Python Finishing-day11

One, thread

1. Basic use

Create threads in two ways

The first type:

Import Threadingdef F1 (ARG):    print (ARG) t=threading. Thread (target=f1,args= (123,)) T.start ()

Results:

123

The second type:

Import Threadingclass Myclass (threading. Thread):    def __init__ (Self,func,args):        self.func=func        self.args=args        Super (myclass,self). __init __ ()    def run (self):        Self.func (Self.args) def F2 (ARG):    print (ARG) obj=myclass (f2,123) Obj.start ()

Results:

123

The second method is to create the already class ourselves and then call threading. Thread this parent class, and then use Super to make the call

2, the creator consumer model (queue, but unlike RABBITMQ, this is Python's own)

Queue: There are four queues in total, namely FIFO queue, LIFO queue, Priority queue, two-way queue

Import Queueq=queue. Queue (2) print (Q.empty ()) q.put (one) q.put () print (Q.qsize ()) print (Q.get ()) Q.get () Q.task_done () print (Q.get ()) Q.get () Q.task_done () #q. Join ()

Results:

True211

This is the normal FIFO queue.

Put is put data, whether blocking, blocking Yes timeout

Get is fetching data (default blocking), blocking, time-out when blocking

Queue. Queue (2) Maximum length

Qsize () True number

MaxSize Maximum number of supported

Join, Task_done, block the process, and no longer block when a task in the queue finishes executing

Import Queueq=queue. Lifoqueue () q.put (123) q.put (345) print (Q.get ()) Q1=queue. Priorityqueue () Q1.put ((1, "WZC1")) Q1.put ((1, "Wzc11")) Q1.put ((1, "wzc1111")) Q1.put ((1, "wzc111")) Q1.put ((3, "WZC3") ) Q1.put ((2, "WZC4")) print (Q1.get ()) Q2=queue.deque () q2.append (123) q2.append (333) q2.appendleft (456) print (Q2.pop () ) Print (Q2.popleft ())

Results:

345 (1, ' wzc1 ') 333456

Post-backward-out queue ==lifoqueue

Priority Queue ==priorityqueue

Bidirectional queue ==deque

Thread Lock

The difference between lock and Rlock, one is to support only single-layer lock, one is to support multi-layer lock

Import Threadingimport timenum=10def func (WWW):    global NUM    www.acquire ()    num-=1    time.sleep (1)    Print (NUM)    www.release () lock=threading. Lock () for I in range:    t=threading. Thread (target=func,args= (lock,))    T.start ()

Results:

9876543210

Mport threadingdef func (i,e):    print (i)    e.wait () #检测是什么信号    print (i+100) event=threading. Event () for I in range:    t=threading. Thread (target=func,args= (i,event,))    T.start () event.clear () #禁止信号inp =input (">>>") if InP = = "1":    Event.set () #通行信号

Results:

012345678910111213141516171819>>>1103102106107108109112113115118101104110114117100116105119111

Another way to use

Import threadingdef func (I,con):    print (i)    con.acquire ()    con.wait ()    print (i+100)    con.release ( ) c=threading. Condition () for I in range:    t=threading. Thread (target=func,args= (I,c,))    T.start () while True:    inp=input (">>>")    if InP = = "Q":        Break    C.acquire ()    c.notify (int (INP))    c.release ()

Results:

012345678910111213141516171819>>>3>>>1011001022>>>1031045>>> 105108106109107

Ii. process

1. Basic use

　　

From multiprocessing import processfrom  multiprocessing import queuesimport multiprocessingimport timedef foo (i, ARG):    arg.put (i)    print ("Say HI", I,arg.qsize ()) li=queues. Queue (20,ctx=multiprocessing) for I in range:    p=process (target=foo,args= (I,li,))     P.start ()

process test without the IF __name__ = = ' __main__ ': Windows cannot execute, but Linux and mac can, plus can execute

Basic use

Default data is not shared

Queue

Array

Manager.dict

Pipe

Process Pool

Array

From multiprocessing import processfrom  multiprocessing import arrayimport multiprocessingimport timedef foo (i,arg ):    arg[i]=i+100    for items in arg:        print (items)    print ("========") Li=array ("I", ten) for I in Range (10):    p=process (target=foo,args= (I,li,))    P.start ()

Results:

　　

100000000000========10010100000000========1001011020000000========100101102103000000======== 10010110210310400000========1001011021031041050000========100101102103104105106000======== 10010110210310410510610700========1001011021031041051061071080========100101102103104105106107108109========

Manager.dict

From multiprocessing import processfrom  multiprocessing import managerimport multiprocessingimport timedef foo (i, ARG):    arg[i]=i+100    print (Arg.values ()) Obj=manager () li=obj.dict () for I in range:    p=process (target= Foo,args= (I,li,))    P.start () Time.sleep (0.1)

Results:

[100] [100, 101] [100, 101, 102] [100, 101, 102, 103] [100, 101, 102, 103, 104] [100, 101, 102, 103, 104, 105] [100, 101, 102, 103, 104, 105, 106] [100, 101, 102, 103, 104, 105, 106, 107] [100, 101, 102, 103, 104, 105, 106, 107, 108, 109] [100, 101, 102, 103, 104, 105, 106, 107, 108, 109]

Process Pool

Pool.close () All tasks are completed

Pool.terminal () immediate termination

From multiprocessing import poolimport timedef F1 (ARG):    time.sleep (1)    print (ARG) Pool=pool (5) for I in range (30) :    #pool. Apply (func=f1,args= (i))    Pool.apply_async (func=f1,args= (i)) pool.close () #time. Sleep (1) # Pool.terminate () Pool.join ()

Results:

01234567891110121314161517181921222023242527262829

Third, the co-process

1. When to use the co-process

2, Greenlet

3, Gevent

Greenlet:

From Greenlet import Greenletdef test1 ():    print (All)    gr2.swith ()    print (Gr2.swith) ()    def test2 ():    Print (Gr1.swith) (    ) print (Gr1=greenlet) (    test1) gr2=greenlet (test2) Gr1.swith ()

Gevent:

From gevent import monkey;monkey.patch.all () import geventimport requestsdef f (URL):    print ("GET:%s"% URL)    resp =requests.get (URL)    data=resp.text    print ("%d bytes received from%s"% (len (data), URL)) Gevent.joinall ([    Gevent.spwan (F, ' Https://www.baidu.con '),    Gevent.spwan (F, ' Https://www.yahoo.con '),    Gevent.spwan (F, ' Https://www.github.con ')])

Python Finishing-day11