searxng/searx/engines/__init__.py
2014-01-10 23:38:08 +01:00

254 lines
9.9 KiB
Python

'''
searx is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
searx is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with searx. If not, see < http://www.gnu.org/licenses/ >.
(C) 2013- by Adam Tauber, <asciimoo@gmail.com>
'''
from os.path import realpath, dirname, splitext, join
from imp import load_source
import grequests
from itertools import izip_longest, chain
from operator import itemgetter
from urlparse import urlparse
from searx import settings
import ConfigParser
import sys
from datetime import datetime
engine_dir = dirname(realpath(__file__))
searx_dir = join(engine_dir, '../../')
engines_config = ConfigParser.SafeConfigParser()
engines_config.read(join(searx_dir, 'engines.cfg'))
number_of_searches = 0
engines = {}
categories = {'general': []}
def load_module(filename):
modname = splitext(filename)[0]
if modname in sys.modules:
del sys.modules[modname]
filepath = join(engine_dir, filename)
module = load_source(modname, filepath)
module.name = modname
return module
if not engines_config.sections():
print '[E] Error no engines found. Edit your engines.cfg'
exit(2)
for engine_config_name in engines_config.sections():
engine_data = engines_config.options(engine_config_name)
engine = load_module(engines_config.get(engine_config_name, 'engine')+'.py')
engine.name = engine_config_name
for param_name in engine_data:
if param_name == 'engine':
continue
if param_name == 'categories':
if engines_config.get(engine_config_name, param_name) == 'none':
engine.categories = []
else:
engine.categories = map(str.strip, engines_config.get(engine_config_name, param_name).split(','))
continue
setattr(engine, param_name, engines_config.get(engine_config_name, param_name))
for engine_attr in dir(engine):
if engine_attr.startswith('_'):
continue
if getattr(engine, engine_attr) == None:
print '[E] Engine config error: Missing attribute "{0}.{1}"'.format(engine.name, engine_attr)
sys.exit(1)
engines[engine.name] = engine
engine.stats = {'result_count': 0, 'search_count': 0, 'page_load_time': 0, 'score_count': 0, 'errors': 0}
if hasattr(engine, 'categories'):
for category_name in engine.categories:
categories.setdefault(category_name, []).append(engine)
else:
categories['general'].append(engine)
def default_request_params():
return {'method': 'GET', 'headers': {}, 'data': {}, 'url': '', 'cookies': {}}
def make_callback(engine_name, results, suggestions, callback, params):
# creating a callback wrapper for the search engine results
def process_callback(response, **kwargs):
cb_res = []
response.search_params = params
engines[engine_name].stats['page_load_time'] += (datetime.now() - params['started']).total_seconds()
try:
search_results = callback(response)
except Exception, e:
engines[engine_name].stats['errors'] += 1
results[engine_name] = cb_res
print '[E] Error with engine "{0}":\n\t{1}'.format(engine_name, str(e))
return
for result in search_results:
result['engine'] = engine_name
if 'suggestion' in result:
# TODO type checks
suggestions.add(result['suggestion'])
continue
cb_res.append(result)
results[engine_name] = cb_res
return process_callback
def score_results(results):
flat_res = filter(None, chain.from_iterable(izip_longest(*results.values())))
flat_len = len(flat_res)
engines_len = len(results)
results = []
# deduplication + scoring
for i,res in enumerate(flat_res):
res['parsed_url'] = urlparse(res['url'])
res['engines'] = [res['engine']]
weight = 1.0
if hasattr(engines[res['engine']], 'weight'):
weight = float(engines[res['engine']].weight)
elif res['engine'] in settings.weights:
weight = float(settings.weights[res['engine']])
score = int((flat_len - i)/engines_len)*weight+1
duplicated = False
for new_res in results:
p1 = res['parsed_url'].path[:-1] if res['parsed_url'].path.endswith('/') else res['parsed_url'].path
p2 = new_res['parsed_url'].path[:-1] if new_res['parsed_url'].path.endswith('/') else new_res['parsed_url'].path
if res['parsed_url'].netloc == new_res['parsed_url'].netloc and\
p1 == p2 and\
res['parsed_url'].query == new_res['parsed_url'].query and\
res.get('template') == new_res.get('template'):
duplicated = new_res
break
if duplicated:
if len(res.get('content', '')) > len(duplicated.get('content', '')):
duplicated['content'] = res['content']
duplicated['score'] += score
duplicated['engines'].append(res['engine'])
if duplicated['parsed_url'].scheme == 'https':
continue
elif res['parsed_url'].scheme == 'https':
duplicated['url'] = res['parsed_url'].geturl()
duplicated['parsed_url'] = res['parsed_url']
else:
res['score'] = score
results.append(res)
return sorted(results, key=itemgetter('score'), reverse=True)
def search(query, request, selected_engines):
global engines, categories, number_of_searches
requests = []
results = {}
suggestions = set()
number_of_searches += 1
user_agent = request.headers.get('User-Agent', '')
for selected_engine in selected_engines:
if selected_engine['name'] not in engines:
continue
engine = engines[selected_engine['name']]
request_params = default_request_params()
request_params['headers']['User-Agent'] = user_agent
request_params['category'] = selected_engine['category']
request_params['started'] = datetime.now()
request_params = engine.request(query, request_params)
callback = make_callback(selected_engine['name'], results, suggestions, engine.response, request_params)
request_args = dict(headers = request_params['headers']
,hooks = dict(response=callback)
,cookies = request_params['cookies']
,timeout = settings.request_timeout
)
if request_params['method'] == 'GET':
req = grequests.get
else:
req = grequests.post
request_args['data'] = request_params['data']
# ignoring empty urls
if not request_params['url']:
continue
requests.append(req(request_params['url'], **request_args))
grequests.map(requests)
for engine_name,engine_results in results.items():
engines[engine_name].stats['search_count'] += 1
engines[engine_name].stats['result_count'] += len(engine_results)
results = score_results(results)
for result in results:
for res_engine in result['engines']:
engines[result['engine']].stats['score_count'] += result['score']
return results, suggestions
def get_engines_stats():
# TODO refactor
pageloads = []
results = []
scores = []
errors = []
scores_per_result = []
max_pageload = max_results = max_score = max_errors = max_score_per_result = 0
for engine in engines.values():
if engine.stats['search_count'] == 0:
continue
results_num = engine.stats['result_count']/float(engine.stats['search_count'])
load_times = engine.stats['page_load_time']/float(engine.stats['search_count'])
if results_num:
score = engine.stats['score_count'] / float(engine.stats['search_count'])
score_per_result = score / results_num
else:
score = score_per_result = 0.0
max_results = max(results_num, max_results)
max_pageload = max(load_times, max_pageload)
max_score = max(score, max_score)
max_score_per_result = max(score_per_result, max_score_per_result)
max_errors = max(max_errors, engine.stats['errors'])
pageloads.append({'avg': load_times, 'name': engine.name})
results.append({'avg': results_num, 'name': engine.name})
scores.append({'avg': score, 'name': engine.name})
errors.append({'avg': engine.stats['errors'], 'name': engine.name})
scores_per_result.append({'avg': score_per_result, 'name': engine.name})
for engine in pageloads:
engine['percentage'] = int(engine['avg']/max_pageload*100)
for engine in results:
engine['percentage'] = int(engine['avg']/max_results*100)
for engine in scores:
engine['percentage'] = int(engine['avg']/max_score*100)
for engine in scores_per_result:
engine['percentage'] = int(engine['avg']/max_score_per_result*100)
for engine in errors:
if max_errors:
engine['percentage'] = int(float(engine['avg'])/max_errors*100)
else:
engine['percentage'] = 0
return [('Page loads (sec)', sorted(pageloads, key=itemgetter('avg')))
,('Number of results', sorted(results, key=itemgetter('avg'), reverse=True))
,('Scores', sorted(scores, key=itemgetter('avg'), reverse=True))
,('Scores per result', sorted(scores_per_result, key=itemgetter('avg'), reverse=True))
,('Errors', sorted(errors, key=itemgetter('avg'), reverse=True))
]