inline conditional assignment python

• Learn Python
• Python Lists
• Python Dictionaries
• Python Strings
• Python Functions
• Learn Pandas & NumPy
• Pandas Tutorials
• Numpy Tutorials
• Learn Data Visualization
• Python Seaborn
• Python Matplotlib

Inline If in Python: The Ternary Operator in Python

• September 16, 2021 December 20, 2022

In this tutorial, you’ll learn how to create inline if statements in Python. This is often known as the Python ternary operator, which allows you to execute conditional if statements in a single line, allowing statements to take up less space and often be written in my easy-to-understand syntax! Let’s take a look at what you’ll learn.

The Quick Answer: Use the Python Ternary Operator

Table of Contents

What is the Python Ternary Operator?

A ternary operator is an inline statement that evaluates a condition and returns one of two outputs. It’s an operator that’s often used in many programming languages, including Python, as well as math. The Python ternary operator has been around since Python 2.5, despite being delayed multiple times.

The syntax of the Python ternary operator is a little different than that of other languages. Let’s take a look at what it looks like:

Now let’s take a look at how you can actually write an inline if statement in Python.

How Do you Write an Inline If Statement in Python?

Before we dive into writing an inline if statement in Python, let’s take a look at how if statements actually work in Python. With an if statement you must include an if , but you can also choose to include an else statement, as well as one more of else-ifs, which in Python are written as elif .

The traditional Python if statement looks like this:

This can be a little cumbersome to write, especially if you conditions are very simple. Because of this, inline if statements in Python can be really helpful to help you write your code faster.

Let’s take a look at how we can accomplish this in Python:

This is significantly easier to write. Let’s break this down a little bit:

• We assign a value to x , which will be evaluated
• We declare a variable, y , which we assign to the value of 10, if x is True. Otherwise, we assign it a value of 20.

We can see how this is written out in a much more plain language than a for-loop that may require multiple lines, thereby wasting space.

Tip! This is quite similar to how you’d written a list comprehension. If you want to learn more about Python List Comprehensions, check out my in-depth tutorial here . If you want to learn more about Python for-loops, check out my in-depth guide here .

Now that you know how to write a basic inline if statement in Python, let’s see how you can simplify it even further by omitting the else statement.

How To Write an Inline If Statement Without an Else Statement

Now that you know how to write an inline if statement in Python with an else clause, let’s take a look at how we can do this in Python.

Before we do this, let’s see how we can do this with a traditional if statement in Python

You can see that this still requires you to write two lines. But we know better – we can easily cut this down to a single line. Let’s get started!

We can see here that really what this accomplishes is remove the line break between the if line and the code it executes.

Now let’s take a look at how we can even include an elif clause in our inline if statements in Python!

Check out some other Python tutorials on datagy.io, including our complete guide to styling Pandas and our comprehensive overview of Pivot Tables in Pandas !

How to Write an Inline If Statement With an Elif Statement

Including an else-if, or elif , in your Python inline if statement is a little less intuitive. But it’s definitely doable! So let’s get started. Let’s imagine we want to write this if-statement:

Let’s see how we can easily turn this into an inline if statement in Python:

This is a bit different than what we’ve seen so far, so let’s break it down a bit:

• First, we evaluate is x == 1. If that’s true, the conditions end and y = 10.
• Otherwise, we create another condition in brackets
• First we check if x == 20, and if that’s true, then y = 20. Note that we did not repeated y= here.
• Finally, if neither of the other decisions are true, we assign 30 to y

This is definitely a bit more complex to read, so you may be better off creating a traditional if statement.

In this post, you learned how to create inline if statement in Python! You learned about the Python ternary operator and how it works. You also learned how to create inline if statements with else statements, without else statements, as well as with else if statements.

To learn more about Python ternary operators, check out the official documentation here .

Nik Piepenbreier

Nik is the author of datagy.io and has over a decade of experience working with data analytics, data science, and Python. He specializes in teaching developers how to use Python for data science using hands-on tutorials. View Author posts

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

Python One Line Conditional Assignment

Problem : How to perform one-line if conditional assignments in Python?

Example : Say, you start with the following code.

You want to set the value of x to 42 if boo is True , and do nothing otherwise.

Let’s dive into the different ways to accomplish this in Python. We start with an overview:

Exercise : Run the code. Are all outputs the same?

Next, you’ll dive into each of those methods and boost your one-liner superpower !

Method 1: Ternary Operator

The most basic ternary operator x if c else y returns expression x if the Boolean expression c evaluates to True . Otherwise, if the expression c evaluates to False , the ternary operator returns the alternative expression y .

Let’s go back to our example problem! You want to set the value of x to 42 if boo is True , and do nothing otherwise. Here’s how to do this in a single line:

While using the ternary operator works, you may wonder whether it’s possible to avoid the ...else x part for clarity of the code? In the next method, you’ll learn how!

If you need to improve your understanding of the ternary operator, watch the following video:

You can also read the related article:

• Python One Line Ternary

Method 2: Single-Line If Statement

Like in the previous method, you want to set the value of x to 42 if boo is True , and do nothing otherwise. But you don’t want to have a redundant else branch. How to do this in Python?

The solution to skip the else part of the ternary operator is surprisingly simple— use a standard if statement without else branch and write it into a single line of code :

To learn more about what you can pack into a single line, watch my tutorial video “If-Then-Else in One Line Python” :

Method 3: Ternary Tuple Syntax Hack

A shorthand form of the ternary operator is the following tuple syntax .

Syntax : You can use the tuple syntax (x, y)[c] consisting of a tuple (x, y) and a condition c enclosed in a square bracket. Here’s a more intuitive way to represent this tuple syntax.

In fact, the order of the <OnFalse> and <OnTrue> operands is just flipped when compared to the basic ternary operator. First, you have the branch that’s returned if the condition does NOT hold. Second, you run the branch that’s returned if the condition holds.

Clever! The condition boo holds so the return value passed into the x variable is the <OnTrue> branch 42 .

Don’t worry if this confuses you—you’re not alone. You can clarify the tuple syntax once and for all by studying my detailed blog article.

Related Article : Python Ternary — Tuple Syntax Hack

Python One-Liners Book: Master the Single Line First!

Python programmers will improve their computer science skills with these useful one-liners.

Python One-Liners will teach you how to read and write “one-liners”: concise statements of useful functionality packed into a single line of code. You’ll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert.

The book’s five chapters cover (1) tips and tricks, (2) regular expressions, (3) machine learning, (4) core data science topics, and (5) useful algorithms.

Detailed explanations of one-liners introduce key computer science concepts and boost your coding and analytical skills . You’ll learn about advanced Python features such as list comprehension , slicing , lambda functions , regular expressions , map and reduce functions, and slice assignments .

You’ll also learn how to:

• Leverage data structures to solve real-world problems , like using Boolean indexing to find cities with above-average pollution
• Use NumPy basics such as array , shape , axis , type , broadcasting , advanced indexing , slicing , sorting , searching , aggregating , and statistics
• Calculate basic statistics of multidimensional data arrays and the K-Means algorithms for unsupervised learning
• Create more advanced regular expressions using grouping and named groups , negative lookaheads , escaped characters , whitespaces, character sets (and negative characters sets ), and greedy/nongreedy operators
• Understand a wide range of computer science topics , including anagrams , palindromes , supersets , permutations , factorials , prime numbers , Fibonacci numbers, obfuscation , searching , and algorithmic sorting

By the end of the book, you’ll know how to write Python at its most refined , and create concise, beautiful pieces of “Python art” in merely a single line.

Get your Python One-Liners on Amazon!!

While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.

To help students reach higher levels of Python success, he founded the programming education website Finxter.com that has taught exponential skills to millions of coders worldwide. He’s the author of the best-selling programming books Python One-Liners (NoStarch 2020), The Art of Clean Code (NoStarch 2022), and The Book of Dash (NoStarch 2022). Chris also coauthored the Coffee Break Python series of self-published books. He’s a computer science enthusiast, freelancer , and owner of one of the top 10 largest Python blogs worldwide.

His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.

• Control Flow

Python Inline If Else (With 5 Examples)

You can use Python inline if to write an if else statement on a single line.

It allows you to write a single line of code instead of using a traditional if-else statement block.

Python inline if is also known as the Python Ternary Operator.

Syntax of Python inline if else assignment

The syntax of Python inline if else assignment is as follows:

Let’s break down the syntax of an inline if statement.

value_if_true : This value will be returned if the condition is true.

condition : This is a Boolean expression that evaluates to be either true or false.

value_if_false : This value will be returned if the condition is false.

For example, the following code would return the value “Hello” if the variable x is greater than 10, and the value “Goodbye” if it is not:

This code would print the following output:

Here are some additional things to keep in mind when using inline if in Python:

• The condition must be a Boolean expression.
• The value_if_true and value_if_false expressions must be of the same type.
• If the condition is false, the value_if_false expression will be evaluated.
• If the condition is true, the value_if_true expression will be evaluated.

Uses & Examples

Uses of Python inline if else

You can use Inline ifs in a variety of situations, such as:

• Assigning values to variables
• Calling functions
• Making decisions

They can be a helpful way to make your code more concise and readable.

However, it is important to use them sparingly.

As they can make your code more difficult to understand if you overused the inline if else assignment.

Assigning values to variables using Python inline if

Here’s an example to illustrate how to use the inline if statement to assign values to variables.

In this example, first of all, we have to evaluate the condition age >= 18 .

Since the value of age is 20, the condition is true, and the value True is assigned to the variable is_adult .

You can use the inline if statement as nested inline if else statements as well.

This allows you for more complex assignments.

Here’s an example.

y is greater

In this example, we checked if x is greater than y .

If true, we assigned “x is greater” to z .

Then we checked If y is greater than x .

If true, the program executes the nested inline if statement, and assigns the value “y is greater” to z . Otherwise, if x and y are equal, we assign the innermost value “x and y are equal”.

Calling functions using Python inline if

Here’s another example that calls a function with the inline if else statement.

Click on this code and it will be copied automatically.

Then you can run it on our  free Online Python Compiler .

The code gives the following output.

Even and positive

In this example, we have two custom functions: is_even() and is_positive() .

The is_even() function takes a number as input and checks if it’s an even number, returning True if it is, and False otherwise.

The is_positive() function takes a number as input and checks if it’s a positive number, returning True if it is, and False otherwise.

We then have a variable x set to 8.

Then, we used the inline if else statement to evaluate the conditions is_even(x) and is_positive(x) .

If both conditions are true (in this case, x is even and positive), the value assigned to the message variable is “Even and positive”.

If any of the conditions is false (if x is either not even or not positive), the value assigned to the message is “Not even or positive”.

Making decisions using Python inline if

You can make decisions in Python using the inline if else assignment.

Here is an example,

Error occurred

In this example, we used the inline if statement to format a message based on the value of is_error .

If is_error is True, we assigned the value “Error occurred” to the message .

Otherwise, if is_error is False, the program assigns the value “No errors found” to the message .

Related Articles:

While loop in python (with examples), python program for adding two numbers, print numbers from 1 to 10 using while loop in python, what does == mean in python, cryptography vs pycryptodome: understand the difference, python program for grading system (with code), python program to print triangular number up to given number using while loop, how to see type of variable in python, python program to find sum of first n natural numbers using while loop, how to use os module in python: a comprehensive guide, what is textblob library in python the ultimate guide, recent articles:, python program to convert integer to roman, python program to convert miles to kilometers, python program to convert fahrenheit to celsius, python program to convert binary to decimal, python program to convert decimal to binary, python program to convert kilometers to miles, python program to convert celsius to fahrenheit, python program to print hello world: a beginner’s guide, python program to print prime numbers, python program to add two numbers without addition operator, python program to add two numbers with user input, related tutorials:, python fundamentals: learn the basics of python programming., control flow: learn about conditional statements and loops, functions: learn modular programming from basics, oop: the art of organizing code for maximum reusability..

This community is dedicated to spreading the knowledge and benefits of Python programming to people of all ages and skill levels. This community driven platform is dedicated to providing comprehensive, up-to-date education in a fun and interactive way.

Whether you’re looking to start a new career, enhance your current skills, or just learn for fun, Python Mania is your one-stop-shop for all of your need. Join us today and become a part of the rapidly growing community of Python programmers!

FOR THE LOVE OF PYTHON! Copyright © 2023 PythonMania.org

How to Write the Python if Statement in one Line

• online practice

Have you ever heard of writing a Python if statement in a single line? Here, we explore multiple ways to do exactly that, including using conditional expressions in Python.

The if statement is one of the most fundamental statements in Python. In this article, we learn how to write the Python if in one line.

The if is a key piece in writing Python code. It allows developers to control the flow and logic of their code based on information received at runtime. However, many Python developers do not know they may reduce the length and complexity of their if statements by writing them in a single line.

For this article, we assume you’re somewhat familiar with Python conditions and comparisons. If not, don’t worry! Our Python Basics Course will get you up to speed in no time. This course is included in the Python Basics Track , a full-fledged Python learning track designed for complete beginners.

We start with a recap on how Python if statements work. Then, we explore some examples of how to write if statements in a single line. Let’s get started!

How the if Statement Works in Python

Let’s start with the basics. An if statement in Python is used to determine whether a condition is True or False . This information can then be used to perform specific actions in the code, essentially controlling its logic during execution.

The structure of the basic if statement is as follows:

The <expression> is the code that evaluates to either True or False . If this code evaluates to True, then the code below (represented by <perform_action> ) executes.

Python uses whitespaces to indicate which lines are controlled by the if statement. The if statement controls all indented lines below it. Typically, the indentation is set to four spaces (read this post if you’re having trouble with the indentation ).

As a simple example, the code below prints a message if and only if the current weather is sunny:

The if statement in Python has two optional components: the elif statement, which executes only if the preceding if/elif statements are False ; and the else statement, which executes only if all of the preceding if/elif statements are False. While we may have as many elif statements as we want, we may only have a single else statement at the very end of the code block.

Here’s the basic structure:

Here’s how our previous example looks after adding elif and else statements. Change the value of the weather variable to see a different message printed:

How to Write a Python if in one Line

Writing an if statement in Python (along with the optional elif and else statements) uses a lot of whitespaces. Some people may find it confusing or tiresome to follow each statement and its corresponding indented lines.

To overcome this, there is a trick many Python developers often overlook: write an if statement in a single line !

Though not the standard, Python does allow us to write an if statement and its associated action in the same line. Here’s the basic structure:

As you can see, not much has changed. We simply need to “pull” the indented line <perform_action> up to the right of the colon character ( : ). It’s that simple!

Let’s check it with a real example. The code below works as it did previously despite the if statement being in a single line. Test it out and see for yourself:

Writing a Python if Statement With Multiple Actions in one Line

That’s all well and good, but what if my if statement has multiple actions under its control? When using the standard indentation, we separate different actions in multiple indented lines as the structure below shows:

Can we do this in a single line? The surprising answer is yes! We use semicolons to separate each action in the same line as if placed in different lines.

Here’s how the structure looks:

And an example of this functionality:

Have you noticed how each call to the print() function appears in its own line? This indicates we have successfully executed multiple actions from a single line. Nice!

By the way, interested in learning more about the print() function? We have an article on the ins and outs of the print() function .

Writing a Full Python if/elif/else Block Using Single Lines

You may have seen this coming, but we can even write elif and else statements each in a single line. To do so, we use the same syntax as writing an if statement in a single line.

Here’s the general structure:

Looks simple, right? Depending on the content of your expressions and actions, you may find this structure easier to read and understand compared to the indented blocks.

Here’s our previous example of a full if/elif/else block, rewritten as single lines:

Using Python Conditional Expressions to Write an if/else Block in one Line

There’s still a final trick to writing a Python if in one line. Conditional expressions in Python (also known as Python ternary operators) can run an if/else block in a single line.

A conditional expression is even more compact! Remember it took at least two lines to write a block containing both if and else statements in our last example.

In contrast, here’s how a conditional expression is structured:

The syntax is somewhat harder to follow at first, but the basic idea is that <expression> is a test. If the test evaluates to True , then <value_if_true> is the result. Otherwise, the expression results in <value_if_false> .

As you can see, conditional expressions always evaluate to a single value in the end. They are not complete replacements for an if/elif/else block. In fact, we cannot have elif statements in them at all. However, they’re most helpful when determining a single value depending on a single condition.

Take a look at the code below, which determines the value of is_baby depending on whether or not the age is below five:

This is the exact use case for a conditional expression! Here’s how we rewrite this if/else block in a single line:

Much simpler!

Go Even Further With Python!

We hope you now know many ways to write a Python if in one line. We’ve reached the end of the article, but don’t stop practicing now!

If you do not know where to go next, read this post on how to get beyond the basics in Python . If you’d rather get technical, we have a post on the best code editors and IDEs for Python . Remember to keep improving!

You may also like

How Do You Write a SELECT Statement in SQL?

What Is a Foreign Key in SQL?

Enumerate and Explain All the Basic Elements of an SQL Query

if-elif-else statement on one line in Python

Last updated: Apr 9, 2024 Reading time · 4 min

# Table of Contents

• If-Elif-Else statement on one line in Python
• Shorthand if-else statement in Python

# If-Elif-Else statement on one line in Python

Use a nested ternary operator to implement an if-elif-else statement on one line.

The first ternary should check for a condition and if the condition is not met, it should return another ternary that does the job of an elif/else statement.

The ternary operator is very similar to an if/else statement.

The example checks if the name variable is falsy and if it is, the string "James Doe" is returned, otherwise, the name variable is returned.

# Using nested ternaries in Python

To have an inline if-elif-else statement, we have to use a nested ternary.

You can wrap the statement in parentheses to make it more readable.

The first ternary in the example checks if the variable stores a value greater than 100 .

If the condition is met, the number 10 gets returned.

The nested ternary operator checks if the variable is less than 100 .

If the condition is met, the number 20 is returned, otherwise, 0 is returned.

Here is another example.

If the condition isn't met, the else statement runs and the nested ternary checks for another condition.

The nested ternary checks if the variable stores a value of less than 100 and if the condition is met, the string b gets returned. This is the elif statement.

If the condition isn't met, the else statement runs and the string c gets returned.

# The equivalent of the nested ternary in an if-elif-else statement

Here is how we would implement the ternary operator of the example using if/elif/else statements.

Using if-elif-else statements is a bit more readable, but it is also a bit more verbose.

Whether using a nested ternary operator makes your code more readable depends on the complexity of the conditions you are checking for.

Using the shorthand syntax isn't always recommended.

# Shorthand if-else statement in Python

The ternary operator can also be used if you need a shorthand if-else statement.

The ternary operator will return the value to the left if the condition is met, otherwise, the value in the else statement is returned.

The operator in the example checks if variable1 is greater than variable2 .

Here is the same code sample but using the longer form syntax.

# a if condition else b

The syntax of the ternary operator is a if condition else b .

You can also store the result in a variable.

The example checks if the name variable is falsy and if it is the string "bobby hadz" is returned, otherwise the name variable is returned.

I've also written an article on how to check for multiple conditions in an if statement .

# Additional Resources

You can learn more about the related topics by checking out the following tutorials:

• Styling multiline 'if' statements in Python
• Get the first item in a list that matches condition - Python
• Find the index of Elements that meet a condition in Python
• Using f-string for conditional formatting in Python
• Check if all/any elements in List meet condition in Python
• ValueError: Circular reference detected in Python [Solved]
• Process finished with exit code 139 (interrupted by signal 11: SIGSEGV)
• Python argparse: unrecognized arguments error [Solved]
• How to exit an if statement in Python [5 Ways]

Borislav Hadzhiev

Web Developer

Copyright © 2024 Borislav Hadzhiev

DEV Community

Posted on Jul 5, 2023

Understanding the Python Inline If Statement

The Python inline if statement, also known as the ternary operator, allows for a concise way of writing conditional expressions in a single line of code. It is a compact alternative to the traditional if-else statement.

The syntax of the inline if statement consists of three parts: the condition, the expression to be evaluated if the condition is true, and the expression to be evaluated if the condition is false.

The result of the expression is returned based on the evaluation of the condition. If the condition is true, the expression returns the value specified before the if keyword. If the condition is false, the expression returns the value specified after the else keyword. This feature is particularly useful when a simple conditional check needs to be performed without the need for a full if-else block.

In this article, we will provide a comprehensive understanding of the Python inline if statement, also known as the ternary operator. It will explain what the inline if statement is, how it works, and why it is a useful feature in Python programming.

Using the Inline If Statement in Python

In Python, the inline if statement, often referred to as the ternary operator, provides a concise way to write conditional expressions.

It allows you to evaluate a condition and return one of two values, depending on whether the condition is true or false. The ternary operator follows the syntax: value_if_true if condition else value_if_false.

This compact syntax is particularly useful when you want to assign a value based on a condition without using a full if-else block. For example:

In this example, the inline if statement is used to assign the maximum value between x and y to the variable max_value. If the condition x > y is true, x is assigned to max_value; otherwise, y is assigned.

Evaluating the Condition in Python Inline If Statement

In Python, boolean expressions are used to evaluate conditions and determine whether they are true or false. These expressions can consist of logical operators such as and, or, and not, as well as comparison operators like ==, !=, <, >, <=, and >=.

In addition to explicitly True and False values, Python also has the concept of truthy and falsey values. Truthy values are considered to be true in a boolean context, while falsey values are considered to be false. Examples of truthy values include non-zero numbers, non-empty strings, non-empty lists, and non-empty dictionaries. On the other hand, examples of falsey values include zero, an empty string, an empty list, an empty dictionary, and None.

Understanding boolean expressions and truthy/falsey values is crucial for working with conditional statements and control flow in Python. It allows developers to write concise and efficient code by leveraging the flexibility of boolean expressions and making use of truthy/falsey values to simplify conditional checks.

Let's look at an example to understand how it works:

In this example, we have a variable x initialized with the value 10. We use the inline if statement to check if x is divisible by 2 (x % 2 == 0). If the condition is true, the expression "Even" is assigned to the variable result, otherwise, the expression "Odd" is assigned. The output of this code would be Even, as 10 is divisible by 2. This demonstrates how the inline if statement allows us to evaluate different conditions and execute expressions based on the result.

Use Cases of Python Inline If Statement

The inline if statement allows us to perform a quick conditional check and return a value based on the result. Here are some common use cases for the inline if statement:

Assigning a value conditionally:

We can use the inline if statement to assign a value based on a condition. For example, x = 10 if condition else 20 assigns the value 10 to x if the condition is true, otherwise it assigns 20.

In this code, condition is a boolean variable that determines the condition to be evaluated. If condition is True, the inline if statement assigns the value 10 to x. If condition is False, it assigns the value 20 to x. The value of x is then printed to the console.

You can modify the condition variable to control whether x is assigned 10 or 20 based on the condition.

Filtering a list

The inline if statement can be used to filter elements from a list based on a condition. For instance, [x for x in list if x > 5] returns a new list containing only the elements that are greater than 5.

In this code, the inline if statement [x for x in my_list if x > 5] is used to filter the elements from my_list. Only the elements that satisfy the condition x > 5 are included in the new list, filtered_list. In this case, the resulting filtered_list will contain the elements [6, 8, 9, 7], as they are the elements greater than 5 in the original my_list.

You can modify the condition x > 5 to suit your specific filtering requirement.

Performing calculations:

We can use the inline if statement to perform calculations based on a condition. For example, result = x * 2 if condition else x / 2 calculates the result as x multiplied by 2 if the condition is true, otherwise it divides x by 2.

In this code, x is a variable containing a numerical value. The inline if statement x * 2 if condition else x / 2 is used to calculate the result. If condition is True, it multiplies x by 2 and assigns the result to result. If condition is False, it divides x by 2 and assigns the result to result.

You can modify the value of x and the condition variable to perform the calculation based on your specific conditions.

Returning different values:

The inline if statement is useful when we want to return different values based on a condition. For instance, result = "Even" if x % 2 == 0 else "Odd" assigns the string "Even" to result if x is an even number, otherwise it assigns the string "Odd".

In this code, the inline if statement "Even" if x % 2 == 0 else "Odd" is used to assign the string "Even" to result if x is an even number. If x is not an even number, it assigns the string "Odd" to result.

You can modify the value of x to test different conditions and observe how the inline if statement returns different values based on the condition.

The inline if statement provides a concise and readable way to express conditional logic in Python, making the code more compact and easier to understand. However, it should be used judiciously to maintain the code's readability and avoid excessive nesting.

Advantages and Disadvantages of Using the Python Inline If Statement

Using the inline if statement in Python offers several advantages and disadvantages. Here are some that you might consider when using the inline if statement in Python:

Advantages of Python Inline If Statement

• Concise and readable code: It provides a compact way to express conditional logic in a single line, making the code more streamlined and easier to understand. Developers can avoid writing lengthy if-else blocks and achieve the same functionality with a shorter and more elegant syntax. This not only saves time and effort but also improves code readability, making it easier for others to comprehend and maintain the codebase.
• Avoidance of unnecessary code blocks: Inline if statement can avoid unnecessary code blocks. With traditional if statements, you would need to define separate code blocks for each condition. However, with the inline if statement, you can condense the code into a single line, making it more concise and easier to read. This can greatly improve the efficiency of your code and make it less prone to errors.

Potential Disadvantages of Python Inline If Statement

• Reduced readability in complex expressions: When used in complex expressions, inline if statement can lead to reduced readability. Nested inline ifs or long conditions can make the code harder to understand and maintain. It is important to strike a balance between conciseness and readability when using the inline if statement in Python.
• Limited Functionality Compared to if-else Statements: While it can be handy for simple conditions, inline if statement has limited functionality compared to if-else statements. The inline if statement can only handle a single condition and two possible outcomes, making it less suitable for complex logic or multiple conditions. In such cases, using traditional if-else statements with multiple branches provides more flexibility and readability.

Best Practices for Using the Inline If Statement

When writing inline if statements in Python, it is important to follow certain best practices to ensure code readability and maintainability. Here is an example that demonstrates these best practices:

result = 10 if condition else 20

In this example, the condition is evaluated and if it is true, the value 10 is assigned to the variable result. Otherwise, the value 20 is assigned.

This concise syntax can be useful in cases where a simple decision needs to be made based on a condition. However, it is important to keep the inline if statement simple and avoid complex expressions or multiple statements within the if-else block. By following these best practices, code readability is improved, making it easier for others to understand and maintain the code.

Keep expressions simple and straightforward

When using the Python inline if statement, it is important to keep the expressions simple and straightforward. This means avoiding complex logic or multiple nested conditions. By keeping the expressions simple, it becomes easier to understand and maintain the code.

It is also recommended to use clear variable names that reflect the intention of the condition. This helps to improve the readability and comprehendibility of the code. Overall, simplicity and clarity are key principles to follow when using the Python inline if statement.

Use parentheses for clarity

To ensure clarity and avoid ambiguity, it is a good practice to enclose the condition within parentheses. This not only makes the code more readable but also helps to prevent any potential confusion regarding operator precedence.

Using parentheses is especially important when nesting multiple inline if statements or when combining them with other expressions. By following this convention, we can enhance the understandability and maintainability of our Python code.

Avoid nesting multiple inline if statements

When using the inline if statement in Python, it is important to avoid nesting multiple inline if statements within each other. While nesting can be tempting to achieve more complex conditional expressions, it can quickly lead to code that is difficult to read and understand.

Instead, it is recommended to use if-else statements or refactor the code to separate simpler conditional expressions. This approach improves readability and maintainability of the code, making it easier for other developers to comprehend and modify.

Learning Python with a Python online compiler

Learning a new programming language might be intimidating if you're just starting out. Lightly IDE, however, makes learning Python simple and convenient for everybody. Lightly IDE was made so that even complete novices may get started writing code.

Lightly IDE's intuitive design is one of its many strong points. If you've never written any code before, don't worry; the interface is straightforward. You may quickly get started with Python programming with our Python online compiler with only a few clicks.

The best part of Lightly IDE is that it is cloud-based, so your code and projects are always accessible from any device with an internet connection. You can keep studying and coding regardless of where you are at any given moment.

Lightly IDE is a great place to start if you're interested in learning Python. Learn and collaborate with other learners and developers on your projects and receive comments on your code now.

Read more: Understanding the Python Inline If Statement

Top comments (0)

Templates let you quickly answer FAQs or store snippets for re-use.

Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink .

Hide child comments as well

For further actions, you may consider blocking this person and/or reporting abuse

📚 How to see what changed in Composer files

Ion Bazan - May 17

1325. Delete Leaves With a Given Value

MD ARIFUL HAQUE - May 17

Resolving Email Issues with SMTP on WordPress

Softdiscover Team - May 17

Late loading images using JS

amythical - May 17

We're a place where coders share, stay up-to-date and grow their careers.

• Python Inline If

In Python, the inline if statement, also known as the ternary operator, provides a concise way to write conditional expressions. This tutorial will explore the syntax and use cases of the inline if statement, demonstrating how it simplifies code and enhances readability.

Prerequisites:

• Basic understanding of Python syntax and conditional statements.

Syntax of Inline If

The syntax of the inline if statement is: x if condition else y .

• If the condition is true, the value of x is returned.
• If the condition is false, the value of y is returned.

Using Inline If for Assignment

Inline if statements are often used for variable assignments, simplifying the code and reducing lines.

Nested Inline If Statements

You can nest inline if statements to handle multiple conditions in a single line.

Inline If with Function Calls

Inline if statements can be used as arguments for function calls.

Inline If for List Comprehension

Inline if can be utilized within list comprehensions to filter elements.

Avoiding Overuse and Readability

While inline if statements offer concise code, avoid excessive nesting for improved readability.

The Python inline if (ternary operator) is a powerful tool for creating concise and readable conditional expressions. It simplifies code and reduces the need for additional lines, making your code more efficient and expressive. However, use it judiciously to maintain code readability and understandability. Happy coding!

Bonus!   If you’d like to learn more python  consider taking this course!

• Python Higher Order Functions: A Powerful Tool for Your Programming Journey
• Python Data Analyst Salary: How Much Can You Earn in Each State?
• Mastering .rfind() in Python: A Comprehensive Guide for Python Enthusiasts
• Python Projects for Your Portfolio: Boosting Your Python Skills and Landing Your Dream Job!
• What is Python Function Signature
• Python Null: Understanding the Mysteries of ‘None’ in Python
• How to Remove From Set Python
• How to do a Python Import From Parent Directory
• A Comprehensive Guide to Python /n Escape Sequence

• Module 2: The Essentials of Python »
• Conditional Statements
• View page source

Conditional Statements 

There are reading-comprehension exercises included throughout the text. These are meant to help you put your reading to practice. Solutions for the exercises are included at the bottom of this page.

In this section, we will be introduced to the if , else , and elif statements. These allow you to specify that blocks of code are to be executed only if specified conditions are found to be true, or perhaps alternative code if the condition is found to be false. For example, the following code will square x if it is a negative number, and will cube x if it is a positive number:

Please refer to the “Basic Python Object Types” subsection to recall the basics of the “boolean” type, which represents True and False values. We will extend that discussion by introducing comparison operations and membership-checking, and then expanding on the utility of the built-in bool type.

Comparison Operations 

Comparison statements will evaluate explicitly to either of the boolean-objects: True or False . There are eight comparison operations in Python:

The first six of these operators are familiar from mathematics:

Note that = and == have very different meanings. The former is the assignment operator, and the latter is the equality operator:

Python allows you to chain comparison operators to create “compound” comparisons:

Whereas == checks to see if two objects have the same value, the is operator checks to see if two objects are actually the same object. For example, creating two lists with the same contents produces two distinct lists, that have the same “value”:

Thus the is operator is most commonly used to check if a variable references the None object, or either of the boolean objects:

Use is not to check if two objects are distinct:

bool and Truth Values of Non-Boolean Objects 

Recall that the two boolean objects True and False formally belong to the int type in addition to bool , and are associated with the values 1 and 0 , respectively:

Likewise Python ascribes boolean values to non-boolean objects. For example,the number 0 is associated with False and non-zero numbers are associated with True . The boolean values of built-in objects can be evaluated with the built-in Python command bool :

and non-zero Python integers are associated with True :

The following built-in Python objects evaluate to False via bool :

Zero of any numeric type: 0 , 0.0 , 0j

Any empty sequence, such as an empty string or list: '' , tuple() , [] , numpy.array([])

Empty dictionaries and sets

Thus non-zero numbers and non-empty sequences/collections evaluate to True via bool .

The bool function allows you to evaluate the boolean values ascribed to various non-boolean objects. For instance, bool([]) returns False wherease bool([1, 2]) returns True .

if , else , and elif 

We now introduce the simple, but powerful if , else , and elif conditional statements. This will allow us to create simple branches in our code. For instance, suppose you are writing code for a video game, and you want to update a character’s status based on her/his number of health-points (an integer). The following code is representative of this:

Each if , elif , and else statement must end in a colon character, and the body of each of these statements is delimited by whitespace .

The following pseudo-code demonstrates the general template for conditional statements:

In practice this can look like:

In its simplest form, a conditional statement requires only an if clause. else and elif clauses can only follow an if clause.

Similarly, conditional statements can have an if and an else without an elif :

Conditional statements can also have an if and an elif without an else :

Note that only one code block within a single if-elif-else statement can be executed: either the “if-block” is executed, or an “elif-block” is executed, or the “else-block” is executed. Consecutive if-statements, however, are completely independent of one another, and thus their code blocks can be executed in sequence, if their respective conditional statements resolve to True .

Reading Comprehension: Conditional statements

Assume my_list is a list. Given the following code:

What will happen if my_list is [] ? Will IndexError be raised? What will first_item be?

Assume variable my_file is a string storing a filename, where a period denotes the end of the filename and the beginning of the file-type. Write code that extracts only the filename.

my_file will have at most one period in it. Accommodate cases where my_file does not include a file-type.

"code.py" \(\rightarrow\) "code"

"doc2.pdf" \(\rightarrow\) "doc2"

"hello_world" \(\rightarrow\) "hello_world"

Inline if-else statements 

Python supports a syntax for writing a restricted version of if-else statements in a single line. The following code:

can be written in a single line as:

This is suggestive of the general underlying syntax for inline if-else statements:

The inline if-else statement :

The expression A if <condition> else B returns A if bool(<condition>) evaluates to True , otherwise this expression will return B .

This syntax is highly restricted compared to the full “if-elif-else” expressions - no “elif” statement is permitted by this inline syntax, nor are multi-line code blocks within the if/else clauses.

Inline if-else statements can be used anywhere, not just on the right side of an assignment statement, and can be quite convenient:

We will see this syntax shine when we learn about comprehension statements. That being said, this syntax should be used judiciously. For example, inline if-else statements ought not be used in arithmetic expressions, for therein lies madness:

Short-Circuiting Logical Expressions 

Armed with our newfound understanding of conditional statements, we briefly return to our discussion of Python’s logic expressions to discuss “short-circuiting”. In Python, a logical expression is evaluated from left to right and will return its boolean value as soon as it is unambiguously determined, leaving any remaining portions of the expression unevaluated . That is, the expression may be short-circuited .

For example, consider the fact that an and operation will only return True if both of its arguments evaluate to True . Thus the expression False and <anything> is guaranteed to return False ; furthermore, when executed, this expression will return False without having evaluated bool(<anything>) .

To demonstrate this behavior, consider the following example:

According to our discussion, the pattern False and short-circuits this expression without it ever evaluating bool(1/0) . Reversing the ordering of the arguments makes this clear.

In practice, short-circuiting can be leveraged in order to condense one’s code. Suppose a section of our code is processing a variable x , which may be either a number or a string . Suppose further that we want to process x in a special way if it is an all-uppercased string. The code

is problematic because isupper can only be called once we are sure that x is a string; this code will raise an error if x is a number. We could instead write

but the more elegant and concise way of handling the nestled checking is to leverage our ability to short-circuit logic expressions.

See, that if x is not a string, that isinstance(x, str) will return False ; thus isinstance(x, str) and x.isupper() will short-circuit and return False without ever evaluating bool(x.isupper()) . This is the preferable way to handle this sort of checking. This code is more concise and readable than the equivalent nested if-statements.

Reading Comprehension: short-circuited expressions

Consider the preceding example of short-circuiting, where we want to catch the case where x is an uppercased string. What is the “bug” in the following code? Why does this fail to utilize short-circuiting correctly?

Links to Official Documentation 

Truth testing

Boolean operations

Comparisons

‘if’ statements

Reading Comprehension Exercise Solutions: 

Conditional statements

If my_list is [] , then bool(my_list) will return False , and the code block will be skipped. Thus first_item will be None .

First, check to see if . is even contained in my_file . If it is, find its index-position, and slice the string up to that index. Otherwise, my_file is already the file name.

Short-circuited expressions

fails to account for the fact that expressions are always evaluated from left to right. That is, bool(x.isupper()) will always be evaluated first in this instance and will raise an error if x is not a string. Thus the following isinstance(x, str) statement is useless.

An In-Depth Guide to Inline If-Else in Python

Conditional logic is a fundamental building block of programming. Performing different actions based on Boolean conditions allows code to make decisions and handle real-world scenarios. Python provides several ways to implement conditional logic, including if-else blocks, switch/case statements, and the inline if-else one-liner.

In this comprehensive guide, we‘ll explore when and how to use Python‘s inline if-else construct. By the end, you‘ll understand:

• The syntax for inline if-else statements
• How to use inline if-else for conditional evaluation
• Examples of common use cases
• Advantages and limitations of inline if-else
• Alternatives like if-else blocks and ternary operators
• Best practices for readable and maintainable inline if-else code

So whether you‘re a Python beginner or an experienced developer, you‘ll learn the ins and outs of inline if-else for writing idiomatic Python code. Let‘s get started!

What Is Inline If-Else in Python?

Inline if-else allows conditional logic to be defined on one line:

This compact syntax evaluates first_expression if condition is True, and second_expression if it‘s False.

Python‘s design emphasizes code readability through inherent simplicity. The inline if-else construct adheres to this philosophy by distilling conditional logic down to a concise one-liner.

For basic decision making in simple cases, inline if-else improves readability compared to verbose multi-line if-else blocks. But it can also create messy "nested ifs" if overused. We‘ll explore guidelines for when to use inline if-else later on.

First, let‘s break down the syntax in more detail.

Inline If-Else Syntax

Here are the components that make up inline if-else statements in Python:

• first_expression – Any valid Python expression to evaluate if condition is True
• condition – A Boolean expression that results in either True or False
• else – The Python keyword denoting the False case
• second_expression – Another expression to evaluate if condition is False

Some things to note about the syntax:

• The entire statement must be on one line
• if and else keywords are required
• The condition follows the if and precedes the else
• Expressions can be values, function calls, operations, etc.

Proper indentation does not matter since it‘s a single line, unlike multi-line if-else blocks.

Let‘s look at a few examples of valid inline if-else syntax:

We‘ll explore more complex examples of using inline if-else throughout this guide. First, let‘s discuss why and when you might want to use it.

When to Use Inline If-Else

Inline if-else statements serve two main purposes in Python:

• Conditional assignment – Assign variable values based on a condition
• Conditional execution – Conditionally run expressions or code blocks

Some common use cases include:

• Set a default value if a condition fails
• Return one value or another based on the input
• Print "Success" or "Failure" depending on a test
• Print, return, or assign inline instead of if-else block
• Since Python has no built-in ? : operator

In general, use inline if-else for straightforward conditional logic that fits on a single line. Avoid complex multi-line conditions or nested inline ifs.

Next, let‘s look at examples of using inline if-else for conditional assignment and execution.

Python Inline If-Else Examples

Let‘s explore some common examples of using inline if-else in Python.

Conditional Assignment

One of the most frequent uses of inline if-else is to conditionally assign variables.

For example, we can set a default value if a condition fails:

If user_input evaluates to False, my_var gets set to "default" .

Another example is picking between two values based on a condition:

If age is 18 or over, access becomes "allowed" , else it‘s assigned "denied" .

Let‘s break down what this code does:

• Evaluate whether age >= 18
• If True: assign the string "allowed" to access
• If False: assign "denied" to access

This provides a concise inline conditional assignment in one line.

Conditional Function Returns

Another common use case is returning values conditionally from functions:

Here we define get_status() which returns "Pass" or "Fail" based on the grade argument.

Using inline if-else lets us avoid bulky multi-line if-else blocks inside the function.

Conditional Code Execution

For quick one-line conditionals, we can also execute expressions or code blocks:

Rather than wrapping this in a verbose if-else block, inline if-else lets us compactly print one message or the other.

Inline if-else is commonly used to print conditional debug messages and output:

We can conditionally print debug info by checking a debugging flag.

Ternary Operator Equivalent

Since Python has no built-in ternary operator, inline if-else can be used to mimic ternary behavior:

This provides equivalent conditional assignment in Python using inline if-else.

Python Inline If-Else vs. Alternatives

Inline if-else is handy for compact single line conditionals, but it‘s not a one-size-fits-all solution. Let‘s compare it to if-else blocks and ternary operators.

Inline If-Else vs. If-Else Blocks

Standard if-else blocks allow complex conditional logic across multiple lines:

The equivalent inline if-else would be messy:

Use if-else blocks when:

• Conditions are complex or require explanation
• Conditional logic spans multiple lines
• Expressions are multi-line
• Nesting inline if-else would get confusing

Use inline if-else for:

• Simple one-line conditional assignment or execution
• Returning values conditionally from functions
• Concise alternative to single if-else block

Inline If-Else vs. Ternary Operators

Some languages like JavaScript provide ternary operators for inline conditionals:

Ternary operators are more concise than inline if-else, but only work for simple variable assignment.

Use ternary operators when:

• Language supports ? and : ternary syntax
• Quickly assigning variable values inline
• Condition and expressions fit on one line

Use inline if-else when:

• Coding in Python (no ternary operator)
• Returning conditionally from functions
• Conditionally executing code blocks
• Requires if and else keywords

Comparison Table

Here‘s a quick comparison of inline if-else vs if blocks and ternary operators:

Potential Pitfalls and Debugging Tips

While handy, inline if-else does have some pitfalls to avoid. Let‘s go over some potential issues and debugging tips.

Messy Nested Statements

Nesting multiple inline if-else statements can quickly get confusing:

Better approaches:

• Use if-else blocks for complex conditional logic
• Break into multiple statements using variables
• Limit inline if-else nesting to 2 levels maximum

Indentation Problems

Since it‘s one line, inline if-else doesn‘t use indentation. But wrong indentation can still break code:

Avoid issues by:

• Not indenting inline if-else statements
• Using a code linter to catch incorrect indentation
• Being careful when converting if-else blocks to inline style

Missing Parentheses

Forgetting parentheses around conditions is a common mistake:

This compares score to the boolean True/False rather than the number 90 .

Remember to:

• Enclose conditions in parentheses
• Use a linter to catch missing parens
• Take care to not omit parens when refactoring if-else blocks

With proper indentation, judicious use, and testing, you can avoid these potential pitfalls when using inline if-else.

Best Practices for Readable Inline If-Else

To keep inline if-else readable and maintainable, here are some best practices:

• Limit to one line – Avoid multi-line expressions or statements
• Use judiciously – Refactor to if-else block if it gets messy
• Parenthesize conditions – Ensure proper boolean logic
• Check indentation – No indent since it‘s one line
• Limit nesting – Nesting beyond 2 is confusing
• Comment complex cases – Add comments explaining complex logic

Keeping the conditional logic simple and using inline if-else minimally will ensure clean readable code.

Putting It All Together: A Real Example

Let‘s walk through a real-world example using inline if-else.

Imagine we‘re writing a simple game where players can be in "active" or "inactive" status determined by their score:

We use inline if-else here to:

• Conditionally assign status based on the score
• Concisely set the value in one line without a verbose if-else block
• Improve readability since it‘s straightforward conditional logic

For more complex cases like multiple score thresholds, we‘d want to refactor to a full if-else block. But inline if-else works well here for basic single-line conditional assignment.

Key Takeaways

Let‘s recap the key points about using inline if-else in Python:

• Use for straightforward one-line conditionals
• Assign values or return conditionally from functions
• Avoid complex multi-line logic or nested statements
• Can mimic a ternary operator for concise conditionals
• Improves readability through simplicity in simple cases
• If-else blocks work better for complex logic spanning lines
• Watch for indentation, nesting, and missing parens
• Apply judiciously based on use case

Inline if-else is a handy construct for conditionally evaluating expressions and executing code in Python. Its concise single-line syntax promotes readable code when applied properly.

For straightforward conditional assignment and logic, inline if-else produces clean and idiomatic Python code. But be ready to refactor to standard if-else blocks when things get more complex.

Hopefully this guide provided a solid foundational understanding of inline if-else. Applying its principles will help you write Python code that‘s efficient, readable, and conditioned for success!

You maybe like,

Related posts, "no module named ‘setuptools‘" – a complete troubleshooting guide.

As a Python developer, few errors are as frustrating as seeing ImportError: No module named setuptools when trying to install or run code that depends…

"numpy.float64 Cannot be Interpreted as an Integer" – A Detailed Guide to Fixing This Common NumPy Error

As a Python developer, have you ever encountered an error like this? TypeError: ‘numpy.float64‘ object cannot be interpreted as an integer If so, you‘re not…

"Unindent does not match any outer indentation level" – Common Python Indentation Error Explained

Have you encountered cryptic errors like "Unindent does not match any outer indentation level" while running your Python programs? These indentation-related errors are quite common…

10 Python List Methods to Boost Your Linux Sysadmin Skills

As a Linux system administrator, Python is an invaluable tool to have in your belt. With just a few lines of Python, you can automate…

11 Best Python IDEs for Ubuntu in 2022

An integrated development environment (IDE) is an essential tool for Python developers. IDEs streamline the coding process with features like intelligent code completion, visual debugging,…

30 Python Scripts Examples – Python Scripts Beginners Guide

Python is one of the most popular and in-demand programming languages today. Its simple syntax, rich set of libraries and versatility make it suitable for…

Conditional expression (ternary operator) in Python

Python has a conditional expression (sometimes called a "ternary operator"). You can write operations like if statements in one line with conditional expressions.

• 6. Expressions - Conditional expressions — Python 3.11.3 documentation

Basics of the conditional expression (ternary operator)

If ... elif ... else ... by conditional expressions, list comprehensions and conditional expressions, lambda expressions and conditional expressions.

See the following article for if statements in Python.

• Python if statements (if, elif, else)

In Python, the conditional expression is written as follows.

The condition is evaluated first. If condition is True , X is evaluated and its value is returned, and if condition is False , Y is evaluated and its value is returned.

If you want to switch the value based on a condition, simply use the desired values in the conditional expression.

If you want to switch between operations based on a condition, simply describe each corresponding expression in the conditional expression.

An expression that does not return a value (i.e., an expression that returns None ) is also acceptable in a conditional expression. Depending on the condition, either expression will be evaluated and executed.

The above example is equivalent to the following code written with an if statement.

You can also combine multiple conditions using logical operators such as and or or .

• Boolean operators in Python (and, or, not)

By combining conditional expressions, you can write an operation like if ... elif ... else ... in one line.

However, it is difficult to understand, so it may be better not to use it often.

The following two interpretations are possible, but the expression is processed as the first one.

In the sample code below, which includes three expressions, the first expression is interpreted like the second, rather than the third:

By using conditional expressions in list comprehensions, you can apply operations to the elements of the list based on the condition.

See the following article for details on list comprehensions.

• List comprehensions in Python

Conditional expressions are also useful when you want to apply an operation similar to an if statement within lambda expressions.

In the example above, the lambda expression is assigned to a variable for convenience, but this is not recommended by PEP8.

Refer to the following article for more details on lambda expressions.

• Lambda expressions in Python

Related Categories

Related articles.

• Shallow and deep copy in Python: copy(), deepcopy()
• Composite two images according to a mask image with Python, Pillow
• OpenCV, NumPy: Rotate and flip image
• pandas: Check if DataFrame/Series is empty
• Check pandas version: pd.show_versions
• Python if statement (if, elif, else)
• pandas: Find the quantile with quantile()
• Handle date and time with the datetime module in Python
• Get image size (width, height) with Python, OpenCV, Pillow (PIL)
• Convert between Unix time (Epoch time) and datetime in Python
• Convert BGR and RGB with Python, OpenCV (cvtColor)
• Matrix operations with NumPy in Python
• pandas: Replace values in DataFrame and Series with replace()
• Uppercase and lowercase strings in Python (conversion and checking)
• Calculate mean, median, mode, variance, standard deviation in Python

Python Conditional Assignment

When you want to assign a value to a variable based on some condition, like if the condition is true then assign a value to the variable, else assign some other value to the variable, then you can use the conditional assignment operator.

In this tutorial, we will look at different ways to assign values to a variable based on some condition.

1. Using Ternary Operator

The ternary operator is very special operator in Python, it is used to assign a value to a variable based on some condition.

It goes like this:

Here, the value of variable will be value_if_true if the condition is true, else it will be value_if_false .

Let's see a code snippet to understand it better.

You can see we have conditionally assigned a value to variable c based on the condition a > b .

2. Using if-else statement

if-else statements are the core part of any programming language, they are used to execute a block of code based on some condition.

Using an if-else statement, we can assign a value to a variable based on the condition we provide.

Here is an example of replacing the above code snippet with the if-else statement.

3. Using Logical Short Circuit Evaluation

Logical short circuit evaluation is another way using which you can assign a value to a variable conditionally.

The format of logical short circuit evaluation is:

It looks similar to ternary operator, but it is not. Here the condition and value_if_true performs logical AND operation, if both are true then the value of variable will be value_if_true , or else it will be value_if_false .

Let's see an example:

But if we make condition True but value_if_true False (or 0 or None), then the value of variable will be value_if_false .

So, you can see that the value of c is 20 even though the condition a < b is True .

So, you should be careful while using logical short circuit evaluation.

While working with lists , we often need to check if a list is empty or not, and if it is empty then we need to assign some default value to it.

Let's see how we can do it using conditional assignment.

Here, we have assigned a default value to my_list if it is empty.

Assign a value to a variable conditionally based on the presence of an element in a list.

Now you know 3 different ways to assign a value to a variable conditionally. Any of these methods can be used to assign a value when there is a condition.

The cleanest and fastest way to conditional value assignment is the ternary operator .

if-else statement is recommended to use when you have to execute a block of code based on some condition.

Happy coding! 😊

Python Inline If | Different ways of using Inline if in Python

While doing programming, the coder needs to do concise and clean code. As a result, they prefer choosing the concise version of big statements. Inline if is a concise version of if…else statement can be written in just one line. It basically contains two statements and executes either of them based on the condition provided. So, let us see the various ways in which one can use inline if in python.

Ways to use Python inline if statement:

• Inline If Without Else
• With Else Statement
• Inline If Elif

Python Inline if Without else:

Parameters:.

• <condition>: the condition to be evaluated
• <statement>: executed if the condition evaluation is true

Example: Python Inline if without else

Explanation:

Here, the con consists of the Boolean value True. As a result, the condition is satisfied, and the statement print (‘The condition is True’) is executed.

Python Inline if with else statement:

• <statemetn1>: executed if the condition evaluation is true
• <condition>: the condition that will determine which statement to follow
• <statement2>: executed if the condition evaluation is false

Example: Python Inline if with else

The value of color is ‘blue’. As a result, the condition doesn’t satisfy and so the statement in else part is executed.

Python Inline if with elif:

Although it can look a bit messy, writing an inline if- elif statement is possible and can be used as an expression wherever necessary.

Example: Python Inline if with elif

It will first compare and check the value of 10, whether or not it is lesser than 10. As it is false, it goes into the next statement and checks if the value is more than 10. And ultimately, since none of the condition satisfies, it executes the last else part and prints the statement The value is equal to 10

Advantages of Python Inline if:

By now, we have understood how to use an inline if statement in different forms. But if we want to implement it into our program, we should know about its advantage and its disadvantage.

Since it itself is an expression, it can be used inside other expressions as well. It can be used as an expression inside a list, lambda functions, etc.

In this example, we have used the inline if expression as an expression for the list. It checks that if the element is less than 50, it will add it to the list. Otherwise, it will subtract 50 from the number and then add it to the list.

Disadvantage of Python Inline if:

Being an expression, it definitely serves various purposes. However, it is also the cause of disadvantage for the inline if. Since it is an expression, one can’t use any statement inside it.

Syntax Error is that in the else part, a=a+1 is a statement, and since inline if it is an expression, one cannot write a statement inside it.

Conclusion:

So, these are the various ways in which the inline if statement can be used. Since it is an expression, it comprises of both advantages and disadvantages. The usage of inline if should be done according to the program’s requirement to deliver the most optimized and accurate result.

However, if you have any doubts or questions, do let me know in the comment section below. I will try to help you as soon as possible.

Happy Pythoning!

For the last example you could just do: b=10 a+=-1 if b==10 else 1

Yes, I’ve updated the article.

Python Enhancement Proposals

• Python »
• PEP Index »

PEP 572 – Assignment Expressions

The importance of real code, exceptional cases, scope of the target, relative precedence of :=, change to evaluation order, differences between assignment expressions and assignment statements, specification changes during implementation, _pydecimal.py, datetime.py, sysconfig.py, simplifying list comprehensions, capturing condition values, changing the scope rules for comprehensions, alternative spellings, special-casing conditional statements, special-casing comprehensions, lowering operator precedence, allowing commas to the right, always requiring parentheses, why not just turn existing assignment into an expression, with assignment expressions, why bother with assignment statements, why not use a sublocal scope and prevent namespace pollution, style guide recommendations, acknowledgements, a numeric example, appendix b: rough code translations for comprehensions, appendix c: no changes to scope semantics.

This is a proposal for creating a way to assign to variables within an expression using the notation NAME := expr .

As part of this change, there is also an update to dictionary comprehension evaluation order to ensure key expressions are executed before value expressions (allowing the key to be bound to a name and then re-used as part of calculating the corresponding value).

During discussion of this PEP, the operator became informally known as “the walrus operator”. The construct’s formal name is “Assignment Expressions” (as per the PEP title), but they may also be referred to as “Named Expressions” (e.g. the CPython reference implementation uses that name internally).

Naming the result of an expression is an important part of programming, allowing a descriptive name to be used in place of a longer expression, and permitting reuse. Currently, this feature is available only in statement form, making it unavailable in list comprehensions and other expression contexts.

Additionally, naming sub-parts of a large expression can assist an interactive debugger, providing useful display hooks and partial results. Without a way to capture sub-expressions inline, this would require refactoring of the original code; with assignment expressions, this merely requires the insertion of a few name := markers. Removing the need to refactor reduces the likelihood that the code be inadvertently changed as part of debugging (a common cause of Heisenbugs), and is easier to dictate to another programmer.

During the development of this PEP many people (supporters and critics both) have had a tendency to focus on toy examples on the one hand, and on overly complex examples on the other.

The danger of toy examples is twofold: they are often too abstract to make anyone go “ooh, that’s compelling”, and they are easily refuted with “I would never write it that way anyway”.

The danger of overly complex examples is that they provide a convenient strawman for critics of the proposal to shoot down (“that’s obfuscated”).

Yet there is some use for both extremely simple and extremely complex examples: they are helpful to clarify the intended semantics. Therefore, there will be some of each below.

However, in order to be compelling , examples should be rooted in real code, i.e. code that was written without any thought of this PEP, as part of a useful application, however large or small. Tim Peters has been extremely helpful by going over his own personal code repository and picking examples of code he had written that (in his view) would have been clearer if rewritten with (sparing) use of assignment expressions. His conclusion: the current proposal would have allowed a modest but clear improvement in quite a few bits of code.

Another use of real code is to observe indirectly how much value programmers place on compactness. Guido van Rossum searched through a Dropbox code base and discovered some evidence that programmers value writing fewer lines over shorter lines.

Case in point: Guido found several examples where a programmer repeated a subexpression, slowing down the program, in order to save one line of code, e.g. instead of writing:

they would write:

Another example illustrates that programmers sometimes do more work to save an extra level of indentation:

This code tries to match pattern2 even if pattern1 has a match (in which case the match on pattern2 is never used). The more efficient rewrite would have been:

Syntax and semantics

In most contexts where arbitrary Python expressions can be used, a named expression can appear. This is of the form NAME := expr where expr is any valid Python expression other than an unparenthesized tuple, and NAME is an identifier.

The value of such a named expression is the same as the incorporated expression, with the additional side-effect that the target is assigned that value:

There are a few places where assignment expressions are not allowed, in order to avoid ambiguities or user confusion:

This rule is included to simplify the choice for the user between an assignment statement and an assignment expression – there is no syntactic position where both are valid.

Again, this rule is included to avoid two visually similar ways of saying the same thing.

This rule is included to disallow excessively confusing code, and because parsing keyword arguments is complex enough already.

This rule is included to discourage side effects in a position whose exact semantics are already confusing to many users (cf. the common style recommendation against mutable default values), and also to echo the similar prohibition in calls (the previous bullet).

The reasoning here is similar to the two previous cases; this ungrouped assortment of symbols and operators composed of : and = is hard to read correctly.

This allows lambda to always bind less tightly than := ; having a name binding at the top level inside a lambda function is unlikely to be of value, as there is no way to make use of it. In cases where the name will be used more than once, the expression is likely to need parenthesizing anyway, so this prohibition will rarely affect code.

This shows that what looks like an assignment operator in an f-string is not always an assignment operator. The f-string parser uses : to indicate formatting options. To preserve backwards compatibility, assignment operator usage inside of f-strings must be parenthesized. As noted above, this usage of the assignment operator is not recommended.

An assignment expression does not introduce a new scope. In most cases the scope in which the target will be bound is self-explanatory: it is the current scope. If this scope contains a nonlocal or global declaration for the target, the assignment expression honors that. A lambda (being an explicit, if anonymous, function definition) counts as a scope for this purpose.

There is one special case: an assignment expression occurring in a list, set or dict comprehension or in a generator expression (below collectively referred to as “comprehensions”) binds the target in the containing scope, honoring a nonlocal or global declaration for the target in that scope, if one exists. For the purpose of this rule the containing scope of a nested comprehension is the scope that contains the outermost comprehension. A lambda counts as a containing scope.

The motivation for this special case is twofold. First, it allows us to conveniently capture a “witness” for an any() expression, or a counterexample for all() , for example:

Second, it allows a compact way of updating mutable state from a comprehension, for example:

However, an assignment expression target name cannot be the same as a for -target name appearing in any comprehension containing the assignment expression. The latter names are local to the comprehension in which they appear, so it would be contradictory for a contained use of the same name to refer to the scope containing the outermost comprehension instead.

For example, [i := i+1 for i in range(5)] is invalid: the for i part establishes that i is local to the comprehension, but the i := part insists that i is not local to the comprehension. The same reason makes these examples invalid too:

While it’s technically possible to assign consistent semantics to these cases, it’s difficult to determine whether those semantics actually make sense in the absence of real use cases. Accordingly, the reference implementation [1] will ensure that such cases raise SyntaxError , rather than executing with implementation defined behaviour.

This restriction applies even if the assignment expression is never executed:

For the comprehension body (the part before the first “for” keyword) and the filter expression (the part after “if” and before any nested “for”), this restriction applies solely to target names that are also used as iteration variables in the comprehension. Lambda expressions appearing in these positions introduce a new explicit function scope, and hence may use assignment expressions with no additional restrictions.

Due to design constraints in the reference implementation (the symbol table analyser cannot easily detect when names are re-used between the leftmost comprehension iterable expression and the rest of the comprehension), named expressions are disallowed entirely as part of comprehension iterable expressions (the part after each “in”, and before any subsequent “if” or “for” keyword):

A further exception applies when an assignment expression occurs in a comprehension whose containing scope is a class scope. If the rules above were to result in the target being assigned in that class’s scope, the assignment expression is expressly invalid. This case also raises SyntaxError :

(The reason for the latter exception is the implicit function scope created for comprehensions – there is currently no runtime mechanism for a function to refer to a variable in the containing class scope, and we do not want to add such a mechanism. If this issue ever gets resolved this special case may be removed from the specification of assignment expressions. Note that the problem already exists for using a variable defined in the class scope from a comprehension.)

See Appendix B for some examples of how the rules for targets in comprehensions translate to equivalent code.

The := operator groups more tightly than a comma in all syntactic positions where it is legal, but less tightly than all other operators, including or , and , not , and conditional expressions ( A if C else B ). As follows from section “Exceptional cases” above, it is never allowed at the same level as = . In case a different grouping is desired, parentheses should be used.

The := operator may be used directly in a positional function call argument; however it is invalid directly in a keyword argument.

Some examples to clarify what’s technically valid or invalid:

Most of the “valid” examples above are not recommended, since human readers of Python source code who are quickly glancing at some code may miss the distinction. But simple cases are not objectionable:

This PEP recommends always putting spaces around := , similar to PEP 8 ’s recommendation for = when used for assignment, whereas the latter disallows spaces around = used for keyword arguments.)

In order to have precisely defined semantics, the proposal requires evaluation order to be well-defined. This is technically not a new requirement, as function calls may already have side effects. Python already has a rule that subexpressions are generally evaluated from left to right. However, assignment expressions make these side effects more visible, and we propose a single change to the current evaluation order:

• In a dict comprehension {X: Y for ...} , Y is currently evaluated before X . We propose to change this so that X is evaluated before Y . (In a dict display like {X: Y} this is already the case, and also in dict((X, Y) for ...) which should clearly be equivalent to the dict comprehension.)

Most importantly, since := is an expression, it can be used in contexts where statements are illegal, including lambda functions and comprehensions.

Conversely, assignment expressions don’t support the advanced features found in assignment statements:

• Multiple targets are not directly supported: x = y = z = 0 # Equivalent: (z := (y := (x := 0)))
• Single assignment targets other than a single NAME are not supported: # No equivalent a [ i ] = x self . rest = []
• Priority around commas is different: x = 1 , 2 # Sets x to (1, 2) ( x := 1 , 2 ) # Sets x to 1
• Iterable packing and unpacking (both regular or extended forms) are not supported: # Equivalent needs extra parentheses loc = x , y # Use (loc := (x, y)) info = name , phone , * rest # Use (info := (name, phone, *rest)) # No equivalent px , py , pz = position name , phone , email , * other_info = contact
• Inline type annotations are not supported: # Closest equivalent is "p: Optional[int]" as a separate declaration p : Optional [ int ] = None
• Augmented assignment is not supported: total += tax # Equivalent: (total := total + tax)

The following changes have been made based on implementation experience and additional review after the PEP was first accepted and before Python 3.8 was released:

• for consistency with other similar exceptions, and to avoid locking in an exception name that is not necessarily going to improve clarity for end users, the originally proposed TargetScopeError subclass of SyntaxError was dropped in favour of just raising SyntaxError directly. [3]
• due to a limitation in CPython’s symbol table analysis process, the reference implementation raises SyntaxError for all uses of named expressions inside comprehension iterable expressions, rather than only raising them when the named expression target conflicts with one of the iteration variables in the comprehension. This could be revisited given sufficiently compelling examples, but the extra complexity needed to implement the more selective restriction doesn’t seem worthwhile for purely hypothetical use cases.

Examples from the Python standard library

env_base is only used on these lines, putting its assignment on the if moves it as the “header” of the block.

• Current: env_base = os . environ . get ( "PYTHONUSERBASE" , None ) if env_base : return env_base
• Improved: if env_base := os . environ . get ( "PYTHONUSERBASE" , None ): return env_base

Avoid nested if and remove one indentation level.

• Current: if self . _is_special : ans = self . _check_nans ( context = context ) if ans : return ans
• Improved: if self . _is_special and ( ans := self . _check_nans ( context = context )): return ans

Code looks more regular and avoid multiple nested if. (See Appendix A for the origin of this example.)

• Current: reductor = dispatch_table . get ( cls ) if reductor : rv = reductor ( x ) else : reductor = getattr ( x , "__reduce_ex__" , None ) if reductor : rv = reductor ( 4 ) else : reductor = getattr ( x , "__reduce__" , None ) if reductor : rv = reductor () else : raise Error ( "un(deep)copyable object of type %s " % cls )
• Improved: if reductor := dispatch_table . get ( cls ): rv = reductor ( x ) elif reductor := getattr ( x , "__reduce_ex__" , None ): rv = reductor ( 4 ) elif reductor := getattr ( x , "__reduce__" , None ): rv = reductor () else : raise Error ( "un(deep)copyable object of type %s " % cls )

tz is only used for s += tz , moving its assignment inside the if helps to show its scope.

• Current: s = _format_time ( self . _hour , self . _minute , self . _second , self . _microsecond , timespec ) tz = self . _tzstr () if tz : s += tz return s
• Improved: s = _format_time ( self . _hour , self . _minute , self . _second , self . _microsecond , timespec ) if tz := self . _tzstr (): s += tz return s

Calling fp.readline() in the while condition and calling .match() on the if lines make the code more compact without making it harder to understand.

• Current: while True : line = fp . readline () if not line : break m = define_rx . match ( line ) if m : n , v = m . group ( 1 , 2 ) try : v = int ( v ) except ValueError : pass vars [ n ] = v else : m = undef_rx . match ( line ) if m : vars [ m . group ( 1 )] = 0
• Improved: while line := fp . readline (): if m := define_rx . match ( line ): n , v = m . group ( 1 , 2 ) try : v = int ( v ) except ValueError : pass vars [ n ] = v elif m := undef_rx . match ( line ): vars [ m . group ( 1 )] = 0

A list comprehension can map and filter efficiently by capturing the condition:

Similarly, a subexpression can be reused within the main expression, by giving it a name on first use:

Note that in both cases the variable y is bound in the containing scope (i.e. at the same level as results or stuff ).

Assignment expressions can be used to good effect in the header of an if or while statement:

Particularly with the while loop, this can remove the need to have an infinite loop, an assignment, and a condition. It also creates a smooth parallel between a loop which simply uses a function call as its condition, and one which uses that as its condition but also uses the actual value.

An example from the low-level UNIX world:

Rejected alternative proposals

Proposals broadly similar to this one have come up frequently on python-ideas. Below are a number of alternative syntaxes, some of them specific to comprehensions, which have been rejected in favour of the one given above.

A previous version of this PEP proposed subtle changes to the scope rules for comprehensions, to make them more usable in class scope and to unify the scope of the “outermost iterable” and the rest of the comprehension. However, this part of the proposal would have caused backwards incompatibilities, and has been withdrawn so the PEP can focus on assignment expressions.

Broadly the same semantics as the current proposal, but spelled differently.

Since EXPR as NAME already has meaning in import , except and with statements (with different semantics), this would create unnecessary confusion or require special-casing (e.g. to forbid assignment within the headers of these statements).

(Note that with EXPR as VAR does not simply assign the value of EXPR to VAR – it calls EXPR.__enter__() and assigns the result of that to VAR .)

Additional reasons to prefer := over this spelling include:

• In if f(x) as y the assignment target doesn’t jump out at you – it just reads like if f x blah blah and it is too similar visually to if f(x) and y .
• import foo as bar
• except Exc as var
• with ctxmgr() as var

To the contrary, the assignment expression does not belong to the if or while that starts the line, and we intentionally allow assignment expressions in other contexts as well.

• NAME = EXPR
• if NAME := EXPR

reinforces the visual recognition of assignment expressions.

This syntax is inspired by languages such as R and Haskell, and some programmable calculators. (Note that a left-facing arrow y <- f(x) is not possible in Python, as it would be interpreted as less-than and unary minus.) This syntax has a slight advantage over ‘as’ in that it does not conflict with with , except and import , but otherwise is equivalent. But it is entirely unrelated to Python’s other use of -> (function return type annotations), and compared to := (which dates back to Algol-58) it has a much weaker tradition.

This has the advantage that leaked usage can be readily detected, removing some forms of syntactic ambiguity. However, this would be the only place in Python where a variable’s scope is encoded into its name, making refactoring harder.

Execution order is inverted (the indented body is performed first, followed by the “header”). This requires a new keyword, unless an existing keyword is repurposed (most likely with: ). See PEP 3150 for prior discussion on this subject (with the proposed keyword being given: ).

This syntax has fewer conflicts than as does (conflicting only with the raise Exc from Exc notation), but is otherwise comparable to it. Instead of paralleling with expr as target: (which can be useful but can also be confusing), this has no parallels, but is evocative.

One of the most popular use-cases is if and while statements. Instead of a more general solution, this proposal enhances the syntax of these two statements to add a means of capturing the compared value:

This works beautifully if and ONLY if the desired condition is based on the truthiness of the captured value. It is thus effective for specific use-cases (regex matches, socket reads that return '' when done), and completely useless in more complicated cases (e.g. where the condition is f(x) < 0 and you want to capture the value of f(x) ). It also has no benefit to list comprehensions.

Advantages: No syntactic ambiguities. Disadvantages: Answers only a fraction of possible use-cases, even in if / while statements.

Another common use-case is comprehensions (list/set/dict, and genexps). As above, proposals have been made for comprehension-specific solutions.

This brings the subexpression to a location in between the ‘for’ loop and the expression. It introduces an additional language keyword, which creates conflicts. Of the three, where reads the most cleanly, but also has the greatest potential for conflict (e.g. SQLAlchemy and numpy have where methods, as does tkinter.dnd.Icon in the standard library).

As above, but reusing the with keyword. Doesn’t read too badly, and needs no additional language keyword. Is restricted to comprehensions, though, and cannot as easily be transformed into “longhand” for-loop syntax. Has the C problem that an equals sign in an expression can now create a name binding, rather than performing a comparison. Would raise the question of why “with NAME = EXPR:” cannot be used as a statement on its own.

As per option 2, but using as rather than an equals sign. Aligns syntactically with other uses of as for name binding, but a simple transformation to for-loop longhand would create drastically different semantics; the meaning of with inside a comprehension would be completely different from the meaning as a stand-alone statement, while retaining identical syntax.

Regardless of the spelling chosen, this introduces a stark difference between comprehensions and the equivalent unrolled long-hand form of the loop. It is no longer possible to unwrap the loop into statement form without reworking any name bindings. The only keyword that can be repurposed to this task is with , thus giving it sneakily different semantics in a comprehension than in a statement; alternatively, a new keyword is needed, with all the costs therein.

There are two logical precedences for the := operator. Either it should bind as loosely as possible, as does statement-assignment; or it should bind more tightly than comparison operators. Placing its precedence between the comparison and arithmetic operators (to be precise: just lower than bitwise OR) allows most uses inside while and if conditions to be spelled without parentheses, as it is most likely that you wish to capture the value of something, then perform a comparison on it:

Once find() returns -1, the loop terminates. If := binds as loosely as = does, this would capture the result of the comparison (generally either True or False ), which is less useful.

While this behaviour would be convenient in many situations, it is also harder to explain than “the := operator behaves just like the assignment statement”, and as such, the precedence for := has been made as close as possible to that of = (with the exception that it binds tighter than comma).

Some critics have claimed that the assignment expressions should allow unparenthesized tuples on the right, so that these two would be equivalent:

(With the current version of the proposal, the latter would be equivalent to ((point := x), y) .)

However, adopting this stance would logically lead to the conclusion that when used in a function call, assignment expressions also bind less tight than comma, so we’d have the following confusing equivalence:

The less confusing option is to make := bind more tightly than comma.

It’s been proposed to just always require parentheses around an assignment expression. This would resolve many ambiguities, and indeed parentheses will frequently be needed to extract the desired subexpression. But in the following cases the extra parentheses feel redundant:

Frequently Raised Objections

C and its derivatives define the = operator as an expression, rather than a statement as is Python’s way. This allows assignments in more contexts, including contexts where comparisons are more common. The syntactic similarity between if (x == y) and if (x = y) belies their drastically different semantics. Thus this proposal uses := to clarify the distinction.

The two forms have different flexibilities. The := operator can be used inside a larger expression; the = statement can be augmented to += and its friends, can be chained, and can assign to attributes and subscripts.

Previous revisions of this proposal involved sublocal scope (restricted to a single statement), preventing name leakage and namespace pollution. While a definite advantage in a number of situations, this increases complexity in many others, and the costs are not justified by the benefits. In the interests of language simplicity, the name bindings created here are exactly equivalent to any other name bindings, including that usage at class or module scope will create externally-visible names. This is no different from for loops or other constructs, and can be solved the same way: del the name once it is no longer needed, or prefix it with an underscore.

(The author wishes to thank Guido van Rossum and Christoph Groth for their suggestions to move the proposal in this direction. [2] )

As expression assignments can sometimes be used equivalently to statement assignments, the question of which should be preferred will arise. For the benefit of style guides such as PEP 8 , two recommendations are suggested.

• If either assignment statements or assignment expressions can be used, prefer statements; they are a clear declaration of intent.
• If using assignment expressions would lead to ambiguity about execution order, restructure it to use statements instead.

The authors wish to thank Alyssa Coghlan and Steven D’Aprano for their considerable contributions to this proposal, and members of the core-mentorship mailing list for assistance with implementation.

Appendix A: Tim Peters’s findings

Here’s a brief essay Tim Peters wrote on the topic.

I dislike “busy” lines of code, and also dislike putting conceptually unrelated logic on a single line. So, for example, instead of:

instead. So I suspected I’d find few places I’d want to use assignment expressions. I didn’t even consider them for lines already stretching halfway across the screen. In other cases, “unrelated” ruled:

is a vast improvement over the briefer:

The original two statements are doing entirely different conceptual things, and slamming them together is conceptually insane.

In other cases, combining related logic made it harder to understand, such as rewriting:

as the briefer:

The while test there is too subtle, crucially relying on strict left-to-right evaluation in a non-short-circuiting or method-chaining context. My brain isn’t wired that way.

But cases like that were rare. Name binding is very frequent, and “sparse is better than dense” does not mean “almost empty is better than sparse”. For example, I have many functions that return None or 0 to communicate “I have nothing useful to return in this case, but since that’s expected often I’m not going to annoy you with an exception”. This is essentially the same as regular expression search functions returning None when there is no match. So there was lots of code of the form:

I find that clearer, and certainly a bit less typing and pattern-matching reading, as:

It’s also nice to trade away a small amount of horizontal whitespace to get another _line_ of surrounding code on screen. I didn’t give much weight to this at first, but it was so very frequent it added up, and I soon enough became annoyed that I couldn’t actually run the briefer code. That surprised me!

There are other cases where assignment expressions really shine. Rather than pick another from my code, Kirill Balunov gave a lovely example from the standard library’s copy() function in copy.py :

The ever-increasing indentation is semantically misleading: the logic is conceptually flat, “the first test that succeeds wins”:

Using easy assignment expressions allows the visual structure of the code to emphasize the conceptual flatness of the logic; ever-increasing indentation obscured it.

A smaller example from my code delighted me, both allowing to put inherently related logic in a single line, and allowing to remove an annoying “artificial” indentation level:

That if is about as long as I want my lines to get, but remains easy to follow.

So, in all, in most lines binding a name, I wouldn’t use assignment expressions, but because that construct is so very frequent, that leaves many places I would. In most of the latter, I found a small win that adds up due to how often it occurs, and in the rest I found a moderate to major win. I’d certainly use it more often than ternary if , but significantly less often than augmented assignment.

I have another example that quite impressed me at the time.

Where all variables are positive integers, and a is at least as large as the n’th root of x, this algorithm returns the floor of the n’th root of x (and roughly doubling the number of accurate bits per iteration):

It’s not obvious why that works, but is no more obvious in the “loop and a half” form. It’s hard to prove correctness without building on the right insight (the “arithmetic mean - geometric mean inequality”), and knowing some non-trivial things about how nested floor functions behave. That is, the challenges are in the math, not really in the coding.

If you do know all that, then the assignment-expression form is easily read as “while the current guess is too large, get a smaller guess”, where the “too large?” test and the new guess share an expensive sub-expression.

To my eyes, the original form is harder to understand:

This appendix attempts to clarify (though not specify) the rules when a target occurs in a comprehension or in a generator expression. For a number of illustrative examples we show the original code, containing a comprehension, and the translation, where the comprehension has been replaced by an equivalent generator function plus some scaffolding.

Since [x for ...] is equivalent to list(x for ...) these examples all use list comprehensions without loss of generality. And since these examples are meant to clarify edge cases of the rules, they aren’t trying to look like real code.

Note: comprehensions are already implemented via synthesizing nested generator functions like those in this appendix. The new part is adding appropriate declarations to establish the intended scope of assignment expression targets (the same scope they resolve to as if the assignment were performed in the block containing the outermost comprehension). For type inference purposes, these illustrative expansions do not imply that assignment expression targets are always Optional (but they do indicate the target binding scope).

Let’s start with a reminder of what code is generated for a generator expression without assignment expression.

• Original code (EXPR usually references VAR): def f (): a = [ EXPR for VAR in ITERABLE ]
• Translation (let’s not worry about name conflicts): def f (): def genexpr ( iterator ): for VAR in iterator : yield EXPR a = list ( genexpr ( iter ( ITERABLE )))

Let’s add a simple assignment expression.

• Original code: def f (): a = [ TARGET := EXPR for VAR in ITERABLE ]
• Translation: def f (): if False : TARGET = None # Dead code to ensure TARGET is a local variable def genexpr ( iterator ): nonlocal TARGET for VAR in iterator : TARGET = EXPR yield TARGET a = list ( genexpr ( iter ( ITERABLE )))

Let’s add a global TARGET declaration in f() .

• Original code: def f (): global TARGET a = [ TARGET := EXPR for VAR in ITERABLE ]
• Translation: def f (): global TARGET def genexpr ( iterator ): global TARGET for VAR in iterator : TARGET = EXPR yield TARGET a = list ( genexpr ( iter ( ITERABLE )))

Or instead let’s add a nonlocal TARGET declaration in f() .

• Original code: def g (): TARGET = ... def f (): nonlocal TARGET a = [ TARGET := EXPR for VAR in ITERABLE ]
• Translation: def g (): TARGET = ... def f (): nonlocal TARGET def genexpr ( iterator ): nonlocal TARGET for VAR in iterator : TARGET = EXPR yield TARGET a = list ( genexpr ( iter ( ITERABLE )))

Finally, let’s nest two comprehensions.

• Original code: def f (): a = [[ TARGET := i for i in range ( 3 )] for j in range ( 2 )] # I.e., a = [[0, 1, 2], [0, 1, 2]] print ( TARGET ) # prints 2
• Translation: def f (): if False : TARGET = None def outer_genexpr ( outer_iterator ): nonlocal TARGET def inner_generator ( inner_iterator ): nonlocal TARGET for i in inner_iterator : TARGET = i yield i for j in outer_iterator : yield list ( inner_generator ( range ( 3 ))) a = list ( outer_genexpr ( range ( 2 ))) print ( TARGET )

Because it has been a point of confusion, note that nothing about Python’s scoping semantics is changed. Function-local scopes continue to be resolved at compile time, and to have indefinite temporal extent at run time (“full closures”). Example:

This document has been placed in the public domain.

Source: https://github.com/python/peps/blob/main/peps/pep-0572.rst

Last modified: 2023-10-11 12:05:51 GMT

• Python Basics
• Interview Questions
• Python Quiz
• Popular Packages
• Python Projects
• Practice Python
• AI With Python
• Learn Python3
• Python Automation
• Python Web Dev
• DSA with Python
• Python OOPs
• Dictionaries

Python Operators

Precedence and associativity of operators in python.

• Python Arithmetic Operators
• Difference between / vs. // operator in Python
• Python - Star or Asterisk operator ( * )
• What does the Double Star operator mean in Python?
• Division Operators in Python
• Modulo operator (%) in Python
• Python Logical Operators
• Python OR Operator
• Difference between 'and' and '&' in Python
• not Operator in Python | Boolean Logic

Ternary Operator in Python

• Python Bitwise Operators

Python Assignment Operators

Assignment operators in python.

• Walrus Operator in Python 3.8
• Increment += and Decrement -= Assignment Operators in Python
• Merging and Updating Dictionary Operators in Python 3.9
• New '=' Operator in Python3.8 f-string

Python Relational Operators

• Comparison Operators in Python
• Python NOT EQUAL operator
• Difference between == and is operator in Python
• Chaining comparison operators in Python
• Python Membership and Identity Operators
• Difference between != and is not operator in Python

In Python programming, Operators in general are used to perform operations on values and variables. These are standard symbols used for logical and arithmetic operations. In this article, we will look into different types of Python operators. 

• OPERATORS: These are the special symbols. Eg- + , * , /, etc.
• OPERAND: It is the value on which the operator is applied.

Types of Operators in Python

• Arithmetic Operators
• Comparison Operators
• Logical Operators
• Bitwise Operators
• Assignment Operators
• Identity Operators and Membership Operators

Arithmetic Operators in Python

Python Arithmetic operators are used to perform basic mathematical operations like addition, subtraction, multiplication , and division .

In Python 3.x the result of division is a floating-point while in Python 2.x division of 2 integers was an integer. To obtain an integer result in Python 3.x floored (// integer) is used.

Example of Arithmetic Operators in Python

Division operators.

In Python programming language Division Operators allow you to divide two numbers and return a quotient, i.e., the first number or number at the left is divided by the second number or number at the right and returns the quotient. 

There are two types of division operators: 

Float division

• Floor division

The quotient returned by this operator is always a float number, no matter if two numbers are integers. For example:

Example: The code performs division operations and prints the results. It demonstrates that both integer and floating-point divisions return accurate results. For example, ’10/2′ results in ‘5.0’ , and ‘-10/2’ results in ‘-5.0’ .

Integer division( Floor division)

The quotient returned by this operator is dependent on the argument being passed. If any of the numbers is float, it returns output in float. It is also known as Floor division because, if any number is negative, then the output will be floored. For example:

Example: The code demonstrates integer (floor) division operations using the // in Python operators . It provides results as follows: ’10//3′ equals ‘3’ , ‘-5//2’ equals ‘-3’ , ‘ 5.0//2′ equals ‘2.0’ , and ‘-5.0//2’ equals ‘-3.0’ . Integer division returns the largest integer less than or equal to the division result.

Precedence of Arithmetic Operators in Python

The precedence of Arithmetic Operators in Python is as follows:

• P – Parentheses
• E – Exponentiation
• M – Multiplication (Multiplication and division have the same precedence)
• D – Division
• A – Addition (Addition and subtraction have the same precedence)
• S – Subtraction

The modulus of Python operators helps us extract the last digit/s of a number. For example:

• x % 10 -> yields the last digit
• x % 100 -> yield last two digits

Arithmetic Operators With Addition, Subtraction, Multiplication, Modulo and Power

Here is an example showing how different Arithmetic Operators in Python work:

Example: The code performs basic arithmetic operations with the values of ‘a’ and ‘b’ . It adds (‘+’) , subtracts (‘-‘) , multiplies (‘*’) , computes the remainder (‘%’) , and raises a to the power of ‘b (**)’ . The results of these operations are printed.

Note: Refer to Differences between / and // for some interesting facts about these two Python operators.

Comparison of Python Operators

In Python Comparison of Relational operators compares the values. It either returns True or False according to the condition.

= is an assignment operator and == comparison operator.

Precedence of Comparison Operators in Python

In Python, the comparison operators have lower precedence than the arithmetic operators. All the operators within comparison operators have the same precedence order.

Example of Comparison Operators in Python

Let’s see an example of Comparison Operators in Python.

Example: The code compares the values of ‘a’ and ‘b’ using various comparison Python operators and prints the results. It checks if ‘a’ is greater than, less than, equal to, not equal to, greater than, or equal to, and less than or equal to ‘b’ .

Logical Operators in Python

Python Logical operators perform Logical AND , Logical OR , and Logical NOT operations. It is used to combine conditional statements.

Precedence of Logical Operators in Python

The precedence of Logical Operators in Python is as follows:

• Logical not
• logical and

Example of Logical Operators in Python

The following code shows how to implement Logical Operators in Python:

Example: The code performs logical operations with Boolean values. It checks if both ‘a’ and ‘b’ are true ( ‘and’ ), if at least one of them is true ( ‘or’ ), and negates the value of ‘a’ using ‘not’ . The results are printed accordingly.

Bitwise Operators in Python

Python Bitwise operators act on bits and perform bit-by-bit operations. These are used to operate on binary numbers.

Precedence of Bitwise Operators in Python

The precedence of Bitwise Operators in Python is as follows:

• Bitwise NOT
• Bitwise Shift
• Bitwise AND
• Bitwise XOR

Here is an example showing how Bitwise Operators in Python work:

Example: The code demonstrates various bitwise operations with the values of ‘a’ and ‘b’ . It performs bitwise AND (&) , OR (|) , NOT (~) , XOR (^) , right shift (>>) , and left shift (<<) operations and prints the results. These operations manipulate the binary representations of the numbers.

Python Assignment operators are used to assign values to the variables.

Let’s see an example of Assignment Operators in Python.

Example: The code starts with ‘a’ and ‘b’ both having the value 10. It then performs a series of operations: addition, subtraction, multiplication, and a left shift operation on ‘b’ . The results of each operation are printed, showing the impact of these operations on the value of ‘b’ .

Identity Operators in Python

In Python, is and is not are the identity operators both are used to check if two values are located on the same part of the memory. Two variables that are equal do not imply that they are identical. 

Example Identity Operators in Python

Let’s see an example of Identity Operators in Python.

Example: The code uses identity operators to compare variables in Python. It checks if ‘a’ is not the same object as ‘b’ (which is true because they have different values) and if ‘a’ is the same object as ‘c’ (which is true because ‘c’ was assigned the value of ‘a’ ).

Membership Operators in Python

In Python, in and not in are the membership operators that are used to test whether a value or variable is in a sequence.

Examples of Membership Operators in Python

The following code shows how to implement Membership Operators in Python:

Example: The code checks for the presence of values ‘x’ and ‘y’ in the list. It prints whether or not each value is present in the list. ‘x’ is not in the list, and ‘y’ is present, as indicated by the printed messages. The code uses the ‘in’ and ‘not in’ Python operators to perform these checks.

in Python, Ternary operators also known as conditional expressions are operators that evaluate something based on a condition being true or false. It was added to Python in version 2.5. 

It simply allows testing a condition in a single line replacing the multiline if-else making the code compact.

Syntax :   [on_true] if [expression] else [on_false] 

Examples of Ternary Operator in Python

The code assigns values to variables ‘a’ and ‘b’ (10 and 20, respectively). It then uses a conditional assignment to determine the smaller of the two values and assigns it to the variable ‘min’ . Finally, it prints the value of ‘min’ , which is 10 in this case.

In Python, Operator precedence and associativity determine the priorities of the operator.

Operator Precedence in Python

This is used in an expression with more than one operator with different precedence to determine which operation to perform first.

Let’s see an example of how Operator Precedence in Python works:

Example: The code first calculates and prints the value of the expression 10 + 20 * 30 , which is 610. Then, it checks a condition based on the values of the ‘name’ and ‘age’ variables. Since the name is “ Alex” and the condition is satisfied using the or operator, it prints “Hello! Welcome.”

Operator Associativity in Python

If an expression contains two or more operators with the same precedence then Operator Associativity is used to determine. It can either be Left to Right or from Right to Left.

The following code shows how Operator Associativity in Python works:

Example: The code showcases various mathematical operations. It calculates and prints the results of division and multiplication, addition and subtraction, subtraction within parentheses, and exponentiation. The code illustrates different mathematical calculations and their outcomes.

To try your knowledge of Python Operators, you can take out the quiz on Operators in Python . 

Python Operator Exercise Questions

Below are two Exercise Questions on Python Operators. We have covered arithmetic operators and comparison operators in these exercise questions. For more exercises on Python Operators visit the page mentioned below.

Q1. Code to implement basic arithmetic operations on integers

Q2. Code to implement Comparison operations on integers

Explore more Exercises: Practice Exercise on Operators in Python

Please Login to comment...

Similar reads.

• python-basics
• Python-Operators

Improve your Coding Skills with Practice

What kind of Experience do you want to share?