[Python] how to create uniform nested lists and convert them in to multi dimensional arrays?

i would like to create a nested list of arbitrary depth (containing numerical values specifically) with uniform arbitrary lengths at each level and then compress it to a NumPy array of minimum dimensions ie. if a layer of lists all length 1 all lists at that depth are unpacked.

example:


import random as ran
import numpy as np

prompt = (3,1,5,1)
#promt length and positions of 1 should be arbitrarily
old_list = []

for a in range(prompt[0]):
old_list.append([])
for b in range(prompt[1]):
old_list[a].append([])
for c in range(prompt[2]):
old_list[a].append([])
for d in range(prompt[3]):
#using random outputs for simplicity, could be anything
old_list[a][c].append(ran.randint(0, 10))

new_list = []
for a in range(prompt[0]):
new_list.append([])
#prompt[1] should be automatically skipped as it is 1
for c in range(prompt[2]):
#prompt[3] should be automatically skipped as it is 1
new_list[a].append(old_list[a][0][c][0])
final = np.array(new_list)

print(f'''{final}
is clearly and more useful and tidier than
{old_list} ''')


I expect there is some way of automating for loops in the manner described, and compacting them as well, in NumPy, but I don't Know where to get started. any help would be apreciated. thankyou!

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