Python Design Patterns - List Data Structure

The Lists data structure is a versatile datatype in Python, which can be written as a list of comma separated values between square brackets.

Syntax

Here is the basic syntax for the structure −

List_name = [ elements ];

If you observe, the syntax is declared like arrays with the only difference that lists can include elements with different data types. The arrays include elements of the same data type. A list can contain a combination of strings, integers and objects. Lists can be used for the implementation of stacks and queues.

Lists are mutable. These can be changed as and when needed.

Example - How to implement lists?

The following program shows the implementations of lists −

main.py

my_list = ['p','r','o','b','e']
# Output: p
print(my_list[0])

# Output: o
print(my_list[2])

# Output: e
print(my_list[4])

# Error! Only integer can be used for indexing
# my_list[4.0]

# Nested List
n_list = ["Happy", [2,0,1,5]]

# Nested indexing

# Output: a
print(n_list[0][1])

# Output: 5
print(n_list[1][3])

Output

The above program generates the following output −

p
o
e
a
5

The built-in functions of Python lists are as follows −

• Append()− It adds element to the end of list.

• Extend()− It adds elements of the list to another list.

• Insert()− It inserts an item to the defined index.

• Remove()− It deletes the element from the specified list.

• Reverse()− It reverses the elements in list.

• sort() − It helps to sort elements in chronological order.