it applies to all the callback methods inside it.
Parameters:
inline: Children are provided as ``*args`` instead of a list argument (not recommended for very long lists).
meta: Provides two arguments: ``children`` and ``meta`` (instead of just the first)
tree: Provides the entire tree as the argument, instead of the children.
Example:
::
@v_args(inline=True)
class SolveArith(Transformer):
def add(self, left, right):
return left + right
class ReverseNotation(Transformer_InPlace):
@v_args(tree=True)
def tree_node(self, tree):
tree.children = tree.children[::-1]
"""
if tree and (meta or inline):
raise ValueError("Visitor functions cannot combine 'tree' with 'meta' or 'inline'.")
func = None
if meta:
if inline:
func = _vargs_meta_inline
else:
func = _vargs_meta
elif inline:
func = _vargs_inline
elif tree:
func = _vargs_tree
if wrapper is not None:
if func is not None:
raise ValueError("Cannot use 'wrapper' along with 'tree', 'meta' or 'inline'.")
func = wrapper
def _visitor_args_dec(obj):
return _apply_decorator(obj, _visitor_args_func_dec, visit_wrapper=func)
return _visitor_args_dec
###}
#--- Visitor Utilities ---
class CollapseAmbiguities(Transformer):
"""
Transforms a tree that contains any number of _ambig nodes into a list of trees,
each one containing an unambiguous tree.
The length of the resulting list is the product of the length of all _ambig nodes.
Warning: This may quickly explode for highly ambiguous trees.
"""
def _ambig(self, options):
return sum(options, [])
def __default__(self, data, children_lists, meta):
return [Tree(data, children, meta) for children in combine_alternatives(children_lists)]
def __default_token__(self, t):
return [t]
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