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Edit File : btm_utils.py \| Size : 9.71 KB
"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) Back

Edit File : btm_utils.py | Size : 9.71 KB

"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)

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