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https://github.com/KevinMidboe/mktxp-no-cli.git
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96 lines
4.2 KiB
Python
96 lines
4.2 KiB
Python
# coding=utf8
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# Copyright (c) 2020 Arseniy Kuznenowov
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##
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# This program is free software; you can redistribute it and/or
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# modify it under the terms of the GNU General Public License
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# as published by the Free Software Foundation; either version 2
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# of the License, or (at your option) any later version.
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##
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from timeit import default_timer
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from datetime import datetime
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from mktxp.cli.config.config import config_handler
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class CollectorHandler:
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''' MKTXP Collectors Handler
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'''
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def __init__(self, entries_handler, collector_registry):
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self.entries_handler = entries_handler
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self.collector_registry = collector_registry
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self.last_collect_timestamp = 0
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def collect_synchronous(self):
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"""
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Collect the metrics of all router entries defined in the current users configuration synchronously.
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This function iterates over each router entry one-by-one.
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Thus, the total runtime of this function scales linearly with the number of registered routers.
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"""
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for router_entry in self.entries_handler.router_entries:
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if not router_entry.api_connection.is_connected():
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# let's pick up on things in the next run
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router_entry.api_connection.connect()
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continue
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for collector_ID, collect_func in self.collector_registry.registered_collectors.items():
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start = default_timer()
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yield from collect_func(router_entry)
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router_entry.time_spent[collector_ID] += default_timer() - start
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def collect_single(self, router_entry):
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results = []
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for collector_ID, collect_func in self.collector_registry.registered_collectors.items():
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start = default_timer()
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result = list(collect_func(router_entry))
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results += result
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router_entry.time_spent[collector_ID] += default_timer() - start
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return results
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def collect_parallel(self, max_worker_threads=5):
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"""
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Collect the metrics of all router entries defined in the current users configuration in parallel.
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This function iterates over multiple routers in parallel (depending on the value of max_worker_threads).
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Thus, the total runtime scales sub linearly (number_of_routers / max_worker_threads).
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"""
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with ThreadPoolExecutor(max_workers=max_worker_threads) as executor:
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futures = []
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for router_entry in self.entries_handler.router_entries:
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if not router_entry.api_connection.is_connected():
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# let's pick up on things in the next run
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router_entry.api_connection.connect()
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continue
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# Publish the collection function as a future
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futures.append(executor.submit(self.collect_single, router_entry))
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for future in as_completed(futures):
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yield from future.result()
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def collect(self):
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now = datetime.now().timestamp()
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diff = now - self.last_collect_timestamp
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if diff < config_handler.system_entry().minimal_collect_interval:
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if config_handler.system_entry().verbose_mode:
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print(f'An attemp to collect metrics within minimal collection interval: {diff} < {config_handler.system_entry().minimal_collect_interval}')
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print('deferring..')
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return
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self.last_collect_timestamp = now
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yield from self.collector_registry.bandwidthCollector.collect()
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# Check whether to run in parallel by looking at the mktxp system configuration
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parallel = config_handler.system_entry().fetch_routers_in_parallel
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max_worker_threads = config_handler.system_entry().max_worker_threads
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if parallel:
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yield from self.collect_parallel(max_worker_threads=max_worker_threads)
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else:
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yield from self.collect_synchronous()
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