Metadata-Version: 2.1
Name: tps-threadpool-executor
Version: 0.4
Summary: tps_threadpool_executor,it can run function specify times every second
Home-page: UNKNOWN
Author: bfzs
Author-email: ydf0509@sohu.com
Maintainer: ydf
Maintainer-email: ydf0509@sohu.com
License: BSD License
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
        ```python
        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)
        
        
        ```
Keywords: threadpool_executor,ThreadPoolExecutorShrinkAble,ThreadPoolExecutor,tps,qps
Platform: all
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: Implementation
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Software Development :: Libraries
Description-Content-Type: text/markdown
