"""Create a full-text search index for offline search."""
import html
import pickle
import re
from importlib import import_module
from os import path
from typing import IO, Any, Dict, Iterable, List, Optional, Set, Tuple, Type
from docutils import nodes
from docutils.nodes import Element, 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 function 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: str = None
language_name: str = None
stopwords: Set[str] = set()
js_splitter_code: str = None
js_stemmer_rawcode: str = None
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[str] = set()
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: Dict[str, Any] = {
'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',
}
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: List[str] = []
self.found_title_words: List[str] = []
self.lang = lang
def is_meta_keywords(self, node: Element) -> bool:
if (isinstance(node, (addnodes.meta, addnodes.docutils_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, Element) 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 search index 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: Dict[str, str] = {} # docname -> title
self._filenames: Dict[str, str] = {} # docname -> filename
self._mapping: Dict[str, Set[str]] = {} # stemmed word -> set(docname)
# stemmed words in titles -> set(docname)
self._title_mapping: Dict[str, Set[str]] = {}
self._stem_cache: Dict[str, str] = {} # word -> stemmed word
self._objtypes: Dict[Tuple[str, str], int] = {} # objtype -> index
# objtype index -> (domain, type, objname (localized))
self._objnames: Dict[int, Tuple[str, str, str]] = {}
# add language-specific SearchLanguage instance
lang_class: Type[SearchLanguage] = languages.get(lang)
# 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: SearchLanguage = SearchEnglish(options)
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, List[Tuple[int, int, int, str, str]]]:
rv: Dict[str, List[Tuple[int, int, int, str, 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('.')
plist = 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
plist.append((fn2index[docname], typeindex, prio, shortanchor, name))
return rv
def get_terms(self, fn2index: Dict) -> Tuple[Dict[str, List[str]], Dict[str, List[str]]]:
rvs: 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) -> Optional[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