Python Literals: What Are They And Why Should You Care About Them

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Athena Ozanich
Athena Ozanich



Python literals are vital to any Python-based software application, and understanding them is crucial.

Young woman discovering how she can use Python literals to improve her software programming code.

This post will cover everything you need to know about Python literals, what they are and how they work. You will also discover their syntax and see some code examples of them in use.

Without further ado, let's get started.

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What Are Literals in Python

Python literals are data stored within the source code for your software to operate correctly. These pieces of data are static and do not change throughout the operation of the program or application.

Python literals are typically used to designate data that users should not be able to alter, such as data that specifies the operating parameters of the software. You will need to set static values for any software you write.

Now that you know what Python literals are, you may ask yourself what they look like, and one is created. Let's start by addressing the first question and look at the Python literal syntax.

What is the difference between literal and string in Python?

Comparing Python strings and literals is like comparing apples to oranges since one is a type of value and the other is a data type. Python literals are a data type and can hold any value type, such as strings, numbers, and more.

Because Python literals are used to store base data for the source code of your software, they need to be robust enough to work with any data. Python literals can hold any data you need; let's look at some examples next.

Literals in Python Example

Python can store anything you need for your source code to work correctly. However, once they are set, the developers and software can only change them in the source code directly. Let's look at examples of the different types of data you can store in a Python literal.

Types of Literals in Python


Strings are one of the most common data value types you will work with in Python, and there are many ways to format strings, and literals support all of them.

s = 'It\'s Always Sunny' # in a single quote t = "It's Always Sunny" # in double quotes m = '''It\'s Always Sunny''' # multi-line String sqc = 'D' # character literal in single quote dqc = "R" # character literal in double quotes


Numeric values are another value you will find yourself working with often. Let's see what numeric literals look like in Python.

nb = 0b10100 # Binary Literals nd = 50 # Decimal Literal no = 0o320 # Octal Literal nh = 0x12b # Hexadecimal Literal nf = 24.8 # Float Literal


Boolean values are beneficial, especially in the source code of your software, as they are frequently used to set operating parameters. Let's see how those are done next.

one = (1 == True) # true two = (2 == False) # false three = (3 == True) # false boolTruMath = True + 10 # Result is 11 boolFalseMath = False + 10 # Result is 10


Collections are also helpful, and the fact is you will likely need them to store collections of data in your source code. An example might be a collection of permissions and restrictions for specific resources stored in a Python dictionary. Let's look at some collections next.

numList = [1, 2, 3, 4, 5] # List numTuple = (1, 2, 3, 4, 5) # Tuple numSet = {'1', '2', '3', '4', '5'} # Set peopleDict = {'D': 'Deandra', 'C': 'Charlie', 'M': 'Mac'} # Dictionary


Finally, a special literal is used to signify a null value, and the None keyword can be used in a literal when you need a value to be null or — no value.

iAmNone = None # Special literals

Moving Forward With Python Literals

Python literals can and likely will be the lifeblood of your software development process, and using them will become much more natural as you work with them. With that said, as usual, the best way to move forward with learning about literals and how to use them is to put them to use. Practice creating literals and learn how you can interact with them and maximize their benefits.


Topics: What Is Python?

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