# [SOLVED] Is there a better way to find index of an element without using list built-in functions?

## Issue

We can get the index of an element in a list using the `.index()` function.
I was wondering if there’s any better way to find the index without using the built-in function (of list).

Currently, I have written the following code using `enumerate`:

``````x = int(input("Enter a number to get the index:"))
l = [3,11,4,9,1,23,5]
if x in l: # I think this line is unnecessary and is increasing the time.
for i, val in enumerate(l):
#Instead checking for x above can i use
#if x == val: Don't worry about the indentation I'll fix it.
print(f"Index of {x} is {i}.")
else:
``````

So, is there a better way(in terms of time taken) to accomplish this?
I want a better implementation than the code I have written above and not in terms of `.index`.

## Solution

use list comprehension in python

``````l = [3, 11, 4, 9, 1, 23, 5, 11]
indexes = [index for index in range(len(l)) if l[index] == 11]
``````

## output:

``````[1, 7]
``````

use `numpy` for finding the matching indices.

``````l = [3, 11, 4, 9, 1, 23, 5, 11]
np_array = np.array(l)
item_index = np.where(np_array == 11)
print (item_index)
``````

## Numpy is efficient:

``````import random
import time

import numpy as np

limit = 10 ** 7
l = [None] * limit
for i in range(limit):
l[i] = random.randint(0, 1000000)

start = time.time()
np_array = np.array(l)
item_index = np.where(np_array == 11)
print('time taken by numpy', time.time() - start)

start = time.time()
for index, value in enumerate(l):
if (value == 11):
pass
print('time taken by enumerate',time.time() - start)
``````

## Output:

``````time taken by numpy 0.9375550746917725
time taken by enumerate 1.4508612155914307
``````

## timeit

``````import random
import sys
import time
from multiprocessing import Process

import numpy as np

start = time.time()
limit = (10 ** 4)
l = [None] * limit
for i in range(limit):
l[i] = random.randint(0, 1000000)

def testNumpy():
np_array = np.array(l)
for i in range(1000):
value = random.randint(0, 1000000)
item_index = np.where(np_array == value)

def testEnumerate():
for i in range(1000):
randValue = random.randint(0, 1000000)
for index, value in enumerate(l):
if (value == randValue):
pass

def _testNumpy(repeat):
import timeit
s = """\
testNumpy()
"""
print(timeit.timeit(stmt=s, setup="from __main__ import testNumpy", number=repeat, globals=globals()),
end=":numpy\n")

def _testEnumerate(repeat):
import timeit
s = """\
testEnumerate()
"""
print(timeit.timeit(stmt=s, setup="from __main__ import testEnumerate", number=repeat, globals=globals()),
end=':enumerate\n')

if __name__ == "__main__":
repeat = 10
processes = [Process(target=_testNumpy, args=(repeat,)), Process(target=_testEnumerate, args=(repeat,))]
for process in processes:
process.start()

for process in processes:
process.join()
``````

## Output:

``````0.2232685430001311:numpy
8.573617108999997:enumerate
``````