Flask快速入门(12) — local与偏函数

多个线程修改同一个数据，复制多份变量给每个线程用，比如我们用的request，怎样让不同的请求有自己的request。就是为每个线程开辟一块空间进行数据存储

不用threading.local

from threading import Thread
import time
ctx = -1
def task(arg):
    global ctx
    ctx = arg
    # time.sleep(2)
    print(ctx)

for i in range(10):
    t = Thread(target=task,args=(i,))
    t.start()

使用threading.local

from threading import Thread,local
# 特殊的对象
ctx = local()
def task(arg):
    ctx.value = arg
    # time.sleep(2)
    print(ctx.value)
for i in range(10):
    t = Thread(target=task,args=(i,))
    t.start()

通过字典自定义threading.local（函数）

from threading import Thread, get_ident
storage = {}
def set(k, v):
    ident = get_ident()  # 获取线程id
    if ident in storage:
        storage[ident][k] = v
    else:
        storage[ident] = {k: v}
def get(k):
    ident = get_ident()
    return storage[ident][k]
def task(arg):
    set('val', arg)
    v = get('val')
    print(v)
for i in range(10):
    t = Thread(target=task, args=(i,))
    t.start()

面向对象版

from threading import Thread,get_ident
class Local(object):
    storage = {}
    def get(self,k):
        ident = get_ident()
        return Local.storage[ident][k]

    def set(self,k,v):
        ident = get_ident()
        if ident in Local.storage:
            Local.storage[ident][k] = v
        else:
            Local.storage[ident] = {k:v}
obj = Local()
def task(arg):
    obj.set('val',arg)
    v = obj.get('val')
    print(v)

for i in range(10):
    t = Thread(target=task,args=(i,))
    t.start()

通过setattr和getattr实现

from threading import Thread,get_ident

class Local(object):
    storage = {}
    def __setattr__(self, key, value):
        ident = get_ident()
        if ident in self.storage:
            self.storage[ident][key] = value
        else:
            self.storage[ident] = {key:value}

    def __getattr__(self, key):
        ident = get_ident()
        return self.storage[ident][key]
obj = Local()
def task(arg):
    obj.value = arg
    print(obj.value)

for i in range(10):
    t = Thread(target=task,args=(i,))
    t.start()

每个对象有自己的存储空间（字典）

from threading import Thread,get_ident

class Local(object):
    def __init__(self):
        object.__setattr__(self,'storage',{})
        # self.storage = {}
    def __setattr__(self, key, value):
        ident = get_ident()
        if ident in self.storage:
            self.storage[ident][key] = value
        else:
            self.storage[ident] = {key:value}
    def __getattr__(self, key):
        ident = get_ident()
        return self.storage[ident][key]
obj = Local()
def task(arg):
    obj.value = arg
    print(obj.value)
for i in range(10):
    t = Thread(target=task,args=(i,))
    t.start()

兼容线程和协程（源码到request中去看，看local的__getattr__,setattr）

# 如果是协程get_ident获取的是协程id
try:
    from greenlet import getcurrent as get_ident  
except Exception as e:
    from threading import get_ident
from threading import Thread
import time
class Local(object):
    def __init__(self):
        object.__setattr__(self,'storage',{})
    def __setattr__(self, k, v):
        ident = get_ident()
        if ident in self.storage:
            self.storage[ident][k] = v
        else:
            self.storage[ident] = {k: v}
    def __getattr__(self, k):
        ident = get_ident()
        return self.storage[ident][k]
obj = Local()
def task(arg):
    obj.val = arg
    obj.xxx = arg
    print(obj.val)
for i in range(10):
    t = Thread(target=task,args=(i,))
    t.start()
   

partial偏函数

# 偏函数的第二个部分(可变参数)，按原有函数的参数顺序进行补充，参数将作用在原函数上，最后偏函数返回一个新函数
from functools import partial
def test(a,b,c,d):
    return a+b+c+d

tes=partial(test,1,2)
print(tes(3,4))