1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
|
"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
pass
#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)
|
