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import ast
import collections
from itertools import chain, combinations, product
import re
import sys
from .asttokens import asttokens
from .tree import Tree
def make_tree(code):
def make(node, parent=None):
if hasattr(node, 'first_token'):
data = {'start': node.first_token.startpos, 'end': node.last_token.endpos, 'ast': node}
else:
data = {'start': parent.first_token.startpos, 'end': parent.last_token.endpos, 'ast': parent}
if not hasattr(node, '_fields'):
return Tree(str(node), data=data)
children = []
for field, value in ast.iter_fields(node):
if value is None:
continue
if isinstance(value, ast.AST):
if not value._fields:
child = Tree(field, [Tree(value.__class__.__name__)], data=data)
else:
child = Tree(field, [make(value, node)], data=data)
elif isinstance(value, list):
child = Tree(field, [make(v, node) for v in value], data=data)
else:
child = Tree(field, [make(value, node)], data=data)
children.append(child)
return Tree(node.__class__.__name__, children, data=data)
pytree = asttokens.ASTTokens(code, parse=True).tree
return make(pytree)
def stringify(tree):
return re.sub('\n *', ' ', tree.__repr__())
# induce a pattern from the specified nodes in the tree
def make_pattern(tree, nodes):
label = tree.label
if not tree:
if label == 'Return':
return Tree(label, [Tree('$')])
return None
if any(n is tree for n in nodes):
# remove variable names
if label == 'Name':
return Tree(label, [Tree('id'), tree[1]])
elif label == 'arg':
return Tree(label, [Tree('arg')])
else:
return tree
subpats = [make_pattern(child, nodes) for child in tree]
if not any(subpats):
return None
# extra nodes to include in the pattern
if label in ('Call', 'FunctionDef'):
# store function names
pat = Tree(label, [tree[0]] + [s for s in subpats if s is not None])
elif label == 'args':
# (args arg1 … argN)
# store position of matching argument, by including (only) the
# root node of all nonmatching arguments
pat = Tree(label, [s if s is not None else Tree(tree[i].label) for i, s in enumerate(subpats)])
elif label == 'UnaryOp':
# store operator
pat = Tree(label, [tree[0], subpats[1]])
elif label == 'BinOp' or label == 'Compare':
# store operator and left and/or right side
children = []
if subpats[0]:
children += [subpats[0]]
children += [tree[1]]
if subpats[2]:
children += [subpats[2]]
pat = Tree(label, children)
else:
# store children if they match some part of the pattern
pat = Tree(label, [s for s in subpats if s is not None])
return pat
def get_variables(tree):
variables = collections.defaultdict(list)
for node, parent in tree.subtrees_with_parents():
if not node:
continue
if node.label == 'Name' and parent.label != 'func':
name = node[0][0].label
variables[name].append(node)
elif node.label == 'FunctionDef':
# (FunctionDef name (args (arguments (args arg0 arg1 … argN))))
for arg in node[1][0][0]:
if arg:
name = arg[0][0].label
variables[name].append(arg)
return variables
literals = {'Num', 'Str', 'NameConstant'}
short_range = {
'Return', 'Delete', 'Assign', 'AugAssign', 'Raise', 'BoolOp',
'BinOp', 'UnaryOp', 'Lambda', 'Call', 'Dict', 'Set', 'List'
}
def get_patterns(code):
tree = make_tree(code)
variables = get_variables(tree)
for var, nodes in variables.items():
for selected in chain(
combinations(nodes, 2)):
pat = make_pattern(tree, selected)
if pat:
yield pat, selected
# yield patterns for variable-literal / literal-literal pairs
# yield patterns for singleton literals
# (only within certain statements and expressions)
def patterns_with_literals(node):
if not node:
return
if node.label in short_range:
vars = [n for n in node.subtrees() if any(n is vn for var_nodes in variables.values() for vn in var_nodes)]
lits = [n for n in node.subtrees() if n.label in literals]
for selected in chain(
combinations(lits, 2),
product(lits, vars)):
pat = make_pattern(tree, selected)
if pat:
yield pat, selected
else:
for child in node:
yield from patterns_with_literals(child)
# extra nodes for Python
for n in tree.subtrees():
# empty return
if n.label == 'Return':
pat = make_pattern(tree, [n])
if pat:
yield pat, [n]
yield from patterns_with_literals(tree)
def get_attributes(programs):
# extract attributes from training data
patterns = collections.defaultdict(list)
for code in programs:
for pat, nodes in get_patterns(code):
patterns[pat] += [code]
attrs = collections.OrderedDict()
for pat, progs in sorted(patterns.items(), key=lambda x: len(x[1]), reverse=True):
if len(progs) < 5:
break
attrs['regex-{}'.format(len(attrs))] = {'desc': pat, 'programs': progs}
return attrs
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