I was running some of the answers to see what is the fastest way for a large number. So, I found that we can convert the int to an array and it can give the correct results and it is faster.
arrayint=np.array(myInt)
newList = myList / arrayint
This a comparison of all answers above
import numpy as np
import time
import random
myList = random.sample(range(1, 100000), 10000)
myInt = 10
start_time = time.time()
arrayint=np.array(myInt)
newList = myList / arrayint
end_time = time.time()
print(newList,end_time-start_time)
start_time = time.time()
newList = np.array(myList) / myInt
end_time = time.time()
print(newList,end_time-start_time)
start_time = time.time()
newList = [x / myInt for x in myList]
end_time = time.time()
print(newList,end_time-start_time)
start_time = time.time()
myList[:] = [x / myInt for x in myList]
end_time = time.time()
print(newList,end_time-start_time)
start_time = time.time()
newList = map(lambda x: x/myInt, myList)
end_time = time.time()
print(newList,end_time-start_time)
start_time = time.time()
newList = [i/myInt for i in myList]
end_time = time.time()
print(newList,end_time-start_time)
start_time = time.time()
newList = np.divide(myList, myInt)
end_time = time.time()
print(newList,end_time-start_time)
start_time = time.time()
newList = np.divide(myList, myInt)
end_time = time.time()
print(newList,end_time-start_time)