Python Array vs. List | What’s Difference?
In this tutorial, we will understand the key difference between the Python array vs. list with the help of examples.
Python is a popular high-level computer programming language known for its simplicity and versatility in the world. It provides an extensive set of data structures that help programmers to manage and organize data.
Such data structures provided by Python are lists, tuples, sets, and dictionaries that offer several features and functions. Out of these, lists are the most simple, effective, and easy-to-use data structure in Python.
Python, on the other hand, does not offer built-in support to the array. To use an array in Python, we need to import the array module or use the NumPy package in the program. This is the major difference between the array and list.
However, both can be used to store a collection of elements or data, but there are also some fundamental differences between array and list.
So, in this tutorial, we will explore the fundamental difference between array and list in Python. We will understand the basic introductions of each data structure, compare their performance, and discuss the scenarios where we will prefer to use over each other.
Before understanding about this topic in deep, let’s have a brief introduction to both data structures.
What is an Array in Python?
An array in Python is a linear data structure used to store a fixed-size sequential collection of homogenous elements (i.e. data) i.e. belonging to the similar data type.
To create an array in Python, we need to use NumPy module or the built-in array module, as shown in the below code.
import array as arr
or
import numpy as np
Array is an ordered, mutable, and enclosed in square brackets ([ ]). It can store the non-unique elements. In an array, elements are allocated in contiguous memory locations (i.e. one after another) that allow programmers to easy modification, addition, deletion, accessing of elements.
Let us take an example program based on the array.
Example:
# Creating an array containing elements of same data type.
import array
arr = array.array('i', [10, 20, 30, 40])
# Accessing elements of array.
for i in arr:
print(i)
What is a List in Python?
A list is a built-in linear data structure in Python used to store a collection of heterogeneous elements of different data types. It is a mutable data type, meaning we can add, remove, or modified into the existing list without creating a new list object.
We can also resize lists at runtime as well as perform different many operations, such as indexing, iterating, and slicing. Elements of a list are enclosed in a square bracket and separated by each element by a comma.
Here is an example of it.
Example:
# Creating a list containing three elements having different data types.
mixed_list = [10, "Python", ['a','b', 'c']]
# Accessing elements of array.
for i in mixed_list:
print(i)
Output:
10
Python
['a', 'b', 'c']
Lists are an ordered collection of elements, which means elements are stored in a particular order. We can use index to access elements of a list.
Differences Between Array and List in Python
(a) Definition and Purpose:
The first key difference between arrays and lists is their definition and purpose. Arrays store a fixed-size sequential collection of elements of the same data type.
Lists, on the other hand, store a collection of elements of different data types and we can resize it at runtime.
(b) Data Type Support
Arrays are homogeneous in nature that can only store elements of the similar data type, while lists are heterogeneous in nature that can store elements of different data types.
This means that arrays are more limited in features than lists, but they can be more efficient in regarding with memory usage and processing speed.
(c) Memory Allocation:
In Python, arrays are static in nature. We need to define the array size before using it in the program. Lists, on the other hand, are dynamic in nature. They shrink and expand in accordance with elements added or deleted from the list.
(d) Wastage of Memory:
As we know, it is essential to declare the array size before using it. So, if we enter lesser elements in an array as compared to declared size, then a lot of memory will waste.
List, on the other hand, is dynamic in nature. Because of this feature, no waste of memory occurs in the list data type.
(e) Methods and Functions Availability:
One of the major difference between array vs. list in Python is that array provides a lesser number of methods and functions. Programmers need to define their own code to perform certain tasks.
List, on the other hand, provides programmers numerous methods and functions to perform various tasks without writing long code.
(f) Flexibility:
An array does not provide flexibility. It only stores elements under size defined at the time of declaration. While a list provides a flexibility feature. It allows to add elements in the list without changing the size of list.
(g) Insertion and Deletion:
When we insert or delete an element in an array, a lot of shifting of elements takes place after the insertion point or the deletion point, which can be time-consuming. In contrast, we can easily insert or delete elements in the list without shifting other elements into the list.
(h) Performance:
Arrays can be more efficient as compared to lists while working with large amounts of data. This is because they have a fixed size and are allocated into the contiguous blocks of memory, which makes them faster to access and process.
In contrast, lists can consume more memory and may be slower to access and process.
(i) Usage in Python:
Single-dimensional array is used in Python as an object but for using multi-dimensional array, we will have to use numpy arrays. In contrast, a single or multidimensional array is directly used as an object in Python.
(j) When to Use an Array vs. a List:
Arrays are best suitable for storing large amounts of data of the same data type. They are especially useful when working with scientific computing, data analysis, and mathematical operations.
In contrast, lists are more versatile and can store a variety of data types and sizes. They are suitable for those cases where we do not know the size of the data in advance and can be need to be adjusted at runtime. They can be used in many situations, like storing user input, managing files and directories, and building complex data structures.
Google FAQ on Python Array vs. List
Q: It is possible to convert an array to a list in Python?
A: Yes, it is possible to convert an array to a list using the tolist() method provided by the NumPy module.
Q: It is possible to nest lists and arrays in Python?
A: Yes, it is possible to nest lists and arrays in Python. It means that we will create a list or an array of lists or arrays.
Q: Which data structure is faster in Python array or list?
A: Arrays are in general faster than compared to lists when working with large amounts of data of the same data type because they are allocated into the contiguous blocks of memory, which makes them faster to access and process.
In this tutorial, you have known about the basic difference between Python array vs. list. The primal difference between array and list in Python is their definition and purpose. Arrays are best appropriate for storing large amounts of data of the same type. They are more efficient in terms of memory usage and processing speed.
In contrast, lists are more versatile that can store elements of different data types with varying sizes. They are perfect for scenarios where we do not know the size of the data in advance and may be need to be adjusted during runtime.
It is necessary for any programmer to know the difference between list and array in Python who works with large amounts of data. By understanding strengths and weaknesses of arrays and lists, programmers can pick out the relevant data structure for their particular scenarios and optimize their code for better performance.
Hope that you will have understood the basic points of difference between array vs. list in Python.
Thanks for reading!!!
