How to use lock as a mutex in multiprocessing?

I want to have two processes, one writing and one reading on/from the same variable. The data written is like this:

[0, 0]
[0, 1]
[1, 0]
[1, 1]
[2, 0]
[2, 1]
[3, 0]
[3, 1]
[4, 0]
[4, 1]
[5, 0]
[5, 1]
[6, 0]
[6, 1]
[7, 0]
[7, 1]
[8, 0]
[8, 1]
[9, 0]
[9, 1]

But I'm having trouble because the reading process is reading between the variable change, forming new pairs, so I want to use a Lock/Mutex to prevent this from happening again. I guess I'd have to lock the object before changing it. OBS: The object is shared between processes using a manager.

Here is the main code:

import multiprocessing

def mde(dad, mutex):
    for i in range(10):
        for j in range(2):
            mutex.acquire()
            dad[0] = i
            dad[1] = j
            mutex.release()
def mda(dad):
    c = 0
    while c < 30:
        print(dad)
        c += 1

if __name__ == '__main__':
    manager = multiprocessing.Manager()
    mutex = manager.Lock()
    dado = manager.list([0, 0])
    p1 = multiprocessing.Process(target=mde, args=(dado, mutex,))
    p2 = multiprocessing.Process(target=mda, args=(dado,))
    p1.start()
    p2.start()
    p1.join()
    p2.join()

As you can see I tried to lock and unlock the variable in the writing process but the result still was mixed up. What am I doing wrong?

Here is the corrected version (credit to MisterMiyagi). Both workers are waiting for each other to do their task, i.e. modifying the list, or displaying it.

import multiprocessing

NX = 10
NY = 2


def mde(dad, mutex):
    for i in range(NX):
        for j in range(NY):
            mutex.acquire()
            dad[0] = i
            dad[1] = j
            mutex.release()


def mda(dad, mutex):
    c = 0
    while c <= NX*NY:
        mutex.acquire()
        print(dad)
        c += 1
        mutex.release()

if __name__ == '__main__':
    manager = multiprocessing.Manager()
    mutex = manager.Lock()
    dado = manager.list([0, 0])
    p1 = multiprocessing.Process(target=mde, args=(dado, mutex,))
    p2 = multiprocessing.Process(target=mda, args=(dado, mutex,))
    p1.start()
    p2.start()
    p1.join()
    p2.join()