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。