def test_correct_query():
schema = fields.Schema(a=fields.TEXT(spelling=True), b=fields.TEXT)
ix = RamStorage().create_index(schema)
w = ix.writer()
w.add_document(a=u("alfa bravo charlie delta"))
w.add_document(a=u("delta echo foxtrot golf"))
w.add_document(a=u("golf hotel india juliet"))
w.add_document(a=u("juliet kilo lima mike"))
w.commit()
s = ix.searcher()
qp = QueryParser("a", ix.schema)
qtext = u('alpha ("brovo november" OR b:dolta) detail')
q = qp.parse(qtext, ix.schema)
c = s.correct_query(q, qtext)
assert c.query.__unicode__() == '(a:alfa AND (a:"bravo november" OR b:dolta) AND a:detail)'
assert c.string == 'alfa ("bravo november" OR b:dolta) detail'
qtext = u('alpha b:("brovo november" a:delta) detail')
q = qp.parse(qtext, ix.schema)
c = s.correct_query(q, qtext)
assert c.query.__unicode__() == '(a:alfa AND b:"brovo november" AND a:delta AND a:detail)'
assert c.string == 'alfa b:("brovo november" a:delta) detail'
hf = highlight.HtmlFormatter(classname="c")
assert c.format_string(hf) == '<strong class="c term0">alfa</strong> b:("brovo november" a:delta) detail'
def search(self, query, page= -1, page_size=10):
search_results = list()
qp_artist = QueryParser('title', self.artist_searcher.schema)
query = qp_artist.parse(unicode(query))
if page < 1:
artist_hits = self.artist_searcher.search(query, limit=None, sortedby='title')
else:
artist_hits = self.artist_searcher.search(query, page, page_size, sortedby='title')
for hit in artist_hits:
search_results.append(SearchResult(self._artist_from_document(hit), Type.ARTIST))
qp_album = QueryParser('title', self.album_searcher.schema)
query = qp_album.parse(unicode(query))
if page < 1:
album_hits = self.album_searcher.search(query, limit=None, sortedby='title')
else:
album_hits = self.album_searcher.search(query, page, page_size, sortedby='title')
for hit in album_hits:
search_results.append(SearchResult(self._album_from_document(hit), Type.ALBUM))
qp_track = QueryParser('title', self.track_searcher.schema)
query = qp_track.parse(unicode(query))
if page < 1:
track_hits = self.track_searcher.search(query, limit=None, sortedby='title')
else:
track_hits = self.track_searcher.search(query, page, page_size, sortedby='title')
for hit in track_hits:
search_results.append(SearchResult(self._track_from_document(hit), Type.TRACK))
return search_results
def test_correct_query():
schema = fields.Schema(a=fields.TEXT(), b=fields.TEXT)
with TempIndex(schema) as ix:
with ix.writer() as w:
w.add_document(a=u"alfa bravo charlie delta")
w.add_document(a=u"delta echo foxtrot golf")
w.add_document(a=u"golf hotel india juliet")
w.add_document(a=u"juliet kilo lima mike")
with ix.searcher() as s:
qp = QueryParser("a", ix.schema)
qtext = u'alpha ("brovo november" OR b:dolta) detail'
q = qp.parse(qtext, ix.schema)
c = s.correct_query(q, qtext)
cq = c.query
assert isinstance(cq, query.And)
assert cq[0].text == "alfa"
assert isinstance(cq[1], query.Or)
assert isinstance(cq[1][0], query.Phrase)
assert cq[1][0].words == ["bravo", "november"]
qtext = u'alpha b:("brovo november" a:delta) detail'
q = qp.parse(qtext, ix.schema)
c = s.correct_query(q, qtext)
assert c.query.__unicode__() == '(a:alfa AND b:"brovo november" AND a:delta AND a:detail)'
assert c.string == 'alfa b:("brovo november" a:delta) detail'
hf = highlight.HtmlFormatter(classname="c")
assert c.format_string(hf) == '<strong class="c term0">alfa</strong> b:("brovo november" a:delta) detail'
def test_wildcard_existing_terms():
s = fields.Schema(key=fields.ID, value=fields.TEXT)
ix = RamStorage().create_index(s)
w = ix.writer()
w.add_document(key=u("a"), value=u("alfa bravo bear charlie delta"))
w.add_document(key=u("a"), value=u("boggle echo render rendering renders"))
w.commit()
r = ix.reader()
qp = QueryParser("value", ix.schema)
def words(terms):
z = []
for t in terms:
assert t[0] == "value"
z.append(t[1])
return " ".join(sorted(z))
q = qp.parse(u("b*"))
ts = q.existing_terms(r)
assert_equal(ts, set())
ts = q.existing_terms(r, expand=True)
assert_equal(words(ts), "bear boggle bravo")
q = qp.parse(u("[a TO f]"))
ts = q.existing_terms(r)
assert_equal(ts, set())
ts = q.existing_terms(r, expand=True)
assert_equal(words(ts), "alfa bear boggle bravo charlie delta echo")
q = query.Variations("value", "render")
ts = q.existing_terms(r, expand=False)
assert_equal(ts, set())
ts = q.existing_terms(r, expand=True)
assert_equal(words(ts), "render rendering renders")
def find(q):
ix = Index()
parser = QueryParser("content", schema=SCHEMA)
print parser.parse(unicode(q))
results = ix.find(q)
if len(results):
print "Found in %d documents" % len(results)
else:
print "Not found"
def _search_tag_groups(self, is_filtering_tags):
seen = None
query_parser = QueryParser("tag", self._index.schema)
options = {"limit": None, "groupedby": sorting.FieldFacet("tag", allow_overlap=True), "maptype": sorting.Count}
with self._index.searcher() as searcher:
total = searcher.search(query_parser.parse("*"), **options).groups()
if not is_filtering_tags:
seen = searcher.search(query_parser.parse("* AND flags:%s" % Status.SEEN), **options).groups()
return seen, total
class WhooshGuess(object):
def __init__(self):
self.storage = RamStorage()
schema = Schema(key=ID(stored=True), \
ask=BOOLEAN(stored=True), \
content=TEXT(stored=True, analyzer=RegexTokenizer()))
self.ix = self.storage.create_index(schema)
self.writer = self.ix.writer()
self.is_train = False
for s in greeting.split('\n'):
self.train(u'matchinggreeting', s)
@property
def is_ok(self):
return self.is_train
def train(self, key, line):
splits = u' '.join(list(lang.tokenizezh(line)))
ask = lang.is_question(key)
#print ask
#print splits
self.writer.add_document(key=key, content=splits, ask=ask)
def train_ok(self):
self.writer.commit(optimize=True)
self.searcher = self.ix.searcher()
self.parser = QueryParser("content", schema=self.ix.schema)
self.is_train = True
def guess(self, s, is_ask = None):
assert(self.is_train)
keys = list(lang.keyword(s))
if len(keys) == 0:
return ''
# MUST contain the keys
keys = u' '.join(keys)
splits = u' '.join(list(lang.tokenizezh(s)))
#q = self.parser.parse(splits + ' OR ' + keys)
q1 = self.parser.parse(keys)
q2 = self.parser.parse(splits)
q = q1 | q2
#print unicode(q)
if not is_ask:
ask = query.Term(u"ask", lang.is_question(s))
else:
ask = query.Term(u"ask", is_ask)
results = self.searcher.search(q, filter=ask)
for hit in results:
return hit['key']
return ''
def update_changeset_index(self):
idx = open_dir(self.index_location, indexname=CHGSET_IDX_NAME)
with idx.searcher() as searcher:
writer = idx.writer()
writer_is_dirty = False
try:
indexed_total = 0
repo_name = None
for repo_name, repo in self.repo_paths.items():
# skip indexing if there aren't any revs in the repo
num_of_revs = len(repo)
if num_of_revs < 1:
continue
qp = QueryParser('repository', schema=CHGSETS_SCHEMA)
q = qp.parse(u"last:t AND %s" % repo_name)
results = searcher.search(q)
# default to scanning the entire repo
last_rev = 0
start_id = None
if len(results) > 0:
# assuming that there is only one result, if not this
# may require a full re-index.
start_id = results[0]['raw_id']
last_rev = repo.get_changeset(revision=start_id).revision
# there are new changesets to index or a new repo to index
if last_rev == 0 or num_of_revs > last_rev + 1:
# delete the docs in the index for the previous
# last changeset(s)
for hit in results:
q = qp.parse(u"last:t AND %s AND raw_id:%s" %
(repo_name, hit['raw_id']))
writer.delete_by_query(q)
# index from the previous last changeset + all new ones
indexed_total += self.index_changesets(writer,
repo_name, repo, start_id)
writer_is_dirty = True
log.debug('indexed %s changesets for repo %s' % (
indexed_total, repo_name)
)
finally:
if writer_is_dirty:
log.debug('>> COMMITING CHANGES TO CHANGESET INDEX<<')
writer.commit(merge=True)
log.debug('>>> FINISHED REBUILDING CHANGESET INDEX <<<')
else:
writer.cancel
log.debug('>> NOTHING TO COMMIT TO CHANGESET INDEX<<')
def GET(self):
url = web.input().get('url')
qp = QueryParser('url', schema = ix.schema)
q = qp.parse(url)
r = searcher.search(q, limit = 1)
doc = list(r)[0]
qp = QueryParser('refers_to', schema = ix.schema)
q = qp.parse(url)
refs = searcher.search(q, limit = 25)
return render.show(doc, refs, DocumentSearcher(ix))
def test_query_terms():
qp = QueryParser("a", None)
q = qp.parse("alfa b:(bravo OR c:charlie) delta")
assert sorted(q.iter_all_terms()) == [("a", "alfa"), ("a", "delta"),
("b", "bravo"), ("c", "charlie")]
q = qp.parse("alfa brav*")
assert sorted(q.iter_all_terms()) == [("a", "alfa")]
q = qp.parse('a b:("b c" d)^2 e')
tokens = [(t.fieldname, t.text, t.boost) for t in q.all_tokens()]
assert tokens == [('a', 'a', 1.0), ('b', 'b', 2.0), ('b', 'c', 2.0),
('b', 'd', 2.0), ('a', 'e', 1.0)]
def bm25_retrieve (query, num_res):
ix = open_dir('index')
searcher = ix.searcher()
query_terms = query.split(' ')
bool_query = ''
for term in query_terms:
bool_query += term + ' OR '
parser = QueryParser("content", ix.schema)
real_query = parser.parse(bool_query)
results = searcher.search(real_query, limit = num_res)
new_results = {}
res_len = len(results)
#assume that top 10 results is relevant
ri = {}
ni = {}
R = 10
N = res_len
for term in query_terms:
ri[term] = 0
ni[term] = 0
#for each term in the query, calculate its ri and ni
for term in query_terms:
for res in searcher.search(real_query):
if term in res['content']:
ri[term] += 1
parser = QueryParser("content", ix.schema)
term_query = parser.parse(term)
ni[term] = len(searcher.search(term_query, limit = 500))
#for each document, calculate its bm25 score
if num_res > 10:
for res in results:
new_results[res['id']] = 0
for res in results:
for term in query_terms:
reg = re.compile(term)
#fi is the i's term's frequency in the document
fi = len(reg.findall(res['content']))
k1 = 1.5
b = 0.75
avdl = 200
K = k1 * (1 - b + b * len(res['content']) / 200)
new_results[res['id']] += math.log((ri[term]+0.5)*(N-ni[term]-R+ri[term]+0.5)/(R-ri[term]+0.5)/(ni[term]-ri[term]+0.5)) * (k1 + 1) * fi / (K + fi)
return new_results
def contacts(self, query):
if query:
to = QueryParser('to', self._index.schema)
cc = QueryParser('cc', self._index.schema)
bcc = QueryParser('bcc', self._index.schema)
with self._index.searcher() as searcher:
to = searcher.search(to.parse("*%s*" % query), limit=None,
groupedby=sorting.FieldFacet('to', allow_overlap=True)).groups()
cc = searcher.search(cc.parse("*%s*" % query), limit=None,
groupedby=sorting.FieldFacet('cc', allow_overlap=True)).groups()
bcc = searcher.search(bcc.parse("*%s*" % query), limit=None,
groupedby=sorting.FieldFacet('bcc', allow_overlap=True)).groups()
return flatten([to, cc, bcc])
return []
def get_answer(message):
if '/' in message[0]:
return None
rx = r'jova,?\s(.+)$'
m = re.match(rx, message)
if not m or len(m.groups(1)) < 1:
return None
global ix
search_terms = m.groups(1)[0]
parser = QueryParser("content", ix.schema)
qry = parser.parse(search_terms)
with ix.searcher() as searcher:
results = searcher.search(qry)
result = None
if len(results) == 0:
return None
if len(results) == 1:
result = results[0]
else:
result = random.choice(results)
if result is None or 'path' not in result:
return None
return result['path'], 'plain-text'
return None
def searchNote(self):
pattern = self.searchEdit.text()
qres = []
with self.ix.searcher() as searcher:
queryp = QueryParser("content", self.ix.schema)
queryp.add_plugin(RegexPlugin())
query = queryp.parse('r"' + pattern + '"')
# r"pattern" is the desired regex term format
pathFacet = sorting.FieldFacet("path")
scores = sorting.ScoreFacet()
results = searcher.search(
query, limit=None, sortedby=[pathFacet, scores]) # default limit is 10!
for r in results:
listItem = QListWidgetItem()
title = r['title']
text = r['path']
term = r.highlights("content")
qres.append([title, text, term])
html = """
<style>
body { font-size: 14px; }
.path { font-size: 12px; color: #009933; }
</style>
"""
for ti, te, hi in qres:
html += ("<p><a href='" + te + "'>" + ti +
"</a><br/><span class='path'>" +
te + "</span><br/>" + hi + "</p>")
self.searchView.setHtml(html)
def findsnippets(query, daterange=None, page=1,ndocs=PER_PAGE, MAX_SEARCH_RESULTS=MAX_SEARCH_RESULTS,distribution=True):
ix = open_dir(indexdir)
res=[]
daycount={}
with ix.searcher() as searcher:
parser = QueryParser("content", ix.schema)
myquery = parser.parse(query)
if daterange!=None:
datequery=DateRange("date", daterange[0],daterange[1])
results = searcher.search(datequery & myquery,limit=MAX_SEARCH_RESULTS)
else:
results = searcher.search(myquery,limit=MAX_SEARCH_RESULTS)
if distribution:
myfacet=Facets().add_field("date",maptype=sorting.Count)
if daterange!=None:
datequery=DateRange("date", daterange[0],daterange[1])
daycount_orig=searcher.search(datequery & myquery, groupedby=myfacet,limit=MAX_SEARCH_RESULTS)
else:
daycount_orig=searcher.search(myquery, groupedby=myfacet,limit=MAX_SEARCH_RESULTS)
for day in daycount_orig.groups():
daycount[day]=daycount_orig.groups()[day]
for result in results[(page-1)*ndocs:page*ndocs]:
doc=PoorDoc(docidentifier=result['identifier'],date=int(result['date'].strftime("%Y%m%d")))
snippet=result.highlights("content", text=doc.getcontent())
res.append({'title':result['title'],'identifier':result['identifier'],'date':result['date'],'snippet':snippet})
total_docs=results.estimated_length()
return res, total_docs, daycount
else:
for result in results[(page-1)*ndocs:page*ndocs]:
doc=PoorDoc(docidentifier=result['identifier'],date=int(result['date'].strftime("%Y%m%d")))
snippet=result.highlights("content", text=doc.getcontent())
res.append({'title':result['title'],'identifier':result['identifier'],'date':result['date'],'snippet':snippet})
total_docs=results.estimated_length()
return res, total_docs
def finddocs(query, daterange=None, page=1,ndocs=PER_PAGE, MAX_SEARCH_RESULTS=MAX_SEARCH_RESULTS,distribution=True):
ix = open_dir(indexdir)
res=[]
daycount={}
with ix.searcher() as searcher:
parser = QueryParser("content", ix.schema)
myquery = parser.parse(query)
if distribution:
myfacet=Facets().add_field("date",maptype=sorting.UnorderedList)
if daterange!=None:
datequery=DateRange("date", daterange[0],daterange[1])
results=searcher.search(datequery & myquery, groupedby=myfacet,limit=MAX_SEARCH_RESULTS)
else:
results=searcher.search(myquery, groupedby=myfacet,limit=MAX_SEARCH_RESULTS)
doc_cnt=0
for day,docs in results.groups().iteritems():
daycount[day]=len(docs)
for result in docs:
if doc_cnt in range((page-1)*ndocs,page*ndocs):
res.append({'title':searcher.stored_fields(result)['title'],'identifier':searcher.stored_fields(result)['identifier'],'date':searcher.stored_fields(result)['date']})
doc_cnt+=1
total_docs=results.estimated_length()
return res, total_docs, daycount
else:
if daterange!=None:
datequery=DateRange("date", daterange[0],daterange[1])
results=searcher.search(datequery & myquery, limit=MAX_SEARCH_RESULTS)
else:
results=searcher.search(myquery, limit=MAX_SEARCH_RESULTS)
for result in results[(page-1)*ndocs:page*ndocs]:
res.append({'title':result['title'],'identifier':result['identifier'],'date':result['date']})
total_docs=results.estimated_length()
return res, total_docs
def searchNote(self):
""" Sorting criteria: "title > path > content"
Search matches are organized into html source.
"""
pattern = self.searchEdit.text()
if not pattern:
return
results = []
print("Searching using", pattern)
with self.ix.searcher() as searcher:
matches = []
for f in ["title", "path", "content"]:
queryp = QueryParser(f, self.ix.schema)
queryp.add_plugin(RegexPlugin())
# r"pattern" is the desired regex term format
query = queryp.parse('r"' + pattern + '"')
ms = searcher.search(query, limit=None) # default limit is 10!
for m in ms:
if not m in matches:
matches.append(m)
for r in matches:
title = r['title']
path = r['path']
term = r.highlights("content")
results.append([title, path, term])
html = ""
for title, path, hi in results:
html += ("<p><a href='" + path + "'>" + title +
"</a><br/><span class='path'>" +
path + "</span><br/>" + hi + "</p>")
self.searchView.setHtml(html)
print("Finished searching", pattern)
def __call__(self, query):
"""search"""
query = unicode(query)
query_parser = QueryParser("description", schema=self.ix.schema)
myquery = query_parser.parse(query)
# Old code: too strict
# extendedquery = Or([myquery] +
# [Term(field, query) for field in self.keywords])
# New code: too permissive
# extendedquery = [myquery]
excluded = set(["AND", "OR", "NOT"])
terms = [i for i in query.split() if i not in excluded]
# for field in self.keywords:
# extendedquery.extend([Term(field, term) for term in terms])
# extendedquery = Or(extendedquery)
# Code should look something like
# Or([myquery] + [Or(
# extendedquery = [myquery]
extendedquery = And(
[
Or(
[myquery]
+ [Term("description", term), Term("name", term)]
+ [Term(field, term) for field in self.keywords]
)
for term in terms
]
)
# perform the search
searcher = self.ix.searcher()
return [i["name"] for i in searcher.search(extendedquery, limit=None)]
def populateTable(self, searchterm=None):
self.infoTable.clear()
self.infoTable.setHorizontalHeaderLabels( [ "Title", "Authors", "Tags", "Year", "Read" ] )
self.infoTable.setRowCount(0)
self.infoTable.horizontalHeader().setResizeMode(0, QHeaderView.Stretch)
self.infoTable.verticalHeader().hide()
if( searchterm == None or searchterm == "" ):
papers = KKDocument.objects.all()
for p in papers:
a = ', '.join([x.name for x in p.authors.all()])
t = ', '.join([x.tag for x in p.tags.all()])
self.newEntry(p.title, a, t, p.year, p)
return # were done here - all papers printed
# only if there is a searchterm:
# search full text with whoosh
print "FINDING %s" % searchterm
searcher = self.whoosh_ix.searcher()
parser = QueryParser("content", schema = self.whoosh_schema)
query = parser.parse(unicode(searchterm))
whoosh_results = searcher.search(query)
print "FOUND", len(whoosh_results), "Objects"
for r in whoosh_results:
p = KKDocument.objects.get(localFile=r['path'])
a = ', '.join([x.name for x in p.authors.all()])
t = ', '.join([x.tag for x in p.tags.all()])
self.newEntry(p.title, a, t, p.year, p)
def OnlyOneSearch(queryStr="",index=".index"):
ix=get_index(index)
searcher = ix.searcher()
parser = QueryParser("name", schema = ix.schema)
query=parser.parse(queryStr)
results = searcher.search(query)
return results
def search_datasets(self, search_phrase, limit=None):
"""Search for just the datasets."""
from collections import defaultdict
from whoosh.qparser import QueryParser
parser = QueryParser("doc", schema=self.dataset_index.schema)
query = parser.parse(search_phrase)
datasets = defaultdict(SearchResult)
with self.dataset_index.searcher() as searcher:
results = searcher.search(query, limit=limit)
for hit in results:
vid = hit.get('vid')
bvid = hit.get('bvid')
type = hit.get('type')
datasets[bvid].vid = bvid
if type == 'b':
datasets[bvid].bundle_found = True
datasets[bvid].b_score += hit.score
else:
datasets[bvid].p_score += hit.score
datasets[bvid].partitions.add(vid)
return datasets
def get(self):
wikiResults = None
jobResults = None
projectResults = None
if 'searchScope' in request.args and 'searchTerm' in request.args:
searchTerm = request.args.get('searchTerm')
searchScope = request.args.get('searchScope')
index = open_dir('app/search/index')
parser = QueryParser("content", schema=index.schema)
with index.searcher() as searcher:
if searchScope in ['everything', 'wiki']:
wikiResults = [{'title':result['title'], 'url':'http://jhcwiki.jhc.co.uk/wiki/index.php/' + result['title'].replace(' ', '_')} for result in searcher.search(parser.parse(searchTerm), limit=200) if result['type'] == 'WIKI']
if searchScope in ['everything', 'jobs']:
jobResults = [{'title':result['title'], 'url':''} for result in searcher.search(parser.parse(searchTerm), limit=200) if result['type'] == 'JOB']
if searchScope in ['everything', 'projects']:
projectResults = [{'title':result['title'], 'url':url_for('projects.projectDetail', projectCode = result['title'].split('-')[0].strip())} for result in searcher.search(parser.parse(searchTerm), limit=200) if result['type'] == 'PROJECT']
else:
searchTerm = ''
searchScope = 'everything'
return render_template('search/search.html', wikiResults=wikiResults, jobResults=jobResults , projectResults=projectResults, searchTerm=searchTerm, searchScope=searchScope, title="Search")
def grid_search(rookie_avg, surround, fragment_char_limit, whoosh_results, corpus, query_string):
'''
find best top parameter for whoosh snips. top parameter controls how many ... delimited fragments
best = minimize distance w/ average size of rookie snip
'''
best = {""}
best_distance_so_far = 1000000000
index = open_dir("indexes/{}/".format(corpus))
corpusid = getcorpusid(corpus)
for top in range(1, 5): # basically fixed for now
with index.searcher() as srch:
query_parser = QueryParser("content", schema=index.schema)
qry = query_parser.parse(query_string)
results = srch.search(qry, limit=None)
results.fragmenter.surround = surround
results.fragmenter.maxchars = fragment_char_limit
sum_ = 0
for s_ix, a in enumerate(results):
path = a.get("path").replace("/", "")
sents = get_preproc_sentences(path, corpusid)
sss = unicode(" ".join(sents).encode("ascii", "ignore"))
sss = str(a.highlights("content", text=sss, top=top))
sum_ += len(sss)
diff = abs(rookie_avg - sum_/len(results))
print "top of {} gives diff of {}".format(top, diff)
if diff < best_distance_so_far:
best = top
best_distance_so_far = diff
print "best top = {}".format(best)
return best
def index_query(environ, **kwargs):
"""
Return a generator of tiddlers that match
the provided arguments.
"""
logging.debug('entering with %s', environ)
print 'getting called on index_query'
config = environ['tiddlyweb.config']
#store = environ['tiddlyweb.store']
query_parts = []
for field, value in kwargs.items():
if field == 'tag':
field = 'tags'
query_parts.append('%s:%s' % (field, value))
query_string = ' '.join(query_parts)
print 'getting inside on index_query'
schema = config.get('wsearch.schema', SEARCH_DEFAULTS['wsearch.schema'])
searcher = get_searcher(config)
parser = QueryParser('text', schema=Schema(**schema))
query = parser.parse(query_string)
logging.debug('query parsed to %s' % query)
results = searcher.search(query)
def tiddler_from_result(result):
print 'r', result
bag, title = result['id'].split(':', 1)
tiddler = Tiddler(title, bag)
return tiddler
#return store.get(tiddler)
for result in results:
yield tiddler_from_result(result)
return
def stage3():
ix = open_dir(index_directory)
if not ix:
print "No index"
return
parser = QueryParser("content", ix.schema)
with ix.searcher() as searcher:
try:
while True:
search_phrase = raw_input('Search phrase: ')
if not search_phrase: continue
search_phrase = search_phrase.decode(sys.stdin.encoding)
myquery = parser.parse(search_phrase)
results = searcher.search(myquery)
if results:
for result in results:
print "%s - %s (%s)" % (result['url'],result['title'], result['company'])
else:
print "No matching results"
print "\r\n"
except KeyboardInterrupt:
print "\nBae..."
return
def search(q, default_field="content"):
ix = index.open_dir(SEARCH_INDEX)
searcher = ix.searcher()
parser = QueryParser(default_field, schema=ix.schema)
query = parser.parse(q)
results = searcher.search(query)
return results
def search(request):
hits = []
results = []
query = request.GET.get('q', None)
newspaper = request.GET.get('newspaper', None)
if newspaper is not None:
index_dir = "C:/Django Projects/searcher/modules/index" + newspaper
ix = index.open_dir(index_dir)
searcher = ix.searcher()
if query is not None and query != u"":
query = query.replace('+', ' AND ').replace(' -', ' NOT ')
parser = QueryParser("content", schema=ix.schema)
try:
qry = parser.parse(query)
except:
qry = None
if qry is not None:
hits = searcher.search(qry)
for hit in hits:
title = hit['title']
url = hit['url']
date = hit['date']
highlights = hit.highlights("content")
keywords_list = [keyword for keyword, score in searcher.key_terms_from_text("content", hit['content'])]
keywords = ", ".join(keywords_list)
results.append(Result(title,url,date,highlights,keywords))
variables = RequestContext(request, {
'query': query,
'hits': results
})
return render_to_response('search.html', variables)
def crearEsquemaCorreo():
correo1 = "1.txt"
correoEsquema = Schema(remitente=ID(stored=True), destinatarios=KEYWORD(stored=True), fecha=DATETIME(stored=True),asunto=KEYWORD(stored=True), cuerpo=TEXT(stored=True))
if not os.path.exists("indexCorreo"):
os.mkdir("indexCorreo")
iC = index.create_in("indexCorreo", correoEsquema)
iC = open_dir("indexCorreo")
writer = iC.writer()
fecha = "20101015"
date_email = datetime.strptime(fecha, "%Y%m%d")
writer.add_document(remitente=u"unoarrobagmail.com", destinatarios=u"dosarrobagmail.com tresarrobagmail.com", fecha=date_email,asunto=u"Contrato de compraventa con la constructora",cuerpo=u"Estimados socios: ya hemos firmado el contrato de compraventa con el cliente preferencial. Espero noticias vuestras. Un saludo,")
#writer.add_document(email=u"dosarrobagmail.com", name=u"Pedro Guerra")
#writer.add_document(email=u"tresarrobagmail.com", name=u"Ana Montero")
#writer.add_document(email=u"cuatroarrobagmail.com", name=u"Luis Pontes")
writer.commit()
qp = QueryParser("remitente", schema=iC.schema)
q = qp.parse(u"unoarrobagmail.com")
with iC.searcher() as s:
results = s.search(q)
print results[0]
def search_files(index_dir, content):
"""
search file content in index
if not hit: return False
if hit: return results
"""
index_exist = index.exists_in(index_dir)
if not index_exist:
print ("index not exist")
return False
ix = index.open_dir(index_dir)
content = unicode(content)
with ix.searcher() as searcher:
parser = QueryParser("content", ix.schema)
query = parser.parse(content)
# whoosh.searching.Results
results = searcher.search(query)
print (type(results))
l = len(results)
print l
for h in results:
# whoosh.searching.Hit
print type(h)
print h
return results
return False
def test_correct_spell_field():
ana = analysis.StemmingAnalyzer()
schema = fields.Schema(text=fields.TEXT(analyzer=ana, spelling=True))
with TempIndex(schema) as ix:
with ix.writer() as w:
w.add_document(text=u"rendering shading modeling reactions")
with ix.searcher() as s:
text = s.schema["text"]
spell_text = s.schema["spell_text"]
r = s.reader()
words = [text.from_bytes(t) for t in r.lexicon("text")]
assert words == ["model", "reaction", "render", "shade"]
words = [spell_text.from_bytes(t) for t in r.lexicon("spell_text")]
assert words == ["modeling", "reactions", "rendering", "shading"]
qp = QueryParser("text", s.schema)
qtext = u"renderink"
q = qp.parse(qtext, s.schema)
r = s.search(q)
assert len(r) == 0
c = s.correct_query(q, qtext)
assert c.string == "rendering"
assert c.query == query.Term("text", "rendering")
hf = highlight.HtmlFormatter(classname="c")
assert c.format_string(hf) == '<strong class="c term0">rendering</strong>'
def search_song_by_title(title, index):
results_list = list()
qp = QueryParser('title', schema=index.schema)
q = qp.parse(u"{}".format(title))
with index.searcher() as searcher:
results = searcher.search(q)
for result in results:
data = {
'title': result['title'],
'artist': result['artist'],
'full_lyrics': result['full_lyrics'],
'lyrics': result['lyrics'],
'album': result['album']
}
results_list.append(data)
return results_list
def lookup(self, key, field="entity_id"):
if key == 'entities' or key is None:
return self._entities()
key = self._prep_key(key)
qp = QueryParser("object_id", schema=self.schema)
q = qp.parse(key)
lst = set()
with self.index.searcher() as searcher:
results = searcher.search(q, limit=None)
for result in results:
e = self.objects.get(result['object_id'], None)
if e is not None:
lst.add(e)
return b2u(list(lst))
def testBuscarPalabrasClave(autor):
"""
Busca las palabras clave del texto que acompaña al cuadro
"""
ix = whoosh.index.open_dir("ficheros/index")
parser = QueryParser("autor", ix.schema)
myquery = parser.parse(autor)
with ix.searcher() as searcher:
results = searcher.search(myquery)
print results
keywords = [
keyword
for keyword, score in results.key_terms("descripcion", numterms=4)
]
return keywords
def search(ix, search_key):
qp = QueryParser("body", schema=ix.schema, termclass=MyFuzzyTerm)
q = qp.parse(search_key)
try:
with ix.searcher() as s:
results = s.search(q)
data = [res['data'] for res in results]
return {
"hits": len(data),
"data": data,
"error": None,
"msg": "Success"
}
except Exception as e:
return {"hits":None, "data":None, "error":str(e),\
"msg":"Invalid search / unknown error"}
def search(query):
"""Search the stopindex for `query` using Whoosh."""
from info import IDX_NAME
ix = open_dir(IDX_NAME)
parser = QueryParser("name", ix.schema)
q = parser.parse(query)
with ix.searcher() as s:
results = s.search(q, limit=100)
if not results:
resp = []
else:
resp = [(r['name'], r['location'], r['sid']) for r in results]
return resp
def _search(self, query='', field=None, index=None, terms=False, limit=None):
''' query (exaxct mathch) search '''
index = index or self._default_index
ix = self.get_index(index)
fieldin = field or 'content'
qp = QueryParser(fieldin, ix.schema)
qp.add_plugin(ws.qparser.SingleQuotePlugin())
query = qp.parse(query, normalize=False)
with ix.searcher() as searcher:
if terms is True:
results = searcher.search(query, terms=True, limit=limit).matched_terms()
else:
results = list(searcher.search(query, limit=limit).items())
return results
def index():
search_field = request.args.get('search')
text = request.args.get('word')
if text == None:
text = ""
else:
pass
# text = "大学"
schema = Schema(title=TEXT(stored=True), content=TEXT, url=STORED, created_at=STORED, inn=STORED, out=STORED)
ix = open_dir('daigo_search_dir')
t = Tokenizer()
str_output = ""
for token in t.tokenize(text):
str_output += token.surface + " "
with ix.searcher() as searcher:
query_ = QueryParser("content", ix.schema)
query = query_.parse(str_output)
results = searcher.search(query)
if int(results.estimated_length())>2:
pass
else:
query = QueryParser("content", ix.schema, group=OrGroup).parse(str_output) # OR検索へ
results = searcher.search(query)
titles = []
timestamps = []
urls = []
oldr =""
for r in results:
if r != oldr:
titles.append(r['title'])
timestamps.append(r['inn']+"～"+r["out"])
urls.append(r["url"])
oldr = r
df = pd.DataFrame(columns=['動画タイトル', 'URL','この辺りかも'])
df["動画タイトル"] = titles
df["この辺りかも"] = timestamps
df["URL"] = urls
return render_template('search.html',word=text, search_result=df.to_html(classes='books',index=False,justify="center"))
def clusterVars(ind, path):
chars = []
# Importance (# lines of dialogue)
nameParser = QueryParser("name", schema=ind.schema)
for character in lists.characters:
query = nameParser.parse(character["Name"][0])
with ind.searcher() as searcher:
results = searcher.search(query, limit=None)
obj = {}
obj["Name"] = character["Name"][0]
obj["NumQuotes"] = 0
for result in results:
obj["NumQuotes"] += len(result['quote'].split('\n'))
chars.append(obj)
# Interest in Luke (Luke mentions), Force / Dark Side mentions
query1 = Or([Phrase("quote", ["red","five"]),Term("quote","luke"),Term("quote","skywalker")])
query2 = Or([Phrase("quote",["dark","side"]),Term("quote","force")])
with ind.searcher() as searcher:
results1 = searcher.search(query1, limit=None)
results2 = searcher.search(query2, limit=None, terms=True)
for character in chars:
character["InterestInLuke"] = 0
character["ForceMentions"] = 0
for result1 in results1:
if result1['name'] == character["Name"].upper():
character["InterestInLuke"] += 1
for result2 in results2:
if result2['name'] == character["Name"].upper():
character["ForceMentions"] += 1
# Take proportions
for character in chars:
if character["NumQuotes"] > 0:
character["InterestInLuke"] = (character["InterestInLuke"] + 0.0) / character["NumQuotes"]
character["ForceMentions"] = (character["ForceMentions"] + 0.0) / character["NumQuotes"]
# Character sentiment average
charSents = charSentiment(ind, path)
for charSent in charSents:
for character in chars:
if character["Name"] == charSent:
character["Sentiment"] = charSents[charSent]
return chars
def update_index_emailthreads(self, groupsio_token, config):
"""
Update the search index using the email archives
of groups.io subgroups. This method uses the Groups.io
API via methods defined in groupsio_util.py
"""
# Get the set of indexed ids:
# ------
indexed_ids = set()
p = QueryParser("kind", schema=self.ix.schema)
q = p.parse("emailthread")
with self.ix.searcher() as s:
results = s.search(q,limit=None)
for result in results:
indexed_ids.add(result['id'])
# Get the set of remote ids:
# ------
archive = get_mbox_archives(groupsio_token)
writer = self.ix.writer()
count = 0
# archives is a dictionary
# keys are IDs (urls)
# values are dictionaries
# Start by collecting all the things
remote_ids = set()
for k in archives.keys():
remote_ids.add(k)
# drop indexed_ids
for drop_id in indexed_ids:
writer.delete_by_term('id',drop_id)
# add remote_ids
for add_id in remote_ids:
item = archives[add_id]
self.add_emailthread(writer, item, config, update=False)
count += 1
writer.commit()
print("Done, updated %d Groups.io email threads in the index" % count)
def mostrar_lista(event):
lb.delete(0, END)
ix = open_dir(dir_index)
with ix.searcher() as searcher:
my_query = str(
en_fecha_comienzo.get()) + " TO " + str(en_fecha_fin)
qp = QueryParser("fechaPublicacion", ix.schema)
q = qp.parse(my_query)
results = searcher.search(q)
for r in results:
lb.insert(END, "Titulo: " + r['titulo'])
lb.insert(
END, "Fecha publicacion: " +
r['fechaPublicacion'].strftime('%Y/%m/%d'))
lb.insert(END, "")
def delete(cached):
"Remove file from index."
ix = open_dir(DIRECTORY, NAME)
with ix.searcher() as searcher, ix.writer() as w:
qp = QueryParser(u'cached', ix.schema)
q = qp.parse(unicode(cached))
results = searcher.search(q)
if len(results) == 0:
# Should only happen if user hasn't done run skid-update since
# adding the paper being deleted.
print 'Cached file %r not found in index.' % cached
elif len(results) == 1:
w.delete_document(results[0].docnum)
return True
else:
assert False, 'This should never happen. ' \
'Multiple (%s) results for %r found for cached file.' % (len(results), cached)
def test_multi(self):
import transaction
from whoosh_tm.datamanager import WhooshDataManager
from whoosh.qparser import QueryParser
from whoosh.index import create_in, open_dir
import threading
with TempDirectory() as d:
ix1 = create_in(d.path, dummy_schema)
ix2 = open_dir(d.path)
def add_document1():
dm1 = WhooshDataManager(ix1)
t = transaction.get()
t.join(dm1)
dm1.add_document(
title=u"First document",
path=u"/a",
content=u"This is the first document we've added!")
transaction.commit()
def add_document2():
dm2 = WhooshDataManager(ix2)
t = transaction.get()
t.join(dm2)
dm2.add_document(
title=u"Second document",
path=u"/b",
content=u"The second one is even more interesting!")
transaction.commit()
th1 = threading.Thread(target=add_document1)
th2 = threading.Thread(target=add_document2)
th1.start()
th2.start()
th1.join()
th2.join()
ix3 = open_dir(d.path)
with ix3.searcher() as searcher:
parser = QueryParser("content", ix3.schema)
results = searcher.search(parser.parse('second'))
self.assertEqual(len(results), 1)
self.assertEqual(results[0]["title"], "Second document")
def more_like_this(request, pid):
ix = index.open_dir(settings.WHOOSH_INDEX)
searcher = ix.searcher()
qp = QueryParser("pid", schema=ix.schema)
qq = qp.parse(pid)
doc = searcher.search(qq)
first = doc[0]
title = "%s: %s" % (first['type'], first['title'])
res = first.more_like_this("content", numterms=NUM_TERMS)
res = map(decorate, res)
ix.close()
messages.info(request, 'Posts similar to <b>%s</b>' % title)
return res
def ApartadoB(fecha):
ix = open_dir("index")
qp = QueryParser("fecha", schema=ix.schema)
query = unicode("'"+fecha+" to today'")
qp.add_plugin(DateParserPlugin(free=True))
q = qp.parse(query)
print(q)
s=ix.searcher()
results = s.search(q)
print(results)
for n in results:
print n.get("fecha")
print n.get("remitente")
print n.get("destinatarios")
print n.get("asunto")
print("*************\n")
return results
def readData(self, data):
results = None
# init searcher
with self.ix.searcher() as searcher:
parser = QueryParser(data["query_field"],
self.ix.schema,
plugins=[],
group=qparser.OrGroup)
# parser.add_plugin(qparser.FuzzyTermPlugin())
myquery = parser.parse(data["query_str"])
# print("-=-=-=-=-=-=", parser.filters())
results = [
dict(d_)
for d_ in searcher.search(myquery, limit=self.search_limit)
]
# print(parser, myquery)
return results
def get_wiki_articles(answers, ix):
qp = QueryParser("title", schema=ix.schema)
#print("Searching For: %s"%answers)
q = qp.parse(answers)
with ix.searcher() as s:
results = s.search(q, limit=1)
fname = None
if len(results) > 0:
for result in results:
fname = result['file_path']
title = result['title']
#print("Found: %s"%result['title'])
text = get_article_text(fname, title)
else:
text = None
return text
def getMentionGraph(self, coreUsers: list):
qp = QueryParser("mentionsUsers", schema=self.ix.schema)
tq = qp.parse("*") # something in mentionUsers
ret = defaultdict(lambda: defaultdict(int))
with self.getSearcher() as s:
for uid in coreUsers:
uq = whoosh.query.Term("user", uid) # limit to uid
q = whoosh.query.And([uq, tq])
res = s.search(q, limit=10000000)
thisUserContrib = ret[uid]
for r in res:
mentions = r["mentionsUsers"]
mentions = mentions.split(",")
for m in mentions:
thisUserContrib[m] += 1
return ret
def full_text_search(q):
ix = open_dir(const.TRANSCRIBED_WHOOSH_INDEX_DIR_PATH)
parser = QueryParser("transcript", ix.schema)
q = q.decode('utf-8')
query = parser.parse(q)
results = []
with ix.searcher() as searcher:
res = searcher.search(query)
for r in res:
results.append(
(r.fields()["transcription_id"], r.highlights("transcript")))
return results
def search(ix, query, project_ids=[], limit=10):
query_parser = QueryParser("name", schema=ix.schema)
whoosh_query = query_parser.parse(query)
is_project_filter = len(project_ids) > 0
ids = []
with ix.searcher() as searcher:
if is_project_filter:
project_id_terms = Or(
[Term("project_id", project_id) for project_id in project_ids])
results = searcher.search(whoosh_query,
filter=project_id_terms,
limit=limit)
else:
results = searcher.search(whoosh_query, limit=limit)
for result in results:
ids.append(result["id"])
return ids
class HamsterIndex(object):
def __init__(self, path):
if not os.path.exists(path):
os.mkdir(path)
self.index = create_in(path, MovieSchema)
self.index = open_dir(path)
self.q_parser = QueryParser("title", self.index.schema)
def index_movie(self, movie):
u = unicode
cast = movie["cast"]
actors = [c['name'] for c in cast]
director = movie["director"]
directors = [c['name'] for c in cast]
writer = self.index.writer()
writer.add_document(imdb_id=u(movie["_id"]),
title=u(movie["title"]),
genre=u(";".join(movie["genres"])),
plot=u(movie.get("plot", "")),
cast=u(";".join(actors)),
director=u(";".join(directors)),
rating=movie["rating"])
writer.commit()
def list_all(self):
num = 0
retval = []
with self.index.searcher() as searcher:
for res in searcher.reader().all_stored_fields():
num += 1
retval.append(res)
return retval
def query(self, querystring):
querystring = unicode(querystring)
myquery = self.q_parser.parse(querystring)
with self.index.searcher() as searcher:
results = searcher.search(myquery)
retval = []
for res in results:
retval.append(res.fields())
return retval
def busquedaTitulos(descripcion):
ix = open_dir("index")
# print ix.doc_count_all() #esto te dice cuantos has indexado por si no estas seguro
# for r in ix.searcher().documents():
# print("entrada: "+str(r))
qp = QueryParser("descripcion", schema=ix.schema)
q = qp.parse(unicode(str(descripcion)))
s = ix.searcher()
results = s.search(q)
titulos = []
for r in results:
titulos.append(r.get("titulo"))
return titulos
def query_article_by_key(key=""):
"""
查询文章内容通过key
"""
if len(key) <= 0:
return []
result = list()
index = open_dir(INDEX_PATH)
searcher = index.searcher()
parser = QueryParser("content", schema=index.schema)
result_list = searcher.search(parser.parse(key))
for hit in result_list:
result.append(hit)
return result
def index_search(search_terms, document_root):
qp = QueryParser("content", schema=markupserve_index.schema)
query = qp.parse(safe_unicode(search_terms))
results = collections.defaultdict(list)
split_terms = shlex.split(search_terms)
with markupserve_index.searcher() as searcher:
query_results = searcher.search(query, limit=None)
for result in query_results:
filename = result["path"].decode("utf-8").decode("unicode-escape")
results[filename].append(
result.highlights("content").decode("utf-8").decode(
"unicode-escape"))
return results
def search(self, searchStr, lang):
''' Search for a code snippet based off a search string (searchStr)
and the language
s.search("How to append to a list", "Python")
'''
with self.ix.searcher() as searcher:
qp = QueryParser("description", self.ix.schema, group=OrGroup)
# Since the index is singularized, we must search using a
# singularized string.
query = qp.parse(
unicode("(%s) AND (lang:%s)" %
(self.singularize(searchStr), lang)))
results = searcher.search(query)
returnThis = [(x['description'].lower(), x['path'])
for x in results]
return returnThis
def modify(self, name, metadata):
"""
Modify a document metadata
"""
# Let's check if the document exist
# It must be present in the index
qp = QueryParser("hash", schema=self.index.schema)
q = qp.parse(name)
with self.index.searcher() as s:
# No results
if len(s.search(q)) == 0:
raise IOError("Document does not exist")
# So we do have a document, we just need to update it
metadata['hash'] = name
# Write everything into the index
self.__update_index(metadata)
def test_can_search_id_and_summary_TODO(self):
#arrange
self.insert_ticket("test x")
self.insert_ticket("test 1")
fieldboosts = dict(
id=1,
summary=1,
)
mfp = MultifieldPlugin(list(fieldboosts.keys()), )
pins = [WhitespacePlugin, PhrasePlugin, mfp]
parser = QueryParser(None, WhooshBackend.SCHEMA, plugins=pins)
parsed_query = parser.parse("1")
result = self.whoosh_backend.query(parsed_query)
self.print_result(result)
self.assertEqual(2, result.hits)
def find(self, text):
'''
通过关键字查找一篇文章
:param text: 关键字
:return: 返回一个dict，包括path, title, content
'''
searcher = self.ix.searcher()
ret_list = []
parser = QueryParser("content", schema=self.ix.schema)
try:
word = parser.parse(text)
except:
word = None
if word is not None:
hits = searcher.search(word, limit=None)
for hit in hits:
ret_list.append(dict(hit))
return ret_list
def search(self, user_query):
'''Search the index for wikis that relate to the user's query.'''
# Exchange some speed by searching for variations of what the user
# queried for to improve search quality.
parser = QueryParser('content',
schema=self._ix.schema,
termclass=query.Variations)
q = parser.parse(u'{0}'.format(user_query))
results = []
with self._ix.searcher() as searcher:
hits = searcher.search(q)
hits.fragmenter = self._context_fragmenter
for hit in hits:
results.append(
SearchResult(hit['path'], hit.highlights('content')))
return results
def find(self, querystring, parser=None, **kwargs):
"""Parses querystring, runs the query in this index, and returns a
Result object. Any additional keyword arguments are passed to
Searcher.search() along with the parsed query.
:querystring: The query string to parse and search for.
:parser: A Parser object to use to parse 'querystring'.
The default is to use a standard qparser.QueryParser.
This object must implement a parse(str) method which returns a
query.Query instance.
:*returns*: searching.Results
"""
if parser is None:
from whoosh.qparser import QueryParser
parser = QueryParser(self.schema)
return self.searcher().search(parser.parse(querystring), **kwargs)
def search_similar(self, entity, skip=[]):
with self.index.searcher() as searcher:
qp = QueryParser("fingerprint", schema=self.index.schema)
# parser.add_plugin(qparser.FuzzyTermPlugin())
tokens = set()
for fp in entity.fingerprints:
tokens.update(fp.split())
if entity.country:
tokens.add('country:%s' % entity.country)
tokens = ' OR '.join(tokens)
tokens = ['(%s)' % tokens]
for uid in skip:
tokens.append('(NOT uid:%s)' % uid)
q = ' AND '.join(tokens)
q = qp.parse(q)
restrict_q = Term("uid", entity.uid)
for result in searcher.search(q, mask=restrict_q):
yield result.get('uid')
