Python 中的多处理创建单个进程

Question

I have an issue with multiprocessing in python, refer to my code below:

processArray = []
downtimeObj = []
for x in range(0,len(clientMaster)):
    downtimeObj.append(Downtime(clientMaster[x]))
    processArray.append(multiprocessing.Process(target=downtimeObj[x].live(),))
    for j in range(len(processArray)):
        processArray[j].start()
    for z in range(len(processArray)):
        processArray[z].join()

Here I have an array of processes "processArray" and an array of objects of class Downtime. In my client master, im trying to iterate through the number of clients I have and create an object for each client, thereby creating a process for each client.

The current code creates a single process and runs the live() function chronologically.

I wish for all clients to have separate processes and the object.live() function to run simultaneously.

Answer 1

You should change indentation and first run loop which only creates all processes. Next loop which runs .start() . And finally loop which use .join()

And Process() (similar to Thread() ) needs function's name without () so later it can use () to start in in new process.

target=downtimeObj[x].live

If you use with () then it runs live() in current process and send its result as argument for Process() like

result = downtimeObj[x].live()
Process(target=result)

You could also learn to use for -loop without range(len()) - it will be more readable.

processArray = []
downtimeObj = []

# --- loop ---

for item in clientMaster:
    obj = Downtime(item)
    downtimeObj.append(obj)
    p = multiprocessing.Process(target=obj.live)
    processArray.append(p)

# --- after loop ---

for p in processArray:
    p.start()

for p in processesArray:
    p.join()

---

OR you should at least .join() run outside first loop

processArray = []
downtimeObj = []

# --- loop ---

for item in clientMaster:
    obj = Downtime(item)
    downtimeObj.append(obj)
    p = multiprocessing.Process(target=obj.live)
    processArray.append(p)
    p.start()

# --- after loop ---

for p in processesArray:
    p.join()

---

EDIT:

If you need to send arguments then use tuple ie. (value1, value2)

Process(target=obj.live, args=(value1, value2))

and will run live(value1, value2)

For single argument you also need tuple ie. (value1,)
It needs , inside ( ) to create tuple with single element.

Process(target=obj.live, args=(value1,))

and will run live(value1)

You can see it also in documentation Process

---

EDIT:

If you want to use Pool to always runs only 5 processes and get all results

from multiprocessing import Pool

# --- function for Process ---

def my_function(item, arg1, arg2):
    obj = Downtime(item)
    return obj.live(arg1, arg2)

# --- create arguments for all processes ---

arguments = []

for item in clientMaster:
    arguments.append( (item, value1, value2) )

# --- use Pool and wait for all results ---

with Pool(5) as p:
     results = p.starmap(my_function, arguments)

# --- display all results ---

print(results)