• Flask之线程与协程


    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)
    源码Local对象
    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()
  • 相关阅读:
    configure new Linux/Mac
    Python input()和raw_input()的区别
    python json读取txt文本 解析str 出错No JSON object could be decoded
    python TypeError: 'str' object does not support item assignment”
    python中对字典按照value排序
    腾讯实习面试被虐记
    软件里的实践出真知
    c链表实现遇到的错误
    Linux命令(2)
    yum的使用及配置
  • 原文地址:https://www.cnblogs.com/shenjianping/p/13269731.html
Copyright © 2020-2023  润新知