transform.py 29.5 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
"""transformation.py - transformation functions for converting the
                       concrete into the abstract syntax tree

Copyright 2016  by Eckhart Arnold (arnold@badw.de)
                Bavarian Academy of Sciences an Humanities (badw.de)

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied.  See the License for the specific language governing
permissions and limitations under the License.
"""

import inspect
from functools import partial, reduce, singledispatch

23
from DHParser.syntaxtree import Node, WHITESPACE_PTYPE, TOKEN_PTYPE, MockParser
24

25
26
27
28
from DHParser.toolkit import expand_table, smart_list, re, typing

from typing import AbstractSet, Any, ByteString, Callable, cast, Container, Dict, \
    Iterator, List, NamedTuple, Sequence, Union, Text, Tuple
29

30
31
32
33
34
__all__ = ('TransformationDict',
           'TransformationProc',
           'ConditionFunc',
           'KeyFunc',
           'transformation_factory',
35
36
37
           'key_parser_name',
           'key_tag_name',
           'traverse',
38
           'is_named',
39
           'replace_by_single_child',
Eckhart Arnold's avatar
Eckhart Arnold committed
40
           'reduce_single_child',
41
           'replace_or_reduce',
42
43
           'replace_parser',
           'collapse',
44
           'merge_children',
45
46
           'replace_content',
           'apply_if',
47
           'traverse_locally',
48
           'is_anonymous',
49
50
51
52
           'is_whitespace',
           'is_empty',
           'is_expendable',
           'is_token',
53
           'is_one_of',
54
           'has_content',
di68kap's avatar
di68kap committed
55
           'has_parent',
56
57
58
59
60
61
62
63
           'lstrip',
           'rstrip',
           'strip',
           'keep_children',
           'keep_children_if',
           'keep_tokens',
           'keep_nodes',
           'keep_content',
64
           'remove_children_if',
eckhart's avatar
eckhart committed
65
           'remove_nodes',
66
67
68
69
70
           'remove_content',
           'remove_first',
           'remove_last',
           'remove_whitespace',
           'remove_empty',
di68kap's avatar
di68kap committed
71
           'remove_anonymous_empty',
72
73
           'remove_expendables',
           'remove_brackets',
74
75
           'remove_infix_operator',
           'remove_single_child',
76
77
78
79
           'remove_tokens',
           'flatten',
           'forbid',
           'require',
80
81
           'assert_content',
           'assert_condition',
eckhart's avatar
eckhart committed
82
           'assert_has_children')
83
84


85
TransformationProc = Callable[[List[Node]], None]
Eckhart Arnold's avatar
Eckhart Arnold committed
86
87
TransformationDict = Dict[str, Sequence[Callable]]
ProcessingTableType = Dict[str, Union[Sequence[Callable], TransformationDict]]
88
89
ConditionFunc = Callable  # Callable[[List[Node]], bool]
KeyFunc = Callable[[Node], str]
eckhart's avatar
eckhart committed
90
CriteriaType = Union[int, str, Callable]
91
92


93
def transformation_factory(t1=None, t2=None, t3=None, t4=None, t5=None):
94
    """Creates factory functions from transformation-functions that
95
    dispatch on the first parameter after the context parameter.
96
97
98
99

    Decorating a transformation-function that has more than merely the
    ``node``-parameter with ``transformation_factory`` creates a
    function with the same name, which returns a partial-function that
100
    takes just the context-parameter.
101
102
103
104
105
106
107
108
109
110

    Additionally, there is some some syntactic sugar for
    transformation-functions that receive a collection as their second
    parameter and do not have any further parameters. In this case a
    list of parameters passed to the factory function will be converted
    into a collection.

    Main benefit is readability of processing tables.

    Usage:
eckhart's avatar
eckhart committed
111
        @transformation_factory(AbstractSet[str])
112
        def remove_tokens(context, tokens):
113
114
115
            ...
      or, alternatively:
        @transformation_factory
116
        def remove_tokens(context, tokens: AbstractSet[str]):
117
118
119
120
121
122
            ...

    Example:
        trans_table = { 'expression': remove_tokens('+', '-') }
      instead of:
        trans_table = { 'expression': partial(remove_tokens, tokens={'+', '-'}) }
123
124

    Parameters:
125
        t1:  type of the second argument of the transformation function,
126
127
            only necessary if the transformation functions' parameter list
            does not have type annotations.
128
129
130
131
132
133
134
    """

    def decorator(f):
        sig = inspect.signature(f)
        params = list(sig.parameters.values())[1:]
        if len(params) == 0:
            return f  # '@transformer' not needed w/o free parameters
135
        assert t1 or params[0].annotation != params[0].empty, \
136
137
            "No type information on second parameter found! Please, use type " \
            "annotation or provide the type information via transfomer-decorator."
138
        p1type = t1 or params[0].annotation
139
        f = singledispatch(f)
eckhart's avatar
eckhart committed
140
141
142
143
144
145
146
147
148
149
150
151
        try:
            if len(params) == 1 and issubclass(p1type, Container) \
                    and not issubclass(p1type, Text) and not issubclass(p1type, ByteString):
                def gen_special(*args):
                    c = set(args) if issubclass(p1type, AbstractSet) else \
                        list(args) if issubclass(p1type, Sequence) else args
                    d = {params[0].name: c}
                    return partial(f, **d)

                f.register(p1type.__args__[0], gen_special)
        except AttributeError:
            pass  # Union Type does not allow subclassing, but is not needed here
152
153
154
155
156
157

        def gen_partial(*args, **kwargs):
            d = {p.name: arg for p, arg in zip(params, args)}
            d.update(kwargs)
            return partial(f, **d)

158
159
160
161
162
        for t in (p1type, t2, t3, t4, t5):
            if t:
                f.register(t, gen_partial)
            else:
                break
163
164
        return f

165
    if isinstance(t1, type(lambda: 1)):
166
167
168
        # Provide for the case that transformation_factory has been
        # written as plain decorator and not as a function call that
        # returns the decorator proper.
169
170
        func = t1
        t1 = None
171
172
173
174
175
        return decorator(func)
    else:
        return decorator


176
def key_parser_name(node: Node) -> str:
177
178
179
    return node.parser.name


180
def key_tag_name(node: Node) -> str:
181
182
183
    return node.tag_name


184
def traverse(root_node: Node,
Eckhart Arnold's avatar
Eckhart Arnold committed
185
             processing_table: ProcessingTableType,
186
187
188
             key_func: KeyFunc=key_tag_name) -> None:
    """
    Traverses the snytax tree starting with the given ``node`` depth
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
    first and applies the sequences of callback-functions registered
    in the ``calltable``-dictionary.

    The most important use case is the transformation of a concrete
    syntax tree into an abstract tree (AST). But it is also imaginable
    to employ tree-traversal for the semantic analysis of the AST.

    In order to assign sequences of callback-functions to nodes, a
    dictionary ("processing table") is used. The keys usually represent
    tag names, but any other key function is possible. There exist
    three special keys:
        '+': always called (before any other processing function)
        '*': called for those nodes for which no (other) processing
             function appears in the table
        '~': always called (after any other processing function)

    Args:
        root_node (Node): The root-node of the syntax tree to be traversed
        processing_table (dict): node key -> sequence of functions that
            will be applied to matching nodes in order. This dictionary
209
210
            is interpreted as a `compact_table`. See
            `toolkit.expand_table` or ``EBNFCompiler.EBNFTransTable`
211
212
213
214
        key_func (function): A mapping key_func(node) -> keystr. The default
            key_func yields node.parser.name.

    Example:
215
216
        table = { "term": [replace_by_single_child, flatten],
            "factor, flowmarker, retrieveop": replace_by_single_child }
217
218
        traverse(node, table)
    """
219
220
221
222
223
224
    # Is this optimazation really needed?
    if '__cache__' in processing_table:
        # assume that processing table has already been expanded
        table = processing_table
        cache = processing_table['__cache__']
    else:
225
226
        # normalize processing_table entries by turning single values
        # into lists with a single value
227
228
        table = {name: cast(Sequence[Callable], smart_list(call))
                 for name, call in list(processing_table.items())}
229
        table = expand_table(table)
Eckhart Arnold's avatar
Eckhart Arnold committed
230
        cache = table.setdefault('__cache__', cast(TransformationDict, dict()))
231
232
        # change processing table in place, so its already expanded and cache filled next time
        processing_table.clear()
233
234
235
236
237
238
        processing_table.update(table)

    # assert '__cache__' in processing_table
    # # Code without optimization
    # table = {name: smart_list(call) for name, call in list(processing_table.items())}
    # table = expand_table(table)
Eckhart Arnold's avatar
Eckhart Arnold committed
239
    # cache = {}  # type: Dict[str, List[Callable]]
240

241
242
    def traverse_recursive(context):
        node = context[-1]
243
244
        if node.children:
            for child in node.result:
245
246
                context.append(child)
                traverse_recursive(context)  # depth first
247
                node.error_flag = max(node.error_flag, child.error_flag)  # propagate error flag
248
                context.pop()
249
250

        key = key_func(node)
251
252
253
        try:
            sequence = cache[key]
        except KeyError:
254
255
256
257
258
259
260
261
262
263
            sequence = table.get('+', []) + \
                       table.get(key, table.get('*', [])) + \
                       table.get('~', [])
            # '+' always called (before any other processing function)
            # '*' called for those nodes for which no (other) processing function
            #     appears in the table
            # '~' always called (after any other processing function)
            cache[key] = sequence

        for call in sequence:
264
            call(context)
265

266
    traverse_recursive([root_node])
267
268
    # assert processing_table['__cache__']

269

270
#######################################################################
271
#
272
273
# meta transformations, i.e. transformations that call other
# transformations
274
#
275
#######################################################################
276
277


278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
@transformation_factory(Dict)
def traverse_locally(context: List[Node],
                     processing_table: Dict,            # actually: ProcessingTableType
                     key_func: Callable=key_tag_name):  # actually: KeyFunc
    """Transforms the syntax tree starting from the last node in the context
    according to the given processing table. The purpose of this function is
    to apply certain transformations locally, i.e. only for those nodes that
    have the last node in the context as their parent node.
    """
    traverse(context[-1], processing_table, key_func)


# @transformation_factory(List[Callable])
# def apply_to_child(context: List[Node], transformations: List[Callable], condition: Callable):
#     """Applies a list of transformations to those children that meet a specifc condition."""
#     node = context[-1]
#     for child in node.children:
#         context.append(child)
#         if condition(context):
#             for transform in transformations:
#                 transform(context)
#         context.pop()


@transformation_factory(Callable)
def apply_if(context: List[Node], transformation: Callable, condition: Callable):
    """Applies a transformation only if a certain condition is met."""
    if condition(context):
        transformation(context)


#######################################################################
#
# conditionals that determine whether the context (or the last node in
# the context for that matter) fulfill a specific condition.
# ---------------------------------------------------------------------
#
# The context of a node is understood as a list of all parent nodes
# leading up to and including the node itself. If represented as list,
# the last element of the list is the node itself.
#
#######################################################################


def is_single_child(context: List[Node]) -> bool:
    return len(context[-2].children) == 1


def is_named(context: List[Node]) -> bool:
    return bool(context[-1].parser.name)


def is_anonymous(context: List[Node]) -> bool:
    return not context[-1].parser.name


def is_whitespace(context: List[Node]) -> bool:
    """Removes whitespace and comments defined with the
    ``@comment``-directive."""
    return context[-1].parser.ptype == WHITESPACE_PTYPE


def is_empty(context: List[Node]) -> bool:
    return not context[-1].result


def is_expendable(context: List[Node]) -> bool:
    return is_empty(context) or is_whitespace(context)


@transformation_factory(AbstractSet[str])
def is_token(context: List[Node], tokens: AbstractSet[str] = frozenset()) -> bool:
    """Checks whether the last node in the context has `ptype == TOKEN_PTYPE`
    and it's content matches one of the given tokens. Leading and trailing
    whitespace-tokens will be ignored. In case an empty set of tokens is passed,
    any token is a match. If only ":" is given all anonymous tokens but no other
    tokens are a match.
    """
    def stripped(nd: Node) -> str:
        # assert node.parser.ptype == TOKEN_PTYPE
        if nd.children:
            i, k = 0, len(nd.children)
            while i < len(nd.children) and nd.children[i].parser.ptype == WHITESPACE_PTYPE:
                i += 1
            while k > 0 and nd.children[k-1].parser.ptype == WHITESPACE_PTYPE:
                k -= 1
            return "".join(child.content for child in node.children[i:k])
        return nd.content
    node = context[-1]
    return (node.parser.ptype == TOKEN_PTYPE
            and ((not tokens or stripped(node) in tokens)
                 or (not node.parser.name and len(tokens) == 1 and ":" in tokens)))


@transformation_factory(AbstractSet[str])
def is_one_of(context: List[Node], tag_name_set: AbstractSet[str]) -> bool:
    """Returns true, if the node's tag_name is one of the given tag names."""
    return context[-1].tag_name in tag_name_set


@transformation_factory(str)
def has_content(context: List[Node], regexp: str) -> bool:
    """Checks a node's content against a regular expression."""
    return bool(re.match(regexp, context[-1].content))


@transformation_factory(AbstractSet[str])
def has_parent(context: List[Node], tag_name_set: AbstractSet[str]) -> bool:
    """Checks whether a node with one of the given tag names appears somewhere
     in the context before the last node in the context."""
    for i in range(2, len(context)):
        if context[-i].tag_name in tag_name_set:
            return True
    return False


#######################################################################
#
# utility functions (private)
#
#######################################################################


def _replace_by(node: Node, child: Node):
402
403
404
405
406
407
408
409
    if not child.parser.name:
        child.parser = MockParser(node.parser.name, child.parser.ptype)
        # parser names must not be overwritten, else: child.parser.name = node.parser.name
    node.parser = child.parser
    node._errors.extend(child._errors)
    node.result = child.result


410
def _reduce_child(node: Node, child: Node):
411
412
413
414
    node._errors.extend(child._errors)
    node.result = child.result


415
def _pick_child(context: List[Node], criteria: CriteriaType):
eckhart's avatar
eckhart committed
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
    """Returns the first child that meets the criteria."""
    if isinstance(criteria, int):
        try:
            return context[-1].children[criteria]
        except IndexError:
            return None
    elif isinstance(criteria, str):
        for child in context[-1].children:
            if child.tag_name == criteria:
                return child
        return None
    else:  # assume criteria has type ConditionFunc
        for child in context[-1].children:
            context.append(child)
            evaluation = criteria(context)
            context.pop()
            if evaluation:
                return child
        return None
435
436


437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
#######################################################################
#
# rearranging transformations
#
# - tree may be rearranged (e.g.flattened)
# - nodes that are not leaves may be dropped
# - order is preserved
# - leave content is preserved (though not necessarily the leaves
#   themselves)
#
#######################################################################


# @transformation_factory(int, str, Callable)
# def replace_by_child(context: List[Node], criteria: CriteriaType=is_single_child):
#     """
#     Replaces a node by the first of its immediate descendants
#     that meets the `criteria`. The criteria can either be the
#     index of the child (counting from zero), or the tag name or
#     a boolean-valued function on the context of the child.
#     If no child matching the criteria is found, the node will
#     not be replaced.
#     With the default value for `criteria` the same semantics is
#     the same that of `replace_by_single_child`.
#     """
#     child = _pick_child(context, criteria)
#     if child:
#         _replace_by(context[-1], child)
#
#
# @transformation_factory(int, str, Callable)
# def content_from_child(context: List[Node], criteria: CriteriaType = is_single_child):
#     """
#     Reduces a node, by transferring the result of the first of its
#     immediate descendants that meets the `criteria` to this node,
#     but keeping this node's parser entry. The criteria can either
#     be the index of the child (counting from zero), or the tag
#     name or a boolean-valued function on the context of the child.
#     If no child matching the criteria is found, the node will
#     not be replaced.
#     With the default value for `criteria` this has the same semantics
#     as `content_from_single_child`.
#     """
#     child = _pick_child(context, criteria)
#     if child:
#         _reduce_child(context[-1], child)
483
484


485
486
def replace_by_single_child(context: List[Node]):
    """
487
488
489
    Removes single branch node, replacing it by its immediate descendant.
    Replacement only takes place, if the last node in the context has
    exactly one child.
490
491
492
    """
    node = context[-1]
    if len(node.children) == 1:
493
        _replace_by(node, node.children[0])
494
495


Eckhart Arnold's avatar
Eckhart Arnold committed
496
def reduce_single_child(context: List[Node]):
497
    """
498
    Reduces a single branch node by transferring the result of its
499
    immediate descendant to this node, but keeping this node's parser entry.
500
501
    Reduction only takes place if the last node in the context has
    exactly one child.
502
503
504
    """
    node = context[-1]
    if len(node.children) == 1:
505
        _reduce_child(node, node.children[0])
506
507
508


@transformation_factory(Callable)
509
510
511
def replace_or_reduce(context: List[Node], condition: Callable=is_named):
    """
    Replaces node by a single child, if condition is met on child,
512
513
    otherwise (i.e. if the child is anonymous) reduces the child.
    """
514
    node = context[-1]
515
    if len(node.children) == 1:
di68kap's avatar
di68kap committed
516
        child = node.children[0]
517
        if condition(context):
518
            _replace_by(node, child)
519
        else:
520
            _reduce_child(node, child)
521
522
523


@transformation_factory
524
525
526
def replace_parser(context: List[Node], name: str):
    """
    Replaces the parser of a Node with a mock parser with the given
527
528
529
    name.

    Parameters:
530
531
        context: the context where the parser shall be replaced
        name: "NAME:PTYPE" of the surogate. The ptype is optional
532
    """
533
    node = context[-1]
534
535
536
537
538
    name, ptype = (name.split(':') + [''])[:2]
    node.parser = MockParser(name, ptype)


@transformation_factory(Callable)
539
540
541
def flatten(context: List[Node], condition: Callable=is_anonymous, recursive: bool=True):
    """
    Flattens all children, that fulfil the given `condition`
542
543
544
545
546
547
548
549
550
551
552
553
    (default: all unnamed children). Flattening means that wherever a
    node has child nodes, the child nodes are inserted in place of the
    node.
     If the parameter `recursive` is `True` the same will recursively be
    done with the child-nodes, first. In other words, all leaves of
    this node and its child nodes are collected in-order as direct
    children of this node.
     Applying flatten recursively will result in these kinds of
    structural transformation:
        (1 (+ 2) (+ 3)     ->   (1 + 2 + 3)
        (1 (+ (2 + (3))))  ->   (1 + 2 + 3)
    """
554
    node = context[-1]
555
    if node.children:
Eckhart Arnold's avatar
Eckhart Arnold committed
556
        new_result = []     # type: List[Node]
557
        for child in node.children:
558
559
            context.append(child)
            if child.children and condition(context):
560
                if recursive:
561
                    flatten(context, condition, recursive)
562
563
564
                new_result.extend(child.children)
            else:
                new_result.append(child)
565
            context.pop()
566
567
568
        node.result = tuple(new_result)


569
570
571
def collapse(context: List[Node]):
    """
    Collapses all sub-nodes of a node by replacing them with the
572
    string representation of the node.
573
    """
574
    node = context[-1]
575
    node.result = node.content
576
577
578


@transformation_factory
579
580
def merge_children(context: List[Node], tag_names: List[str]):
    """
581
582
583
    Joins all children next to each other and with particular tag-names
    into a single child node with a mock-parser with the name of the
    first tag-name in the list.
584
    """
Eckhart Arnold's avatar
Eckhart Arnold committed
585
    node = context[-1]
586
    result = []
587
    name, ptype = ('', tag_names[0]) if tag_names[0][:1] == ':' else (tag_names[0], '')
588
    if node.children:
589
        i = 0
590
591
592
593
594
595
596
597
598
599
600
        L = len(node.children)
        while i < L:
            while i < L and not node.children[i].tag_name in tag_names:
                result.append(node.children[i])
                i += 1
            k = i + 1
            while (k < L and node.children[k].tag_name in tag_names
                   and bool(node.children[i].children) == bool(node.children[k].children)):
                k += 1
            if i < L:
                result.append(Node(MockParser(name, ptype),
Eckhart Arnold's avatar
Eckhart Arnold committed
601
602
                                   reduce(lambda a, b: a + b,
                                          (node.children for node in node.children[i:k]))))
603
604
605
606
607
            i = k
        node.result = tuple(result)


@transformation_factory
608
def replace_content(context: List[Node], func: Callable):  # Callable[[Node], ResultType]
di68kap's avatar
di68kap committed
609
    """Replaces the content of the node. ``func`` takes the node's result
610
611
    as an argument an returns the mapped result.
    """
612
    node = context[-1]
613
614
615
    node.result = func(node.result)


616
617
618
619
620
621
622
623
624
#######################################################################
#
# destructive transformations:
#
# - leaves may be dropped (e.g. if deemed irrelevant)
# - errors of dropped leaves will be lost
# - no promise that order will be preserved
#
#######################################################################
625
626


627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
@transformation_factory(Callable)
def lstrip(context: List[Node], condition: Callable = is_expendable):
    """Recursively removes all leading child-nodes that fulfill a given condition."""
    node = context[-1]
    i = 1
    while i > 0 and node.children:
        lstrip(context + [node.children[0]], condition)
        i, L = 0, len(node.children)
        while i < L and condition(context + [node.children[i]]):
            i += 1
        if i > 0:
            node.result = node.children[i:]


@transformation_factory(Callable)
def rstrip(context: List[Node], condition: Callable = is_expendable):
    """Recursively removes all leading nodes that fulfill a given condition."""
    node = context[-1]
    i, L = 0, len(node.children)
    while i < L and node.children:
        rstrip(context + [node.children[-1]], condition)
        L = len(node.children)
        i = L
        while i > 0 and condition(context + [node.children[i-1]]):
            i -= 1
        if i < L:
            node.result = node.children[:i]


@transformation_factory(Callable)
eckhart's avatar
eckhart committed
657
def strip(context: List[Node], condition: Callable = is_expendable):
658
659
660
661
662
    """Removes leading and trailing child-nodes that fulfill a given condition."""
    lstrip(context, condition)
    rstrip(context, condition)


663
@transformation_factory(slice)
664
def keep_children(context: List[Node], section: slice = slice(None)):
665
    """Keeps only child-nodes which fall into a slice of the result field."""
666
    node = context[-1]
667
    if node.children:
668
        node.result = node.children[section]
669
670
671


@transformation_factory(Callable)
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
def keep_children_if(context: List[Node], condition: Callable):
    """Removes all children for which `condition()` returns `True`."""
    node = context[-1]
    if node.children:
        node.result = tuple(c for c in node.children if condition(context + [c]))


@transformation_factory
def keep_tokens(context: List[Node], tokens: AbstractSet[str] = frozenset()):
    """Removes any among a particular set of tokens from the immediate
    descendants of a node. If ``tokens`` is the empty set, all tokens
    are removed."""
    keep_children_if(context, partial(is_token, tokens=tokens))


@transformation_factory
def keep_nodes(context: List[Node], tag_names: AbstractSet[str]):
    """Removes children by tag name."""
    keep_children_if(context, partial(is_one_of, tag_name_set=tag_names))


@transformation_factory
def keep_content(context: List[Node], regexp: str):
    """Removes children depending on their string value."""
    keep_children_if(context, partial(has_content, regexp=regexp))


@transformation_factory(Callable)
def remove_children_if(context: List[Node], condition: Callable):
701
702
703
704
705
706
    """Removes all children for which `condition()` returns `True`."""
    node = context[-1]
    if node.children:
        node.result = tuple(c for c in node.children if not condition(context + [c]))


eckhart's avatar
eckhart committed
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
# @transformation_factory(Callable)
# def remove_children(context: List[Node],
#                     condition: Callable = TRUE_CONDITION,
#                     section: slice = slice(None)):
#     """Removes all nodes from a slice of the result field if the function
#     `condition(child_node)` evaluates to `True`."""
#     node = context[-1]
#     if node.children:
#         c = node.children
#         N = len(c)
#         rng = range(*section.indices(N))
#         node.result = tuple(c[i] for i in range(N)
#                             if i not in rng or not condition(context + [c[i]]))
#         # selection = []
#         # for i in range(N):
#         #     context.append(c[i])
#         #     if not i in rng or not condition(context):
#         #         selection.append(c[i])
#         #     context.pop()
#         # if len(selection) != c:
#         #     node.result = tuple(selection)
728
729
730
731


remove_whitespace = remove_children_if(is_whitespace)  # partial(remove_children_if, condition=is_whitespace)
remove_empty = remove_children_if(is_empty)
di68kap's avatar
di68kap committed
732
remove_anonymous_empty = remove_children_if(lambda ctx: is_empty(ctx) and is_anonymous(ctx))
733
remove_expendables = remove_children_if(is_expendable)  # partial(remove_children_if, condition=is_expendable)
734
remove_anonymous_expendables = remove_children_if(lambda ctx: is_anonymous(ctx) and is_expendable(ctx))
735
736
737
remove_first = apply_if(keep_children(slice(1, None)), lambda ctx: len(ctx[-1].children) > 1)
remove_last = apply_if(keep_children(slice(None, -1)), lambda ctx: len(ctx[-1].children) > 1)
remove_brackets = apply_if(keep_children(slice(1, -1)), lambda ctx: len(ctx[-1].children) >= 2)
738
remove_infix_operator = keep_children(slice(0, None, 2))
739
remove_single_child = apply_if(keep_children(slice(0)), lambda ctx: len(ctx[-1].children) == 1)
740
741
742


@transformation_factory
743
def remove_tokens(context: List[Node], tokens: AbstractSet[str] = frozenset()):
744
    """Removes any among a particular set of tokens from the immediate
745
746
    descendants of a node. If ``tokens`` is the empty set, all tokens
    are removed."""
747
    remove_children_if(context, partial(is_token, tokens=tokens))
748
749
750


@transformation_factory
eckhart's avatar
eckhart committed
751
def remove_nodes(context: List[Node], tag_names: AbstractSet[str]):
Eckhart Arnold's avatar
Eckhart Arnold committed
752
    """Removes children by tag name."""
753
    remove_children_if(context, partial(is_one_of, tag_name_set=tag_names))
754
755
756


@transformation_factory
757
def remove_content(context: List[Node], regexp: str):
758
    """Removes children depending on their string value."""
759
    remove_children_if(context, partial(has_content, regexp=regexp))
760
761
762
763


########################################################################
#
764
# AST semantic validation functions (EXPERIMENTAL!!!)
765
766
767
#
########################################################################

768
@transformation_factory(Callable)
Eckhart Arnold's avatar
Eckhart Arnold committed
769
def assert_condition(context: List[Node], condition: Callable, error_msg: str = ''):
770
    """Checks for `condition`; adds an error message if condition is not met."""
771
    node = context[-1]
772
    if not condition(context):
773
774
775
776
777
778
779
780
781
782
783
784
785
        if error_msg:
            node.add_error(error_msg % node.tag_name if error_msg.find("%s") > 0 else error_msg)
        else:
            cond_name = condition.__name__ if hasattr(condition, '__name__') \
                        else condition.__class__.__name__ if hasattr(condition, '__class__') \
                        else '<unknown>'
            node.add_error("transform.assert_condition: Failed to meet condition " + cond_name)


assert_has_children = assert_condition(lambda nd: nd.children, 'Element "%s" has no children')


@transformation_factory
786
def assert_content(context: List[Node], regexp: str):
787
    node = context[-1]
788
    if not has_content(context, regexp):
789
        node.add_error('Element "%s" violates %s on %s' %
790
                       (node.parser.name, str(regexp), node.content))
791

792
793

@transformation_factory
794
def require(context: List[Node], child_tags: AbstractSet[str]):
795
    node = context[-1]
796
797
798
799
800
801
802
    for child in node.children:
        if child.tag_name not in child_tags:
            node.add_error('Element "%s" is not allowed inside "%s".' %
                           (child.parser.name, node.parser.name))


@transformation_factory
803
def forbid(context: List[Node], child_tags: AbstractSet[str]):
804
    node = context[-1]
805
806
807
808
    for child in node.children:
        if child.tag_name in child_tags:
            node.add_error('Element "%s" cannot be nested inside "%s".' %
                           (child.parser.name, node.parser.name))