Concurrent futures threading running at same speed as non-threading

[buran]

import concurrent.futures
from concurrent.futures import ThreadPoolExecutor

def add(args):
    print('inside add')
    return sum(args)

args = [(4, 2), (9, 3), (16, 2)]

with ThreadPoolExecutor(max_workers=5) as executor:
    for result in executor.map(add, args):
        print(result)

Output:
inside add
inside add
6
inside add
12
18

[billykid999]

Still I think you want executor.submit(i, ConnectHandler, ip), not executor.submit(i(ConnectHandler, ip))

using executor.map would expect that you pass iterable as second argument

                for i in inlistx:
                    executor = ThreadPoolExecutor(max_workers=50)
                    res = executor.submit(i, ConnectHandler,ip)
                    res.result()

It came out to the same 32 seconds as before. I also tried res = executor.submit(i, ConnectHandler) and it parsed correctly at about 30ish seconds. It's okay I tried not the end of the world. I will keep working at it, at least I learned something new.

[buran]

Note that it may be multithreading vs multiprocessing issue (i.e. as I am not 100% sure I understand what you do, I don't know if multithreading vs multiprocessing should be used). Try using ProcessPoolExecutor instead

[billykid999]

Note that it may be multithreading vs multiprocessing issue (i.e. as I am not 100% sure I understand what you do, I don't know if multithreading vs multiprocessing should be used). Try using ProcessPoolExecutor instead

these are all I/O operations that send commands to devices and wait for a result, so normally that would be that last place I would look at because of what i've read working with network devices ~ I will however tryi it.