python assignment and if

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! 😊

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!

One line if statement in Python (ternary conditional operator)

In the real world, there are specific classifications and conditions on every action that occurs around us. A twelve-year-old person is a kid, whereas a thirteen-year-old person is a teenager. If the weather is pleasant, you can make plans for an outing. But if it isn’t, you will have to cancel your plans. These conditions control the coding world as well. You will encounter various coding problems where you will have to print the output based on some conditions.

Luckily, Python has a straightforward command and syntax to solve such kinds of problems. These are called conditional statements. So let’s begin our discussion on conditional statements, their syntax, and their applications.

Basic if Statement (Ternary Operator)

Many programming languages have a ternary operator , which defines a conditional expression. The most common usage is to make a terse, simple dependent assignment statement. In other words, it offers a one-line code to evaluate the first expression if the condition is true; otherwise, it considers the second expression. Programming languages derived from C usually have the following syntax:

The Python BDFL (creator of Python, Guido van Rossum) rejected it as non-Pythonic since it is hard to understand for people not used to C. Moreover, the colon already has many uses in Python. So, when PEP 308 was approved, Python finally received its shortcut conditional expression:

It first evaluates the condition; if it returns True , the compiler will consider expression1 to give the result, otherwise expression2 . Evaluation is lazy, so only one expression will be executed.

Let's take a look at this example:

Here we have defined the age variable whose value is fifteen. Now we use the if-else command to print if the kid is an adult or not. The condition for being an adult is that the person’s age should be eighteen or greater than that. We have mentioned this condition in the if-else command. Now let’s see what the output is:

As we can see, we have obtained the output as “kid” based on the value of the age variable.

We can chain the ternary operators as well:

Here we have incorporated multiple conditions. This form is the chained form of ternary operators. Let’s check the output:

This command is the same as the program given below :

The compiler evaluates conditions from left to right, which is easy to double-check with something like the pprint module:

Alternatives To The Ternary Operator

For Python versions lower than 2.5, programmers developed several tricks that somehow emulate the behavior of the ternary conditional operator. They are generally discouraged, but it's good to know how they work:

These are various ways to impose conditions in your code :

We can see that for various inputs, the same output is obtained for the exact value of the variable.

The problem of such an approach is that both expressions will be evaluated no matter what the condition is. As a workaround, lambdas can help:

We obtain the output as follows :

Another approach is using 'and' or 'or' statements:

Yes, most of the workarounds look ugly. Nevertheless, there are situations when it's better to use 'and' or 'or' logic than the ternary operator. For example, when your condition is the same as one of the expressions, you probably want to avoid evaluating it twice:

Indentations And Blocks

Python is very careful of the syntax of programming statements. We have to maintain proper indentation and blocks while we write composite statements like if-else . The correct indentation syntax of the if-else statement is given as follows:

The statements under 'if' are considered a part of one 'block.' The other statements are not part of the if block and are not considered when statements of 'if' are evaluated.

Python will automatically change the text color if you deviate from this indentation and display an error when you run your code. Let's take an example where we intentionally differ from the proper indentation:

We can see here that Python delivers an error message as: "Expected an indented block ."

Also, note the color of 'print' in line 3. All the other text is green, while 'print' has the color red. The color variation happens because of the abrupt indentation of 'print.'

Now let us correct the indentation :

When we have maintained the indentation of Python, we get the output hassle-free.

The else And elif Clauses

Suppose your ‘ if ’ condition is false and you have an alternative statement ready for execution. Then you can easily use the else clause. Now, suppose you have multiple if conditions and an alternative for each one. Then, you can use the elif clause and specify any number of situations. Now let us take an example for each case :

Use of else clause:

The syntax of the if-else statement is straightforward and has been used multiple times in this tutorial. Let us take a fundamental problem: There is a football team selection. The most critical condition for a candidate's eligibility is that he should be seventeen years or older. If his age is greater than or equal to seventeen, the output will be " You are eligible." If the boy is younger than seventeen years of age, the result will be " Sorry. You are not eligible."

Now let’s look at the code for this problem :

Let’s run this code and see what the output is :

The program first asks for the user input of age. We first enter the age as sixteen.

Now let us enter the age as eighteen and observe the output.

Thus we can see that the code assesses the input entered("age") and checks the value against the if-else conditions. If the condition is true, the compiler considers the statement under 'if ' and other statements are ignored. If the condition is false, the compiler executes the statement under 'else ,' and all the other statements are ignored.

Use of elif clause :

We use this clause when we have multiple conditions to check before printing the output. The word elif is compact for ‘ else-if .' When we use the elif clause, the else clause is optional. But if we want to use else clause, there has to be only one clause and that too at the end of the program.

Let us take a problem. We ask the user to enter a number between one and seven, and we display the corresponding weekday name. Let's look at the program for this problem.

The above-given code has elif as well as else clause.

Now let’s check the output:

The program first asks for user input of a number. Let’s enter four.

Now, let's check the output for the input value twelve.

Thus, the code works for any user-entered input value.

Conditions dominate every aspect of our real-life situations. To simulate these real-life conditions properly in our virtual world of coding, we, the programmers, need a good grasp on the control statements like if-else . We hope that this article helped you in understanding conditional statements and their syntax in Python. The various problems discussed in this article will help you understand the fundamental concepts of if-else statements and their applications.

About The Author

Anton Caceres

Python Tips and Tricks

Signup for new content

Thank you for joining our mailing list!

Latest Articles

Five Key Applications of Artificial Intelligence and Machine Learning in Finance and Python's Impact on Them
Essential System Administrator Tools: Script Automation - Bash, Python and PowerShell
The Benefits of Engaging in Python Projects for Beginners
Understanding Web App Development: A Beginner's Guide
Discover How to Get FL Studio for Free and Start Creating Music Today
Programming language
remove python
concatenate string
Code Editors
reset_index()
Train Test Split
Local Testing Server
Python Input
priority queue
web development
uninstall python
python string
code interface
round numbers
train_test_split()
Flask module
Linked List
machine learning
compare string
pandas dataframes
arange() method
Singly Linked List
python scripts
learning python
python bugs
ZipFunction
plus equals
np.linspace
SQLAlchemy advance
Data Structure
csv in python
logging in python
Python Counter
python subprocess
numpy module
Python code generators
python tutorial
csv file python
python logging
Counter class
Python assert
numbers_list
binary search
Insert Node
Python tips
python dictionary
Python's Built-in CSV Library
logging APIs
Constructing Counters
Matplotlib Plotting
any() Function
linear search
Python tools
python update
logging module
Concatenate Data Frames
python comments
Recursion Limit
Data structures
installation
python function
pandas installation
Zen of Python
concatenation
Echo Client
NumPy Pad()
install python
how to install pandas
Philosophy of Programming
concat() function
Socket State
Python YAML
remove a node
function scope
Tuple in Python
pandas groupby
socket programming
Python Modulo
Dictionary Update()
datastructure
bubble sort
find a node
calling function
GroupBy method
Np.Arange()
Modulo Operator
Python Or Operator
Python salaries
pyenv global
NumPy arrays
insertion sort
in place reversal
learn python
python packages
zeros() function
Scikit Learn
HTML Parser
circular queue
effiiciency
python maps
Num Py Zeros
Python Lists
HTML Extraction
selection sort
Programming
install python on windows
reverse string
python Code Editors
pandas.reset_index
Infinite Numbers in Python
Python Readlines()

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 .

Operand	Description
<OnTrue>	The return expression of the operator in case the condition evaluates to
<Condition>	The condition that determines whether to return the <On True> or the <On False> branch.
<OnFalse>	The return expression of the operator in case the condition evaluates to

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!!

Python Course
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

Conditional Statements in Python

Understanding and mastering Python’s conditional statements is fundamental for any programmer aspiring to write efficient and robust code. In this guide, we’ll delve into the intricacies of conditional statements in Python, covering the basics, advanced techniques, and best practices.

What are Conditional Statements?

Conditional Statements are statements in Python that provide a choice for the control flow based on a condition. It means that the control flow of the Python program will be decided based on the outcome of the condition. Now let us see how Conditional Statements are implemented in Python.

Types of Conditional Statements in Python

1. If Conditional Statement in Python

2. if else conditional statements in python, 3. nested if..else conditional statements in python, 4. if-elif-else conditional statements in python, 5. ternary expression conditional statements in python, best practices for using conditional statements.

If the simple code of block is to be performed if the condition holds then the if statement is used. Here the condition mentioned holds then the code of the block runs otherwise not.

Syntax of If Statement :

In a conditional if Statement the additional block of code is merged as an else statement which is performed when if condition is false.

Syntax of Python If-Else :

Nested if..else means an if-else statement inside another if statement. Or in simple words first, there is an outer if statement, and inside it another if – else statement is present and such type of statement is known as nested if statement. We can use one if or else if statement inside another if or else if statements.

The if statements are executed from the top down. As soon as one of the conditions controlling the if is true, the statement associated with that if is executed, and the rest of the ladder is bypassed. If none of the conditions is true, then the final “else” statement will be executed.

The Python ternary Expression determines if a condition is true or false and then returns the appropriate value in accordance with the result. The ternary Expression is useful in cases where we need to assign a value to a variable based on a simple condition, and we want to keep our code more concise — all in just one line of code.

Syntax of Ternary Expression

Keep conditions simple and expressive for better readability.
Avoid deeply nested conditional blocks; refactor complex logic into smaller, more manageable functions.
Comment on complex conditions to clarify their purpose.
Prefer the ternary operator for simple conditional assignments.
Advanced Techniques:
Using short-circuit evaluation for efficiency in complex conditions.
Leveraging the any() and all() functions with conditions applied to iterables.
Employing conditional expressions within list comprehensions and generator expressions.

Conditional Statements in Python – FAQs

What are conditional statements in python.

Conditional statements in Python are used to execute a specific block of code based on the truth value of a condition. The most common conditional statements in Python are if , elif , and else . These allow the program to react differently depending on whether a condition (or a series of conditions) is true or false. x = 10 if x > 5: print("x is greater than 5") elif x == 5: print("x is equal to 5") else: print("x is less than 5")

What is a Conditional Expression in Python?

A conditional expression (also known as a ternary operator) in Python provides a method to simplify conditional statements. It allows for a quick definition of a condition and two possible outcomes (one if the condition is true, and one if the condition is false). The syntax is value_if_true if condition else value_if_false . # Conditional expression example x = 5 result = "High" if x > 10 else "Low" print(result) # Outputs: "Low"

What are Decision-Making Statements in Python?

Decision-making statements in Python help to control the flow of execution based on certain conditions. These include: if statement: Executes a block of code if a specified condition is true. if-else statement: Executes one block of code if the condition is true, and another block if the condition is false. elif (else if) statement: Checks multiple conditions in a sequence and executes a block of code as soon as one of the conditions evaluates to true. Nested if statements: You can nest if statements within another if or else block to create complex decision trees.

What are Conditional Selection Statements in Python?

Conditional selection statements refer to the use of if , elif , and else statements that select specific blocks of code to execute based on conditions. These statements are fundamental for branching in programming, allowing different outcomes depending on the input or state of the program.

What are the Conditional Loops in Python?

While Python supports loops that can incorporate conditions, the term “conditional loops” might specifically refer to loops that run based on a condition. Python provides two primary types of such loops: while loop: Continues to execute as long as a given condition is true. It checks the condition before executing the loop body. # while loop example x = 5 while x < 10: print(x) x += 1 for loop: Iterates over a sequence (like a list, tuple, or string) and executes the loop body for each item in the sequence. Although not traditionally a “conditional” loop, it can incorporate conditions using break and continue to control the loop execution dynamically. # for loop example with condition for i in range(10): if i == 5: break # Exit the loop when i is 5 print(i) These explanations outline how Python uses conditional statements and expressions to manage the flow of execution and make decisions within programs, crucial for creating dynamic and responsive applications

Please Login to comment...

Improve your Coding Skills with Practice

What kind of Experience do you want to share?

Learn Python practically and Get Certified .

Python Fundamentals

Python Variables and Literals
Python Type Conversion
Python Basic Input and Output
Python Operators

Python Flow Control

Python if...else Statement
Python for Loop

Python while Loop

Python break and continue

Python pass Statement

Python Data types

Python Numbers and Mathematics
Python List
Python Tuple
Python String
Python Dictionary
Python Functions
Python Function Arguments
Python Variable Scope
Python Global Keyword
Python Recursion
Python Modules
Python Package
Python Main function

Python Files

Python Directory and Files Management
Python CSV: Read and Write CSV files
Reading CSV files in Python
Writing CSV files in Python
Python Exception Handling
Python Exceptions
Python Custom Exceptions

Python Object & Class

Python Objects and Classes
Python Inheritance
Python Multiple Inheritance
Polymorphism in Python
Python Operator Overloading

Python Advanced Topics

List comprehension
Python Lambda/Anonymous Function
Python Iterators
Python Generators
Python Namespace and Scope
Python Closures
Python Decorators
Python @property decorator
Python RegEx

Python Date and Time

Python datetime
Python strftime()
Python strptime()
How to get current date and time in Python?
Python Get Current Time
Python timestamp to datetime and vice-versa
Python time Module
Python sleep()

Additional Topic

Precedence and Associativity of Operators in Python
Python Keywords and Identifiers
Python Asserts
Python Json
Python *args and **kwargs

Python Tutorials

Python Assert Statement

Python Looping Techniques

In computer programming, the if statement is a conditional statement. It is used to execute a block of code only when a specific condition is met. For example,

Suppose we need to assign different grades to students based on their scores.

If a student scores above 90 , assign grade A
If a student scores above 75 , assign grade B
If a student scores above 65 , assign grade C

These conditional tasks can be achieved using the if statement.

Python if Statement

An if statement executes a block of code only when the specified condition is met.

Here, condition is a boolean expression, such as number > 5 , that evaluates to either True or False .

If condition evaluates to True , the body of the if statement is executed.
If condition evaluates to False , the body of the if statement will be skipped from execution.

Let's look at an example.

Example: Python if Statement

Sample Output 1

If user enters 10 , the condition number > 0 evaluates to True . Therefore, the body of if is executed.

Sample Output 2

If user enters -2 , the condition number > 0 evaluates to False . Therefore, the body of if is skipped from execution.

Indentation in Python

Python uses indentation to define a block of code, such as the body of an if statement. For example,

Here, the body of if has two statements. We know this because two statements (immediately after if ) start with indentation.

We usually use four spaces for indentation in Python, although any number of spaces works as long as we are consistent.

You will get an error if you write the above code like this:

Here, we haven't used indentation after the if statement. In this case, Python thinks our if statement is empty, which results in an error.

An if statement can have an optional else clause. The else statement executes if the condition in the if statement evaluates to False .

Here, if the condition inside the if statement evaluates to

True - the body of if executes, and the body of else is skipped.
False - the body of else executes, and the body of if is skipped

Example: Python if…else Statement

If user enters 10 , the condition number > 0 evalutes to True . Therefore, the body of if is executed and the body of else is skipped.

If user enters 0 , the condition number > 0 evalutes to False . Therefore, the body of if is skipped and the body of else is executed.

Python if…elif…else Statement

The if...else statement is used to execute a block of code among two alternatives.

However, if we need to make a choice between more than two alternatives, we use the if...elif...else statement.

Example: Python if…elif…else Statement

Here, the first condition, number > 0 , evaluates to False . In this scenario, the second condition is checked.

The second condition, number < 0 , evaluates to True . Therefore, the statements inside the elif block is executed.

In the above program, it is important to note that regardless the value of number variable, only one block of code will be executed.

Python Nested if Statements

It is possible to include an if statement inside another if statement. For example,

Here's how this program works.

Video: Python if...else Statement

Sorry about that.

Our premium learning platform, created with over a decade of experience and thousands of feedbacks .

Learn and improve your coding skills like never before.

Interactive Courses
Certificates
2000+ Challenges

7. Simple statements ¶

A simple statement is comprised within a single logical line. Several simple statements may occur on a single line separated by semicolons. The syntax for simple statements is:

7.1. Expression statements ¶

Expression statements are used (mostly interactively) to compute and write a value, or (usually) to call a procedure (a function that returns no meaningful result; in Python, procedures return the value None ). Other uses of expression statements are allowed and occasionally useful. The syntax for an expression statement is:

An expression statement evaluates the expression list (which may be a single expression).

In interactive mode, if the value is not None , it is converted to a string using the built-in repr() function and the resulting string is written to standard output on a line by itself (except if the result is None , so that procedure calls do not cause any output.)

7.2. Assignment statements ¶

Assignment statements are used to (re)bind names to values and to modify attributes or items of mutable objects:

(See section Primaries for the syntax definitions for attributeref , subscription , and slicing .)

An assignment statement evaluates the expression list (remember that this can be a single expression or a comma-separated list, the latter yielding a tuple) and assigns the single resulting object to each of the target lists, from left to right.

Assignment is defined recursively depending on the form of the target (list). When a target is part of a mutable object (an attribute reference, subscription or slicing), the mutable object must ultimately perform the assignment and decide about its validity, and may raise an exception if the assignment is unacceptable. The rules observed by various types and the exceptions raised are given with the definition of the object types (see section The standard type hierarchy ).

Assignment of an object to a target list, optionally enclosed in parentheses or square brackets, is recursively defined as follows.

If the target list is a single target with no trailing comma, optionally in parentheses, the object is assigned to that target.

If the target list contains one target prefixed with an asterisk, called a “starred” target: The object must be an iterable with at least as many items as there are targets in the target list, minus one. The first items of the iterable are assigned, from left to right, to the targets before the starred target. The final items of the iterable are assigned to the targets after the starred target. A list of the remaining items in the iterable is then assigned to the starred target (the list can be empty).

Else: The object must be an iterable with the same number of items as there are targets in the target list, and the items are assigned, from left to right, to the corresponding targets.

Assignment of an object to a single target is recursively defined as follows.

If the target is an identifier (name):

If the name does not occur in a global or nonlocal statement in the current code block: the name is bound to the object in the current local namespace.

Otherwise: the name is bound to the object in the global namespace or the outer namespace determined by nonlocal , respectively.

The name is rebound if it was already bound. This may cause the reference count for the object previously bound to the name to reach zero, causing the object to be deallocated and its destructor (if it has one) to be called.

If the target is an attribute reference: The primary expression in the reference is evaluated. It should yield an object with assignable attributes; if this is not the case, TypeError is raised. That object is then asked to assign the assigned object to the given attribute; if it cannot perform the assignment, it raises an exception (usually but not necessarily AttributeError ).

Note: If the object is a class instance and the attribute reference occurs on both sides of the assignment operator, the right-hand side expression, a.x can access either an instance attribute or (if no instance attribute exists) a class attribute. The left-hand side target a.x is always set as an instance attribute, creating it if necessary. Thus, the two occurrences of a.x do not necessarily refer to the same attribute: if the right-hand side expression refers to a class attribute, the left-hand side creates a new instance attribute as the target of the assignment:

This description does not necessarily apply to descriptor attributes, such as properties created with property() .

If the target is a subscription: The primary expression in the reference is evaluated. It should yield either a mutable sequence object (such as a list) or a mapping object (such as a dictionary). Next, the subscript expression is evaluated.

If the primary is a mutable sequence object (such as a list), the subscript must yield an integer. If it is negative, the sequence’s length is added to it. The resulting value must be a nonnegative integer less than the sequence’s length, and the sequence is asked to assign the assigned object to its item with that index. If the index is out of range, IndexError is raised (assignment to a subscripted sequence cannot add new items to a list).

If the primary is a mapping object (such as a dictionary), the subscript must have a type compatible with the mapping’s key type, and the mapping is then asked to create a key/value pair which maps the subscript to the assigned object. This can either replace an existing key/value pair with the same key value, or insert a new key/value pair (if no key with the same value existed).

For user-defined objects, the __setitem__() method is called with appropriate arguments.

If the target is a slicing: The primary expression in the reference is evaluated. It should yield a mutable sequence object (such as a list). The assigned object should be a sequence object of the same type. Next, the lower and upper bound expressions are evaluated, insofar they are present; defaults are zero and the sequence’s length. The bounds should evaluate to integers. If either bound is negative, the sequence’s length is added to it. The resulting bounds are clipped to lie between zero and the sequence’s length, inclusive. Finally, the sequence object is asked to replace the slice with the items of the assigned sequence. The length of the slice may be different from the length of the assigned sequence, thus changing the length of the target sequence, if the target sequence allows it.

CPython implementation detail: In the current implementation, the syntax for targets is taken to be the same as for expressions, and invalid syntax is rejected during the code generation phase, causing less detailed error messages.

Although the definition of assignment implies that overlaps between the left-hand side and the right-hand side are ‘simultaneous’ (for example a, b = b, a swaps two variables), overlaps within the collection of assigned-to variables occur left-to-right, sometimes resulting in confusion. For instance, the following program prints [0, 2] :

The specification for the *target feature.

7.2.1. Augmented assignment statements ¶

Augmented assignment is the combination, in a single statement, of a binary operation and an assignment statement:

(See section Primaries for the syntax definitions of the last three symbols.)

An augmented assignment evaluates the target (which, unlike normal assignment statements, cannot be an unpacking) and the expression list, performs the binary operation specific to the type of assignment on the two operands, and assigns the result to the original target. The target is only evaluated once.

An augmented assignment statement like x += 1 can be rewritten as x = x + 1 to achieve a similar, but not exactly equal effect. In the augmented version, x is only evaluated once. Also, when possible, the actual operation is performed in-place , meaning that rather than creating a new object and assigning that to the target, the old object is modified instead.

Unlike normal assignments, augmented assignments evaluate the left-hand side before evaluating the right-hand side. For example, a[i] += f(x) first looks-up a[i] , then it evaluates f(x) and performs the addition, and lastly, it writes the result back to a[i] .

With the exception of assigning to tuples and multiple targets in a single statement, the assignment done by augmented assignment statements is handled the same way as normal assignments. Similarly, with the exception of the possible in-place behavior, the binary operation performed by augmented assignment is the same as the normal binary operations.

For targets which are attribute references, the same caveat about class and instance attributes applies as for regular assignments.

7.2.2. Annotated assignment statements ¶

Annotation assignment is the combination, in a single statement, of a variable or attribute annotation and an optional assignment statement:

The difference from normal Assignment statements is that only a single target is allowed.

The assignment target is considered “simple” if it consists of a single name that is not enclosed in parentheses. For simple assignment targets, if in class or module scope, the annotations are evaluated and stored in a special class or module attribute __annotations__ that is a dictionary mapping from variable names (mangled if private) to evaluated annotations. This attribute is writable and is automatically created at the start of class or module body execution, if annotations are found statically.

If the assignment target is not simple (an attribute, subscript node, or parenthesized name), the annotation is evaluated if in class or module scope, but not stored.

If a name is annotated in a function scope, then this name is local for that scope. Annotations are never evaluated and stored in function scopes.

If the right hand side is present, an annotated assignment performs the actual assignment before evaluating annotations (where applicable). If the right hand side is not present for an expression target, then the interpreter evaluates the target except for the last __setitem__() or __setattr__() call.

The proposal that added syntax for annotating the types of variables (including class variables and instance variables), instead of expressing them through comments.

The proposal that added the typing module to provide a standard syntax for type annotations that can be used in static analysis tools and IDEs.

Changed in version 3.8: Now annotated assignments allow the same expressions in the right hand side as regular assignments. Previously, some expressions (like un-parenthesized tuple expressions) caused a syntax error.

7.3. The assert statement ¶

Assert statements are a convenient way to insert debugging assertions into a program:

The simple form, assert expression , is equivalent to

The extended form, assert expression1, expression2 , is equivalent to

These equivalences assume that __debug__ and AssertionError refer to the built-in variables with those names. In the current implementation, the built-in variable __debug__ is True under normal circumstances, False when optimization is requested (command line option -O ). The current code generator emits no code for an assert statement when optimization is requested at compile time. Note that it is unnecessary to include the source code for the expression that failed in the error message; it will be displayed as part of the stack trace.

Assignments to __debug__ are illegal. The value for the built-in variable is determined when the interpreter starts.

7.4. The pass statement ¶

pass is a null operation — when it is executed, nothing happens. It is useful as a placeholder when a statement is required syntactically, but no code needs to be executed, for example:

7.5. The del statement ¶

Deletion is recursively defined very similar to the way assignment is defined. Rather than spelling it out in full details, here are some hints.

Deletion of a target list recursively deletes each target, from left to right.

Deletion of a name removes the binding of that name from the local or global namespace, depending on whether the name occurs in a global statement in the same code block. If the name is unbound, a NameError exception will be raised.

Deletion of attribute references, subscriptions and slicings is passed to the primary object involved; deletion of a slicing is in general equivalent to assignment of an empty slice of the right type (but even this is determined by the sliced object).

Changed in version 3.2: Previously it was illegal to delete a name from the local namespace if it occurs as a free variable in a nested block.

7.6. The return statement ¶

return may only occur syntactically nested in a function definition, not within a nested class definition.

If an expression list is present, it is evaluated, else None is substituted.

return leaves the current function call with the expression list (or None ) as return value.

When return passes control out of a try statement with a finally clause, that finally clause is executed before really leaving the function.

In a generator function, the return statement indicates that the generator is done and will cause StopIteration to be raised. The returned value (if any) is used as an argument to construct StopIteration and becomes the StopIteration.value attribute.

In an asynchronous generator function, an empty return statement indicates that the asynchronous generator is done and will cause StopAsyncIteration to be raised. A non-empty return statement is a syntax error in an asynchronous generator function.

7.7. The yield statement ¶

A yield statement is semantically equivalent to a yield expression . The yield statement can be used to omit the parentheses that would otherwise be required in the equivalent yield expression statement. For example, the yield statements

are equivalent to the yield expression statements

Yield expressions and statements are only used when defining a generator function, and are only used in the body of the generator function. Using yield in a function definition is sufficient to cause that definition to create a generator function instead of a normal function.

For full details of yield semantics, refer to the Yield expressions section.

7.8. The raise statement ¶

If no expressions are present, raise re-raises the exception that is currently being handled, which is also known as the active exception . If there isn’t currently an active exception, a RuntimeError exception is raised indicating that this is an error.

Otherwise, raise evaluates the first expression as the exception object. It must be either a subclass or an instance of BaseException . If it is a class, the exception instance will be obtained when needed by instantiating the class with no arguments.

The type of the exception is the exception instance’s class, the value is the instance itself.

A traceback object is normally created automatically when an exception is raised and attached to it as the __traceback__ attribute. You can create an exception and set your own traceback in one step using the with_traceback() exception method (which returns the same exception instance, with its traceback set to its argument), like so:

The from clause is used for exception chaining: if given, the second expression must be another exception class or instance. If the second expression is an exception instance, it will be attached to the raised exception as the __cause__ attribute (which is writable). If the expression is an exception class, the class will be instantiated and the resulting exception instance will be attached to the raised exception as the __cause__ attribute. If the raised exception is not handled, both exceptions will be printed:

A similar mechanism works implicitly if a new exception is raised when an exception is already being handled. An exception may be handled when an except or finally clause, or a with statement, is used. The previous exception is then attached as the new exception’s __context__ attribute:

Exception chaining can be explicitly suppressed by specifying None in the from clause:

Additional information on exceptions can be found in section Exceptions , and information about handling exceptions is in section The try statement .

Changed in version 3.3: None is now permitted as Y in raise X from Y .

Added the __suppress_context__ attribute to suppress automatic display of the exception context.

Changed in version 3.11: If the traceback of the active exception is modified in an except clause, a subsequent raise statement re-raises the exception with the modified traceback. Previously, the exception was re-raised with the traceback it had when it was caught.

7.9. The break statement ¶

break may only occur syntactically nested in a for or while loop, but not nested in a function or class definition within that loop.

It terminates the nearest enclosing loop, skipping the optional else clause if the loop has one.

If a for loop is terminated by break , the loop control target keeps its current value.

When break passes control out of a try statement with a finally clause, that finally clause is executed before really leaving the loop.

7.10. The continue statement ¶

continue may only occur syntactically nested in a for or while loop, but not nested in a function or class definition within that loop. It continues with the next cycle of the nearest enclosing loop.

When continue passes control out of a try statement with a finally clause, that finally clause is executed before really starting the next loop cycle.

7.11. The import statement ¶

The basic import statement (no from clause) is executed in two steps:

find a module, loading and initializing it if necessary

define a name or names in the local namespace for the scope where the import statement occurs.

When the statement contains multiple clauses (separated by commas) the two steps are carried out separately for each clause, just as though the clauses had been separated out into individual import statements.

The details of the first step, finding and loading modules, are described in greater detail in the section on the import system , which also describes the various types of packages and modules that can be imported, as well as all the hooks that can be used to customize the import system. Note that failures in this step may indicate either that the module could not be located, or that an error occurred while initializing the module, which includes execution of the module’s code.

If the requested module is retrieved successfully, it will be made available in the local namespace in one of three ways:

If the module name is followed by as , then the name following as is bound directly to the imported module.

If no other name is specified, and the module being imported is a top level module, the module’s name is bound in the local namespace as a reference to the imported module

If the module being imported is not a top level module, then the name of the top level package that contains the module is bound in the local namespace as a reference to the top level package. The imported module must be accessed using its full qualified name rather than directly

The from form uses a slightly more complex process:

find the module specified in the from clause, loading and initializing it if necessary;

for each of the identifiers specified in the import clauses:

check if the imported module has an attribute by that name

if not, attempt to import a submodule with that name and then check the imported module again for that attribute

if the attribute is not found, ImportError is raised.

otherwise, a reference to that value is stored in the local namespace, using the name in the as clause if it is present, otherwise using the attribute name

If the list of identifiers is replaced by a star ( '*' ), all public names defined in the module are bound in the local namespace for the scope where the import statement occurs.

The public names defined by a module are determined by checking the module’s namespace for a variable named __all__ ; if defined, it must be a sequence of strings which are names defined or imported by that module. The names given in __all__ are all considered public and are required to exist. If __all__ is not defined, the set of public names includes all names found in the module’s namespace which do not begin with an underscore character ( '_' ). __all__ should contain the entire public API. It is intended to avoid accidentally exporting items that are not part of the API (such as library modules which were imported and used within the module).

The wild card form of import — from module import * — is only allowed at the module level. Attempting to use it in class or function definitions will raise a SyntaxError .

When specifying what module to import you do not have to specify the absolute name of the module. When a module or package is contained within another package it is possible to make a relative import within the same top package without having to mention the package name. By using leading dots in the specified module or package after from you can specify how high to traverse up the current package hierarchy without specifying exact names. One leading dot means the current package where the module making the import exists. Two dots means up one package level. Three dots is up two levels, etc. So if you execute from . import mod from a module in the pkg package then you will end up importing pkg.mod . If you execute from ..subpkg2 import mod from within pkg.subpkg1 you will import pkg.subpkg2.mod . The specification for relative imports is contained in the Package Relative Imports section.

importlib.import_module() is provided to support applications that determine dynamically the modules to be loaded.

Raises an auditing event import with arguments module , filename , sys.path , sys.meta_path , sys.path_hooks .

7.11.1. Future statements ¶

A future statement is a directive to the compiler that a particular module should be compiled using syntax or semantics that will be available in a specified future release of Python where the feature becomes standard.

The future statement is intended to ease migration to future versions of Python that introduce incompatible changes to the language. It allows use of the new features on a per-module basis before the release in which the feature becomes standard.

A future statement must appear near the top of the module. The only lines that can appear before a future statement are:

the module docstring (if any),

blank lines, and

other future statements.

The only feature that requires using the future statement is annotations (see PEP 563 ).

All historical features enabled by the future statement are still recognized by Python 3. The list includes absolute_import , division , generators , generator_stop , unicode_literals , print_function , nested_scopes and with_statement . They are all redundant because they are always enabled, and only kept for backwards compatibility.

A future statement is recognized and treated specially at compile time: Changes to the semantics of core constructs are often implemented by generating different code. It may even be the case that a new feature introduces new incompatible syntax (such as a new reserved word), in which case the compiler may need to parse the module differently. Such decisions cannot be pushed off until runtime.

For any given release, the compiler knows which feature names have been defined, and raises a compile-time error if a future statement contains a feature not known to it.

The direct runtime semantics are the same as for any import statement: there is a standard module __future__ , described later, and it will be imported in the usual way at the time the future statement is executed.

The interesting runtime semantics depend on the specific feature enabled by the future statement.

Note that there is nothing special about the statement:

That is not a future statement; it’s an ordinary import statement with no special semantics or syntax restrictions.

Code compiled by calls to the built-in functions exec() and compile() that occur in a module M containing a future statement will, by default, use the new syntax or semantics associated with the future statement. This can be controlled by optional arguments to compile() — see the documentation of that function for details.

A future statement typed at an interactive interpreter prompt will take effect for the rest of the interpreter session. If an interpreter is started with the -i option, is passed a script name to execute, and the script includes a future statement, it will be in effect in the interactive session started after the script is executed.

The original proposal for the __future__ mechanism.

7.12. The global statement ¶

The global statement is a declaration which holds for the entire current code block. It means that the listed identifiers are to be interpreted as globals. It would be impossible to assign to a global variable without global , although free variables may refer to globals without being declared global.

Names listed in a global statement must not be used in the same code block textually preceding that global statement.

Names listed in a global statement must not be defined as formal parameters, or as targets in with statements or except clauses, or in a for target list, class definition, function definition, import statement, or variable annotation.

CPython implementation detail: The current implementation does not enforce some of these restrictions, but programs should not abuse this freedom, as future implementations may enforce them or silently change the meaning of the program.

Programmer’s note: global is a directive to the parser. It applies only to code parsed at the same time as the global statement. In particular, a global statement contained in a string or code object supplied to the built-in exec() function does not affect the code block containing the function call, and code contained in such a string is unaffected by global statements in the code containing the function call. The same applies to the eval() and compile() functions.

7.13. The nonlocal statement ¶

When the definition of a function or class is nested (enclosed) within the definitions of other functions, its nonlocal scopes are the local scopes of the enclosing functions. The nonlocal statement causes the listed identifiers to refer to names previously bound in nonlocal scopes. It allows encapsulated code to rebind such nonlocal identifiers. If a name is bound in more than one nonlocal scope, the nearest binding is used. If a name is not bound in any nonlocal scope, or if there is no nonlocal scope, a SyntaxError is raised.

The nonlocal statement applies to the entire scope of a function or class body. A SyntaxError is raised if a variable is used or assigned to prior to its nonlocal declaration in the scope.

The specification for the nonlocal statement.

Programmer’s note: nonlocal is a directive to the parser and applies only to code parsed along with it. See the note for the global statement.

7.14. The type statement ¶

The type statement declares a type alias, which is an instance of typing.TypeAliasType .

For example, the following statement creates a type alias:

This code is roughly equivalent to:

annotation-def indicates an annotation scope , which behaves mostly like a function, but with several small differences.

The value of the type alias is evaluated in the annotation scope. It is not evaluated when the type alias is created, but only when the value is accessed through the type alias’s __value__ attribute (see Lazy evaluation ). This allows the type alias to refer to names that are not yet defined.

Type aliases may be made generic by adding a type parameter list after the name. See Generic type aliases for more.

type is a soft keyword .

Added in version 3.12.

Introduced the type statement and syntax for generic classes and functions.

7.1. Expression statements
7.2.1. Augmented assignment statements
7.2.2. Annotated assignment statements
7.3. The assert statement
7.4. The pass statement
7.5. The del statement
7.6. The return statement
7.7. The yield statement
7.8. The raise statement
7.9. The break statement
7.10. The continue statement
7.11.1. Future statements
7.12. The global statement
7.13. The nonlocal statement
7.14. The type statement

Previous topic

6. Expressions

8. Compound statements

Report a Bug
Show Source

How to use python if else in one line with examples

December 31, 2023

How do I write a simple python if else in one line? What are ternary operator in Python? Can we use one liner for complex if and else statements?

In this tutorial I will share different examples to help you understand and learn about usage of ternary operator in one liner if and else condition with Python. Conditional expressions (sometimes called a “ ternary operator ”) have the lowest priority of all Python operations. Programmers coming to Python from C, C++, or Perl sometimes miss the so-called ternary operator ?:. It’s most often used for avoiding a few lines of code and a temporary variable for simple decisions.

I will not go into details of generic ternary operator as this is used across Python for loops and control flow statements. Here we will concentrate on learning python if else in one line using ternary operator

Python if else in one line

The general syntax of single if and else statement in Python is:

Now if we wish to write this in one line using ternary operator, the syntax would be:

In this syntax, first of all the else condition is evaluated.

If condition returns True then value_when_true is returned
If condition returns False then value_when_false is returned

Similarly if you had a variable assigned in the general if else block based on the condition

The same can be written in single line:

Here as well, first of all the condition is evaluated.

if condition returns True then true-expr is assigned to value object
if condition returns False then false-expr is assigned to value object

For simple cases like this, I find it very nice to be able to express that logic in one line instead of four. Remember, as a coder, you spend much more time reading code than writing it, so Python's conciseness is invaluable.

Some important points to remember:

You can use a ternary expression in Python, but only for expressions , not for statements
You cannot use Python if..elif..else block in one line.
The name " ternary " means there are just 3 parts to the operator: condition , then , and else .
Although there are hacks to modify if..elif..else block into if..else block and then use it in single line but that can be complex depending upon conditions and should be avoided
With if-else blocks , only one of the expressions will be executed.
While it may be tempting to always use ternary expressions to condense your code, realise that you may sacrifice readability if the condition as well as the true and false expressions are very complex.

Python Script Example

This is a simple script where we use comparison operator in our if condition

First collect user input in the form of integer and store this value into b
If b is greater than or equal to 0 then return " positive " which will be True condition
If b returns False i.e. above condition was not success then return " negative "
The final returned value i.e. either " positive " or " negative " is stored in object a
Lastly print the value of value a

The multi-line form of this code would be:

Python if..elif..else in one line

Now as I told this earlier, it is not possible to use if..elif..else block in one line using ternary expressions. Although we can hack our way into this but make sure the maximum allowed length of a line in Python is 79 as per PEP-8 Guidelines

We have this if..elif..else block where we return expression based on the condition check:

We can write this if..elif..else block in one-line using this syntax:

In this syntax,

First of all condition2 is evaluated, if return True then expr2 is returned
If condition2 returns False then condition1 is evaluated, if return True then expr1 is returned
If condition1 also returns False then else is executed and expr is returned

As you see, it was easier if we read this in multi-line if..elif..else block while the same becomes hard to understand for beginners.

We can add multiple if else block in this syntax, but we must also adhere to PEP-8 guidelines

Python Script Example-1

In this sample script we collect an integer value from end user and store it in " b ". The order of execution would be:

If the value of b is less than 0 then " neg " is returned
If the value of b is greater than 0 then " pos " is returned.
If both the condition return False , then " zero " is returned

The multi-line form of the code would be:

Output(when if condition is True )

Output(when if condition is False and elif condition is True )

Output(when both if and elif condition are False )

Python script Example-2

We will add some more else blocks in this sample script, the order of the check would be in below sequence :

Collect user input for value b which will be converted to integer type
If value of b is equal to 100 then return " equal to 100 ", If this returns False then next if else condition would be executed
If value of b is equal to 50 then return " equal to 50 ", If this returns False then next if else condition would be executed
If value of b is equal to 40 then return " equal to 40 ", If this returns False then next if else condition would be executed
If value of b is greater than 100 then return " greater than 100 ", If this returns False then next go to else block
Lastly if all the condition return False then return " less than hundred "

The multi-line form of this example would be:

Python nested if..else in one line

We can also use ternary expression to define nested if..else block on one line with Python.

If you have a multi-line code using nested if else block , something like this:

The one line syntax to use this nested if else block in Python would be:

Here, we have added nested if..elif..else inside the else block using ternary expression. The sequence of the check in the following order

If condition1 returns True then expr1 is returned, if it returns False then next condition is checked
If condition-m returns True then expr-m is returned, if it returns False then else block with nested if..elif..else is checked
If condition3 returns True then expr3 is returned, if it returns False then next condition inside the nested block is returned
If condition-n returns True then expr-n is returned, if it returns False then expr5 is returned from the else condition

In this example I am using nested if else inside the else block of our one liner. The order of execution will be in the provided sequence:

First of all collect integer value of b from the end user
If the value of b is equal to 100 then the if condition returns True and " equal to 100 " is returned
If the value of b is equal to 50 then the elif condition returns True and " equal to 50 " is returned
If both if and elif condition returns False then the else block is executed where we have nested if and else condition
Inside the else block , if b is greater than 100 then it returns " greater than 100 " and if it returns False then " less than 100 " is returned

In this tutorial we learned about usage of ternary operator in if else statement to be able to use it in one line. Although Python does not allow if..elif..else statement in one line but we can still break it into if else and then use it in single line form. Similarly we can also use nested if with ternary operator in single line. I shared multiple examples to help you understand the concept of ternary operator with if and else statement of Python programming language

Lastly I hope this tutorial guide on python if else one line was helpful. So, let me know your suggestions and feedback using the comment section.

Deepak Prasad

He is the founder of GoLinuxCloud and brings over a decade of expertise in Linux, Python, Go, Laravel, DevOps, Kubernetes, Git, Shell scripting, OpenShift, AWS, Networking, and Security. With extensive experience, he excels in various domains, from development to DevOps, Networking, and Security, ensuring robust and efficient solutions for diverse projects. You can connect with him on his LinkedIn profile.

Can't find what you're searching for? Let us assist you.

Enter your query below, and we'll provide instant results tailored to your needs.

If my articles on GoLinuxCloud has helped you, kindly consider buying me a coffee as a token of appreciation.

For any other feedbacks or questions you can send mail to [email protected]

Thank You for your support!!

Python If-Else Statement in One Line - Ternary Operator Explained

Single-line conditionals in python here’s when to and when not to use them.

Python isn’t the fastest programming language out there, but boy is it readable and efficient to write. Everyone knows what conditional statements are, but did you know you can write if statements in one line of Python code? As it turns out you can, and you’ll learn all about it today.

After reading, you’ll know everything about Python’s If Else statements in one line. You’ll understand when to use them, and when it’s best to avoid them and stick to conventional conditional statements.

Don’t feel like reading? Watch my video instead:

Want to get hired as a data scientist? Running a data science blog might help:

Can Blogging About Data Science Really Get You Hired as a Data Scientist?

What’s Wrong With the Normal If Statement?

Absolutely nothing. Splitting conditional statements into multiple lines of code has been a convention for ages. Most programming languages require the usage of curly brackets, and hence the single line if statements are not an option. Other languages allow writing only simple conditionals in a single line.

And then there’s Python. Before diving into If Else statements in one line, let’s first make a short recap on regular conditionals.

For example, you can check if a condition is true with the following syntax:

The variable age is less than 18 in this case, so Go home. is printed to the console. You can spice things up by adding an else condition that gets evaluated if the first condition is False :

This time age is greater than 18, so Welcome! gets printed to the console. Finally, you can add one or multiple elif conditions. These are used to capture the in-between cases. For example, you can print something entirely different if age is between 16 (included) and 18 (excluded):

The variable age is 17, which means the condition under elif is True , hence Not sure... is printed to the console.

Pretty basic stuff, so we naturally don’t want to spend so many lines of code writing it. As it turns out, you can use the ternary operator in Python to evaluate conditions in a single line.

Ternary Operator in Python

A ternary operator exists in some programming languages, and it allows you to shorten a simple If-Else block. It takes in 3 or more operands:

Value if true - A value that’s returned if the condition evaluates to True.
Condition - A boolean condition that has to be satisfied to return value if true.
Value if false - A value that’s returned if the condition evaluates to False. In code, it would look like this:

You can even write else-if logic in Python’s ternary operator. In that case, the syntax changes slightly:

I have to admit - it looks a bit abstract when written like this. You’ll see plenty of practical examples starting from the next section.

One-Line If Statement (Without Else)

A single-line if statement just means you’re deleting the new line and indentation. You’re still writing the same code, with the only twist being that it takes one line instead of two.

Note: One-line if statement is only possible if there’s a single line of code following the condition. In any other case, wrap the code that will be executed inside a function.

Here’s how to transform our two-line if statement to a single-line conditional:

As before, age is less than 18 so Go home. gets printed.

What if you want to print three lines instead of one? As said before, the best practice is to wrap the code inside a function:

One-line if statements in Python are pretty boring. The real time and space saving benefit happens when you add an else condition.

You’ll benefit the most from one-line if statements if you add one or multiple else conditions.

One-Line If-Else Statement

Now we can fully leverage the power of Python’s ternary operator. The code snippet below stores Go home. to a new variable outcome if the age is less than 18 or Welcome! otherwise:

As you would guess, Welcome! is printed to the console as age is set to 19. If you want to print multiple lines or handle more complex logic, wrap everything you want to be executed into a function - just as before.

You now have a clear picture of how the ternary operator works on a simple one-line if-else statement. We can add complexity by adding more conditions to the operator.

One-Line If-Elif-Else Statement

Always be careful when writing multiple conditions in a single line of code. The logic will still work if the line is 500 characters long, but it’s near impossible to read and maintain it.

You should be fine with two conditions in one line, as the code is still easy to read. The following example prints Go home. if age is below 16, Not Sure... if age is between 16 (included) and 18 (excluded), and Welcome otherwise:

You’ll see Not sure... printed to the console, since age is set to 17. What previously took us six lines of code now only takes one. Neat improvement, and the code is still easy to read and maintain.

What else can you do with one-line if statements? Well, a lot. We’ll explore single-line conditionals for list operations next.

Example: One-Line Conditionals for List Operations

Applying some logic to a list involves applying the logic to every list item, and hence iterating over the entire list. Before even thinking about a real-world example, let’s see how you can write a conditional statement for every list item in a single line of code.

How to Write IF and FOR in One Line

You’ll need to make two changes to the ternary operator:

Surround the entire line of code with brackets [] Append the list iteration code (for element in array) after the final else Here’s how the generic syntax looks like:

It’s not that hard, but let’s drive the point home with an example. The following code snippet prints + if the current number of a range is greater than 5 and - otherwise. The numbers range from 1 to 10 (included):

Image 1 - If and For in a single line in Python (image by author)

Let’s now go over an additional real-world example.

Example: Did Student Pass the Exam?

To start, we’ll declare a list of students. Each student is a Python dictionary object with two keys: name and test score:

We want to print that the student has passed the exam if the score is 50 points or above. If the score was below 50 points, we want to print that the student has failed the exam.

In traditional Python syntax, we would manually iterate over each student in the list and check if the score is greater than 50:

Image 2 - List iteration with traditional Python syntax (image by author)

The code works, but we need 5 lines to make a simple check and store the results. You can use your newly-acquired knowledge to reduce the amount of code to a single line:

Image 3 - One-line conditional and a loop with Python (image by author)

The results are identical, but we have a much shorter and neater code. It’s just on the boundary of being unreadable, which is often a tradeoff with ternary operators and single-line loops. You often can’t have both readable code and short Python scripts.

Just because you can write a conditional in one line, it doesn’t mean you should. Readability is a priority. Let’s see in which cases you’re better off with traditional if statements.

Be Careful With One-Line Conditionals

Just because code takes less vertical space doesn’t mean it’s easier to read. Now you’ll see the perfect example of that claim.

The below snippet checks a condition for every possible grade (1-5) with a final else condition capturing invalid input. The conditions take 12 lines of code to write, but the entire snippet is extremely readable:

As expected, you’ll see Grade = 1 printed to the console, but that’s not what we’re interested in. We want to translate the above snippet into a one-line if-else statement with the ternary operator.

It’s possible - but the end result is messy and unreadable:

This is an example of an extreme case where you have multiple conditions you have to evaluate. It’s better to stick with the traditional if statements, even though they take more vertical space.

Take home point: A ternary operator with more than two conditions is just a nightmare to write and debug.

And there you have it - everything you need to know about one-line if-else statements in Python. You’ve learned all there is about the ternary operator, and how to write conditionals starting with a single if to five conditions in between.

Remember to keep your code simple. The code that’s easier to read and maintain is a better-written code at the end of the day. Just because you can cram everything into a single line, doesn’t mean you should. You’ll regret it as soon as you need to make some changes.

An even cleaner way to write long conditionals is by using structural pattern matching - a new feature introduced in Python 3.10. It brings the beloved switch statement to Python for extra readability and speed of development.

What do you guys think of one-line if-else statements in Python? Do you use them regularly or have you switched to structural pattern matching? Let me know in the comment section below.

Conditionals >

Now that we understand how to use Boolean values in our programs, it’s time to put those values to use. One way to think of the result of a Boolean expression is that it helps us make a decision in our programs. For example, if we want to do something special in our program when the user inputs the value $ 42 $ into the variable x , then we can write the Boolean expression x == 42 to help us decide if the user input the correct value.

Once we have that decision made, we need some way to tell our program to run a different piece of code based on the outcome of that decision. In Python, as well as most other programming languages, we can use a special construct called an if statement to do this. If statements are one example of a conditional statement in programming.

These conditional statements allow us to affect the control flow of our programs. Effectively, we can use a Boolean expression to determine whether a particular piece of code should be executed or not. In an if statement , we include a Boolean expression and a block of statements. If the Boolean expression evaluates to True , then we execute the code in the block of statements. If it is False , then we skip the block and continue with the rest of the program.

The structure of an if statement in Python is shown below:

In this structure, we have a <boolean expression> that is evaluated. After the Boolean expression is a colon : .

Then, the <block of statements> is included below the if statement’s first line, and it must be indented one level. In Python, the <block of statements> must include at least one line of code, otherwise Python won’t be able to understand it.

Indentation in Python

Let’s briefly discuss indentation in Python, since it is very important and is usually something that trips up new Python developers. Most programming languages use symbols such as curly braces {} to surround blocks of statements in code, making it easy to tell where one block ends and another begins. Similarly, those languages also use symbols such as semicolons ; at the end of each line of code, indicating the end of a particular statement.

These programming languages use those symbols to make it clear to both the developer and the computer where a particular line or block of code begins and ends, and it makes it very easy for tools to understand and run the code. As an interesting side effect, it also means that the code doesn’t need to follow any particular structure beyond the use of those symbols - many of the languages allow developers to place multiple statements, or even entire programs, on a single line of code. Likewise, indentation is completely optional, and only done to help make the code more readable.

Python takes a different approach. Instead of using symbols like semicolons ; and curly braces {} to show the structure of the code, Python uses newlines and indentation for this purpose. By doing so, Python is simultaneously simpler (since it has fewer symbols to learn) and more complex (the indentation has meaning) than other languages. It’s really a tradeoff, though most Python programmers will admit that not having to deal with special symbols in Python is well worth the effort of making sure that the indentation is correct, especially since most other languages follow the same conventions anyway, even if it isn’t strictly required.

So, how can we indent code in Python? Typically, we use four consecutive spaces for each level of indentation. So, below the conditional statement if <boolean expression>: shown above, we would place four spaces before the first line of the <block of statements> , and then continue to do so for each line below that should be included in the block of code.

Thankfully, most text editors used for programming, such as Codio, Atom, Visual Studio Code, and more, are all configured to convert tabs to spaces. So, we can simply press the Tab key on the keyboard to insert the correct amount of spaces for one level of indentation. Likewise, we can usually use Shift+Tab to remove four spaces.

Finally, it is worth noting that there is a special symbol that actually is a tab in text, which is represented as \t in a string. Like the newline symbol, we can’t see it in our UI in most cases, but it is there. Some non-programming text editors, such as Notepad in Windows, will insert that symbol instead of four spaces when we press the Tab key. If we try to run a program that contains those symbols, the Python interpreter may not be able to read our program and will give us an error about inconsistent use of tabs and spaces. If that happens, we’ll need to make sure our program is consistently using only tabs or spaces for indentation. Most editors used for programming have a special function for converting tabs to spaces, and there are lots of online tools available for this as well.

Code Tracing Example - False

Let’s go through a couple of code tracing examples in Python Tutor to see how an if statement works in code.

Consider this program in Python:

We can see this example by clicking on this Python Tutor link. At first, our window should look something like this:

When we step through the program, the first line of code will ask the user to input a number, so Python Tutor will show an input box at the bottom of the window:

For this first time through the program, let’s assume the user inputs the string "42" as input:

So, when we click Submit, we’ll see the integer value $ 42 $ stored in the variable x in the Global frame:

At this point, we’ve reached the if statement. The first step is to evaluate the Boolean expression x == 7 . Since x is actually storing the value $ 42 $ , this statement will evaluate to False . So, when we click the Next button on the state below:

We’ll see that the program arrow jumps past the block of statements in the if statement. So, the next line will simply print the goodbye message:

The entire process is shown in the animation below:

As we can see, when the Boolean expression evaluates to False , we’ll just skip the block of statements inside of the if statement.

Code Tracing Example - True

Now let’s see what happens when the Boolean expression evaluates to True instead. To see that, we can go back to the point where our program is asking for input, as shown below:

This time, we’ll assume the user inputs the string "7" as input.

So, when we click Submit, we’ll see the integer value $ 7 $ stored in the variable x in the Global frame:

This time, when we reach the if statement, we’ll see that the Boolean expression x == 7 will evaluate to True . So, when we click the Next button, we’ll be taken to the block of statements inside of the if statement:

Here, we’ll print the special message for finding a lucky number:

Then, we’ll print the program’s goodbye message:

The entire process can be seen in this animation:

So, when the Boolean expression evaluates to True , we’ll run the code inside the if statement. If it is False , then we’ll just skip past the if statement and continue with the rest of our program.

If Statement Flowchart

Another way to visualize an if statement is using a flowchart. Consider the following Python code:

This Python code can also be represented as the flowchart shown below:

When we read flowcharts like this, we typically go from top to bottom, starting with the circle labeled “START”. The first step is to read input from the user, and store that value in the variable x .

Then, we reach a decision node, which uses a diamond shape. This node asks if the value in the variable x is greater than 0. Notice that there are two lines coming from the decision node: one labeled “True” and another labeled “False”. They correspond to the possible values that can result from evaluating the Boolean expression x > 0 . So, if the result of that expression is True , then we’ll follow the path that exits the diamond from the side labeled “True”, and we’ll output the value x to the terminal. Once that is done, we can follow that path around to the next box that will output the string "Goodbye" .

If that result is False , then we’ll follow the downward path labeled “False” and skip the path to the side. Instead, we’ll just reach the line that prints "Goodbye" and then end the program.

As we learn how to use if statements in our code, we might find it easier to use flowcharts or other tools to help understand exactly what our program will do. The path that a program takes through a flowchart like this is called the control flow of the program. We’ll discuss that topic a bit more toward the end of this lab.

Last modified by: Russell Feldhausen Jun 27, 2024

Assignment Expressions: The Walrus Operator

Discussion (8)

In this lesson, you’ll learn about the biggest change in Python 3.8: the introduction of assignment expressions . Assignment expression are written with a new notation (:=) .This operator is often called the walrus operator as it resembles the eyes and tusks of a walrus on its side.

Assignment expressions allow you to assign and return a value in the same expression. For example, if you want to assign to a variable and print its value, then you typically do something like this:

In Python 3.8, you’re allowed to combine these two statements into one, using the walrus operator:

The assignment expression allows you to assign True to walrus , and immediately print the value. But keep in mind that the walrus operator does not do anything that isn’t possible without it. It only makes certain constructs more convenient, and can sometimes communicate the intent of your code more clearly.

One pattern that shows some of the strengths of the walrus operator is while loops where you need to initialize and update a variable. For example, the following code asks the user for input until they type quit :

This code is less than ideal. You’re repeating the input() statement, and somehow you need to add current to the list before asking the user for it. A better solution is to set up an infinite while loop, and use break to stop the loop:

This code is equivalent to the code above, but avoids the repetition and somehow keeps the lines in a more logical order. If you use an assignment expression, then you can simplify this loop further:

This moves the test back to the while line, where it should be. However, there are now several things happening at that line, so it takes a bit more effort to read it properly. Use your best judgement about when the walrus operator helps make your code more readable.

PEP 572 describes all the details of assignment expressions, including some of the rationale for introducing them into the language, as well as several examples of how the walrus operator can be used. The Python 3.8 documentation also includes some good examples of assignment expressions.

Here are a few resources for more info on using bpython, the REPL (Read–Eval–Print Loop) tool used in most of these videos:

Discover bpython: A Python REPL With IDE-Like Features
A better Python REPL: bpython vs python
bpython Homepage
bpython Docs

00:00 In this video, you’ll learn about what’s being called the walrus operator. One of the biggest changes in Python 3.8 is the introduction of these assignment expressions. So, what does it do?

00:12 Well, it allows the assignment and the return of a value in the same expression, using a new notation. On the left side, you’d have the name of the object that you’re assigning, and then you have the operator, a colon and an equal sign ( := ), affectionately known as the walrus operator as it resembles the eyes and tusks of a walrus on its side.

00:32 And it’s assigning this expression on the right side, so it’s assigning and returning the value in the same expression. Let me have you practice with this operator with some code.

00:44 Throughout this tutorial, when I use a REPL, I’m going to be using this custom REPL called bpython . I’ll include links on how to install bpython below this video.

00:53 So, how do you use this assignment operator? Let me have you start with a small example. You could have an object named walrus and assign it the value of False , and then you could print it. In Python 3.8, you can combine those two statements and do a single statement using the walrus operator. So inside of print() , you could say walrus , the new object, and use the operator, the assignment expression := , and a space, and then say True . That’s going to do two things. Most notably, in reverse order, it returned the value True . And then it also assigned the value to walrus , and of course the type of 'bool' .

01:38 Keep in mind, the walrus operator doesn’t do anything that isn’t possible without it. It only makes certain constructs a bit more convenient, and can sometimes communicate the intent of your code more clearly.

01:48 Let me show you another example. It’s a pattern that shows some of the strengths of the walrus operator inside of while loops, where you need to initialize and update a variable. For example, create a new file, and name it write_something.py . Here’s write_something.py .

02:09 It starts with inputs , which will be a list. So create a list called inputs .

02:16 Into an object named current , use an input() statement. The input() statement is going to provide a prompt and read a string in from standard input. The prompt will be this, "Write something: " .

02:28 So when the user inputs that, that’ll go into current . So while current != "quit" — if the person has not typed quit yet— you’re going to take inputs and append the current value.

02:44 And then here, you’re asking to "Write something: " again.

02:50 Down here at my terminal, after saving—let’s see, make sure you’re saved. Okay. Now that’s saved.

03:00 So here, I could say, Hello , Welcome , and then finally quit , which then would quit it. So, this code isn’t ideal.

03:08 You’re repeating the input() statement twice, and somehow you need to add current to the list before asking the user for it. So a better solution is going to be to set up maybe an infinite while loop, and then use a break to stop the loop. How would that look?

03:22 You’re going to rearrange this a little bit. Move the while loop up, and say while True:

03:35 and here say if current == "quit": then break . Otherwise, go ahead and append it. So, a little different here, but this is a while loop that’s going to continue as long as it doesn’t get broken out of by someone typing quit . Okay.

03:53 Running it again. And there, you can see it breaking out. Nice. So, that code avoids the repetition and kind of keeps things in a more logical order, but there’s a way to simplify this to use that new assignment expression, the walrus operator. In that case, you’re going to modify this quite a bit.

04:17 Here you’re going to say while , current and then use that assignment operator ( := ) to create current .

04:23 But also, while doing that, check to see that it’s not equal to "quit" . So here, each time that assigns the value to current and it’s returned, so the value can be checked.

04:35 So while , current , assigning the value from the input() , and then if it’s not equal to "quit" , you’re going to append current . Make sure to save.

04:42 Run the code one more time.

04:47 And it works the same. This moves that test all the way back to the while line, where it should be. However, there’s a couple of things now happening all in one line, and that might take a little more effort to read what’s happening and to understand it properly.

05:00 There are a handful of other examples that you could look into to learn a little more about assignment expressions. I’ll include a link to PEP 572, and also a link to the Python docs for version 3.8, both of which include more code examples.

05:14 So you need to use your best judgment as to when this operator’s going to make your code more readable and more useful. In the next video, you’ll learn about the new feature of positional-only arguments.

rajeshboyalla on Dec. 4, 2019

Why do you use list() to initialize a list rather than using [] ?

Geir Arne Hjelle RP Team on Dec. 4, 2019

My two cents about list() vs [] (I wrote the original article this video series is based on):

I find spelling out list() to be more readable and easier to notice and interpret than []
[] is several times faster than list() , but we’re still talking nanoseconds. On my computer [] takes about 15ns, while list() runs in 60ns. Typically, lists are initiated once, so this does not cause any meaningful slowdown of code.

That said, if I’m initializing a list with existing elements, I usually use [elem1, elem2, ...] , since list(...) has different–and sometimes surprising–semantics.

Jason on April 3, 2020

Sorry for my ignorance, did the the standard assignment = operator work in this way? I don’t understand what has been gained from adding the := operator. If anything I think it will allow people to write more obfuscated code. But minds better than mine have been working on this, so I’ll have to take their word it is an improvement.

As for the discussion on whether [] is more readable than list(). I’d never seen list() before, so to me [] is better. I’ve only just come over from the dark 2.7 side so maybe it’s an old python programmer thing?

Oh I checked the operation on the assignment operator. I was obviously wrong. lol Still I think the existing operator could’ve been tweaked to do the same thing as := … I’m still on the fence about that one.

gedece on April 3, 2020

you are right in that the existing operator could have worked, but it can lead to something unexpected.

if you do something like

if (newvar = somevar): it gives a traceback, because you are supposed to use == for comparations.

So if you use the normal operator for this, then that expression is valid and you’ll be hard pressed to realize the mistake.

It then makes complete sense to use a different operator as that helps to clarify intent in code.

Jason on April 6, 2020

Yes, I’ve accidentaly done that in other languages before and it can be a difficult to “see” bug.

varelaautumn on Sept. 26, 2020

I watched this earlier today and now tonight I just can’t stop myself from throwing these walrus operators everywhere.

(I’m new and learning so these are just personal fooling around programs)

For example I have this function which cycles through a bunch of other very simple parsing functions that check if my input string is valid in the context of the game state. If the string doesn’t pass one of these parsers it returns a string with an error message such as “Input must be less than 5 characters”. And then the parse_input function returns that error string.

I mean it’s not a huge change, but it saves an extra call of the function, and I feel like it makes it much more readable.

I’m not sure if this other case might be considered abuse of the walrus operator, but I decided to use it twice in one line.

This function repeatedly asks for input. If the input does not pass the parser functions, then the error will be returned and printed out in the while loop. Otherwise the input was valid and it gets returned.

I’m able to pass my input into a function and check the result of that function all while retaining my input and the return of the function as their own variables to be used in the next line.

I think the walrus operator helped me put all the relevant details on the three lines. Like if you just read the first words of each line, it basically says “while error, print error, else return input_string.” I don’t see how I could have done that without this cool walrus operator so I’m really appreciative for this video you made! I’ve been converted to a strong believer in the walrus operator.

Geir Arne Hjelle RP Team on Sept. 26, 2020

@varelaautumn Nice examples, thanks for sharing!

I agree that the walrus operator will not revolutionize your code, but it can bring these sorts of small improvements that add up in the long run.

Become a Member to join the conversation.

Python Tutorial

File handling, python modules, python numpy, python pandas, python matplotlib, python scipy, machine learning, python mysql, python mongodb, python reference, module reference, python how to, python examples, python assignment operators.

Assignment operators are used to assign values to variables:

Operator	Example	Same As
=	x = 5	x = 5
+=	x += 3	x = x + 3
-=	x -= 3	x = x - 3
*=	x *= 3	x = x * 3
/=	x /= 3	x = x / 3
%=	x %= 3	x = x % 3
//=	x //= 3	x = x // 3
**=	x **= 3	x = x ** 3
&=	x &= 3	x = x & 3
\|=	x \|= 3	x = x \| 3
^=	x ^= 3	x = x ^ 3
>>=	x >>= 3	x = x >> 3
<<=	x <<= 3	x = x << 3

COLOR PICKER

Contact Sales

If you want to use W3Schools services as an educational institution, team or enterprise, send us an e-mail: [email protected]

Report Error

If you want to report an error, or if you want to make a suggestion, send us an e-mail: [email protected]

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

Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers
Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand
OverflowAI GenAI features for Teams
OverflowAPI Train & fine-tune LLMs
Labs The future of collective knowledge sharing
About the company Visit the blog

Collectives™ on Stack Overflow

Find centralized, trusted content and collaborate around the technologies you use most.

Q&A for work

Connect and share knowledge within a single location that is structured and easy to search.

Get early access and see previews of new features.

Python conditional assignment operator

Does a Python equivalent to the Ruby ||= operator ("set the variable if the variable is not set") exist?

Example in Ruby :

conditional-statements

1 It doesn't set it if it's not set - it sets it if its current value is false ( false or nil ). Granted, this distinction is more important in languages that e.g. treat 0 and "" as false, but still – user395760 Commented Jun 19, 2011 at 12:23
what is the use case for this ruby operator? – David Heffernan Commented Jun 19, 2011 at 12:54
1 The way to do it would be to use a try except NameError as indicated by phihag, butthis does not make myuch sense in Python as stated by everyone here. In Ruby it is more usefull due to the way people do pass arbitrary code blocks to be run inside a function. The target function than might need to set a variable that was not initialized in the foreign block it executed. There are no such cases in Python. – jsbueno Commented Jun 19, 2011 at 19:45

10 Answers 10

I'm surprised no one offered this answer. It's not as "built-in" as Ruby's ||= but it's basically equivalent and still a one-liner:

Of course, locals() is just a dictionary, so you can do:

I would use

Much shorter than all of your alternatives suggested here, and straight to the point. Read, "set x to 'default' if x is not set otherwise keep it as x." If you need None , 0 , False , or "" to be valid values however, you will need to change this behavior, for instance:

This sort of thing is also just begging to be turned into a function you can use everywhere easily:

at which point, you can use it as:

Finally, if you are really missing your Ruby infix notation, you could overload ||=| (or something similar) by following this guy's hack: http://code.activestate.com/recipes/384122-infix-operators/

7 Your first example doesn't work: >>> x = 'default' if not x else x Traceback (most recent call last): File "<stdin>", line 1, in <module> NameError: name 'x' is not defined – J Jones Commented Jan 30, 2015 at 23:06
10 This is an incorrect answer, and will fail if x does not exist. Since the question asks for a way to test for existance, this solution will not work. – Shayne Commented Mar 29, 2016 at 8:47
2 This answer solved the problem "conditional assignment". set a variable if it was not set. of course, everything on the right must be defined, else you will get an error (I just took it as a pseudo-code). x = "value1" if True else "value2" . in general. x = 'value1' if condition else 'value2' – Maubeh Commented Jan 6, 2019 at 14:54
This answer is both valid and very useful, and educational to boot. I would suggest a note be added that the variable must exist -within- the answer text, but fantastic otherwise. – Danin Commented Jun 19, 2022 at 0:00

No, the replacement is:

However, wanting to use this construct is a sign of overly complicated code flow. Usually, you'd do the following:

and never be unsure whether v is set or not. If it's one of many options that can either be set or not, use a dictionary and its get method which allows a default value.

2 No, you don't use except: . – user395760 Commented Jun 19, 2011 at 12:33
@delnan I didn't want to make specific assumptions about the nature of complicated() . Added it. – phihag Commented Jun 19, 2011 at 12:35
You sure? @emish offers a much simpler solution. – Donal Lafferty Commented Dec 17, 2012 at 16:39
That's a bad solution. Not only is it more complicated, but it's also much worse performance-wise. I would go as far as suggest to remove this solution from the question. – yuvalm2 Commented Mar 19, 2021 at 14:02
Using a try . . .except for control flow is bad practice. An exception should be used when something is wrong not when trying to assign a variable. – Paul D. Commented Nov 7, 2022 at 20:33

There is conditional assignment in Python 2.5 and later - the syntax is not very obvious hence it's easy to miss. Here's how you do it:

For further reference, check out the Python 2.5 docs .

This is not what is being asked for. – Shayne Commented Mar 29, 2016 at 8:49
So for the question being asked: variable = "bla bla" if not variable else variable – D. Ror. Commented Nov 7, 2023 at 14:08

(can't comment or I would just do that) I believe the suggestion to check locals above is not quite right. It should be:

to be correct in all contexts.

However, despite its upvotes, I don't think even that is a good analog to the Ruby operator. Since the Ruby operator allows more than just a simple name on the left:

The exception method is probably closest analog.

No, not knowing which variables are defined is a bug, not a feature in Python.

Use dicts instead:

I usually do this the following way:

I do this... just sharing in case it's useful for the OP or anyone else...

I think what you are looking for, if you are looking for something in a dictionary, is the setdefault method:

*** KeyError: 'q2' (Pdb)

The important thing to note in my example is that the setdefault method changes the dictionary if and only if the key that the setdefault method refers to is not present.

I am not sure I understand the question properly here ... Trying to "read" the value of an "undefined" variable name will trigger a NameError . (see here, that Python has "names" , not variables...).

As pointed out in the comments by delnan, the code below is not robust and will break in numerous situations ...

Nevertheless, if your variable "exists", but has some sort of dummy value, like None , the following would work :

(see this paragraph about Truth Values )

2 This breaks as soon as the value might be 0, "", an empty string, or anything else that's "falsy". Explicitly check whether it is None . – user395760 Commented Jun 19, 2011 at 12:46
Oh yes, you are right, I hadn't thought of that. Thanks for the hint ! I have actually never had the need to do this "or" thing, and I thought it was a valid answer to the question ... but the question itself does not seem to be relevqnt to Python anyway ... – tsimbalar Commented Jun 19, 2011 at 12:47

Your Answer

Reminder: Answers generated by artificial intelligence tools are not allowed on Stack Overflow. Learn more

Sign up or log in

Post as a guest.

Required, but never shown

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy .

Not the answer you're looking for? Browse other questions tagged python variables conditional-statements or ask your own question .

The Overflow Blog
The world’s largest open-source business has plans for enhancing LLMs
Looking under the hood at the tech stack that powers multimodal AI
Featured on Meta
Join Stack Overflow’s CEO and me for the first Stack IRL Community Event in...
User activation: Learnings and opportunities
What does a new user need in a homepage experience on Stack Overflow?
Announcing the new Staging Ground Reviewer Stats Widget

Hot Network Questions

How to rectify a mistake in DS 160
Class and macro with same name from different libraries
How to sum all the elements in a group in specific row with the package `listofitems`?
What does "either" refer to in "We don't have to run to phone booths anymore, either"?
What is an apologetic to confront Schellenberg's non-resistant divine hiddenness argument?
Need help in tikzpicture
Where is this citation in the Vana Parva of the Mahabharata?
Cartoon Network (Pakistan or India) show around 2007 or 2009 featuring a brother and sister who fight but later become allies
Can I use a Forward Transformer in a Flyback Converter Circuit?
How can I assign a heredoc to a variable in a way that's portable across Unix and Mac?
Movie from the fifties where aliens look human but wear sunglasses to hide that they have no irises (color) in their eyes - only whites!
how does the US justice system combat rights violations that happen when bad practices are given a new name to avoid old rulings?
〈ü〉 vs 〈ue〉 in German, particularly names
Can turbo trainers be easily damaged when instaling a cassette?
Was the total glaciation of the world, a.k.a. snowball earth, due to Bok space clouds?
meaning of a sentence from Agatha Christie (Murder of Roger Ackroyd)
What was the newest chess piece
Could a Gamma Ray Burst knock a Space Mirror out of orbit?
Why is Germany looking to import workers from Kenya, specifically?
Counting the number of meetings
Understanding “Your true airspeed will be the same, but your airspeed as opposed to the ground is much faster.” Bhutan Paro International Airport PBH
Help with understanding a rigid geometry proof
How to make a soundless world
Grothendieck topoi as a constructive property

COMMENTS

python
19 If one line code is definitely going to happen for you, Python 3.8 introduces assignment expressions affectionately known as "the walrus operator".
Python Conditional Assignment (in 3 Ways)
Conditionally assigning a value in Python is a basic programming task. In this tutorial, we will look at 3 different ways to assign values conditionally in Python.
Conditional Statements in Python
In this step-by-step tutorial you'll learn how to work with conditional ("if") statements in Python. Master if-statements and see how to write complex decision making code in your programs.
Python's Assignment Operator: Write Robust Assignments
In this tutorial, you'll learn how to use Python's assignment operators to write assignment statements that allow you to create, initialize, and update variables in your code.
How to Write the Python if Statement in one Line
Learn how to write a Python if statement in one line using either inline if/elif/else blocks or conditional expressions.
One line if statement in Python (ternary conditional operator)
Many programming languages have a ternary operator, which defines a conditional expression. The most common usage is to make a terse, simple dependent assignment statement. In other words, it offers a one-line code to evaluate the first expression if the condition is true; otherwise, it considers the second expression.
Python One Line Conditional Assignment
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.
Conditional Statements in Python
Conditional statements in Python are used to execute a specific block of code based on the truth value of a condition. The most common conditional statements in Python are if, elif, and else. These allow the program to react differently depending on whether a condition (or a series of conditions) is true or false.
Python if, if...else Statement (With Examples)
In computer programming, we use the if statement to run a block of code only when a specific condition is met. In this tutorial, we will learn about Python if...else statements with the help of examples.
Assign within if statement Python
9 For Python 3.8+, PEP 572 introduces Assignment Expressions This allows assigning to variables within an expression using the notation NAME := expr. It can be used within if statements, for example:
7. Simple statements
Assignment is defined recursively depending on the form of the target (list). When a target is part of a mutable object (an attribute reference, subscription or slicing), the mutable object must ultimately perform the assignment and decide about its validity, and may raise an exception if the assignment is unacceptable.
How To Use Assignment Expressions in Python
Introduction Python 3.8, released in October 2019, adds assignment expressions to Python via the := syntax. The assignment expression syntax is also sometimes called "the walrus operator" because := vaguely resembles a walrus with tusks.
How to use python if else in one line with examples
Learn how to use python if else statement in one line using ternary operator. You can also hack your way to use nested if else or if elif else in single line
The Walrus Operator: Python's Assignment Expressions
In this tutorial, you'll learn about assignment expressions and the walrus operator. The biggest change back in Python 3.8 was the inclusion of the := operator, which you can use to assign variables in the middle of expressions. You'll see several examples of how to take advantage of this feature.
Best way to do conditional assignment in python
Best way to do conditional assignment in python Asked 13 years, 1 month ago Modified 2 years, 7 months ago Viewed 24k times
Python If-Else Statement in One Line
Python supports if-else statements in one line - but should you use them and how? When should you opt for regular if statements? Read to find out.
If :: Introduction to Python
The structure of an if statement in Python is shown below: if < boolean expression >: < block of statements > In this structure, we have a <boolean expression> that is evaluated. After the Boolean expression is a colon :. Then, the <block of statements> is included below the if statement's first line, and it must be indented one level.
Assignment Expressions: The Walrus Operator
In this lesson, you'll learn about the biggest change in Python 3.8: the introduction of assignment expressions. Assignment expression are written with a new notation (:=).This operator is often called the walrus operator as it resembles the eyes and tusks of a walrus on its side.
Python Assignment Operators
Python Assignment Operators. Assignment operators are used to assign values to variables: Operator. Example. Same As. Try it. =. x = 5. x = 5.
python
python variable-assignment edited May 1 at 21:43 mkrieger1 22.1k 5 63 76 asked Sep 7, 2011 at 18:08 Spencer 22.2k 34 89 123 7
PEP 572
Unparenthesized assignment expressions are prohibited for the value of a keyword argument in a call. Example: foo(x = y := f(x)) # INVALID foo(x=(y := f(x))) # Valid, though probably confusing. This rule is included to disallow excessively confusing code, and because parsing keyword arguments is complex enough already.
Python conditional assignment operator
There is conditional assignment in Python 2.5 and later - the syntax is not very obvious hence it's easy to miss. Here's how you do it: x = true_value if condition else false_value

Python Conditional Assignment

1. Using Ternary Operator

2. Using if-else statement

3. Using Logical Short Circuit Evaluation

How to Write the Python if Statement in one Line

How the if Statement Works in Python

How to Write a Python if in one Line

Writing a Python if Statement With Multiple Actions in one Line

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

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

Go Even Further With Python!

You may also like

One line if statement in Python (ternary conditional operator)

Basic if Statement (Ternary Operator)

Alternatives To The Ternary Operator

Indentations And Blocks

The else And elif Clauses

Use of else clause:

Use of elif clause :

About The Author

Anton Caceres

Signup for new content

Latest Articles

Python One Line Conditional Assignment

Method 1: Ternary Operator

Method 2: Single-Line If Statement

Method 3: Ternary Tuple Syntax Hack

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

Conditional Statements in Python

1. If Conditional Statement in Python

Syntax of Ternary Expression

Conditional Statements in Python – FAQs

What is a Conditional Expression in Python?

What are Decision-Making Statements in Python?

What are Conditional Selection Statements in Python?

What are the Conditional Loops in Python?

Please Login to comment...

Improve your Coding Skills with Practice

What kind of Experience do you want to share?

Popular Tutorials

Python Fundamentals

Python Flow Control

Python Data types

Python Files

Python Object & Class

Python Advanced Topics

Python Date and Time

Additional Topic

Python Tutorials

Indentation in Python

More on Python if…else Statement

Table of Contents

Video: Python if...else Statement

Related Tutorials

7. Simple statements ¶

7.1. Expression statements ¶

7.2. Assignment statements ¶

7.2.1. Augmented assignment statements ¶

7.2.2. Annotated assignment statements ¶

7.3. The assert statement ¶

7.4. The pass statement ¶

7.5. The del statement ¶

7.6. The return statement ¶

7.7. The yield statement ¶

7.8. The raise statement ¶

7.9. The break statement ¶

7.10. The continue statement ¶

7.11. The import statement ¶

7.11.1. Future statements ¶

7.12. The global statement ¶

7.13. The nonlocal statement ¶

7.14. The type statement ¶

Table of Contents

Previous topic

How to use python if else in one line with examples

Python if else in one line

Python Script Example

Python if..elif..else in one line

Python Script Example-1

Python script Example-2