Python Full stack development day34-threading Thread

One, yesterday content review 1. Concepts and theories

Process is the smallest unit of computer resource allocation

Process three-state, synchronous, asynchronous, blocking, non-blocking

2. Creation of processes

Instantiation, self-built class Run,start,join,terminate,daemon, etc.

3. Synchronization control of the process

Lock: Mutual exclusion lock

Semaphore: Lock + counter

Event: Events

4. Inter-process communication queue queue:put, get, empty, full, put_nowait, get_nowait pipe + lock

Data security between processes-process security

Can be any data type

Piping pipe:

With both ends, two-way communication

Need to shut down all the unused ports, will be in the Recv place error

Process not secure

5. Data sharing manager:dict,list

# processes are used on the same computer

# data is not secure between processes

Data sharing between processes currently in use: Message middleware

#memcache

#rabbitmq

#redis

6. Process Pools Pool

#什么情况下用进程池:

# High-CPU code requires process pooling

#进程池cpu个数 +1

# Pool

Apply Sync

Apply_async Asynchronous Commit

#get Get the return value

#close

#join

Map

# Apply_async's simplified version, which implements the close and join methods internally

#但是没有get方法, the return value cannot be accepted

callback function: Apply_async (callback=???)

# The callback function is actually executed in the main process

7, signal volume and process pool differences, the use of semaphores

#在同一时刻只会有n个进程在执行某段代码

#不同:

#信号量是有多少任务开启多少进程, the semaphore still brings a lot of burden to the operating system.

# The number of processes in the pool is fixed, just borrowing the process from the pool to perform the task

The use of semaphores (in the same target function, the high IO portion with multiple processes, the high CPU portion is calculated with semaphores, thus saving process switching overhead):

　　　　　　　　

Two, thread 1. Thread Concepts and Features

Why does a process also have threads open:

　　　　

A thread is the smallest unit in a computer that can be scheduled by the CPU:

Features of Multithreading: concurrency, lightweight, data not isolated

Multi-process Features: concurrency, cumbersome operation, data isolation

2. Thread opening

　　　　　　　　

ImportJSONImportTime,os fromThreadingImportThreaddeffunc (): forIinchRange (10): Time.sleep (0.5)        Print('Thread:', I,os.getpid ())if __name__=='__main__': T= Thread (target=func) T.start () Time.sleep (1)    Print('In main 1', Os.getpid ()) Time.sleep (1)    Print('In main 2', Os.getpid ())

the main thread and the child thread are in the same process

3. Efficiency test

　

 fromMultiprocessingImportProcess fromThreadingImportThreadImport Timedeffunc (num):Print(num**num)if __name__=='__main__': P_lst=[] Start=time.time () forIinchRange (50): P= Process (Target=func, args=(i,)) P.start () P_lst.append (p) forIinchP_lst:i.join ()Print('======', Time.time ()-start) T_lst=[] Start=time.time () forIinchRange (50): T= Thread (Target=func, args=(i,)) T.start () T_lst.append (p) forIinchT_lst:i.join ()Print('********', Time.time ()-start)

Multithreading is more than a few orders of magnitude for high computational tasks

4. Data Isolation Testing

 from Import  =100def  func ():    Global  n    -=1 = Thread (target=  Func) T.start () t.join ()print(n)

data isolation, thread sharing process resources

5. Sub-processes and master processes

 from  threading import   Thread,currentthread  import   time  def   func (): Time.sleep ( 1)  print  ("   child process  "  , CurrentThread ()) T  = Thread (Target=func) T.start ()  print  ( " Span style= "COLOR: #800000" > main process   ", CurrentThread ()) #   The main thread end means the master process ends, and the main line routines waits for the child thread to end  

The main thread end means the master process is finished, and the main thread routines waiting for the child thread to end.6. Global Interpreter lock Gil

　　　　　　

Python Full stack development day34-threading Thread