AlkantarClanX12
Your IP : 3.149.237.231
"Utility functions used by the btm_matcher module"
from . import pytree
from .pgen2 import grammar, token
from .pygram import pattern_symbols, python_symbols
syms = pattern_symbols
pysyms = python_symbols
tokens = grammar.opmap
token_labels = token
TYPE_ANY = -1
TYPE_ALTERNATIVES = -2
TYPE_GROUP = -3
class MinNode(object):
"""This class serves as an intermediate representation of the
pattern tree during the conversion to sets of leaf-to-root
subpatterns"""
def __init__(self, type=None, name=None):
self.type = type
self.name = name
self.children = []
self.leaf = False
self.parent = None
self.alternatives = []
self.group = []
def __repr__(self):
return str(self.type) + ' ' + str(self.name)
def leaf_to_root(self):
"""Internal method. Returns a characteristic path of the
pattern tree. This method must be run for all leaves until the
linear subpatterns are merged into a single"""
node = self
subp = []
while node:
if node.type == TYPE_ALTERNATIVES:
node.alternatives.append(subp)
if len(node.alternatives) == len(node.children):
#last alternative
subp = [tuple(node.alternatives)]
node.alternatives = []
node = node.parent
continue
else:
node = node.parent
subp = None
break
if node.type == TYPE_GROUP:
node.group.append(subp)
#probably should check the number of leaves
if len(node.group) == len(node.children):
subp = get_characteristic_subpattern(node.group)
node.group = []
node = node.parent
continue
else:
node = node.parent
subp = None
break
if node.type == token_labels.NAME and node.name:
#in case of type=name, use the name instead
subp.append(node.name)
else:
subp.append(node.type)
node = node.parent
return subp
def get_linear_subpattern(self):
"""Drives the leaf_to_root method. The reason that
leaf_to_root must be run multiple times is because we need to
reject 'group' matches; for example the alternative form
(a | b c) creates a group [b c] that needs to be matched. Since
matching multiple linear patterns overcomes the automaton's
capabilities, leaf_to_root merges each group into a single
choice based on 'characteristic'ity,
i.e. (a|b c) -> (a|b) if b more characteristic than c
Returns: The most 'characteristic'(as defined by
get_characteristic_subpattern) path for the compiled pattern
tree.
"""
for l in self.leaves():
subp = l.leaf_to_root()
if subp:
return subp
def leaves(self):
"Generator that returns the leaves of the tree"
for child in self.children:
yield from child.leaves()
if not self.children:
yield self
def reduce_tree(node, parent=None):
"""
Internal function. Reduces a compiled pattern tree to an
intermediate representation suitable for feeding the
automaton. This also trims off any optional pattern elements(like
[a], a*).
"""
new_node = None
#switch on the node type
if node.type == syms.Matcher:
#skip
node = node.children[0]
if node.type == syms.Alternatives :
#2 cases
if len(node.children) <= 2:
#just a single 'Alternative', skip this node
new_node = reduce_tree(node.children[0], parent)
else:
#real alternatives
new_node = MinNode(type=TYPE_ALTERNATIVES)
#skip odd children('|' tokens)
for child in node.children:
if node.children.index(child)%2:
continue
reduced = reduce_tree(child, new_node)
if reduced is not None:
new_node.children.append(reduced)
elif node.type == syms.Alternative:
if len(node.children) > 1:
new_node = MinNode(type=TYPE_GROUP)
for child in node.children:
reduced = reduce_tree(child, new_node)
if reduced:
new_node.children.append(reduced)
if not new_node.children:
# delete the group if all of the children were reduced to None
new_node = None
else:
new_node = reduce_tree(node.children[0], parent)
elif node.type == syms.Unit:
if (isinstance(node.children[0], pytree.Leaf) and
node.children[0].value == '('):
#skip parentheses
return reduce_tree(node.children[1], parent)
if ((isinstance(node.children[0], pytree.Leaf) and
node.children[0].value == '[')
or
(len(node.children)>1 and
hasattr(node.children[1], "value") and
node.children[1].value == '[')):
#skip whole unit if its optional
return None
leaf = True
details_node = None
alternatives_node = None
has_repeater = False
repeater_node = None
has_variable_name = False
for child in node.children:
if child.type == syms.Details:
leaf = False
details_node = child
elif child.type == syms.Repeater:
has_repeater = True
repeater_node = child
elif child.type == syms.Alternatives:
alternatives_node = child
if hasattr(child, 'value') and child.value == '=': # variable name
has_variable_name = True
#skip variable name
if has_variable_name:
#skip variable name, '='
name_leaf = node.children[2]
if hasattr(name_leaf, 'value') and name_leaf.value == '(':
# skip parenthesis
name_leaf = node.children[3]
else:
name_leaf = node.children[0]
#set node type
if name_leaf.type == token_labels.NAME:
#(python) non-name or wildcard
if name_leaf.value == 'any':
new_node = MinNode(type=TYPE_ANY)
else:
if hasattr(token_labels, name_leaf.value):
new_node = MinNode(type=getattr(token_labels, name_leaf.value))
else:
new_node = MinNode(type=getattr(pysyms, name_leaf.value))
elif name_leaf.type == token_labels.STRING:
#(python) name or character; remove the apostrophes from
#the string value
name = name_leaf.value.strip("'")
if name in tokens:
new_node = MinNode(type=tokens[name])
else:
new_node = MinNode(type=token_labels.NAME, name=name)
elif name_leaf.type == syms.Alternatives:
new_node = reduce_tree(alternatives_node, parent)
#handle repeaters
if has_repeater:
if repeater_node.children[0].value == '*':
#reduce to None
new_node = None
elif repeater_node.children[0].value == '+':
#reduce to a single occurrence i.e. do nothing
pass
else:
#TODO: handle {min, max} repeaters
raise NotImplementedError
#add children
if details_node and new_node is not None:
for child in details_node.children[1:-1]:
#skip '<', '>' markers
reduced = reduce_tree(child, new_node)
if reduced is not None:
new_node.children.append(reduced)
if new_node:
new_node.parent = parent
return new_node
def get_characteristic_subpattern(subpatterns):
"""Picks the most characteristic from a list of linear patterns
Current order used is:
names > common_names > common_chars
"""
if not isinstance(subpatterns, list):
return subpatterns
if len(subpatterns)==1:
return subpatterns[0]
# first pick out the ones containing variable names
subpatterns_with_names = []
subpatterns_with_common_names = []
common_names = ['in', 'for', 'if' , 'not', 'None']
subpatterns_with_common_chars = []
common_chars = "[]().,:"
for subpattern in subpatterns:
if any(rec_test(subpattern, lambda x: type(x) is str)):
if any(rec_test(subpattern,
lambda x: isinstance(x, str) and x in common_chars)):
subpatterns_with_common_chars.append(subpattern)
elif any(rec_test(subpattern,
lambda x: isinstance(x, str) and x in common_names)):
subpatterns_with_common_names.append(subpattern)
else:
subpatterns_with_names.append(subpattern)
if subpatterns_with_names:
subpatterns = subpatterns_with_names
elif subpatterns_with_common_names:
subpatterns = subpatterns_with_common_names
elif subpatterns_with_common_chars:
subpatterns = subpatterns_with_common_chars
# of the remaining subpatterns pick out the longest one
return max(subpatterns, key=len)
def rec_test(sequence, test_func):
"""Tests test_func on all items of sequence and items of included
sub-iterables"""
for x in sequence:
if isinstance(x, (list, tuple)):
yield from rec_test(x, test_func)
else:
yield test_func(x)