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
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
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
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
|
"""
sphinx.search
~~~~~~~~~~~~~
Create a full-text search index for offline search.
:copyright: Copyright 2007-2021 by the Sphinx team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
import html
import pickle
import re
from importlib import import_module
from os import path
from typing import IO, Any, Dict, Iterable, List, Set, Tuple, Type
from docutils import nodes
from docutils.nodes import Node
from sphinx import addnodes, package_dir
from sphinx.environment import BuildEnvironment
from sphinx.search.jssplitter import splitter_code
from sphinx.util import jsdump
class SearchLanguage:
"""
This class is the base class for search natural language preprocessors. If
you want to add support for a new language, you should override the methods
of this class.
You should override `lang` class property too (e.g. 'en', 'fr' and so on).
.. attribute:: stopwords
This is a set of stop words of the target language. Default `stopwords`
is empty. This word is used for building index and embedded in JS.
.. attribute:: js_splitter_code
Return splitter funcion of JavaScript version. The function should be
named as ``splitQuery``. And it should take a string and return list of
strings.
.. versionadded:: 3.0
.. attribute:: js_stemmer_code
Return stemmer class of JavaScript version. This class' name should be
``Stemmer`` and this class must have ``stemWord`` method. This string is
embedded as-is in searchtools.js.
This class is used to preprocess search word which Sphinx HTML readers
type, before searching index. Default implementation does nothing.
"""
lang = None # type: str
language_name = None # type: str
stopwords = set() # type: Set[str]
js_splitter_code = None # type: str
js_stemmer_rawcode = None # type: str
js_stemmer_code = """
/**
* Dummy stemmer for languages without stemming rules.
*/
var Stemmer = function() {
this.stemWord = function(w) {
return w;
}
}
"""
_word_re = re.compile(r'(?u)\w+')
def __init__(self, options: Dict) -> None:
self.options = options
self.init(options)
def init(self, options: Dict) -> None:
"""
Initialize the class with the options the user has given.
"""
def split(self, input: str) -> List[str]:
"""
This method splits a sentence into words. Default splitter splits input
at white spaces, which should be enough for most languages except CJK
languages.
"""
return self._word_re.findall(input)
def stem(self, word: str) -> str:
"""
This method implements stemming algorithm of the Python version.
Default implementation does nothing. You should implement this if the
language has any stemming rules.
This class is used to preprocess search words before registering them in
the search index. The stemming of the Python version and the JS version
(given in the js_stemmer_code attribute) must be compatible.
"""
return word
def word_filter(self, word: str) -> bool:
"""
Return true if the target word should be registered in the search index.
This method is called after stemming.
"""
return (
len(word) == 0 or not (
((len(word) < 3) and (12353 < ord(word[0]) < 12436)) or
(ord(word[0]) < 256 and (
word in self.stopwords
))))
# SearchEnglish imported after SearchLanguage is defined due to circular import
from sphinx.search.en import SearchEnglish
def parse_stop_word(source: str) -> Set[str]:
"""
parse snowball style word list like this:
* http://snowball.tartarus.org/algorithms/finnish/stop.txt
"""
result = set() # type: Set[str]
for line in source.splitlines():
line = line.split('|')[0] # remove comment
result.update(line.split())
return result
# maps language name to module.class or directly a class
languages = {
'da': 'sphinx.search.da.SearchDanish',
'de': 'sphinx.search.de.SearchGerman',
'en': SearchEnglish,
'es': 'sphinx.search.es.SearchSpanish',
'fi': 'sphinx.search.fi.SearchFinnish',
'fr': 'sphinx.search.fr.SearchFrench',
'hu': 'sphinx.search.hu.SearchHungarian',
'it': 'sphinx.search.it.SearchItalian',
'ja': 'sphinx.search.ja.SearchJapanese',
'nl': 'sphinx.search.nl.SearchDutch',
'no': 'sphinx.search.no.SearchNorwegian',
'pt': 'sphinx.search.pt.SearchPortuguese',
'ro': 'sphinx.search.ro.SearchRomanian',
'ru': 'sphinx.search.ru.SearchRussian',
'sv': 'sphinx.search.sv.SearchSwedish',
'tr': 'sphinx.search.tr.SearchTurkish',
'zh': 'sphinx.search.zh.SearchChinese',
} # type: Dict[str, Any]
class _JavaScriptIndex:
"""
The search index as javascript file that calls a function
on the documentation search object to register the index.
"""
PREFIX = 'Search.setIndex('
SUFFIX = ')'
def dumps(self, data: Any) -> str:
return self.PREFIX + jsdump.dumps(data) + self.SUFFIX
def loads(self, s: str) -> Any:
data = s[len(self.PREFIX):-len(self.SUFFIX)]
if not data or not s.startswith(self.PREFIX) or not \
s.endswith(self.SUFFIX):
raise ValueError('invalid data')
return jsdump.loads(data)
def dump(self, data: Any, f: IO) -> None:
f.write(self.dumps(data))
def load(self, f: IO) -> Any:
return self.loads(f.read())
js_index = _JavaScriptIndex()
class WordCollector(nodes.NodeVisitor):
"""
A special visitor that collects words for the `IndexBuilder`.
"""
def __init__(self, document: nodes.document, lang: SearchLanguage) -> None:
super().__init__(document)
self.found_words = [] # type: List[str]
self.found_title_words = [] # type: List[str]
self.lang = lang
def is_meta_keywords(self, node: addnodes.meta) -> bool:
if isinstance(node, addnodes.meta) and node.get('name') == 'keywords':
meta_lang = node.get('lang')
if meta_lang is None: # lang not specified
return True
elif meta_lang == self.lang.lang: # matched to html_search_language
return True
return False
def dispatch_visit(self, node: Node) -> None:
if isinstance(node, nodes.comment):
raise nodes.SkipNode
elif isinstance(node, nodes.raw):
if 'html' in node.get('format', '').split():
# Some people might put content in raw HTML that should be searched,
# so we just amateurishly strip HTML tags and index the remaining
# content
nodetext = re.sub(r'(?is)<style.*?</style>', '', node.astext())
nodetext = re.sub(r'(?is)<script.*?</script>', '', nodetext)
nodetext = re.sub(r'<[^<]+?>', '', nodetext)
self.found_words.extend(self.lang.split(nodetext))
raise nodes.SkipNode
elif isinstance(node, nodes.Text):
self.found_words.extend(self.lang.split(node.astext()))
elif isinstance(node, nodes.title):
self.found_title_words.extend(self.lang.split(node.astext()))
elif isinstance(node, addnodes.meta) and self.is_meta_keywords(node):
keywords = node['content']
keywords = [keyword.strip() for keyword in keywords.split(',')]
self.found_words.extend(keywords)
class IndexBuilder:
"""
Helper class that creates a searchindex based on the doctrees
passed to the `feed` method.
"""
formats = {
'jsdump': jsdump,
'pickle': pickle
}
def __init__(self, env: BuildEnvironment, lang: str, options: Dict, scoring: str) -> None:
self.env = env
self._titles = {} # type: Dict[str, str]
# docname -> title
self._filenames = {} # type: Dict[str, str]
# docname -> filename
self._mapping = {} # type: Dict[str, Set[str]]
# stemmed word -> set(docname)
self._title_mapping = {} # type: Dict[str, Set[str]]
# stemmed words in titles -> set(docname)
self._stem_cache = {} # type: Dict[str, str]
# word -> stemmed word
self._objtypes = {} # type: Dict[Tuple[str, str], int]
# objtype -> index
self._objnames = {} # type: Dict[int, Tuple[str, str, str]]
# objtype index -> (domain, type, objname (localized))
lang_class = languages.get(lang) # type: Type[SearchLanguage]
# add language-specific SearchLanguage instance
# fallback; try again with language-code
if lang_class is None and '_' in lang:
lang_class = languages.get(lang.split('_')[0])
if lang_class is None:
self.lang = SearchEnglish(options) # type: SearchLanguage
elif isinstance(lang_class, str):
module, classname = lang_class.rsplit('.', 1)
lang_class = getattr(import_module(module), classname)
self.lang = lang_class(options)
else:
# it's directly a class (e.g. added by app.add_search_language)
self.lang = lang_class(options)
if scoring:
with open(scoring, 'rb') as fp:
self.js_scorer_code = fp.read().decode()
else:
self.js_scorer_code = ''
self.js_splitter_code = splitter_code
def load(self, stream: IO, format: Any) -> None:
"""Reconstruct from frozen data."""
if isinstance(format, str):
format = self.formats[format]
frozen = format.load(stream)
# if an old index is present, we treat it as not existing.
if not isinstance(frozen, dict) or \
frozen.get('envversion') != self.env.version:
raise ValueError('old format')
index2fn = frozen['docnames']
self._filenames = dict(zip(index2fn, frozen['filenames']))
self._titles = dict(zip(index2fn, frozen['titles']))
def load_terms(mapping: Dict[str, Any]) -> Dict[str, Set[str]]:
rv = {}
for k, v in mapping.items():
if isinstance(v, int):
rv[k] = {index2fn[v]}
else:
rv[k] = {index2fn[i] for i in v}
return rv
self._mapping = load_terms(frozen['terms'])
self._title_mapping = load_terms(frozen['titleterms'])
# no need to load keywords/objtypes
def dump(self, stream: IO, format: Any) -> None:
"""Dump the frozen index to a stream."""
if isinstance(format, str):
format = self.formats[format]
format.dump(self.freeze(), stream)
def get_objects(self, fn2index: Dict[str, int]
) -> Dict[str, Dict[str, Tuple[int, int, int, str]]]:
rv = {} # type: Dict[str, Dict[str, Tuple[int, int, int, str]]]
otypes = self._objtypes
onames = self._objnames
for domainname, domain in sorted(self.env.domains.items()):
for fullname, dispname, type, docname, anchor, prio in \
sorted(domain.get_objects()):
if docname not in fn2index:
continue
if prio < 0:
continue
fullname = html.escape(fullname)
dispname = html.escape(dispname)
prefix, _, name = dispname.rpartition('.')
pdict = rv.setdefault(prefix, {})
try:
typeindex = otypes[domainname, type]
except KeyError:
typeindex = len(otypes)
otypes[domainname, type] = typeindex
otype = domain.object_types.get(type)
if otype:
# use str() to fire translation proxies
onames[typeindex] = (domainname, type,
str(domain.get_type_name(otype)))
else:
onames[typeindex] = (domainname, type, type)
if anchor == fullname:
shortanchor = ''
elif anchor == type + '-' + fullname:
shortanchor = '-'
else:
shortanchor = anchor
pdict[name] = (fn2index[docname], typeindex, prio, shortanchor)
return rv
def get_terms(self, fn2index: Dict) -> Tuple[Dict[str, List[str]], Dict[str, List[str]]]:
rvs = {}, {} # type: Tuple[Dict[str, List[str]], Dict[str, List[str]]]
for rv, mapping in zip(rvs, (self._mapping, self._title_mapping)):
for k, v in mapping.items():
if len(v) == 1:
fn, = v
if fn in fn2index:
rv[k] = fn2index[fn]
else:
rv[k] = sorted([fn2index[fn] for fn in v if fn in fn2index])
return rvs
def freeze(self) -> Dict[str, Any]:
"""Create a usable data structure for serializing."""
docnames, titles = zip(*sorted(self._titles.items()))
filenames = [self._filenames.get(docname) for docname in docnames]
fn2index = {f: i for (i, f) in enumerate(docnames)}
terms, title_terms = self.get_terms(fn2index)
objects = self.get_objects(fn2index) # populates _objtypes
objtypes = {v: k[0] + ':' + k[1] for (k, v) in self._objtypes.items()}
objnames = self._objnames
return dict(docnames=docnames, filenames=filenames, titles=titles, terms=terms,
objects=objects, objtypes=objtypes, objnames=objnames,
titleterms=title_terms, envversion=self.env.version)
def label(self) -> str:
return "%s (code: %s)" % (self.lang.language_name, self.lang.lang)
def prune(self, docnames: Iterable[str]) -> None:
"""Remove data for all docnames not in the list."""
new_titles = {}
new_filenames = {}
for docname in docnames:
if docname in self._titles:
new_titles[docname] = self._titles[docname]
new_filenames[docname] = self._filenames[docname]
self._titles = new_titles
self._filenames = new_filenames
for wordnames in self._mapping.values():
wordnames.intersection_update(docnames)
for wordnames in self._title_mapping.values():
wordnames.intersection_update(docnames)
def feed(self, docname: str, filename: str, title: str, doctree: nodes.document) -> None:
"""Feed a doctree to the index."""
self._titles[docname] = title
self._filenames[docname] = filename
visitor = WordCollector(doctree, self.lang)
doctree.walk(visitor)
# memoize self.lang.stem
def stem(word: str) -> str:
try:
return self._stem_cache[word]
except KeyError:
self._stem_cache[word] = self.lang.stem(word).lower()
return self._stem_cache[word]
_filter = self.lang.word_filter
for word in visitor.found_title_words:
stemmed_word = stem(word)
if _filter(stemmed_word):
self._title_mapping.setdefault(stemmed_word, set()).add(docname)
elif _filter(word): # stemmer must not remove words from search index
self._title_mapping.setdefault(word, set()).add(docname)
for word in visitor.found_words:
stemmed_word = stem(word)
# again, stemmer must not remove words from search index
if not _filter(stemmed_word) and _filter(word):
stemmed_word = word
already_indexed = docname in self._title_mapping.get(stemmed_word, set())
if _filter(stemmed_word) and not already_indexed:
self._mapping.setdefault(stemmed_word, set()).add(docname)
def context_for_searchtool(self) -> Dict[str, Any]:
if self.lang.js_splitter_code:
js_splitter_code = self.lang.js_splitter_code
else:
js_splitter_code = self.js_splitter_code
return {
'search_language_stemming_code': self.get_js_stemmer_code(),
'search_language_stop_words': jsdump.dumps(sorted(self.lang.stopwords)),
'search_scorer_tool': self.js_scorer_code,
'search_word_splitter_code': js_splitter_code,
}
def get_js_stemmer_rawcodes(self) -> List[str]:
"""Returns a list of non-minified stemmer JS files to copy."""
if self.lang.js_stemmer_rawcode:
return [
path.join(package_dir, 'search', 'non-minified-js', fname)
for fname in ('base-stemmer.js', self.lang.js_stemmer_rawcode)
]
else:
return []
def get_js_stemmer_rawcode(self) -> str:
return None
def get_js_stemmer_code(self) -> str:
"""Returns JS code that will be inserted into language_data.js."""
if self.lang.js_stemmer_rawcode:
js_dir = path.join(package_dir, 'search', 'minified-js')
with open(path.join(js_dir, 'base-stemmer.js')) as js_file:
base_js = js_file.read()
with open(path.join(js_dir, self.lang.js_stemmer_rawcode)) as js_file:
language_js = js_file.read()
return ('%s\n%s\nStemmer = %sStemmer;' %
(base_js, language_js, self.lang.language_name))
else:
return self.lang.js_stemmer_code
|