Testing various approaches of iterating through python lists using indexes

main.py

from time import time
n = 10**4
arr = [i for i in range(n)]

def test_fun(i):
  # some compuatations
  a =0
  b =0
  a+=arr[i]*arr[i]*arr[i]*arr[i]*arr[i]*arr[i]
  b+=arr[i]+arr[i]+arr[i]+arr[i]+arr[i]+arr[i]
  a+=arr[i]*arr[i]*arr[i]*arr[i]*arr[i]*arr[i]
  b+=arr[i]+arr[i]+arr[i]+arr[i]+arr[i]+arr[i]
  a+=arr[i]*arr[i]*arr[i]*arr[i]*arr[i]*arr[i]
  b+=arr[i]+arr[i]+arr[i]+arr[i]+arr[i]+arr[i]
  a+=arr[i]*arr[i]*arr[i]*arr[i]*arr[i]*arr[i]
  b+=arr[i]+arr[i]+arr[i]+arr[i]+arr[i]+arr[i]
  c = a+b
  arr[i] = c

# Approach 1: The standard and most optmimized way[in python]
st = time()
for i in range(n):
  test_fun(i)
fin = time()
print('Time for approach 1: ', fin-st)

# Approach 2
st = time()
i = 0
while(True):
  try:
    test_fun(i)
    i+=1
  except:break
fin = time()
print('Time for approach 2: ', fin-st)

# Approach 3
st = time()
i = 0
while i!=n:
  test_fun(i)
  i+=1
fin = time()
print('Time for approach 3: ', fin-st)

# Approach 4
st = time()
i = 0
while True:
  test_fun(i)
  i+=1
  if i==n:break
fin = time()
print('Time for approach 4: ', fin-st)

Results on colab:

Time for approach 1:  0.030594587326049805
Time for approach 2:  0.03899192810058594
Time for approach 3:  0.2079174518585205
Time for approach 4:  4.617676734924316