# SPDX-License-Identifier: AGPL-3.0-or-later # pylint: disable=missing-module-docstring, missing-function-docstring 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 # pylint: disable=global-statement 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): assert counter_storage is not None assert histogram_storage is not None list_time = [] max_time_total = max_result_count = None # noqa for engine_name in engine_list: 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) time_total_p80 = histogram('engine', engine_name, 'time', 'total').percentage(80) time_http_p80 = histogram('engine', engine_name, 'time', 'http').percentage(80) time_total_p95 = histogram('engine', engine_name, 'time', 'total').percentage(95) time_http_p95 = histogram('engine', engine_name, 'time', 'http').percentage(95) 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_result_count = max(result_count, max_result_count or 0) list_time.append({ 'total': round(time_total, 1), 'total_p80': round(time_total_p80, 1), 'total_p95': round(time_total_p95, 1), 'http': round(time_http, 1), 'http_p80': round(time_http_p80, 1), 'http_p95': round(time_http_p95, 1), 'name': engine_name, 'processing': round(time_total - time_http, 1), 'processing_p80': round(time_total_p80 - time_http_p80, 1), 'processing_p95': round(time_total_p95 - time_http_p95, 1), 'score': score, 'score_per_result': score_per_result, 'result_count': result_count, }) return { 'time': list_time, 'max_time': math.ceil(max_time_total or 0), 'max_result_count': math.ceil(max_result_count or 0), }