forked from Archives/searxng
You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
207 lines
7.6 KiB
Python
207 lines
7.6 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-or-later
|
|
|
|
import typing
|
|
import math
|
|
import contextlib
|
|
from timeit import default_timer
|
|
from operator import itemgetter
|
|
|
|
from searx.engines import engines
|
|
from .models import HistogramStorage, CounterStorage
|
|
from .error_recorder import count_error, count_exception, errors_per_engines
|
|
|
|
__all__ = ["initialize",
|
|
"get_engines_stats", "get_engine_errors",
|
|
"histogram", "histogram_observe", "histogram_observe_time",
|
|
"counter", "counter_inc", "counter_add",
|
|
"count_error", "count_exception"]
|
|
|
|
|
|
ENDPOINTS = {'search'}
|
|
|
|
|
|
histogram_storage: typing.Optional[HistogramStorage] = None
|
|
counter_storage: typing.Optional[CounterStorage] = None
|
|
|
|
|
|
@contextlib.contextmanager
|
|
def histogram_observe_time(*args):
|
|
h = histogram_storage.get(*args)
|
|
before = default_timer()
|
|
yield before
|
|
duration = default_timer() - before
|
|
if h:
|
|
h.observe(duration)
|
|
else:
|
|
raise ValueError("histogram " + repr((*args,)) + " doesn't not exist")
|
|
|
|
|
|
def histogram_observe(duration, *args):
|
|
histogram_storage.get(*args).observe(duration)
|
|
|
|
|
|
def histogram(*args, raise_on_not_found=True):
|
|
h = histogram_storage.get(*args)
|
|
if raise_on_not_found and h is None:
|
|
raise ValueError("histogram " + repr((*args,)) + " doesn't not exist")
|
|
return h
|
|
|
|
|
|
def counter_inc(*args):
|
|
counter_storage.add(1, *args)
|
|
|
|
|
|
def counter_add(value, *args):
|
|
counter_storage.add(value, *args)
|
|
|
|
|
|
def counter(*args):
|
|
return counter_storage.get(*args)
|
|
|
|
|
|
def initialize(engine_names=None):
|
|
"""
|
|
Initialize metrics
|
|
"""
|
|
global counter_storage, histogram_storage
|
|
|
|
counter_storage = CounterStorage()
|
|
histogram_storage = HistogramStorage()
|
|
|
|
# max_timeout = max of all the engine.timeout
|
|
max_timeout = 2
|
|
for engine_name in (engine_names or engines):
|
|
if engine_name in engines:
|
|
max_timeout = max(max_timeout, engines[engine_name].timeout)
|
|
|
|
# histogram configuration
|
|
histogram_width = 0.1
|
|
histogram_size = int(1.5 * max_timeout / histogram_width)
|
|
|
|
# engines
|
|
for engine_name in (engine_names or engines):
|
|
# search count
|
|
counter_storage.configure('engine', engine_name, 'search', 'count', 'sent')
|
|
counter_storage.configure('engine', engine_name, 'search', 'count', 'successful')
|
|
# global counter of errors
|
|
counter_storage.configure('engine', engine_name, 'search', 'count', 'error')
|
|
# score of the engine
|
|
counter_storage.configure('engine', engine_name, 'score')
|
|
# result count per requests
|
|
histogram_storage.configure(1, 100, 'engine', engine_name, 'result', 'count')
|
|
# time doing HTTP requests
|
|
histogram_storage.configure(histogram_width, histogram_size, 'engine', engine_name, 'time', 'http')
|
|
# total time
|
|
# .time.request and ...response times may overlap .time.http time.
|
|
histogram_storage.configure(histogram_width, histogram_size, 'engine', engine_name, 'time', 'total')
|
|
|
|
|
|
def get_engine_errors(engline_list):
|
|
result = {}
|
|
engine_names = list(errors_per_engines.keys())
|
|
engine_names.sort()
|
|
for engine_name in engine_names:
|
|
if engine_name not in engline_list:
|
|
continue
|
|
|
|
error_stats = errors_per_engines[engine_name]
|
|
sent_search_count = max(counter('engine', engine_name, 'search', 'count', 'sent'), 1)
|
|
sorted_context_count_list = sorted(error_stats.items(), key=lambda context_count: context_count[1])
|
|
r = []
|
|
for context, count in sorted_context_count_list:
|
|
percentage = round(20 * count / sent_search_count) * 5
|
|
r.append({
|
|
'filename': context.filename,
|
|
'function': context.function,
|
|
'line_no': context.line_no,
|
|
'code': context.code,
|
|
'exception_classname': context.exception_classname,
|
|
'log_message': context.log_message,
|
|
'log_parameters': context.log_parameters,
|
|
'secondary': context.secondary,
|
|
'percentage': percentage,
|
|
})
|
|
result[engine_name] = sorted(r, reverse=True, key=lambda d: d['percentage'])
|
|
return result
|
|
|
|
|
|
def to_percentage(stats, maxvalue):
|
|
for engine_stat in stats:
|
|
if maxvalue:
|
|
engine_stat['percentage'] = int(engine_stat['avg'] / maxvalue * 100)
|
|
else:
|
|
engine_stat['percentage'] = 0
|
|
return stats
|
|
|
|
|
|
def get_engines_stats(engine_list):
|
|
global counter_storage, histogram_storage
|
|
|
|
assert counter_storage is not None
|
|
assert histogram_storage is not None
|
|
|
|
list_time = []
|
|
list_time_http = []
|
|
list_time_total = []
|
|
list_result_count = []
|
|
list_error_count = []
|
|
list_scores = []
|
|
list_scores_per_result = []
|
|
|
|
max_error_count = max_http_time = max_time_total = max_result_count = max_score = None # noqa
|
|
for engine_name in engine_list:
|
|
error_count = counter('engine', engine_name, 'search', 'count', 'error')
|
|
|
|
if counter('engine', engine_name, 'search', 'count', 'sent') > 0:
|
|
list_error_count.append({'avg': error_count, 'name': engine_name})
|
|
max_error_count = max(error_count, max_error_count or 0)
|
|
|
|
successful_count = counter('engine', engine_name, 'search', 'count', 'successful')
|
|
if successful_count == 0:
|
|
continue
|
|
|
|
result_count_sum = histogram('engine', engine_name, 'result', 'count').sum
|
|
time_total = histogram('engine', engine_name, 'time', 'total').percentage(50)
|
|
time_http = histogram('engine', engine_name, 'time', 'http').percentage(50)
|
|
result_count = result_count_sum / float(successful_count)
|
|
|
|
if result_count:
|
|
score = counter('engine', engine_name, 'score') # noqa
|
|
score_per_result = score / float(result_count_sum)
|
|
else:
|
|
score = score_per_result = 0.0
|
|
|
|
max_time_total = max(time_total, max_time_total or 0)
|
|
max_http_time = max(time_http, max_http_time or 0)
|
|
max_result_count = max(result_count, max_result_count or 0)
|
|
max_score = max(score, max_score or 0)
|
|
|
|
list_time.append({'total': round(time_total, 1),
|
|
'http': round(time_http, 1),
|
|
'name': engine_name,
|
|
'processing': round(time_total - time_http, 1)})
|
|
list_time_total.append({'avg': time_total, 'name': engine_name})
|
|
list_time_http.append({'avg': time_http, 'name': engine_name})
|
|
list_result_count.append({'avg': result_count, 'name': engine_name})
|
|
list_scores.append({'avg': score, 'name': engine_name})
|
|
list_scores_per_result.append({'avg': score_per_result, 'name': engine_name})
|
|
|
|
list_time = sorted(list_time, key=itemgetter('total'))
|
|
list_time_total = sorted(to_percentage(list_time_total, max_time_total), key=itemgetter('avg'))
|
|
list_time_http = sorted(to_percentage(list_time_http, max_http_time), key=itemgetter('avg'))
|
|
list_result_count = sorted(to_percentage(list_result_count, max_result_count), key=itemgetter('avg'), reverse=True)
|
|
list_scores = sorted(list_scores, key=itemgetter('avg'), reverse=True)
|
|
list_scores_per_result = sorted(list_scores_per_result, key=itemgetter('avg'), reverse=True)
|
|
list_error_count = sorted(to_percentage(list_error_count, max_error_count), key=itemgetter('avg'), reverse=True)
|
|
|
|
return {
|
|
'time': list_time,
|
|
'max_time': math.ceil(max_time_total or 0),
|
|
'time_total': list_time_total,
|
|
'time_http': list_time_http,
|
|
'result_count': list_result_count,
|
|
'scores': list_scores,
|
|
'scores_per_result': list_scores_per_result,
|
|
'error_count': list_error_count,
|
|
}
|