In this tutorial, we will learn about **how to find sum of elements in List Python using 5 best examples. **In Python, List allows various operations like, adding elements, searching element, deleting elements, list comparison and so on. One of the basic and widely used operation is adding elements of a List to find the total value. This is one of the vital List operation specially when we deal with large data set. We will learn about finding the total of all elements in a List using various ways in the upcoming section of this tutorial. So let’s get started.

**Python List Overview**

In Python, List is a versatile data structure which is widely used by Python developers. List allows to store collection of items either of same data type(like int) or different data type(like **int, string, float, list**). List is mutable which means once you create a list, you can modify its elements(**add, remove** or **change** elements). List is defined using** ‘[]’** bracket and elements are inserted withing this bracket.

**How to Find Sum of Elements in List Python [5 Best Examples]**

There are various ways to calculate the sum of elements in a list. We will see which all built-in modules are available in Python which can be utilized to find the elements sum in a list.

**Also Read:** **How to Install python-socketio Stable Diffusion [5 Easy Steps]**

**Example-1: Using ‘sum()’ Function**

In Python, **sum()** is a built-in function that takes an iterable of numbers as its argument and returns the total sum of all those numbers. The syntax of sum() function is given below followed by a code where we have defined a list which hold certain number of integer type elements.

We have also imported the module ‘**time’** which can be used to find the total execution time taken to calculate the sum in a list. we have set the timer at the beginning of code using ‘**time.time()’** function. After completing the execution to calculate the sum, we have again set the timer after the completion of logic to find the elements sum in list. The difference between two timer will return the processing(execution) time taken by the code.

**Syntax**

`sum(iterable, start=o)`

**Code using sum() function**

import time num_list = [2,5,3,8,6] start_time = time.time() sum = sum(num_list) print(f"Sum of all List Elements Using built-in sum() function: {sum}") end_time = time.time() total_time = (end_time - start_time) print(f"Processing took: {total_time:.6f}s")

**OUTPUT**

Sum of all List Elements Using built-in sum() function: 24 Processing took: 0.000027s

**Example-2: Using List Comprehension**

In Python, list comprehension is a technique used to create lists in more concise and readable way. It helps to write short code to create a list by applying an expression to each element in an existing iterable and optionally filtering the elements based on a condition. We will modify the above code to use the List comprehension technique to find the sum of elements in defined list. We will notice that it returns the same output as shown below.

**Syntax**

`new_list = [expression for item in iterable if condition]`

**Code using List comprehension**

import time num_list = [2,5,3,8,6] start_time = time.time() sum = sum([x for x in num_list]) print(f"Sum of all List Elements Using List comprehension: {sum}") end_time = time.time() total_time = (end_time - start_time) print(f"Processing took: {total_time:.6f}s")

**OUTPUT**

Sum of all List Elements Using List comprehension: 24 Processing took: 0.000030s

**Example-3: ****Using ‘reduce()’ Function**

In Python,** ‘functools.reduce()’** function is a higher order function that is used to apply a particular function in a cumulative way to the items of an iterable, reducing the iterable to a single output. Let us again modify the same code to use the reduce method to find the sum of elements in defined list. Save and execute below code.

**Syntax**

`functools.reduce(function, iterable[, initializer])`

**Code using reduce() function**

import time from functools import reduce num_list = [2,5,3,8,6] start_time = time.time() sum = reduce(lambda x, y: x + y, num_list) print(f"Sum of all List Elements Using reduce() function: {sum}") end_time = time.time() total_time = (end_time - start_time) print(f"Processing took: {total_time:.6f}s")

**OUTPUT**

Sum of all List Elements Using reduce() function: 24 Processing took: 0.000044s

**Example-4: Using ‘numpy’ Module**

In Python, ‘**numpy’** is very powerful module and used by developers mostly for numerical and mathematical operations. It provides support for large, multi-dimensional arrays and matrices along with a collection of high-level mathematical functions to operate on these arrays. We will calculate the sum of list elements using **sum()** function which is provided by numpy module as shown below. Save and execute the below code. It will return the same output as returned by all other examples previously.

**Code using numpy module**

import time import numpy as np num_list = [2,5,3,8,6] start_time = time.time() sum = np.sum(num_list) print(f"Sum of all List Elements Using numpy Module: {sum}") end_time = time.time() total_time = (end_time - start_time) print(f"Processing took: {total_time:.6f}s")

**OUTPUT**

Sum of all List Elements Using numpy Module: 24 Processing took: 0.000081s

**Example-5: Using for Loop**

In Python, **for loop** is used to iterate over iterable and do certain operation like, add elements, compare elements or any other supported operation. This is the most common and layman approach to find the summation of list elements as the processing time will be comparatively high. If we have thousands of elements in a list, execution time will be high so this approach is not suggested to used as optimized ways are already available as discussed in above examples.

**Syntax**

```
for variable in sequence:
#code to be executed
```

**Code using for loop**

import time num_list = [2,5,3,8,6] start_time = time.time() sum = 0 for num in num_list: sum += num print(f"Sum of all List Elements Using for loop: {sum}") end_time = time.time() total_time = (end_time - start_time) print(f"Processing took: {total_time:.6f}s")

**OUTPUT**

Sum of all List Elements Using for loop: 24 Processing took: 0.000036s

**Summary**

We have discussed various ways to find the summation of elements in a given list. You can learn more about Pythons’ list operations and usage from its official document available at** python.org**.