# -*- coding: utf-8 -*- """ sphinx.search ~~~~~~~~~~~~~ Create a full-text search index for offline search. :copyright: Copyright 2007-2016 by the Sphinx team, see AUTHORS. :license: BSD, see LICENSE for details. """ import re from six import iteritems, itervalues, text_type, string_types from six.moves import cPickle as pickle from docutils.nodes import raw, comment, title, Text, NodeVisitor, SkipNode from os import path from sphinx.util import jsdump, rpartition from sphinx.util.pycompat import htmlescape class SearchLanguage(object): """ 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_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 language_name = None stopwords = set() js_stemmer_rawcode = 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'\w+(?u)') def __init__(self, options): self.options = options self.init(options) def init(self, options): """ Initialize the class with the options the user has given. """ def split(self, input): """ 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): """ 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): """ 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 ( len(word) < 3 or word in self.stopwords or word.isdigit() )))) # SearchEnglish imported after SearchLanguage is defined due to circular import from sphinx.search.en import SearchEnglish def parse_stop_word(source): """ parse snowball style word list like this: * http://snowball.tartarus.org/algorithms/finnish/stop.txt """ result = 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 = { '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(object): """ 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): return self.PREFIX + jsdump.dumps(data) + self.SUFFIX def loads(self, s): 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, f): f.write(self.dumps(data)) def load(self, f): return self.loads(f.read()) js_index = _JavaScriptIndex() class WordCollector(NodeVisitor): """ A special visitor that collects words for the `IndexBuilder`. """ def __init__(self, document, lang): NodeVisitor.__init__(self, document) self.found_words = [] self.found_title_words = [] self.lang = lang def dispatch_visit(self, node): nodetype = type(node) if issubclass(nodetype, comment): raise SkipNode if issubclass(nodetype, raw): # 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)', '', node.astext()) nodetext = re.sub(r'(?is)', '', nodetext) nodetext = re.sub(r'<[^<]+?>', '', nodetext) self.found_words.extend(self.lang.split(nodetext)) raise SkipNode if issubclass(nodetype, Text): self.found_words.extend(self.lang.split(node.astext())) elif issubclass(nodetype, title): self.found_title_words.extend(self.lang.split(node.astext())) class IndexBuilder(object): """ Helper class that creates a searchindex based on the doctrees passed to the `feed` method. """ formats = { 'jsdump': jsdump, 'pickle': pickle } def __init__(self, env, lang, options, scoring): self.env = env # filename -> title self._titles = {} # stemmed word -> set(filenames) self._mapping = {} # stemmed words in titles -> set(filenames) self._title_mapping = {} # word -> stemmed word self._stem_cache = {} # objtype -> index self._objtypes = {} # objtype index -> (domain, type, objname (localized)) self._objnames = {} # add language-specific SearchLanguage instance lang_class = languages.get(lang) if lang_class is None: self.lang = SearchEnglish(options) elif isinstance(lang_class, str): module, classname = lang_class.rsplit('.', 1) lang_class = getattr(__import__(module, None, None, [classname]), 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('utf-8') else: self.js_scorer_code = u'' def load(self, stream, format): """Reconstruct from frozen data.""" if isinstance(format, string_types): 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['filenames'] self._titles = dict(zip(index2fn, frozen['titles'])) def load_terms(mapping): rv = {} for k, v in iteritems(mapping): if isinstance(v, int): rv[k] = set([index2fn[v]]) else: rv[k] = set(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, format): """Dump the frozen index to a stream.""" if isinstance(format, string_types): format = self.formats[format] format.dump(self.freeze(), stream) def get_objects(self, fn2index): rv = {} otypes = self._objtypes onames = self._objnames for domainname, domain in sorted(iteritems(self.env.domains)): for fullname, dispname, type, docname, anchor, prio in \ sorted(domain.get_objects()): # XXX use dispname? if docname not in fn2index: continue if prio < 0: continue fullname = htmlescape(fullname) prefix, name = rpartition(fullname, '.') 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 unicode() to fire translation proxies onames[typeindex] = (domainname, type, text_type(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): rvs = {}, {} for rv, mapping in zip(rvs, (self._mapping, self._title_mapping)): for k, v in iteritems(mapping): 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): """Create a usable data structure for serializing.""" filenames, titles = zip(*sorted(self._titles.items())) fn2index = dict((f, i) for (i, f) in enumerate(filenames)) terms, title_terms = self.get_terms(fn2index) objects = self.get_objects(fn2index) # populates _objtypes objtypes = dict((v, k[0] + ':' + k[1]) for (k, v) in iteritems(self._objtypes)) objnames = self._objnames return dict(filenames=filenames, titles=titles, terms=terms, objects=objects, objtypes=objtypes, objnames=objnames, titleterms=title_terms, envversion=self.env.version) def label(self): return "%s (code: %s)" % (self.lang.language_name, self.lang.lang) def prune(self, filenames): """Remove data for all filenames not in the list.""" new_titles = {} for filename in filenames: if filename in self._titles: new_titles[filename] = self._titles[filename] self._titles = new_titles for wordnames in itervalues(self._mapping): wordnames.intersection_update(filenames) for wordnames in itervalues(self._title_mapping): wordnames.intersection_update(filenames) def feed(self, filename, title, doctree): """Feed a doctree to the index.""" self._titles[filename] = title visitor = WordCollector(doctree, self.lang) doctree.walk(visitor) # memoize self.lang.stem def stem(word): 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: word = stem(word) if _filter(word): self._title_mapping.setdefault(word, set()).add(filename) for word in visitor.found_words: word = stem(word) if word not in self._title_mapping and _filter(word): self._mapping.setdefault(word, set()).add(filename) def context_for_searchtool(self): return dict( search_language_stemming_code = self.lang.js_stemmer_code, search_language_stop_words = jsdump.dumps(sorted(self.lang.stopwords)), search_scorer_tool = self.js_scorer_code, ) def get_js_stemmer_rawcode(self): if self.lang.js_stemmer_rawcode: return path.join( path.dirname(path.abspath(__file__)), 'non-minified-js', self.lang.js_stemmer_rawcode )