def make_query(query_string):
q = Query(query_string)
q.skip = 1
q.top = 10
return q
def view_run_queries(request, topic_num):
# from experiment_configuration import bm25
num = 0
query_file_name = os.path.join(data_dir, topic_num + '.queries')
logging.debug(query_file_name)
start_time = timeit.default_timer()
query_list = []
with open(query_file_name, "r") as query_file:
while query_file and num < 200:
num += 1
line = query_file.readline()
# print line
parts = line.partition(' ')
# print parts
# TODO query_num = parts[0]
query_str = unicode(parts[2])
if query_str:
logging.debug(query_str)
q = Query(query_str)
q.skip = 1
# TODO response = bm25.search(q)
query_list.append(query_str)
else:
break
seconds = timeit.default_timer() - start_time
context_dict = {'topic_num': topic_num, 'seconds': seconds, 'num': num}
return render(request, 'base/query_test.html', context_dict)
def search(request):
"""
Accepts GET request containing query terms,
searches and returns results as JSON.
"""
# invalid HTTP method
if request.method != 'GET':
return HttpResponse(status=405)
# checks input for validity
query_terms = check_input(request.GET.get('q', ''))
# bad request
if not query_terms:
return HttpResponse(status=400)
# get exp ID and load experiment
exp_id = request.session.get('exp_id', False)
experiment = get_or_create_experiment(exp_id)
# execute query
engine = EngineFactory('bing', api_key="")
query = Query(query_terms, top=experiment['top'], result_type="image")
response = engine.search(query)
return HttpResponse(response.to_json(), content_type='application/json')
def run_query(query):
q = Query(query, top=50)
e = EngineFactory("Bing", api_key=bing_api_key)
response = e.search(q)
return response
def run_query(query, condition):
q = Query(query, top=100)
# check cache, if query is there, return results
# else send query to bing, and store the results in the cache
response = bing_engine.search(q)
mod = conditions[condition]
mod_response = mod(response)
return mod_response
def run_query(query, condition):
"""
runs a search query on Bing using the query string passed,
applies the relevant modifier function and returns the results
:param query: (str)the query input by the user
:param condition: (int)the interface condition applied to the user's profile
:return: (Response)the results of the search after applying the correct modifier function
"""
q = Query(query, top=100)
response = e.search(q)
mod = conditions[condition]
mod_results = mod(response)
return mod_results
def run_query(request, result_dict={}, query_terms='', page=1, page_len=10, condition=0, log_performance=False):
# Stops an AWFUL lot of problems when people get up to mischief
if page < 1:
page = 1
ec = get_experiment_context(request)
query = Query(query_terms)
query.skip = page
query.top = page_len
result_dict['query'] = query_terms
search_engine = experiment_setups[condition].get_engine()
result_cache = True
response = None
if result_cache:
if cache.cache.get(str(query)):
response = cache.cache.get(str(query))
else:
response = search_engine.search(query)
cache.cache.set(str(query),response, 500)
else:
response = search_engine.search(query)
num_pages = response.total_pages
result_dict['trec_results'] = None
result_dict['trec_no_results_found'] = True
result_dict['trec_search'] = False
result_dict['num_pages'] = num_pages
print "PAGE"
print num_pages
if num_pages > 0:
result_dict['trec_search'] = True
result_dict['trec_results'] = response.results
result_dict['curr_page'] = response.actual_page
if page > 1:
result_dict['prev_page'] = page - 1
result_dict['prev_page_show'] = True
if (page - 1) == 1:
result_dict['prev_page_link'] = "?query=" + query_terms.replace(' ', '+') + '&page=1&noperf=true'
else:
result_dict['prev_page_link'] = "?query=" + query_terms.replace(' ', '+') + '&page=' + str(page - 1)
if page < num_pages:
result_dict['next_page'] = page + 1
result_dict['next_page_show'] = True
result_dict['next_page_link'] = "?query=" + query_terms.replace(' ', '+') + '&page=' + str(page + 1)
# Disable performance logging - it's a hogging the performance!
# If log_performance is True, we log the performance metrics.
#if log_performance:
# log_event(event="QUERY_PERF",
# request=request,
# query=query_terms,
# metrics=get_query_performance_metrics(result_dict['trec_results'], ec['topicnum']))
return result_dict
def run_query(request,
result_dict={},
query_terms='',
page=1,
page_len=10,
condition=0,
log_performance=False):
# Stops an AWFUL lot of problems when people get up to mischief
if page < 1:
page = 1
ec = get_experiment_context(request)
query = Query(query_terms)
query.skip = page
query.top = page_len
result_dict['query'] = query_terms
search_engine = experiment_setups[condition].get_engine()
result_cache = True
response = None
if result_cache:
if cache.cache.get(str(query)):
response = cache.cache.get(str(query))
else:
response = search_engine.search(query)
cache.cache.set(str(query), response, 500)
else:
response = search_engine.search(query)
num_pages = response.total_pages
result_dict['trec_results'] = None
result_dict['trec_no_results_found'] = True
result_dict['trec_search'] = False
result_dict['num_pages'] = num_pages
print "PAGE"
print num_pages
if num_pages > 0:
result_dict['trec_search'] = True
result_dict['trec_results'] = response.results
result_dict['curr_page'] = response.actual_page
if page > 1:
result_dict['prev_page'] = page - 1
result_dict['prev_page_show'] = True
if (page - 1) == 1:
result_dict[
'prev_page_link'] = "?query=" + query_terms.replace(
' ', '+') + '&page=1&noperf=true'
else:
result_dict[
'prev_page_link'] = "?query=" + query_terms.replace(
' ', '+') + '&page=' + str(page - 1)
if page < num_pages:
result_dict['next_page'] = page + 1
result_dict['next_page_show'] = True
result_dict['next_page_link'] = "?query=" + query_terms.replace(
' ', '+') + '&page=' + str(page + 1)
# Disable performance logging - it's a hogging the performance!
# If log_performance is True, we log the performance metrics.
#if log_performance:
# log_event(event="QUERY_PERF",
# request=request,
# query=query_terms,
# metrics=get_query_performance_metrics(result_dict['trec_results'], ec['topicnum']))
return result_dict
def run_query(request, result_dict, query_terms='', page=1, page_len=10, condition=0, interface=1):
"""
Helper method which populates the results dictionary, and send the user to the right interface.
:param result_dict: dictionary with query terms
:param query_terms:
:param page:
:param page_len:
:param condition:
:param interface:
:return:
"""
# Stops an AWFUL lot of problems when people get up to mischief
log_event(event="QUERY_START", request=request, query=query_terms)
if page < 1:
page = 1
query = Query(query_terms)
query.skip = page
query.top = page_len
result_dict['query'] = query_terms
print query
search_engine = experiment_setups[condition].get_engine()
snippet_sizes = [2, 0, 1, 4]
snippet_surround = [40, 40, 40, 40]
pos = interface - 1
search_engine.snippet_size = snippet_sizes[pos]
search_engine.set_fragmenter(frag_type=2, surround=snippet_surround[pos])
response = search_engine.search(query)
log_event(event="QUERY_END", request=request, query=query_terms)
num_pages = response.total_pages
result_dict['trec_results'] = None
result_dict['trec_no_results_found'] = True
result_dict['trec_search'] = False
result_dict['num_pages'] = num_pages
logging.debug('PAGE %d', num_pages)
if num_pages > 0:
result_dict['trec_search'] = True
result_dict['trec_results'] = response.results[len(response.results)-page_len:len(response.results)]
result_dict['curr_page'] = response.actual_page
print response.actual_page
if page > 1:
result_dict['prev_page'] = page - 1
result_dict['prev_page_show'] = True
if (page - 1) == 1:
result_dict['prev_page_link'] = "?query=" + query_terms.replace(' ', '+') + '&page=1&noperf=true'
else:
result_dict['prev_page_link'] = "?query=" + query_terms.replace(' ', '+') + '&page=' + str(page - 1)
if page < num_pages:
result_dict['next_page'] = page + 1
result_dict['next_page_show'] = True
result_dict['next_page_link'] = "?query=" + query_terms.replace(' ', '+') + '&page=' + str(page + 1)
def __init__(self, key, vals, qrel_handler, engine=None, query_time=0):
self.key = key
self.qrel_handler = qrel_handler
self.query = vals[9:]
# There's quote marks at the start and end of the query, remove them
self.query[0] = self.query[0][1:]
self.query[-1] = self.query[-1][:-1]
self.topic = vals[7]
self.event_count = 0
self.doc_count = 0
self.doc_depth = 0
self.hover_count = 0 # Added by David
self.hover_depth = 0 # Added by David
self.hover_trec_rel_count = 0
self.hover_trec_nonrel_count = 0
self.doc_rel_count = 0
self.doc_marked_list = []
self.doc_unmarked_list = []
self.doc_rel_depth = 0
self.doc_trec_rel_count = 0 # Records documents MARKED that are trec rel
self.doc_trec_nonrel_count = 0 # Records documents MARKED that are not trec rel
self.pages = 0
self.curr_page = 1
self.session_start_time = '{date} {time}'.format(date=vals[0],time=vals[1])
self.session_end_time = None
self.query_time = query_time
self.session_time = 0.0
self.snippet_time = 0.0
self.document_time = 0.0
self.view_serp_time = 0
self.last_serp_view_time = None # Added by David
self.curr_event = None
self.last_event = None
self.last_interaction_event = None
self.last_interaction_time = None
self.last_last_event = None
self.doc_click_time = False
# Probability variables, added by David (2016-11-30)
self.doc_clicked_trec_rel_count = 0
self.doc_clicked_trec_nonrel_count = 0
self.query_response = None # Stores the results for parsing later on.
# Testing by David for new SERP
self.last_serp_event = None
self.new_total_serp = 0.0
# Additional attributes to store details on system lag and imposed delays
self.serp_lag_calculated_for = [] # Added by David, list of times for the queries we've worked out lag for!
self.serp_lag = 0.0 # Added by David
self.last_query_delay_time = None
self.imposed_query_delay = 0.0
self.system_query_delay = 0.0
self.total_query_duration = 0.0
self.last_document_delay_time = None
self.imposed_document_delay = 0.0
self.document_lag = 0.0
# issue query to whoosh and get performance values
self.p = []
self.perf = ['0.0 ' * 14]
if engine:
q = Query(' '.join(self.query))
q.skip = 1
q.top = 1000
#print "Issuing {0}".format(q.terms)
response = engine.search(q)
(un, cond, interface, order, topicnum) = key.split(' ')
self.perf = get_query_performance_metrics(self.qrel_handler, response.results, topicnum)
self.query_response = response
#print self.perf
self.last_event='QUERY_ISSUED'
self.last_time = '{date} {time}'.format(date=vals[0],time=vals[1])
__author__ = 'Craig'
from ifind.search import Query, EngineFactory
q = Query("Google", top=5)
e = EngineFactory("Wikipedia")
print q
print e
response = e.search(q)
for r in response.results:
print r
def main():
bm25 = Whooshtrec(
whoosh_index_dir='fullindex/',
stopwords_file='',
model=1,
newschema=True)
query = Query('Sea Pirates')
query.skip = 1
query.top = 5
bm25.snippet_size = 3
response = bm25.search(query)
i = 1
for result in response.results:
print i,len(result.summary)
#print result.summary
#print "--------------"
soup = BeautifulSoup(result.summary,'html.parser')
text = soup.getText()
#print text
print "--------------"
n = extract_nouns(text)
print set(n)
print "--------------"
sentences = nltk.sent_tokenize(text)
tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences]
#print tokenized_sentences
cat_sentences = []
for ts in tokenized_sentences:
for w in ts:
cat_sentences.append(w)
#print cat_sentences
tagged = nltk.pos_tag(cat_sentences)
nouns = [word for word,pos in tagged if (pos == 'NN' or pos == 'NNP' or pos == 'NNS' or pos == 'NNPS')]
downcased = [x.lower() for x in nouns]
joined = " ".join(downcased).encode('utf-8')
into_string = str(nouns)
print (into_string)
#print tokenized_sentences
print "--------------"
tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences]
chunked_sentences = nltk.chunk.ne_chunk_sents(tagged_sentences, binary=True)
entity_names = []
for tree in chunked_sentences:
# Print results per sentence
# print extract_entity_names(tree)
entity_names.extend(extract_entity_names(tree))
print set(entity_names)
i+=1
from whoosh.index import open_dir
from whoosh.qparser import QueryParser
whoosh_path = sys.argv[1]
stopwords_path = sys.argv[2]
page = 3
page_len = 10
search_engine = Whooshtrec(whoosh_index_dir=whoosh_path,
stopwords_file=stopwords_path,
model=1,
newschema=True)
query = Query('wildlife extinction')
query.skip = page
query.top = page_len
response = search_engine.search(query)
for result in response:
print '{0} {1}'.format(result.whooshid, result.rank)
print response.result_total
print response.results_on_page
print response.actual_page
########
print