最近被多线程给坑了下,没意识到类变量在多线程下是共享的,还有一个就是没意识到 内存释放问题,导致越累越大

1.python 类变量 在多线程情况 下的 是共享的

2.python 类变量 在多线程情况 下的 释放是不完全的

3.python 类变量 在多线程情况 下没释放的那部分 内存 是可以重复利用的

import threading
 import time
   
 class Test:
   
     cache = {}
       
     @classmethod
     def get_value(self, key):
         value = Test.cache.get(key, [])
         return len(value)
   
     @classmethod
     def store_value(self, key, value):
         if not Test.cache.has_key(key):
             Test.cache[key] = range(value)
         else:
             Test.cache[key].extend(range(value))
         return len(Test.cache[key])
   
     @classmethod
     def release_value(self, key):
         if Test.cache.has_key(key):
             Test.cache.pop(key)
         return True
   
     @classmethod
     def print_cache(self):
         print 'print_cache:'
         for key in Test.cache:
             print 'key: %d, value:%d' % (key, len(Test.cache[key]))
   
 def worker(number, value):
     key = number % 5
     print 'threading: %d, store_value: %d' % (number, Test.store_value(key, value))
     time.sleep(10)
     print 'threading: %d, release_value: %s' % (number, Test.release_value(key))
   
 if __name__ == '__main__':
     thread_num = 10
       
     thread_pool = []
     for i in range(thread_num):
         th = threading.Thread(target=worker,args=[i, 1000000])
         thread_pool.append(th)
         thread_pool[i].start()
   
     for thread in thread_pool:
         threading.Thread.join(thread)
       
     Test.print_cache()
     time.sleep(10)
       
     thread_pool = []
     for i in range(thread_num):
         th = threading.Thread(target=worker,args=[i, 100000])
         thread_pool.append(th)
         thread_pool[i].start()
   
     for thread in thread_pool:
         threading.Thread.join(thread)
       
     Test.print_cache()
     time.sleep(10)

公用的数据,除非是只读的,不然不要当类成员变量,一是会共享,二是不好释放。