python多進(jìn)程和多線程奏甫、內(nèi)存共享和進(jìn)程池琉挖、多線程編程

@[toc]

內(nèi)存共享

通過(guò)Value,Array實(shí)現(xiàn)內(nèi)存共享
- 返回一個(gè)從共享內(nèi)存上創(chuàng)建的ctypes對(duì)象
- 從共享內(nèi)存中申請(qǐng)并返回一個(gè)具有ctypes類(lèi)型的數(shù)組對(duì)象
通過(guò)Manager實(shí)現(xiàn)內(nèi)存共享
- Manager返回的管理器對(duì)象控制一個(gè)服務(wù)進(jìn)程，且由該進(jìn)程保存Python對(duì)象并允許其他進(jìn)程通過(guò)代理操作對(duì)象
- 返回的管理器支持類(lèi)型支持list决摧、dict等
- 注意同步：可能需要加鎖亿蒸，尤其碰到+=更新時(shí)

from multiprocessing import Process
from multiprocessing import Manager, Lock
import time
import random

def register(d,name):
    if name in d:
        print('duplicated name found...register anyway...')
        d[name]+=1
    else:
        d[name]=1
    time.sleep(random.random())

def register_with_loc(d,name,lock):
    with lock:
        if name in d:
            print('duplicated name found...register anyway...')
            d[name]+=1
        else:
            d[name]=1
    time.sleep(random.random())

if __name__=='__main__':
    #Manager
    names=['Amy','Lily','Dirk','Lily', 'Denial','Amy','Amy','Amy']
    manager=Manager()
    dic=manager.dict()
    lock=Lock()
    #manager.list()
    students=[]
    for i in range(len(names)):
        #s=Process(target=register,args=(dic,names[i]))
        s=Process(target=register_with_loc,args=(dic,names[i],lock))
        students.append(s)
    for s in students:
        s.start()
    for s in students:
        s.join()
    print('all processes ended...')
    for k,v in dic.items():
        print("{}\t{}".format(k,v))

可以共享字典

duplicated name found...register anyway...
duplicated name found...register anyway...
duplicated name found...register anyway...
duplicated name found...register anyway...
all processes ended...
Amy     4
Dirk    1
Denial  1
Lily    2

進(jìn)程池
- 進(jìn)程開(kāi)啟過(guò)多導(dǎo)致效率下降（同步、切換成本）
- 應(yīng)固定工作進(jìn)程的數(shù)目
  - 由這些進(jìn)程執(zhí)行所有任務(wù)蜜徽，而非開(kāi)啟更多的進(jìn)程
  - 與CPU的核數(shù)相關(guān)

創(chuàng)建進(jìn)程池

Pooll([numprocess [,initializer [, initargs]]])
- numprocess:要?jiǎng)?chuàng)建的進(jìn)程數(shù)祝懂，默認(rèn)使用os.cpu_count()的值
- initializer:每個(gè)工作進(jìn)程啟動(dòng)時(shí)要執(zhí)行的可調(diào)用對(duì)象，默認(rèn)為None
- initargs:initializer的參數(shù)
p.apply()
- 同步調(diào)用
- 只有一個(gè)進(jìn)程執(zhí)行（不并行）
- 但可以直接得到返回結(jié)果（阻塞至返回結(jié)果）
p.apply_async()
- 異步調(diào)用
- 并行執(zhí)行拘鞋，結(jié)果不一定馬上返回（AsyncResult）
- 可以有回調(diào)函數(shù)砚蓬，進(jìn)程池中任意任務(wù)完成后會(huì)立即通知主進(jìn)程，主進(jìn)程將調(diào)用另一個(gè)函數(shù)去處理該結(jié)果盆色，該函數(shù)即回調(diào)函數(shù)灰蛙，其參數(shù)為返回結(jié)果
p.close()
p.join()
- 等待所有工作進(jìn)程退出祟剔，只能在close()或teminate()之后調(diào)用
補(bǔ)充
回調(diào)函數(shù)的參數(shù)只有一個(gè)，即結(jié)果
回調(diào)函數(shù)是由主進(jìn)程調(diào)用的
回調(diào)函數(shù)應(yīng)該迅速結(jié)束
回調(diào)的順序跟子進(jìn)程啟動(dòng)的順序無(wú)關(guān)
p.map()
并行摩梧，主進(jìn)程會(huì)等待所有子進(jìn)程結(jié)束
p.map_async()

from multiprocessing import Process
from multiprocessing import Pool
from multiprocessing import current_process
import matplotlib.pyplot as plt
import os
import time

global_result=[]

def fib(max):
    n,a,b=0,0,1
    while n<max:
        a,b=b,a+b
        n+=1
    return b

def job(n):
    print('{} is working on {}...'.format(os.getpid(),n))
    time.sleep(2)
    return fib(n)

def add_result(res):#callback func
    global global_result
    print("called by {}, result is {}".format(current_process().pid,res))
    #也可以返回進(jìn)程標(biāo)識(shí)信息物延，用以識(shí)別結(jié)果（比如進(jìn)程的參數(shù)）
    #可以用字典存儲(chǔ)
    global_result.append(res)

def add_result_map(res):
    global global_result
    print("called by {}, result is {}".format(current_process().pid,res))
    for r in res:
        global_result.append(r)

if __name__=='__main__':
    p=Pool()#cpu determines
    ms=range(1,20)
    results=[]
    #同步調(diào)用
    #創(chuàng)建多個(gè)進(jìn)程，但是只有一個(gè)執(zhí)行仅父，需要等到執(zhí)行結(jié)束后再可以返結(jié)果
    #并不并行
    for m in ms:
        print('{} will be applied in main'.format(m))
        res=p.apply(job,args=(m,))#會(huì)等待執(zhí)行結(jié)束后再執(zhí)行下一個(gè)
        print(res)
        print('{} is applied in main'.format(m))
        results.append(res)
    p.close()#!!叛薯！
    print(results)
    plt.figure()
    plt.plot(ms,results)
    plt.show()
    plt.close()
    
    #異步調(diào)用
    #可以并行
    '''for m in ms:
        res=p.apply_async(job,args=(m,))#注意這里res只是一個(gè)引用
        results.append(res)
        #如果馬上打印，可能并沒(méi)有結(jié)果
        print(res)
    p.close()
    p.join()
    results2=[]
    for res in results:
        results2.append(res.get())
    print(results2)
    plt.figure()
    plt.plot(ms,results2)
    plt.show()
    plt.close()'''

    #callback
    '''for m in ms:
        p.apply_async(job,args=(m,),callback=add_result)
        #callback函數(shù)只有一個(gè)參數(shù)
        #callback函數(shù)是由主進(jìn)程執(zhí)行的
    p.close()
    p.join()
    plt.figure()
    plt.plot(ms,sorted(global_result))#順序可能是亂的笙纤，這里可以排序解決耗溜，但其他問(wèn)題不一定
    plt.show()
    plt.close()'''


    #使用map
    '''results3=p.map(job,ms)
    print(type(results3))#list
    p.close()
    plt.figure()
    plt.plot(ms,results3)
    plt.show()
    plt.close()'''

    #使用map_async
    '''p.map_async(job,ms,callback=add_result_map)
    p.close()
    p.join()
    plt.figure()
    print(len(ms))
    print(len(global_result))
    plt.plot(ms,global_result)
    plt.show()
    plt.close()'''

同步調(diào)用時(shí)，res=p.apply(job,args=(m,))會(huì)等待執(zhí)行結(jié)束后再執(zhí)行下一個(gè)省容，所以會(huì)消耗很多時(shí)間抖拴，運(yùn)行時(shí)間長(zhǎng)

1 will be applied in main
9028 is working on 1...
1
1 is applied in main
2 will be applied in main
3396 is working on 2...
2
2 is applied in main
3 will be applied in main
17520 is working on 3...
3
3 is applied in main
4 will be applied in main
12984 is working on 4...
5
4 is applied in main
5 will be applied in main
10720 is working on 5...
8
5 is applied in main
6 will be applied in main
18792 is working on 6...
13
6 is applied in main
7 will be applied in main
14768 is working on 7...
21
7 is applied in main
8 will be applied in main
19524 is working on 8...
34
8 is applied in main
9 will be applied in main
9028 is working on 9...
55
9 is applied in main
10 will be applied in main
3396 is working on 10...
89
10 is applied in main
11 will be applied in main
17520 is working on 11...
144
11 is applied in main
12 will be applied in main
12984 is working on 12...
233
12 is applied in main
13 will be applied in main
10720 is working on 13...
377
13 is applied in main
14 will be applied in main
18792 is working on 14...
610
14 is applied in main
15 will be applied in main
14768 is working on 15...
987
15 is applied in main
16 will be applied in main
19524 is working on 16...
1597
16 is applied in main
17 will be applied in main
9028 is working on 17...
2584
17 is applied in main
18 will be applied in main
3396 is working on 18...
4181
18 is applied in main
19 will be applied in main
17520 is working on 19...
6765
19 is applied in main
[1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765]

異步調(diào)用時(shí)，中間打印不出結(jié)果腥椒，只有在全部執(zhí)行結(jié)束之后才會(huì)出結(jié)果阿宅，但是運(yùn)行速度較快。

<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C16A0>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1780>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1828>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C18D0>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1978>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1A20>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1AC8>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1B70>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1C18>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1CC0>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1D68>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1E10>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1EB8>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1F60>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C1FD0>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C80F0>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C8198>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C8240>
<multiprocessing.pool.ApplyResult object at 0x000001EF6A9C82E8>
21056 is working on 1...
16880 is working on 2...
13832 is working on 3...
17564 is working on 4...
21056 is working on 5...
16940 is working on 6...
12728 is working on 7...
6592 is working on 8...
18296 is working on 9...
16880 is working on 10...
13832 is working on 11...
17564 is working on 12...
21056 is working on 13...
16940 is working on 14...
12728 is working on 15...
6592 is working on 16...
18296 is working on 17...
16880 is working on 18...
13832 is working on 19...
[1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765]

回調(diào)函數(shù)的結(jié)果

4600 is working on 1...
4584 is working on 2...
2892 is working on 3...
10088 is working on 4...
14404 is working on 5...
4600 is working on 6...
called by 14812, result is 116212 is working on 7...

4608 is working on 8...
called by 14812, result is 2
4584 is working on 9...
2632 is working on 10...
called by 14812, result is 3
2892 is working on 11...
called by 14812, result is 5
10088 is working on 12...
called by 14812, result is 8
14404 is working on 13...
called by 14812, result is 13
4600 is working on 14...
called by 14812, result is 21
16212 is working on 15...
called by 14812, result is 34
4608 is working on 16...
called by 14812, result is 55
4584 is working on 17...
called by 14812, result is 89
2632 is working on 18...
called by 14812, result is 144
2892 is working on 19...
called by 14812, result is 233
called by 14812, result is 377
called by 14812, result is 610
called by 14812, result is 987
called by 14812, result is 1597
called by 14812, result is 2584
called by 14812, result is 4181
called by 14812, result is 6765

ProcessPoolExecutor

對(duì)multiprocessing進(jìn)一步抽象
提供更簡(jiǎn)單笼蛛、統(tǒng)一的接口
submit(fn, *args, **kwargs)
- returns a Future object representing the execution of the callable
補(bǔ)充：馬上調(diào)用Future的result()會(huì)阻塞
map(func, *iterables, timeout=None)
? func is executed asynchronously, i.e., several calls to func may be made concurrently and returns an iterator of results

import concurrent.futures
from multiprocessing import current_process
import math

PRIMES = [
    1112272535095293,
    1112582705942171,
    1112272535095291,
    1115280095190773,
    1115797848077099,
    11099726899285419]

def is_prime(n):
    print(f"{current_process().pid}")
    if n % 2 == 0:
        return False
    sqrt_n = int(math.floor(math.sqrt(n)))
    for i in range(3, sqrt_n + 1, 2):
        if n % i == 0:
            return False
    return True

def main_submit():
    results=[]
    with concurrent.futures.ProcessPoolExecutor() as executor:
        for number in PRIMES:
            n_future=executor.submit(is_prime,number)
            #print(n_future.result())#block
            results.append(n_future)
            #這里要注意洒放，如果馬上在主進(jìn)程里獲取結(jié)果，即n_future.result()伐弹，即主進(jìn)程會(huì)阻塞拉馋，無(wú)法并行
            #因此建議先將n_future擱進(jìn)list,等啟動(dòng)所有進(jìn)程后再獲取結(jié)果。
        for number, res in zip(PRIMES,results):
            print("%d is prime: %s" % (number,res.result()))

def main_map():
    with concurrent.futures.ProcessPoolExecutor() as executor:
        for number, prime_or_not in zip(PRIMES, executor.map(is_prime, PRIMES)):
            print('%d is prime: %s' % (number, prime_or_not))

if __name__ == '__main__':
    main_submit()
    #main_map()

8004
8004
1112272535095293 is prime: False
4332
18212
18212
18212
1112582705942171 is prime: True
1112272535095291 is prime: True
1115280095190773 is prime: False
1115797848077099 is prime: False
11099726899285419 is prime: False

多進(jìn)程

分布式多進(jìn)程
- 多機(jī)環(huán)境
- 跨設(shè)備數(shù)據(jù)交換
- master-worker模型
- 通過(guò)manager暴露Queue
GIL(Global Interpreter Lock)
- GIL非Python特性惨好，而是實(shí)現(xiàn)Python解釋器（Cpython）時(shí)引入的概念
- GIL本質(zhì)上是互斥鎖煌茴，控制同一時(shí)間共享數(shù)據(jù)只能被一個(gè)任務(wù)修改，以保證數(shù)據(jù)安全
- GIL在解釋器級(jí)保護(hù)共享數(shù)據(jù)日川，在用戶(hù)編程層面保護(hù)數(shù)據(jù)則需要自行加鎖處理
- Cpython解釋器中蔓腐，同一個(gè)進(jìn)程下開(kāi)啟的多線程，同一時(shí)刻只能有一個(gè)線程執(zhí)行龄句，無(wú)法利用多核優(yōu)勢(shì)
  - 可能需要先獲取GIL

多線程編程

多進(jìn)程Process	多線程thread
可以利用多核	無(wú)法利用多核
開(kāi)銷(xiāo)大	開(kāi)銷(xiāo)小
計(jì)算密集型	IO密集型
金融分析	socket回论，爬蟲(chóng)，web

threating模塊
multiprocessing模塊和threating模塊在使用層面十分類(lèi)似
threading.currentThread()：返回當(dāng)前的線程實(shí)例
threading.enumerate()：返回所有正在運(yùn)行線程的list
threading.activeCount()：返回正在運(yùn)行的線程數(shù)量分歇，與len(threading.enumerate())結(jié)果相同
創(chuàng)建多線程
- 通過(guò)指定target參數(shù)
- 通過(guò)繼承Thread類(lèi)
- 設(shè)置守護(hù)線程
  - setDaemon(True)
  - 應(yīng)在start()之前

from threading import Thread,currentThread
import time

def task(name):
    time.sleep(2)
    print('%s print name: %s' %(currentThread().name,name))

class Task(Thread):
    def __init__(self,name):
        super().__init__()
        self._name=name
    
    def run(self):
        time.sleep(2)
        print('%s print name: %s' % (currentThread().name,self._name))

if __name__ == '__main__':
    n=100
    var='test'
    t=Thread(target=task,args=('thread_task_func',))
    t.start()
    t.join()

    t=Task('thread_task_class')
    t.start()
    t.join()
    
    print('main')

Thread-1 print name: thread_task_func
thread_task_class print name: thread_task_class
main

線程同步
- 鎖（threading.Lock,threading.RLock,可重入鎖）
  - 一旦線程獲得重入鎖傀蓉，再次獲取時(shí)將不阻塞
  - 線程必須在每次獲取后釋放一次
  - 區(qū)別：遞歸調(diào)用
- 信號(hào)量 threading.Semaphore
- 事件 threading.Event
- 條件 threading.Condition
- 定時(shí)器 threading.Timer
- Barrier
線程局部變量
隊(duì)列
- queue.Queue
- queue.LifoQueue
- queue.PriorityQueue
線程池 ThreadPoolExecutor

線程和進(jìn)程的比較

from multiprocessing import Process
from threading import Thread
import os,time,random

def dense_cal():
    res=0
    for i in range(100000000):
        res*=i

def dense_io():
    time.sleep(2)#simulate the io delay

def diff_pt(P=True,pn=4,target=dense_cal):
    tlist=[]
    start=time.time()
    for i in range(pn):
        if P:
            p=Process(target=target)
        else:
            p=Thread(target=target)
        tlist.append(p)
        p.start()
    for p in tlist:
        p.join()
    stop=time.time()
    if P:
        name='multi-process'
    else:
        name='multi-thread'
    print('%s run time is %s' %(name,stop-start))

if __name__=='__main__':
    diff_pt(P=True)
    diff_pt(P=False)
    
    diff_pt(P=True,pn=100,target=dense_io)
    diff_pt(P=False,pn=100,target=dense_io)

multi-process run time is 28.328214168548584
multi-thread run time is 64.33887600898743
multi-process run time is 13.335324048995972
multi-thread run time is 5.584061861038208

信號(hào) signal

信號(hào)操作系統(tǒng)中進(jìn)程間通訊的一種有限制的方式
一種異步的通知機(jī)制，提醒進(jìn)程一個(gè)事件已經(jīng)發(fā)生
當(dāng)信號(hào)發(fā)送至進(jìn)程時(shí)职抡，操作系統(tǒng)將中斷其執(zhí)行
? 任何非原子操作都將被中斷
? 如果進(jìn)程定義了該信號(hào)的處理函數(shù)葬燎，將執(zhí)行該函數(shù)，否
則執(zhí)行默認(rèn)處理函數(shù)
? signal.signal(signal.SIGTSTP, handler)
可用于進(jìn)程的中止
Python信號(hào)處理只在主線程中執(zhí)行
? 即使信號(hào)在另一個(gè)線程中接收
? 信號(hào)不能被用作線程間通信的手段
? 只有主線程才被允許設(shè)置新的信號(hào)處理程序

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人面猴
序言：七十年代末，一起剝皮案震驚了整個(gè)濱河市谱净，隨后出現(xiàn)的幾起案子窑邦，更是在濱河造成了極大的恐慌，老刑警劉巖壕探，帶你破解...
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死咒
序言：濱河連續(xù)發(fā)生了三起死亡事件冈钦，死亡現(xiàn)場(chǎng)離奇詭異，居然都是意外死亡李请，警方通過(guò)查閱死者的電腦和手機(jī)瞧筛，發(fā)現(xiàn)死者居然都...
沈念sama閱讀 90,058評(píng)論 2贊 385
救了他兩次的神仙讓他今天三更去死
文/潘曉璐我一進(jìn)店門(mén)，熙熙樓的掌柜王于貴愁眉苦臉地迎上來(lái)捻艳，“玉大人驾窟，你說(shuō)我怎么就攤上這事庆猫∪瞎欤” “怎么了？”我有些...
開(kāi)封第一講書(shū)人閱讀 156,780評(píng)論 0贊 346
道士緝兇錄：失蹤的賣(mài)姜人
文/不壞的土叔我叫張陵月培，是天一觀的道長(zhǎng)嘁字。經(jīng)常有香客問(wèn)我，道長(zhǎng)杉畜，這世上最難降的妖魔是什么纪蜒？我笑而不...
開(kāi)封第一講書(shū)人閱讀 56,388評(píng)論 1贊 283
?港島之戀（遺憾婚禮）
正文為了忘掉前任，我火速辦了婚禮此叠，結(jié)果婚禮上纯续，老公的妹妹穿的比我還像新娘。我一直安慰自己灭袁，他們只是感情好猬错，可當(dāng)我...
茶點(diǎn)故事閱讀 65,430評(píng)論 5贊 384
惡毒庶女頂嫁案：這布局不是一般人想出來(lái)的
文/花漫我一把揭開(kāi)白布。她就那樣靜靜地躺著茸歧，像睡著了一般倦炒。火紅的嫁衣襯著肌膚如雪。梳的紋絲不亂的頭發(fā)上软瞎，一...
開(kāi)封第一講書(shū)人閱讀 49,764評(píng)論 1贊 290
城市分裂傳說(shuō)
那天逢唤，我揣著相機(jī)與錄音，去河邊找鬼涤浇。笑死鳖藕，一個(gè)胖子當(dāng)著我的面吹牛，可吹牛的內(nèi)容都是我干的只锭。我是一名探鬼主播著恩，決...
沈念sama閱讀 38,907評(píng)論 3贊 406
雙鴛鴦連環(huán)套：你想象不到人心有多黑
文/蒼蘭香墨我猛地睜開(kāi)眼，長(zhǎng)吁一口氣：“原來(lái)是場(chǎng)噩夢(mèng)啊……” “哼！你這毒婦竟也來(lái)了页滚？” 一聲冷哼從身側(cè)響起召边，我...
開(kāi)封第一講書(shū)人閱讀 37,679評(píng)論 0贊 266
萬(wàn)榮殺人案實(shí)錄
序言：老撾萬(wàn)榮一對(duì)情侶失蹤，失蹤者是張志新（化名）和其女友劉穎裹驰，沒(méi)想到半個(gè)月后隧熙，有當(dāng)?shù)厝嗽跇?shù)林里發(fā)現(xiàn)了一具尸體，經(jīng)...
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?護(hù)林員之死
正文獨(dú)居荒郊野嶺守林人離奇死亡幻林，尸身上長(zhǎng)有42處帶血的膿包…… 初始之章·張勛以下內(nèi)容為張勛視角年9月15日...
茶點(diǎn)故事閱讀 36,459評(píng)論 2贊 325
?白月光啟示錄
正文我和宋清朗相戀三年贞盯，在試婚紗的時(shí)候發(fā)現(xiàn)自己被綠了。大學(xué)時(shí)的朋友給我發(fā)了我未婚夫和他白月光在一起吃飯的照片沪饺。...
茶點(diǎn)故事閱讀 38,605評(píng)論 1贊 340
活死人
序言：一個(gè)原本活蹦亂跳的男人離奇死亡躏敢，死狀恐怖，靈堂內(nèi)的尸體忽然破棺而出整葡，到底是詐尸還是另有隱情件余，我是刑警寧澤，帶...
沈念sama閱讀 34,270評(píng)論 4贊 329
?日本核電站爆炸內(nèi)幕
正文年R本政府宣布遭居，位于F島的核電站啼器，受9級(jí)特大地震影響，放射性物質(zhì)發(fā)生泄漏俱萍。R本人自食惡果不足惜端壳，卻給世界環(huán)境...
茶點(diǎn)故事閱讀 39,867評(píng)論 3贊 312
男人毒藥：我在死后第九天來(lái)索命
文/蒙蒙一、第九天我趴在偏房一處隱蔽的房頂上張望枪蘑。院中可真熱鬧损谦，春花似錦、人聲如沸岳颇。這莊子的主人今日做“春日...
開(kāi)封第一講書(shū)人閱讀 30,734評(píng)論 0贊 21
一樁弒父案，背后竟有這般陰謀
文/蒼蘭香墨我抬頭看了看天上的太陽(yáng)赦役。三九已至麻敌，卻和暖如春，著一層夾襖步出監(jiān)牢的瞬間掂摔，已是汗流浹背术羔。一陣腳步聲響...
開(kāi)封第一講書(shū)人閱讀 31,961評(píng)論 1贊 265
情欲美人皮
我被黑心中介騙來(lái)泰國(guó)打工，沒(méi)想到剛下飛機(jī)就差點(diǎn)兒被人妖公主榨干…… 1. 我叫王不留乙漓，地道東北人级历。一個(gè)月前我還...
沈念sama閱讀 46,297評(píng)論 2贊 360
代替公主和親
正文我出身青樓，卻偏偏與公主長(zhǎng)得像叭披，于是被迫代替她去往敵國(guó)和親寥殖。傳聞我的和親對(duì)象是個(gè)殘疾皇子玩讳，可洞房花燭夜當(dāng)晚...
茶點(diǎn)故事閱讀 43,472評(píng)論 2贊 348

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