一、前言
还记得在flask中是怎么引入request对象的吗?没错是通过:
from flask import request
那么,这样全局引入的,势必会存在下面的问题,如果多个用户同时发送请求,一个request对象会被多个用户修改,最后大家拿到的返回值就都是最后一个用户的返回值,那么应该如何解决这种问题呢?
(一)threadinglocal
import threading local_values = threading.local() def func(num): local_values.num_ = num print(local_values.num_, threading.current_thread().name) for i in range(10): t = threading.Thread(target=func, args=(i,), name='线程%s' % i) t.start() """ 输出: 0 线程0 1 线程1 2 线程2 3 线程3 4 线程4 5 线程5 6 线程6 7 线程7 8 线程8 9 线程9 """
通过上面的例子可以看出threading.local()对象的作用就是为每一个线程开辟一个独有的空间,用于保存每一个线程自己独有的值,这样不至于一个值被多个线程改来改去造成数据的混乱。
(二)request对象
对于flask中的request有下面三种情况:
- 单进程、单线程,只需要基于全局变量实现即可
- 单进程、多线程,此时需要threading.local()对象来实现,为每一个请求的request单独开辟一个空间,这样不会造成request对象的混乱
- 单进程、单线程、多协程,这种情况threading.local()对象是无法实现的,因为线程中协程的资源都是共享的
那么,如果在flask中支持协程,应该怎么实现呢?
二、自定义支持协程和协程的Local对象
如果要支持线程,可以自定义类似threading.local()对象,那么它是在threading.local()对象的基础上进一步强化,可以支持协程。
import threading from threading import get_ident class Local: def __init__(self): self.storage = {} #会生成字典 {5936: {'num_': 3}, 7796: {'num_': 6}, 7056: {'num_': 7}...} self.get_ident = get_ident def set(self,k,v): ident = self.get_ident() origin = self.storage.get(ident) if not origin: origin = {k:v} else: origin[k] = v self.storage[ident] = origin def get(self,k): ident = self.get_ident() origin = self.storage.get(ident) if not origin: return None return origin.get(k,None) local_values = Local() def task(num): local_values.set('num_',num) print(local_values.get('num_'),threading.current_thread().name) if __name__ == '__main__': for i in range(10): t = threading.Thread(target=task,args=(i,),name='线程%s'%i) t.start() """ 输出 0 线程0 1 线程1 2 线程2 3 线程3 4 线程4 5 线程5 6 线程6 7 线程7 8 线程8 9 线程9 """
在flask的源码werkzeug.local.py文件中:
# since each thread has its own greenlet we can just use those as identifiers # for the context. If greenlets are not available we fall back to the # current thread ident depending on where it is. try: from greenlet import getcurrent as get_ident except ImportError: try: from thread import get_ident except ImportError: from _thread import get_ident class Local(object): __slots__ = ("__storage__", "__ident_func__") def __init__(self): object.__setattr__(self, "__storage__", {}) object.__setattr__(self, "__ident_func__", get_ident) def __iter__(self): return iter(self.__storage__.items()) def __call__(self, proxy): """Create a proxy for a name.""" return LocalProxy(self, proxy) def __release_local__(self): self.__storage__.pop(self.__ident_func__(), None) def __getattr__(self, name): try: return self.__storage__[self.__ident_func__()][name] except KeyError: raise AttributeError(name) def __setattr__(self, name, value): ident = self.__ident_func__() storage = self.__storage__ try: storage[ident][name] = value except KeyError: storage[ident] = {name: value} def __delattr__(self, name): try: del self.__storage__[self.__ident_func__()][name] except KeyError: raise AttributeError(name)
import threading try: from greenlet import getcurrent as get_ident # 协程 except ImportError: try: from thread import get_ident except ImportError: from _thread import get_ident # 线程 class Local(object): def __init__(self): object.__setattr__(self, '__storage__', {}) object.__setattr__(self, '__ident_func__', get_ident) def __getattr__(self, name): try: return self.__storage__[self.__ident_func__()][name] except KeyError: raise AttributeError(name) def __setattr__(self, name, value): ident = self.__ident_func__() storage = self.__storage__ try: storage[ident][name] = value except KeyError: storage[ident] = {name: value} def __delattr__(self, name): try: del self.__storage__[self.__ident_func__()][name] except KeyError: raise AttributeError(name) local_values = Local() def task(num): local_values.num_ = num # 通过对象.key=value的方式触发__setattr__方法 print(local_values.num_, threading.current_thread().name) # 通过对象.key触发__getattr__方法 if __name__ == '__main__': for i in range(10): t = threading.Thread(target=task, args=(i,), name='线程%s' % i) t.start()