tps_threadpool_executor,it can run function specify times every second
Project description
1. pip install tps_threadpool_executor
这个线程池和一般线程池不同,是自动控频的,能够将任意耗时大小的函数控制成指定的运行频率。
此线程池入参不是设置并发大小,而是设置tps大小。
TpsThreadpoolExecutor 基于单进程的当前线程池控频。
DistributedTpsThreadpoolExecutor 基于多台机器的分布式控频,需要安装redis,统计出活跃线程池,从而平分任务。
实现代码
import json
import time
from queue import Queue
import threading
from threadpool_executor_shrink_able.sharp_threadpoolexecutor import ThreadPoolExecutorShrinkAble
import nb_log
import redis
import decorator_libs
import socket
import os
"""
这个线程池和一般线程池不同,是自动控频的,能够将任意函数控制成指定的运行频率。
此线程池入参不是设置并发大小,而是设置tps大小。
"""
class TpsThreadpoolExecutor:
def __init__(self, tps=0):
"""
:param tps: 指定线程池每秒运行多少次函数,为0这不限制运行次数
"""
self.tps = tps
self.time_interval = 1 / tps if tps != 0 else 0
self.pool = ThreadPoolExecutorShrinkAble(500) # 这是使用的智能线程池,所以可以写很大的数字,具体见另一个包的解释。
self.queue = Queue(500)
threading.Thread(target=self._put_task_to_pool_queue).start()
def submit(self, func, *args, **kwargs):
self.queue.put((func, args, kwargs))
def _put_task_to_pool_queue(self):
while True:
time.sleep(self.time_interval)
task = self.queue.get()
self.pool.submit(task[0], *task[1], **task[2])
def shutdown(self, wait=True):
self.pool.shutdown(wait=wait)
def get_host_ip():
ip = ''
host_name = ''
try:
sc = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
sc.connect(('8.8.8.8', 80))
ip = sc.getsockname()[0]
host_name = socket.gethostname()
sc.close()
except Exception:
pass
return ip, host_name
class DistributedTpsThreadpoolExecutor(TpsThreadpoolExecutor, nb_log.LoggerMixin):
"""
这个是redis分布式控频线程池,不是基于incr计数的,是基于统计活跃消费者,然后每个线程池平分频率的。
"""
def __init__(self, tps=0, pool_identify: str = None, redis_url: str = 'redis://:@127.0.0.1/0'):
"""
:param tps: 指定线程池每秒运行多少次函数,为0这不限制运行次数
:param pool_identify: 对相同标识的pool,进行分布式控频,例如多台机器都有标识为1的线程池,则所有机器加起来的运行次数控制成指定频率。
:param redis_url: 'redis://:secret@100.22.233.110/7'
"""
if pool_identify is None or redis_url is None:
raise ValueError('设置的参数错误')
self._pool_identify =pool_identify
super(DistributedTpsThreadpoolExecutor, self).__init__(tps=tps)
self.redis_db = redis.from_url(redis_url)
self.redis_key_pool_identify = f'DistributedTpsThreadpoolExecutor:{pool_identify}'
ip, host_name = get_host_ip()
self.current_process_flag = f'{ip}-{host_name}-{os.getpid()}-{id(self)}'
self._send_heartbeat_to_redis()
self._last_show_pool_instance_num = time.time()
@decorator_libs.keep_circulating(10, block=False, daemon=True)
def _send_heartbeat_to_redis(self):
all_identify = self.redis_db.smembers(self.redis_key_pool_identify)
pool_instance_num = len(all_identify)
if time.time() - self._last_show_pool_instance_num > 60:
self.logger.debug(f'分布式环境中一共有 {pool_instance_num} 个 {self._pool_identify} 标识的线程池')
self.time_interval = (1.0 / self.tps) * pool_instance_num if self.tps != 0 else 0
for identify in all_identify:
identify_dict = json.loads(identify)
if identify_dict['current_process_flag'] == self.current_process_flag:
self.redis_db.srem(self.redis_key_pool_identify, identify)
if time.time() - identify_dict['last_heartbeat_ts'] > 15:
self.redis_db.srem(self.redis_key_pool_identify, identify)
self.redis_db.sadd(self.redis_key_pool_identify, json.dumps(
{'current_process_flag': self.current_process_flag, 'last_heartbeat_ts': time.time(), 'last_heartbeat_time_str': time.strftime('%Y-%m-%d %H:%M:%S')}))
if __name__ == '__main__':
def f1(x):
time.sleep(0.1)
print(x)
def f2(x):
time.sleep(3)
print(x)
# tps_pool = TpsThreadpoolExecutor(tps=7) # 这个是单机控频
tps_pool = DistributedTpsThreadpoolExecutor(tps=7, pool_identify='pool_for_use_print') # 这个是redis分布式控频,不是基于incr计数的,是基于
for i in range(10000):
tps_pool.submit(f1, i)
tps_pool.submit(f1, i * 10)
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