mirror of
https://github.com/Sneed-Group/Poodletooth-iLand
synced 2024-12-28 14:12:52 -06:00
284 lines
9.8 KiB
Python
284 lines
9.8 KiB
Python
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"Utility functions used by the btm_matcher module"
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from . import pytree
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from .pgen2 import grammar, token
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from .pygram import pattern_symbols, python_symbols
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syms = pattern_symbols
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pysyms = python_symbols
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tokens = grammar.opmap
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token_labels = token
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TYPE_ANY = -1
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TYPE_ALTERNATIVES = -2
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TYPE_GROUP = -3
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class MinNode(object):
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"""This class serves as an intermediate representation of the
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pattern tree during the conversion to sets of leaf-to-root
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subpatterns"""
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def __init__(self, type=None, name=None):
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self.type = type
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self.name = name
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self.children = []
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self.leaf = False
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self.parent = None
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self.alternatives = []
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self.group = []
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def __repr__(self):
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return str(self.type) + ' ' + str(self.name)
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def leaf_to_root(self):
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"""Internal method. Returns a characteristic path of the
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pattern tree. This method must be run for all leaves until the
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linear subpatterns are merged into a single"""
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node = self
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subp = []
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while node:
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if node.type == TYPE_ALTERNATIVES:
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node.alternatives.append(subp)
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if len(node.alternatives) == len(node.children):
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#last alternative
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subp = [tuple(node.alternatives)]
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node.alternatives = []
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node = node.parent
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continue
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else:
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node = node.parent
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subp = None
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break
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if node.type == TYPE_GROUP:
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node.group.append(subp)
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#probably should check the number of leaves
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if len(node.group) == len(node.children):
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subp = get_characteristic_subpattern(node.group)
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node.group = []
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node = node.parent
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continue
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else:
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node = node.parent
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subp = None
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break
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if node.type == token_labels.NAME and node.name:
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#in case of type=name, use the name instead
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subp.append(node.name)
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else:
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subp.append(node.type)
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node = node.parent
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return subp
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def get_linear_subpattern(self):
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"""Drives the leaf_to_root method. The reason that
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leaf_to_root must be run multiple times is because we need to
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reject 'group' matches; for example the alternative form
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(a | b c) creates a group [b c] that needs to be matched. Since
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matching multiple linear patterns overcomes the automaton's
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capabilities, leaf_to_root merges each group into a single
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choice based on 'characteristic'ity,
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i.e. (a|b c) -> (a|b) if b more characteristic than c
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Returns: The most 'characteristic'(as defined by
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get_characteristic_subpattern) path for the compiled pattern
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tree.
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"""
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for l in self.leaves():
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subp = l.leaf_to_root()
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if subp:
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return subp
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def leaves(self):
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"Generator that returns the leaves of the tree"
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for child in self.children:
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for x in child.leaves():
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yield x
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if not self.children:
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yield self
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def reduce_tree(node, parent=None):
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"""
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Internal function. Reduces a compiled pattern tree to an
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intermediate representation suitable for feeding the
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automaton. This also trims off any optional pattern elements(like
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[a], a*).
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"""
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new_node = None
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#switch on the node type
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if node.type == syms.Matcher:
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#skip
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node = node.children[0]
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if node.type == syms.Alternatives :
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#2 cases
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if len(node.children) <= 2:
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#just a single 'Alternative', skip this node
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new_node = reduce_tree(node.children[0], parent)
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else:
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#real alternatives
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new_node = MinNode(type=TYPE_ALTERNATIVES)
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#skip odd children('|' tokens)
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for child in node.children:
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if node.children.index(child)%2:
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continue
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reduced = reduce_tree(child, new_node)
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if reduced is not None:
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new_node.children.append(reduced)
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elif node.type == syms.Alternative:
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if len(node.children) > 1:
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new_node = MinNode(type=TYPE_GROUP)
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for child in node.children:
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reduced = reduce_tree(child, new_node)
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if reduced:
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new_node.children.append(reduced)
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if not new_node.children:
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# delete the group if all of the children were reduced to None
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new_node = None
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else:
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new_node = reduce_tree(node.children[0], parent)
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elif node.type == syms.Unit:
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if (isinstance(node.children[0], pytree.Leaf) and
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node.children[0].value == '('):
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#skip parentheses
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return reduce_tree(node.children[1], parent)
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if ((isinstance(node.children[0], pytree.Leaf) and
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node.children[0].value == '[')
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or
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(len(node.children)>1 and
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hasattr(node.children[1], "value") and
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node.children[1].value == '[')):
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#skip whole unit if its optional
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return None
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leaf = True
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details_node = None
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alternatives_node = None
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has_repeater = False
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repeater_node = None
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has_variable_name = False
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for child in node.children:
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if child.type == syms.Details:
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leaf = False
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details_node = child
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elif child.type == syms.Repeater:
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has_repeater = True
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repeater_node = child
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elif child.type == syms.Alternatives:
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alternatives_node = child
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if hasattr(child, 'value') and child.value == '=': # variable name
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has_variable_name = True
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#skip variable name
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if has_variable_name:
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#skip variable name, '='
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name_leaf = node.children[2]
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if hasattr(name_leaf, 'value') and name_leaf.value == '(':
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# skip parenthesis
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name_leaf = node.children[3]
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else:
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name_leaf = node.children[0]
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#set node type
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if name_leaf.type == token_labels.NAME:
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#(python) non-name or wildcard
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if name_leaf.value == 'any':
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new_node = MinNode(type=TYPE_ANY)
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else:
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if hasattr(token_labels, name_leaf.value):
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new_node = MinNode(type=getattr(token_labels, name_leaf.value))
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else:
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new_node = MinNode(type=getattr(pysyms, name_leaf.value))
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elif name_leaf.type == token_labels.STRING:
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#(python) name or character; remove the apostrophes from
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#the string value
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name = name_leaf.value.strip("'")
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if name in tokens:
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new_node = MinNode(type=tokens[name])
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else:
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new_node = MinNode(type=token_labels.NAME, name=name)
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elif name_leaf.type == syms.Alternatives:
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new_node = reduce_tree(alternatives_node, parent)
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#handle repeaters
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if has_repeater:
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if repeater_node.children[0].value == '*':
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#reduce to None
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new_node = None
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elif repeater_node.children[0].value == '+':
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#reduce to a single occurence i.e. do nothing
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pass
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else:
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#TODO: handle {min, max} repeaters
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raise NotImplementedError
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pass
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#add children
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if details_node and new_node is not None:
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for child in details_node.children[1:-1]:
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#skip '<', '>' markers
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reduced = reduce_tree(child, new_node)
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if reduced is not None:
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new_node.children.append(reduced)
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if new_node:
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new_node.parent = parent
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return new_node
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def get_characteristic_subpattern(subpatterns):
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"""Picks the most characteristic from a list of linear patterns
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Current order used is:
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names > common_names > common_chars
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"""
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if not isinstance(subpatterns, list):
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return subpatterns
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if len(subpatterns)==1:
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return subpatterns[0]
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# first pick out the ones containing variable names
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subpatterns_with_names = []
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subpatterns_with_common_names = []
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common_names = ['in', 'for', 'if' , 'not', 'None']
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subpatterns_with_common_chars = []
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common_chars = "[]().,:"
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for subpattern in subpatterns:
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if any(rec_test(subpattern, lambda x: type(x) is str)):
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if any(rec_test(subpattern,
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lambda x: isinstance(x, str) and x in common_chars)):
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subpatterns_with_common_chars.append(subpattern)
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elif any(rec_test(subpattern,
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lambda x: isinstance(x, str) and x in common_names)):
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subpatterns_with_common_names.append(subpattern)
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else:
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subpatterns_with_names.append(subpattern)
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if subpatterns_with_names:
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subpatterns = subpatterns_with_names
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elif subpatterns_with_common_names:
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subpatterns = subpatterns_with_common_names
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elif subpatterns_with_common_chars:
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subpatterns = subpatterns_with_common_chars
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# of the remaining subpatterns pick out the longest one
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return max(subpatterns, key=len)
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def rec_test(sequence, test_func):
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"""Tests test_func on all items of sequence and items of included
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sub-iterables"""
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for x in sequence:
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if isinstance(x, (list, tuple)):
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for y in rec_test(x, test_func):
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yield y
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else:
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yield test_func(x)
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