def get_environment_status(env_dict, exclude_labels=None):
"""
Get the environment status per kind in KINDS and save it in a dictionary
Args:
env_dict (dict): Dictionary that is a copy.deepcopy(ENV_STATUS_DICT)
exclude_labels (list): App labels to ignore leftovers
"""
with ThreadPoolExecutor(max_workers=len(KINDS)) as executor:
for key, kind in zip(env_dict.keys(), KINDS):
executor.submit(
assign_get_values, env_dict, key, kind,
exclude_labels=exclude_labels
)
# All rights reserved.
import logging
import time
from multiprocessing import Process
USE_GEVENT = True
if USE_GEVENT:
import gevent
as_completed = gevent.wait
from gevent.threadpool import ThreadPoolExecutor as ThreadPoolExecutor
else:
from concurrent.futures import ThreadPoolExecutor, as_completed
pool = ThreadPoolExecutor(32)
from kafka_rpc import KRPCClient
from kafka_rpc import KRPCServer
NUMS = 1000
# 213.8162382121568, no concurrent
# 419.71660475278094, no concurrent, use_redis
# 383.26126764939164, no concurrent, use_redis, has verification and encryption
# 2549.6978760136653, threadpool, poolsize 128
# 3408.9112918300966, threadpool, poolsize 64
# 6788.747358099728, threadpool, poolsize 32
# 2777.8816114784295, threadpool, poolsize 16
def launch(): global loop loop = GLibEventLoop(context=GLib.MainContext.default()) executor = ThreadPoolExecutor(max_workers=1) executor.submit(worker)
Simulate a situation when multiple threads of Kafka RPC Client send request to Kafka RPC Server
"""
USE_GEVENT = True
if USE_GEVENT:
import gevent
as_completed = gevent.wait
from gevent.threadpool import ThreadPoolExecutor as ThreadPoolExecutor
else:
from concurrent.futures import ThreadPoolExecutor, as_completed
from kafka_rpc import KRPCClient
pool = ThreadPoolExecutor(128)
# assuming you kafka broker is on localhost:9092
krc = KRPCClient('localhost:9092', topic_name='sum')
# call method concurrently from client to server
# use pool.map if you like
futures = []
for i in range(128):
futures.append(pool.submit(krc.add, 1, 2, timeout=20))
for future in as_completed(futures):
result = future.result()
print(result)
krc.close()
def launch():
executor = ThreadPoolExecutor(max_workers=1)
executor.submit(worker)
from server import socketio
from collections import Counter
from gevent.threadpool import ThreadPoolExecutor
from configparser import ConfigParser
from server import config_file
# プログラミング言語と拡張子の対応表
lang_to_extension = {
"Python3": ".py",
"Java": ".java",
"C": ".c",
"C++": ".cpp"
}
# スレッドプール
executor = ThreadPoolExecutor(
max_workers=int(config_file["system"]["max_worker"]))
def judge_code(submission_id):
"""提出されたコードをジャッジする
Args:
submission_id (str) : 提出ID
Returns:
None
"""
# ジャッジ開始
start_judge(submission_id)
def thread_pool_main(interface_info):
thread_obj = ThreadPoolExecutor(max_workers=1,
thread_name_prefix="WorkExecutor")
# logger.info("Master ThreadPool Executor starts thread worker")
thread_obj.submit(get_response(interface_info))
