python assignment operator expression

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

Assignment Operators in Python

The Python Operators are used to perform operations on values and variables. These are the special symbols that carry out arithmetic, logical, and bitwise computations. The value the operator operates on is known as the Operand. Here, we will cover Different Assignment operators in Python .


=	Assign the value of the right side of the expression to the left side operand	c = a + b
+=	Add right side operand with left side operand and then assign the result to left operand	a += b
-=	Subtract right side operand from left side operand and then assign the result to left operand	a -= b
*=	Multiply right operand with left operand and then assign the result to the left operand	a *= b
/=	Divide left operand with right operand and then assign the result to the left operand	a /= b
%=	Divides the left operand with the right operand and then assign the remainder to the left operand	a %= b
//=	Divide left operand with right operand and then assign the value(floor) to left operand	a //= b
**=	Calculate exponent(raise power) value using operands and then assign the result to left operand	a **= b
&=	Performs Bitwise AND on operands and assign the result to left operand	a &= b
\|=	Performs Bitwise OR on operands and assign the value to left operand	a \|= b
^=	Performs Bitwise XOR on operands and assign the value to left operand	a ^= b
>>=	Performs Bitwise right shift on operands and assign the result to left operand	a >>= b
<<=	Performs Bitwise left shift on operands and assign the result to left operand	a <<= b
:=	Assign a value to a variable within an expression	a := exp

Here are the Assignment Operators in Python with examples.

Assignment Operator

Assignment Operators are used to assign values to variables. This operator is used to assign the value of the right side of the expression to the left side operand.

Addition Assignment Operator

The Addition Assignment Operator is used to add the right-hand side operand with the left-hand side operand and then assigning the result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the addition assignment operator which will first perform the addition operation and then assign the result to the variable on the left-hand side.

S ubtraction Assignment Operator

The Subtraction Assignment Operator is used to subtract the right-hand side operand from the left-hand side operand and then assigning the result to the left-hand side operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the subtraction assignment operator which will first perform the subtraction operation and then assign the result to the variable on the left-hand side.

M ultiplication Assignment Operator

The Multiplication Assignment Operator is used to multiply the right-hand side operand with the left-hand side operand and then assigning the result to the left-hand side operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the multiplication assignment operator which will first perform the multiplication operation and then assign the result to the variable on the left-hand side.

D ivision Assignment Operator

The Division Assignment Operator is used to divide the left-hand side operand with the right-hand side operand and then assigning the result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the division assignment operator which will first perform the division operation and then assign the result to the variable on the left-hand side.

M odulus Assignment Operator

The Modulus Assignment Operator is used to take the modulus, that is, it first divides the operands and then takes the remainder and assigns it to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the modulus assignment operator which will first perform the modulus operation and then assign the result to the variable on the left-hand side.

F loor Division Assignment Operator

The Floor Division Assignment Operator is used to divide the left operand with the right operand and then assigs the result(floor value) to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the floor division assignment operator which will first perform the floor division operation and then assign the result to the variable on the left-hand side.

Exponentiation Assignment Operator

The Exponentiation Assignment Operator is used to calculate the exponent(raise power) value using operands and then assigning the result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the exponentiation assignment operator which will first perform exponent operation and then assign the result to the variable on the left-hand side.

Bitwise AND Assignment Operator

The Bitwise AND Assignment Operator is used to perform Bitwise AND operation on both operands and then assigning the result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the bitwise AND assignment operator which will first perform Bitwise AND operation and then assign the result to the variable on the left-hand side.

Bitwise OR Assignment Operator

The Bitwise OR Assignment Operator is used to perform Bitwise OR operation on the operands and then assigning result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the bitwise OR assignment operator which will first perform bitwise OR operation and then assign the result to the variable on the left-hand side.

Bitwise XOR Assignment Operator

The Bitwise XOR Assignment Operator is used to perform Bitwise XOR operation on the operands and then assigning result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the bitwise XOR assignment operator which will first perform bitwise XOR operation and then assign the result to the variable on the left-hand side.

Bitwise Right Shift Assignment Operator

The Bitwise Right Shift Assignment Operator is used to perform Bitwise Right Shift Operation on the operands and then assign result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the bitwise right shift assignment operator which will first perform bitwise right shift operation and then assign the result to the variable on the left-hand side.

Bitwise Left Shift Assignment Operator

The Bitwise Left Shift Assignment Operator is used to perform Bitwise Left Shift Opertator on the operands and then assign result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the bitwise left shift assignment operator which will first perform bitwise left shift operation and then assign the result to the variable on the left-hand side.

Walrus Operator

The Walrus Operator in Python is a new assignment operator which is introduced in Python version 3.8 and higher. This operator is used to assign a value to a variable within an expression.

Example: In this code, we have a Python list of integers. We have used Python Walrus assignment operator within the Python while loop . The operator will solve the expression on the right-hand side and assign the value to the left-hand side operand ‘x’ and then execute the remaining code.

Assignment Operators in Python – FAQs

What are assignment operators in python.

Assignment operators in Python are used to assign values to variables. These operators can also perform additional operations during the assignment. The basic assignment operator is = , which simply assigns the value of the right-hand operand to the left-hand operand. Other common assignment operators include += , -= , *= , /= , %= , and more, which perform an operation on the variable and then assign the result back to the variable.

What is the := Operator in Python?

The := operator, introduced in Python 3.8, is known as the “walrus operator”. It is an assignment expression, which means that it assigns values to variables as part of a larger expression. Its main benefit is that it allows you to assign values to variables within expressions, including within conditions of loops and if statements, thereby reducing the need for additional lines of code. Here’s an example: # Example of using the walrus operator in a while loop while (n := int(input("Enter a number (0 to stop): "))) != 0: print(f"You entered: {n}") This loop continues to prompt the user for input and immediately uses that input in both the condition check and the loop body.

What is the Assignment Operator in Structure?

In programming languages that use structures (like C or C++), the assignment operator = is used to copy values from one structure variable to another. Each member of the structure is copied from the source structure to the destination structure. Python, however, does not have a built-in concept of ‘structures’ as in C or C++; instead, similar functionality is achieved through classes or dictionaries.

What is the Assignment Operator in Python Dictionary?

In Python dictionaries, the assignment operator = is used to assign a new key-value pair to the dictionary or update the value of an existing key. Here’s how you might use it: my_dict = {} # Create an empty dictionary my_dict['key1'] = 'value1' # Assign a new key-value pair my_dict['key1'] = 'updated value' # Update the value of an existing key print(my_dict) # Output: {'key1': 'updated value'}

What is += and -= in Python?

The += and -= operators in Python are compound assignment operators. += adds the right-hand operand to the left-hand operand and assigns the result to the left-hand operand. Conversely, -= subtracts the right-hand operand from the left-hand operand and assigns the result to the left-hand operand. Here are examples of both: # Example of using += a = 5 a += 3 # Equivalent to a = a + 3 print(a) # Output: 8 # Example of using -= b = 10 b -= 4 # Equivalent to b = b - 4 print(b) # Output: 6 These operators make code more concise and are commonly used in loops and iterative data processing.

Please Login to comment...

How to Underline in Discord
How to Block Someone on Discord
How to Report Someone on Discord
How to add Bots to Discord Servers
GeeksforGeeks Practice - Leading Online Coding Platform

Improve your Coding Skills with Practice

What kind of Experience do you want to share?

Assignment Operators

Add and assign, subtract and assign, multiply and assign, divide and assign, floor divide and assign, exponent and assign, modulo and assign.


			to
			to and assigns the result to
			from and assigns the result to
			by and assigns the result to
			with and assigns the result to ; the result is always a float
			with and assigns the result to ; the result will be dependent on the type of values used
			to the power of and assigns the result to
			is divided by and assigns the result to

For demonstration purposes, let’s use a single variable, num . Initially, we set num to 6. We can apply all of these operators to num and update it accordingly.

Assigning the value of 6 to num results in num being 6.

Expression: num = 6

Adding 3 to num and assigning the result back to num would result in 9.

Expression: num += 3

Subtracting 3 from num and assigning the result back to num would result in 6.

Expression: num -= 3

Multiplying num by 3 and assigning the result back to num would result in 18.

Expression: num *= 3

Dividing num by 3 and assigning the result back to num would result in 6.0 (always a float).

Expression: num /= 3

Performing floor division on num by 3 and assigning the result back to num would result in 2.

Expression: num //= 3

Raising num to the power of 3 and assigning the result back to num would result in 216.

Expression: num **= 3

Calculating the remainder when num is divided by 3 and assigning the result back to num would result in 2.

Expression: num %= 3

We can effectively put this into Python code, and you can experiment with the code yourself! Click the “Run” button to see the output.

The above code is useful when we want to update the same number. We can also use two different numbers and use the assignment operators to apply them on two different values.

Python Basics
Python - Home
Python - Overview
Python - History
Python - Features
Python vs C++
Python - Hello World Program
Python - Application Areas
Python - Interpreter
Python - Environment Setup
Python - Virtual Environment
Python - Basic Syntax
Python - Variables
Python - Data Types
Python - Type Casting
Python - Unicode System
Python - Literals
Python - Operators
Python - Arithmetic Operators
Python - Comparison Operators

Python - Assignment Operators

Python - Logical Operators
Python - Bitwise Operators
Python - Membership Operators
Python - Identity Operators
Python - Operator Precedence
Python - Comments
Python - User Input
Python - Numbers
Python - Booleans
Python Control Statements
Python - Control Flow
Python - Decision Making
Python - If Statement
Python - If else
Python - Nested If
Python - Match-Case Statement
Python - Loops
Python - for Loops
Python - for-else Loops
Python - While Loops
Python - break Statement
Python - continue Statement
Python - pass Statement
Python - Nested Loops
Python Functions & Modules
Python - Functions
Python - Default Arguments
Python - Keyword Arguments
Python - Keyword-Only Arguments
Python - Positional Arguments
Python - Positional-Only Arguments
Python - Arbitrary Arguments
Python - Variables Scope
Python - Function Annotations
Python - Modules
Python - Built in Functions
Python Strings
Python - Strings
Python - Slicing Strings
Python - Modify Strings
Python - String Concatenation
Python - String Formatting
Python - Escape Characters
Python - String Methods
Python - String Exercises
Python Lists
Python - Lists
Python - Access List Items
Python - Change List Items
Python - Add List Items
Python - Remove List Items
Python - Loop Lists
Python - List Comprehension
Python - Sort Lists
Python - Copy Lists
Python - Join Lists
Python - List Methods
Python - List Exercises
Python Tuples
Python - Tuples
Python - Access Tuple Items
Python - Update Tuples
Python - Unpack Tuples
Python - Loop Tuples
Python - Join Tuples
Python - Tuple Methods
Python - Tuple Exercises
Python Sets
Python - Sets
Python - Access Set Items
Python - Add Set Items
Python - Remove Set Items
Python - Loop Sets
Python - Join Sets
Python - Copy Sets
Python - Set Operators
Python - Set Methods
Python - Set Exercises
Python Dictionaries
Python - Dictionaries
Python - Access Dictionary Items
Python - Change Dictionary Items
Python - Add Dictionary Items
Python - Remove Dictionary Items
Python - Dictionary View Objects
Python - Loop Dictionaries
Python - Copy Dictionaries
Python - Nested Dictionaries
Python - Dictionary Methods
Python - Dictionary Exercises
Python Arrays
Python - Arrays
Python - Access Array Items
Python - Add Array Items
Python - Remove Array Items
Python - Loop Arrays
Python - Copy Arrays
Python - Reverse Arrays
Python - Sort Arrays
Python - Join Arrays
Python - Array Methods
Python - Array Exercises
Python File Handling
Python - File Handling
Python - Write to File
Python - Read Files
Python - Renaming and Deleting Files
Python - Directories
Python - File Methods
Python - OS File/Directory Methods
Python - OS Path Methods
Object Oriented Programming
Python - OOPs Concepts
Python - Classes & Objects
Python - Class Attributes
Python - Class Methods
Python - Static Methods
Python - Constructors
Python - Access Modifiers
Python - Inheritance
Python - Polymorphism
Python - Method Overriding
Python - Method Overloading
Python - Dynamic Binding
Python - Dynamic Typing
Python - Abstraction
Python - Encapsulation
Python - Interfaces
Python - Packages
Python - Inner Classes
Python - Anonymous Class and Objects
Python - Singleton Class
Python - Wrapper Classes
Python - Enums
Python - Reflection
Python Errors & Exceptions
Python - Syntax Errors
Python - Exceptions
Python - try-except Block
Python - try-finally Block
Python - Raising Exceptions
Python - Exception Chaining
Python - Nested try Block
Python - User-defined Exception
Python - Logging
Python - Assertions
Python - Built-in Exceptions
Python Multithreading
Python - Multithreading
Python - Thread Life Cycle
Python - Creating a Thread
Python - Starting a Thread
Python - Joining Threads
Python - Naming Thread
Python - Thread Scheduling
Python - Thread Pools
Python - Main Thread
Python - Thread Priority
Python - Daemon Threads
Python - Synchronizing Threads
Python Synchronization
Python - Inter-thread Communication
Python - Thread Deadlock
Python - Interrupting a Thread
Python Networking
Python - Networking
Python - Socket Programming
Python - URL Processing
Python - Generics
Python Libraries
NumPy Tutorial
Pandas Tutorial
SciPy Tutorial
Matplotlib Tutorial
Django Tutorial
OpenCV Tutorial
Python Miscellenous
Python - Date & Time
Python - Maths
Python - Iterators
Python - Generators
Python - Closures
Python - Decorators
Python - Recursion
Python - Reg Expressions
Python - PIP
Python - Database Access
Python - Weak References
Python - Serialization
Python - Templating
Python - Output Formatting
Python - Performance Measurement
Python - Data Compression
Python - CGI Programming
Python - XML Processing
Python - GUI Programming
Python - Command-Line Arguments
Python - Docstrings
Python - JSON
Python - Sending Email
Python - Further Extensions
Python - Tools/Utilities
Python - GUIs
Python Advanced Concepts
Python - Abstract Base Classes
Python - Custom Exceptions
Python - Higher Order Functions
Python - Object Internals
Python - Memory Management
Python - Metaclasses
Python - Metaprogramming with Metaclasses
Python - Mocking and Stubbing
Python - Monkey Patching
Python - Signal Handling
Python - Type Hints
Python - Automation Tutorial
Python - Humanize Package
Python - Context Managers
Python - Coroutines
Python - Descriptors
Python - Diagnosing and Fixing Memory Leaks
Python - Immutable Data Structures
Python Useful Resources
Python - Questions & Answers
Python - Online Quiz
Python - Quick Guide
Python - Reference
Python - Projects
Python - Useful Resources
Python - Discussion
Python Compiler
NumPy Compiler
Matplotlib Compiler
SciPy Compiler
Python - Programming Examples
Selected Reading
UPSC IAS Exams Notes
Developer's Best Practices
Questions and Answers
Effective Resume Writing
HR Interview Questions
Computer Glossary

Python Assignment Operator

The = (equal to) symbol is defined as assignment operator in Python. The value of Python expression on its right is assigned to a single variable on its left. The = symbol as in programming in general (and Python in particular) should not be confused with its usage in Mathematics, where it states that the expressions on the either side of the symbol are equal.

Example of Assignment Operator in Python

Consider following Python statements −

At the first instance, at least for somebody new to programming but who knows maths, the statement "a=a+b" looks strange. How could a be equal to "a+b"? However, it needs to be reemphasized that the = symbol is an assignment operator here and not used to show the equality of LHS and RHS.

Because it is an assignment, the expression on right evaluates to 15, the value is assigned to a.

In the statement "a+=b", the two operators "+" and "=" can be combined in a "+=" operator. It is called as add and assign operator. In a single statement, it performs addition of two operands "a" and "b", and result is assigned to operand on left, i.e., "a".

Augmented Assignment Operators in Python

In addition to the simple assignment operator, Python provides few more assignment operators for advanced use. They are called cumulative or augmented assignment operators. In this chapter, we shall learn to use augmented assignment operators defined in Python.

Python has the augmented assignment operators for all arithmetic and comparison operators.

Python augmented assignment operators combines addition and assignment in one statement. Since Python supports mixed arithmetic, the two operands may be of different types. However, the type of left operand changes to the operand of on right, if it is wider.

The += operator is an augmented operator. It is also called cumulative addition operator, as it adds "b" in "a" and assigns the result back to a variable.

The following are the augmented assignment operators in Python:

Augmented Addition Operator
Augmented Subtraction Operator
Augmented Multiplication Operator
Augmented Division Operator
Augmented Modulus Operator
Augmented Exponent Operator
Augmented Floor division Operator

Augmented Addition Operator (+=)

Following examples will help in understanding how the "+=" operator works −

It will produce the following output −

Augmented Subtraction Operator (-=)

Use -= symbol to perform subtract and assign operations in a single statement. The "a-=b" statement performs "a=a-b" assignment. Operands may be of any number type. Python performs implicit type casting on the object which is narrower in size.

Augmented Multiplication Operator (*=)

The "*=" operator works on similar principle. "a*=b" performs multiply and assign operations, and is equivalent to "a=a*b". In case of augmented multiplication of two complex numbers, the rule of multiplication as discussed in the previous chapter is applicable.

Augmented Division Operator (/=)

The combination symbol "/=" acts as divide and assignment operator, hence "a/=b" is equivalent to "a=a/b". The division operation of int or float operands is float. Division of two complex numbers returns a complex number. Given below are examples of augmented division operator.

Augmented Modulus Operator (%=)

To perform modulus and assignment operation in a single statement, use the %= operator. Like the mod operator, its augmented version also is not supported for complex number.

Augmented Exponent Operator (**=)

The "**=" operator results in computation of "a" raised to "b", and assigning the value back to "a". Given below are some examples −

Augmented Floor division Operator (//=)

For performing floor division and assignment in a single statement, use the "//=" operator. "a//=b" is equivalent to "a=a//b". This operator cannot be used with complex numbers.

Logical Python

Effective Python Tutorials

Python Assignment Operators

Introduction to python assignment operators.

Assignment Operators are used for assigning values to the variables. We can also say that assignment operators are used to assign values to the left-hand side operand. For example, in the below table, we are assigning a value to variable ‘a’, which is the left-side operand.

Operator	Example	Equivalent
=	a = 2	a = 2
+=	a += 2	a = a + 2
-=	a -= 2	a = a – 2
*=	a *= 2	a = a * 2
/=	a /= 2	a = a / 2
%=	a %= 2	a = a % 2
//=	a //= 2	a = a // 2
**=	a **= 2	a = a ** 2
&=	a &= 2	a = a & 2
\|=	a \|= 2	a = a \| 2
^=	a ^= 2	a = a ^ 2
>>=	a >>= 2	a = a >> 2
<<=	a <<= 3	a = a << 2

Assignment Operators

Assignment operator.

Equal to sign ‘=’ is used as an assignment operator. It assigns values of the right-hand side expression to the variable or operand present on the left-hand side.

Assigns value 3 to variable ‘a’.

Addition and Assignment Operator

The addition and assignment operator adds left-side and right-side operands and then the sum is assigned to the left-hand side operand.

Below code is equivalent to: a = a + 2.

Subtraction and Assignment Operator

The subtraction and assignment operator subtracts the right-side operand from the left-side operand, and then the result is assigned to the left-hand side operand.

Below code is equivalent to: a = a – 2.

Multiplication and Assignment Operator

The multiplication and assignment operator multiplies the right-side operand with the left-side operand, and then the result is assigned to the left-hand side operand.

Below code is equivalent to: a = a * 2.

Division and Assignment Operator

The division and assignment operator divides the left-side operand with the right-side operand, and then the result is assigned to the left-hand side operand.

Below code is equivalent to: a = a / 2.

Modulus and Assignment Operator

The modulus and assignment operator divides the left-side operand with the right-side operand, and then the remainder is assigned to the left-hand side operand.

Below code is equivalent to: a = a % 3.

Floor Division and Assignment Operator

The floor division and assignment operator divides the left side operand with the right side operand. The result is rounded down to the closest integer value(i.e. floor value) and is assigned to the left-hand side operand.

Below code is equivalent to: a = a // 3.

Exponential and Assignment Operator

The exponential and assignment operator raises the left-side operand to the power of the right-side operand, and the result is assigned to the left-hand side operand.

Below code is equivalent to: a = a ** 3.

Bitwise AND and Assignment Operator

Bitwise AND and assignment operator performs bitwise AND operation on both the operands and assign the result to the left-hand side operand.

Below code is equivalent to: a = a & 3.

Illustration:

	Numeric Value	Binary Value
	2	010
	3	011

Bitwise OR and Assignment Operator

Bitwise OR and assignment operator performs bitwise OR operation on both the operands and assign the result to the left-hand side operand.

Below code is equivalent to: a = a | 3.

Bitwise XOR and Assignment Operator

Bitwise XOR and assignment operator performs bitwise XOR operation on both the operands and assign the result to the left-hand side operand.

Below code is equivalent to: a = a ^ 3.

Bitwise Right Shift and Assignment Operator

Bitwise right shift and assignment operator right shifts the left operand by the right operand positions and assigns the result to the left-hand side operand.

Below code is equivalent to: a = a >> 1.

Numeric Input	Binary Value	Right shift by 1	Numeric Output
2	0010	0001	1
4	0100	0010	2

Bitwise Left Shift and Assignment Operator

Bitwise left shift and assignment operator left shifts the left operand by the right operand positions and assigns the result to the left-hand side operand.

Below code is equivalent to: a = a << 1.

Numeric Input	Bitwise Value	Left shift by 1	Numeric Output
2	0010	0100	4
4	0100	1000	8

References:

Different Assignment operators in Python
Assignment Operator in Python
Assignment Expressions

Python Operators: Arithmetic, Assignment, Comparison, Logical, Identity, Membership, Bitwise

Operators are special symbols that perform some operation on operands and returns the result. For example, 5 + 6 is an expression where + is an operator that performs arithmetic add operation on numeric left operand 5 and the right side operand 6 and returns a sum of two operands as a result.

Python includes the operator module that includes underlying methods for each operator. For example, the + operator calls the operator.add(a,b) method.

Above, expression 5 + 6 is equivalent to the expression operator.add(5, 6) and operator.__add__(5, 6) . Many function names are those used for special methods, without the double underscores (dunder methods). For backward compatibility, many of these have functions with the double underscores kept.

Python includes the following categories of operators:

Arithmetic Operators

Assignment operators, comparison operators, logical operators, identity operators, membership test operators, bitwise operators.

Arithmetic operators perform the common mathematical operation on the numeric operands.

The arithmetic operators return the type of result depends on the type of operands, as below.

If either operand is a complex number, the result is converted to complex;
If either operand is a floating point number, the result is converted to floating point;
If both operands are integers, then the result is an integer and no conversion is needed.

The following table lists all the arithmetic operators in Python:

Operation	Operator	Function
Sum of two operands	+	operator.add(a,b)
Left operand minus right operand	-	operator.sub(a,b)
	*	operator.mul(a,b)
Left operand raised to the power of right	**	operator.pow(a,b)
	/	operator.truediv(a,b)
equivilant to	//	operator.floordiv(a,b)
Reminder of	%	operator.mod(a, b)

The assignment operators are used to assign values to variables. The following table lists all the arithmetic operators in Python:

Operator	Function	Example in Python Shell
=
+=	operator.iadd(a,b)
-=	operator.isub(a,b)
*=	operator.imul(a,b)
/=	operator.itruediv(a,b)
//=	operator.ifloordiv(a,b)
%=	operator.imod(a, b)
&=	operator.iand(a, b)
\|=	operator.ior(a, b)
^=	operator.ixor(a, b)
>>=	operator.irshift(a, b)
<<=	operator.ilshift(a, b)

The comparison operators compare two operands and return a boolean either True or False. The following table lists comparison operators in Python.

Operator	Function	Description
>	operator.gt(a,b)	True if the left operand is higher than the right one
<	operator.lt(a,b)	True if the left operand is lower than right one
==	operator.eq(a,b)	True if the operands are equal
!=	operator.ne(a,b)	True if the operands are not equal
>=	operator.ge(a,b)	True if the left operand is higher than or equal to the right one
<=	operator.le(a,b)	True if the left operand is lower than or equal to the right one

The logical operators are used to combine two boolean expressions. The logical operations are generally applicable to all objects, and support truth tests, identity tests, and boolean operations.

Operator	Description	Example
and	True if both are true
or	True if at least one is true
not	Returns True if an expression evalutes to false and vice-versa

The identity operators check whether the two objects have the same id value e.i. both the objects point to the same memory location.

Operator	Function	Description	Example in Python Shell
is	operator.is_(a,b)	True if both are true
is not	operator.is_not(a,b)	True if at least one is true

The membership test operators in and not in test whether the sequence has a given item or not. For the string and bytes types, x in y is True if and only if x is a substring of y .

Operator	Function	Description	Example in Python Shell
in	operator.contains(a,b)	Returns True if the sequence contains the specified item else returns False.
not in	not operator.contains(a,b)	Returns True if the sequence does not contains the specified item, else returns False.

Bitwise operators perform operations on binary operands.

Operator	Function	Description
&	operator.and_(a,b)	Sets each bit to 1 if both bits are 1.
\|	operator.or_(a,b)	Sets each bit to 1 if one of two bits is 1.
^	operator.xor(a,b)	Sets each bit to 1 if only one of two bits is 1.
~	operator.invert(a)	Inverts all the bits.
<<	operator.lshift(a,b)	Shift left by pushing zeros in from the right and let the leftmost bits fall off.
>>	operator.rshift(a,b)	Shift right by pushing copies of the leftmost bit in from the left, and let the rightmost bits fall off.

Compare strings in Python
Convert file data to list
Convert User Input to a Number
Convert String to Datetime in Python
How to call external commands in Python?
How to count the occurrences of a list item?
How to flatten list in Python?
How to merge dictionaries in Python?
How to pass value by reference in Python?
Remove duplicate items from list in Python
More Python articles

We are a team of passionate developers, educators, and technology enthusiasts who, with their combined expertise and experience, create in -depth, comprehensive, and easy to understand tutorials.We focus on a blend of theoretical explanations and practical examples to encourages hands - on learning. Visit About Us page for more information.

Python Questions & Answers
Python Skill Test
Python Latest Articles

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 3 Tutorial

Python Strings
Python any()

Operators are special symbols that perform operations on variables and values. For example,

Here, + is an operator that adds two numbers: 5 and 6 .

Types of Python Operators

Here's a list of different types of Python operators that we will learn in this tutorial.

Arithmetic Operators
Assignment Operators
Comparison Operators
Logical Operators
Bitwise Operators
Special Operators

1. Python Arithmetic Operators

Arithmetic operators are used to perform mathematical operations like addition, subtraction, multiplication, etc. For example,

Here, - is an arithmetic operator that subtracts two values or variables.

Operator	Operation	Example
	Addition
	Subtraction
	Multiplication
	Division
	Floor Division
	Modulo
	Power

Example 1: Arithmetic Operators in Python

In the above example, we have used multiple arithmetic operators,

+ to add a and b
- to subtract b from a
* to multiply a and b
/ to divide a by b
// to floor divide a by b
% to get the remainder
** to get a to the power b

2. Python Assignment Operators

Assignment operators are used to assign values to variables. For example,

Here, = is an assignment operator that assigns 5 to x .

Here's a list of different assignment operators available in Python.

Operator	Name	Example
	Assignment Operator
	Addition Assignment
	Subtraction Assignment
	Multiplication Assignment
	Division Assignment
	Remainder Assignment
	Exponent Assignment

Example 2: Assignment Operators

Here, we have used the += operator to assign the sum of a and b to a .

Similarly, we can use any other assignment operators as per our needs.

3. Python Comparison Operators

Comparison operators compare two values/variables and return a boolean result: True or False . For example,

Here, the > comparison operator is used to compare whether a is greater than b or not.

Operator	Meaning	Example
	Is Equal To	gives us
	Not Equal To	gives us
	Greater Than	gives us
	Less Than	gives us
	Greater Than or Equal To	give us
	Less Than or Equal To	gives us

Example 3: Comparison Operators

Note: Comparison operators are used in decision-making and loops . We'll discuss more of the comparison operator and decision-making in later tutorials.

4. Python Logical Operators

Logical operators are used to check whether an expression is True or False . They are used in decision-making. For example,

Here, and is the logical operator AND . Since both a > 2 and b >= 6 are True , the result is True .

Operator	Example	Meaning
	a b	: only if both the operands are
	a b	: if at least one of the operands is
	a	: if the operand is and vice-versa.

Example 4: Logical Operators

Note : Here is the truth table for these logical operators.

5. Python Bitwise operators

Bitwise operators act on operands as if they were strings of binary digits. They operate bit by bit, hence the name.

For example, 2 is 10 in binary, and 7 is 111 .

In the table below: Let x = 10 ( 0000 1010 in binary) and y = 4 ( 0000 0100 in binary)

Operator	Meaning	Example
	Bitwise AND	x & y = 0 ( )
	Bitwise OR	x \| y = 14 ( )
	Bitwise NOT	~x = -11 ( )
	Bitwise XOR	x ^ y = 14 ( )
	Bitwise right shift	x >> 2 = 2 ( )
	Bitwise left shift	x 0010 1000)

6. Python Special operators

Python language offers some special types of operators like the identity operator and the membership operator. They are described below with examples.

Identity operators

In Python, is and is not are used to check if two values are located at the same memory location.

It's important to note that having two variables with equal values doesn't necessarily mean they are identical.

Operator	Meaning	Example
	if the operands are identical (refer to the same object)
	if the operands are not identical (do not refer to the same object)

Example 4: Identity operators in Python

Here, we see that x1 and y1 are integers of the same values, so they are equal as well as identical. The same is the case with x2 and y2 (strings).

But x3 and y3 are lists. They are equal but not identical. It is because the interpreter locates them separately in memory, although they are equal.

Membership operators

In Python, in and not in are the membership operators. They are used to test whether a value or variable is found in a sequence ( string , list , tuple , set and dictionary ).

In a dictionary, we can only test for the presence of a key, not the value.

Operator	Meaning	Example
	if value/variable is in the sequence
	if value/variable is in the sequence

Example 5: Membership operators in Python

Here, 'H' is in message , but 'hello' is not present in message (remember, Python is case-sensitive).

Similarly, 1 is key, and 'a' is the value in dictionary dict1 . Hence, 'a' in y returns False .

Precedence and Associativity of operators in Python

Introduction
Python Arithmetic Operators
Python Assignment Operators
Python Comparison Operators
Python Logical Operators
Python Bitwise operators
Python Special operators

Before we wrap up, let’s put your knowledge of Python operators to the test! Can you solve the following challenge?

Write a function to split the restaurant bill among friends.

Take the subtotal of the bill and the number of friends as inputs.
Calculate the total bill by adding 20% tax to the subtotal and then divide it by the number of friends.
Return the amount each friend has to pay, rounded off to two decimal places.

Video: Operators in Python

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

Python Arithmetic Operators

Arithmetic operators are used with numeric values to perform common mathematical operations:

Operator	Name	Example
+	Addition	x + y
-	Subtraction	x - y
*	Multiplication	x * y
/	Division	x / y
%	Modulus	x % y
**	Exponentiation	x ** y
//	Floor division	x // y

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
:=	print(x := 3)	x = 3 print(x)

Python Comparison Operators

Comparison operators are used to compare two values:

Operator	Name	Example
==	Equal	x == y
!=	Not equal	x != y
>	Greater than	x > y
<	Less than	x < y
>=	Greater than or equal to	x >= y
<=	Less than or equal to	x <= y

Python Logical Operators

Logical operators are used to combine conditional statements:

Operator	Description	Example
and	Returns True if both statements are true	x < 5 and x < 10
or	Returns True if one of the statements is true	x < 5 or x < 4
not	Reverse the result, returns False if the result is true	not(x < 5 and x < 10)

Python Identity Operators

Identity operators are used to compare the objects, not if they are equal, but if they are actually the same object, with the same memory location:

Operator	Description	Example	Try it
is	Returns True if both variables are the same object	x is y
is not	Returns True if both variables are not the same object	x is not y

Python Membership Operators

Membership operators are used to test if a sequence is presented in an object:

Operator	Description	Example	Try it
in	Returns True if a sequence with the specified value is present in the object	x in y
not in	Returns True if a sequence with the specified value is not present in the object	x not in y

Python Bitwise Operators

Bitwise operators are used to compare (binary) numbers:

Operator	Name	Description	Example
&	AND	Sets each bit to 1 if both bits are 1	x & y
\|	OR	Sets each bit to 1 if one of two bits is 1	x \| y
^	XOR	Sets each bit to 1 if only one of two bits is 1	x ^ y
~	NOT	Inverts all the bits	~x
<<	Zero fill left shift	Shift left by pushing zeros in from the right and let the leftmost bits fall off	x << 2
>>	Signed right shift	Shift right by pushing copies of the leftmost bit in from the left, and let the rightmost bits fall off	x >> 2

Operator Precedence

Operator precedence describes the order in which operations are performed.

Parentheses has the highest precedence, meaning that expressions inside parentheses must be evaluated first:

Multiplication * has higher precedence than addition + , and therefor multiplications are evaluated before additions:

The precedence order is described in the table below, starting with the highest precedence at the top:

Operator	Description	Try it
	Parentheses
	Exponentiation
	Unary plus, unary minus, and bitwise NOT
	Multiplication, division, floor division, and modulus
	Addition and subtraction
	Bitwise left and right shifts
	Bitwise AND
	Bitwise XOR
	Bitwise OR
	Comparisons, identity, and membership operators
	Logical NOT
	AND
	OR

If two operators have the same precedence, the expression is evaluated from left to right.

Addition + and subtraction - has the same precedence, and therefor we evaluate the expression from left to right:

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]

Operators and Expressions in Python

Table of Contents

Getting Started With Operators and Expressions

The assignment operator and statements, arithmetic operators and expressions in python, comparison of integer values, comparison of floating-point values, comparison of strings, comparison of lists and tuples, boolean expressions involving boolean operands, evaluation of regular objects in a boolean context, boolean expressions involving other types of operands, compound logical expressions and short-circuit evaluation, idioms that exploit short-circuit evaluation, compound vs chained expressions, conditional expressions or the ternary operator, identity operators and expressions in python, membership operators and expressions in python, concatenation and repetition operators and expressions, the walrus operator and assignment expressions, bitwise operators and expressions in python, operator precedence in python, augmented assignment operators and expressions.

In Python, operators are special symbols, combinations of symbols, or keywords that designate some type of computation. You can combine objects and operators to build expressions that perform the actual computation. So, operators are the building blocks of expressions, which you can use to manipulate your data. Therefore, understanding how operators work in Python is essential for you as a programmer.

In this tutorial, you’ll learn about the operators that Python currently supports. You’ll also learn the basics of how to use these operators to build expressions.

In this tutorial, you’ll:

Get to know Python’s arithmetic operators and use them to build arithmetic expressions
Explore Python’s comparison , Boolean , identity , and membership operators
Build expressions with comparison, Boolean, identity, and membership operators
Learn about Python’s bitwise operators and how to use them
Combine and repeat sequences using the concatenation and repetition operators
Understand the augmented assignment operators and how they work

To get the most out of this tutorial, you should have a basic understanding of Python programming concepts, such as variables , assignments , and built-in data types .

Free Bonus: Click here to download your comprehensive cheat sheet covering the various operators in Python.

Take the Quiz: Test your knowledge with our interactive “Python Operators and Expressions” quiz. You’ll receive a score upon completion to help you track your learning progress:

Interactive Quiz

Test your understanding of Python operators and expressions.

In programming, an operator is usually a symbol or combination of symbols that allows you to perform a specific operation. This operation can act on one or more operands . If the operation involves a single operand, then the operator is unary . If the operator involves two operands, then the operator is binary .

For example, in Python, you can use the minus sign ( - ) as a unary operator to declare a negative number. You can also use it to subtract two numbers:

In this code snippet, the minus sign ( - ) in the first example is a unary operator, and the number 273.15 is the operand. In the second example, the same symbol is a binary operator, and the numbers 5 and 2 are its left and right operands.

Programming languages typically have operators built in as part of their syntax. In many languages, including Python, you can also create your own operator or modify the behavior of existing ones, which is a powerful and advanced feature to have.

In practice, operators provide a quick shortcut for you to manipulate data, perform mathematical calculations, compare values, run Boolean tests, assign values to variables, and more. In Python, an operator may be a symbol, a combination of symbols, or a keyword , depending on the type of operator that you’re dealing with.

For example, you’ve already seen the subtraction operator, which is represented with a single minus sign ( - ). The equality operator is a double equal sign ( == ). So, it’s a combination of symbols:

In this example, you use the Python equality operator ( == ) to compare two numbers. As a result, you get True , which is one of Python’s Boolean values.

Speaking of Boolean values, the Boolean or logical operators in Python are keywords rather than signs, as you’ll learn in the section about Boolean operators and expressions . So, instead of the odd signs like || , && , and ! that many other programming languages use, Python uses or , and , and not .

Using keywords instead of odd signs is a really cool design decision that’s consistent with the fact that Python loves and encourages code’s readability .

You’ll find several categories or groups of operators in Python. Here’s a quick list of those categories:

Assignment operators
Arithmetic operators
Comparison operators
Boolean or logical operators
Identity operators
Membership operators
Concatenation and repetition operators
Bitwise operators

All these types of operators take care of specific types of computations and data-processing tasks. You’ll learn more about these categories throughout this tutorial. However, before jumping into more practical discussions, you need to know that the most elementary goal of an operator is to be part of an expression . Operators by themselves don’t do much:

As you can see in this code snippet, if you use an operator without the required operands, then you’ll get a syntax error . So, operators must be part of expressions, which you can build using Python objects as operands.

So, what is an expression anyway? Python has simple and compound statements. A simple statement is a construct that occupies a single logical line , like an assignment statement. A compound statement is a construct that occupies multiple logical lines, such as a for loop or a conditional statement. An expression is a simple statement that produces and returns a value.

You’ll find operators in many expressions. Here are a few examples:

In the first two examples, you use the addition and division operators to construct two arithmetic expressions whose operands are integer numbers. In the last example, you use the equality operator to create a comparison expression. In all cases, you get a specific value after executing the expression.

Note that not all expressions use operators. For example, a bare function call is an expression that doesn’t require any operator:

In the first example, you call the built-in abs() function to get the absolute value of -7 . Then, you compute 2 to the power of 8 using the built-in pow() function. These function calls occupy a single logical line and return a value. So, they’re expressions.

Finally, the call to the built-in print() function is another expression. This time, the function doesn’t return a fruitful value, but it still returns None , which is the Python null type . So, the call is technically an expression.

Note: All Python functions have a return value, either explicit or implicit. If you don’t provide an explicit return statement when defining a function, then Python will automatically make the function return None .

Even though all expressions are statements, not all statements are expressions. For example, pure assignment statements don’t return any value, as you’ll learn in a moment. Therefore, they’re not expressions. The assignment operator is a special operator that doesn’t create an expression but a statement.

Note: Since version 3.8, Python also has what it calls assignment expressions. These are special types of assignments that do return a value. You’ll learn more about this topic in the section The Walrus Operator and Assignment Expressions .

Okay! That was a quick introduction to operators and expressions in Python. Now it’s time to dive deeper into the topic. To kick things off, you’ll start with the assignment operator and statements.

The assignment operator is one of the most frequently used operators in Python. The operator consists of a single equal sign ( = ), and it operates on two operands. The left-hand operand is typically a variable , while the right-hand operand is an expression.

Note: As you already learned, the assignment operator doesn’t create an expression. Instead, it creates a statement that doesn’t return any value.

The assignment operator allows you to assign values to variables . Strictly speaking, in Python, this operator makes variables or names refer to specific objects in your computer’s memory. In other words, an assignment creates a reference to a concrete object and attaches that reference to the target variable.

Note: To dive deeper into using the assignment operator, check out Python’s Assignment Operator: Write Robust Assignments .

For example, all the statements below create new variables that hold references to specific objects:

In the first statement, you create the number variable, which holds a reference to the number 42 in your computer’s memory. You can also say that the name number points to 42 , which is a concrete object.

In the rest of the examples, you create other variables that point to other types of objects, such as a string , tuple , and list , respectively.

You’ll use the assignment operator in many of the examples that you’ll write throughout this tutorial. More importantly, you’ll use this operator many times in your own code. It’ll be your forever friend. Now you can dive into other Python operators!

Arithmetic operators are those operators that allow you to perform arithmetic operations on numeric values. Yes, they come from math, and in most cases, you’ll represent them with the usual math signs. The following table lists the arithmetic operators that Python currently supports:

Type	Operation	Result
Unary	Positive	without any transformation since this is simply a complement to negation
Binary	Addition	The arithmetic sum of and
Unary	Negation	The value of but with the opposite sign
Binary	Subtraction	subtracted from
Binary	Multiplication	The product of and
Binary	Division	The quotient of divided by , expressed as a float
Binary	Modulo	The remainder of divided by
Binary	Floor division or integer division	The quotient of divided by , rounded to the next smallest whole number
Binary	Exponentiation	raised to the power of

Note that a and b in the Sample Expression column represent numeric values, such as integer , floating-point , complex , rational , and decimal numbers.

Here are some examples of these operators in use:

In this code snippet, you first create two new variables, a and b , holding 5 and 2 , respectively. Then you use these variables to create different arithmetic expressions using a specific operator in each expression.

Note: The Python REPL will display the return value of an expression as a way to provide immediate feedback to you. So, when you’re in an interactive session, you don’t need to use the print() function to check the result of an expression. You can just type in the expression and press Enter to get the result.

Again, the standard division operator ( / ) always returns a floating-point number, even if the dividend is evenly divisible by the divisor:

In the first example, 10 is evenly divisible by 5 . Therefore, this operation could return the integer 2 . However, it returns the floating-point number 2.0 . In the second example, 10.0 is a floating-point number, and 5 is an integer. In this case, Python internally promotes 5 to 5.0 and runs the division. The result is a floating-point number too.

Note: With complex numbers, the division operator doesn’t return a floating-point number but a complex one:

Here, you run a division between an integer and a complex number. In this case, the standard division operator returns a complex number.

Finally, consider the following examples of using the floor division ( // ) operator:

Floor division always rounds down . This means that the result is the greatest integer that’s smaller than or equal to the quotient. For positive numbers, it’s as though the fractional portion is truncated, leaving only the integer portion.

Comparison Operators and Expressions in Python

The Python comparison operators allow you to compare numerical values and any other objects that support them. The table below lists all the currently available comparison operators in Python:

Operator	Operation	Sample Expression	Result
	Equal to		• if the value of is equal to the value of • otherwise
	Not equal to		• if isn’t equal to • otherwise
	Less than		• if is less than • otherwise
	Less than or equal to		• if is less than or equal to • otherwise
	Greater than		• if is greater than • otherwise
	Greater than or equal to		• if is greater than or equal to • otherwise

The comparison operators are all binary. This means that they require left and right operands. These operators always return a Boolean value ( True or False ) that depends on the truth value of the comparison at hand.

Note that comparisons between objects of different data types often don’t make sense and sometimes aren’t allowed in Python. For example, you can compare a number and a string for equality with the == operator. However, you’ll get False as a result:

The integer 2 isn’t equal to the string "2" . Therefore, you get False as a result. You can also use the != operator in the above expression, in which case you’ll get True as a result.

Non-equality comparisons between operands of different data types raise a TypeError exception:

In this example, Python raises a TypeError exception because a less than comparison ( < ) doesn’t make sense between an integer and a string. So, the operation isn’t allowed.

It’s important to note that in the context of comparisons, integer and floating-point values are compatible, and you can compare them.

You’ll typically use and find comparison operators in Boolean contexts like conditional statements and while loops . They allow you to make decisions and define a program’s control flow .

The comparison operators work on several types of operands, such as numbers, strings, tuples, and lists. In the following sections, you’ll explore the differences.

Probably, the more straightforward comparisons in Python and in math are those involving integer numbers. They allow you to count real objects, which is a familiar day-to-day task. In fact, the non-negative integers are also called natural numbers . So, comparing this type of number is probably pretty intuitive, and doing so in Python is no exception.

Consider the following examples that compare integer numbers:

In the first set of examples, you define two variables, a and b , to run a few comparisons between them. The value of a is less than the value of b . So, every comparison expression returns the expected Boolean value. The second set of examples uses two values that are equal, and again, you get the expected results.

Comparing floating-point numbers is a bit more complicated than comparing integers. The value stored in a float object may not be precisely what you’d think it would be. For that reason, it’s bad practice to compare floating-point values for exact equality using the == operator.

Consider the example below:

Yikes! The internal representation of this addition isn’t exactly equal to 3.3 , as you can see in the final example. So, comparing x to 3.3 with the equality operator returns False .

To compare floating-point numbers for equality, you need to use a different approach. The preferred way to determine whether two floating-point values are equal is to determine whether they’re close to one another, given some tolerance.

The math module from the standard library provides a function conveniently called isclose() that will help you with float comparison. The function takes two numbers and tests them for approximate equality:

In this example, you use the isclose() function to compare x and 3.3 for approximate equality. This time, you get True as a result because both numbers are close enough to be considered equal.

For further details on using isclose() , check out the Find the Closeness of Numbers With Python isclose() section in The Python math Module: Everything You Need to Know .

You can also use the comparison operators to compare Python strings in your code. In this context, you need to be aware of how Python internally compares string objects. In practice, Python compares strings character by character using each character’s Unicode code point . Unicode is Python’s default character set .

You can use the built-in ord() function to learn the Unicode code point of any character in Python. Consider the following examples:

The uppercase "A" has a lower Unicode point than the lowercase "a" . So, "A" is less than "a" . In the end, Python compares characters using integer numbers. So, the same rules that Python uses to compare integers apply to string comparison.

When it comes to strings with several characters, Python runs the comparison character by character in a loop.

The comparison uses lexicographical ordering , which means that Python compares the first item from each string. If their Unicode code points are different, this difference determines the comparison result. If the Unicode code points are equal, then Python compares the next two characters, and so on, until either string is exhausted:

In this example, Python compares both operands character by character. When it reaches the end of the string, it compares "o" and "O" . Because the lowercase letter has a greater Unicode code point, the first version of the string is greater than the second.

You can also compare strings of different lengths:

In this example, Python runs a character-by-character comparison as usual. If it runs out of characters, then the shorter string is less than the longer one. This also means that the empty string is the smallest possible string.

In your Python journey, you can also face the need to compare lists with other lists and tuples with other tuples. These data types also support the standard comparison operators. Like with strings, when you use a comparison operator to compare two lists or two tuples, Python runs an item-by-item comparison.

Note that Python applies specific rules depending on the type of the contained items. Here are some examples that compare lists and tuples of integer values:

In these examples, you compare lists and tuples of numbers using the standard comparison operators. When comparing these data types, Python runs an item-by-item comparison.

For example, in the first expression above, Python compares the 2 in the left operand and the 2 in the right operand. Because they’re equal, Python continues comparing 3 and 3 to conclude that both lists are equal. The same thing happens in the second example, where you compare tuples containing the same data.

It’s important to note that you can actually compare lists to tuples using the == and != operators. However, you can’t compare lists and tuples using the < , > , <= , and >= operators:

Python supports equality comparison between lists and tuples. However, it doesn’t support the rest of the comparison operators, as you can conclude from the final two examples. If you try to use them, then you get a TypeError telling you that the operation isn’t supported.

You can also compare lists and tuples of different lengths:

In the first two examples, you get True as a result because 5 is less than 8 . That fact is sufficient for Python to solve the comparison. In the second pair of examples, you get False . This result makes sense because the compared sequences don’t have the same length, so they can’t be equal.

In the final pair of examples, Python compares 5 with 5 . They’re equal, so the comparison continues. Because there are no more values to compare in the right-hand operands, Python concludes that the left-hand operands are greater.

As you can see, comparing lists and tuples can be tricky. It’s also an expensive operation that, in the worst case, requires traversing two entire sequences. Things get more complex and expensive when the contained items are also sequences. In those situations, Python will also have to compare items in a value-by-value manner, which adds cost to the operation.

Boolean Operators and Expressions in Python

Python has three Boolean or logical operators: and , or , and not . They define a set of operations denoted by the generic operators AND , OR , and NOT . With these operators, you can create compound conditions.

In the following sections, you’ll learn how the Python Boolean operators work. Especially, you’ll learn that some of them behave differently when you use them with Boolean values or with regular objects as operands.

You’ll find many objects and expressions that are of Boolean type or bool , as Python calls this type. In other words, many objects evaluate to True or False , which are the Python Boolean values.

For example, when you evaluate an expression using a comparison operator, the result of that expression is always of bool type:

In this example, the expression age > 18 returns a Boolean value, which you store in the is_adult variable. Now is_adult is of bool type, as you can see after calling the built-in type() function.

You can also find Python built-in and custom functions that return a Boolean value. This type of function is known as a predicate function. The built-in all() , any() , callable() , and isinstance() functions are all good examples of this practice.

Consider the following examples:

In this code snippet, you first define a variable called number using your old friend the assignment operator. Then you create another variable called validation_conditions . This variable holds a tuple of expressions. The first expression uses isinstance() to check whether number is an integer value.

The second is a compound expression that combines the modulo ( % ) and equality ( == ) operators to create a condition that checks whether the input value is an even number. In this condition, the modulo operator returns the remainder of dividing number by 2 , and the equality operator compares the result with 0 , returning True or False as the comparison’s result.

Then you use the all() function to determine if all the conditions are true. In this example, because number = 42 , the conditions are true, and all() returns True . You can play with the value of number if you’d like to experiment a bit.

In the final two examples, you use the callable() function. As its name suggests, this function allows you to determine whether an object is callable . Being callable means that you can call the object with a pair of parentheses and appropriate arguments, as you’d call any Python function.

The number variable isn’t callable, and the function returns False , accordingly. In contrast, the print() function is callable, so callable() returns True .

All the previous discussion is the basis for understanding how the Python logical operators work with Boolean operands.

Logical expressions involving and , or , and not are straightforward when the operands are Boolean. Here’s a summary. Note that x and y represent Boolean operands:

Operator	Sample Expression	Result
		• if both and are • otherwise
		• if either or is • otherwise
		• if is • if is

This table summarizes the truth value of expressions that you can create using the logical operators with Boolean operands. There’s something to note in this summary. Unlike and and or , which are binary operators, the not operator is unary, meaning that it operates on one operand. This operand must always be on the right side.

Now it’s time to take a look at how the operators work in practice. Here are a few examples of using the and operator with Boolean operands:

In the first example, both operands return True . Therefore, the and expression returns True as a result. In the second example, the left-hand operand is True , but the right-hand operand is False . Because of this, the and operator returns False .

In the third example, the left-hand operand is False . In this case, the and operator immediately returns False and never evaluates the 3 == 3 condition. This behavior is called short-circuit evaluation . You’ll learn more about it in a moment.

Note: Short-circuit evaluation is also called McCarthy evaluation in honor of computer scientist John McCarthy .

In the final example, both conditions return False . Again, and returns False as a result. However, because of the short-circuit evaluation, the right-hand expression isn’t evaluated.

What about the or operator? Here are a few examples that demonstrate how it works:

In the first three examples, at least one of the conditions returns True . In all cases, the or operator returns True . Note that if the left-hand operand is True , then or applies short-circuit evaluation and doesn’t evaluate the right-hand operand. This makes sense. If the left-hand operand is True , then or already knows the final result. Why would it need to continue the evaluation if the result won’t change?

In the final example, both operands are False , and this is the only situation where or returns False . It’s important to note that if the left-hand operand is False , then or has to evaluate the right-hand operand to arrive at a final conclusion.

Finally, you have the not operator, which negates the current truth value of an object or expression:

If you place not before an expression, then you get the inverse truth value. When the expression returns True , you get False . When the expression evaluates to False , you get True .

There is a fundamental behavior distinction between not and the other two Boolean operators. In a not expression, you always get a Boolean value as a result. That’s not always the rule that governs and and or expressions, as you’ll learn in the Boolean Expressions Involving Other Types of Operands section.

In practice, most Python objects and expressions aren’t Boolean. In other words, most objects and expressions don’t have a True or False value but a different type of value. However, you can use any Python object in a Boolean context, such as a conditional statement or a while loop.

In Python, all objects have a specific truth value. So, you can use the logical operators with all types of operands.

Python has well-established rules to determine the truth value of an object when you use that object in a Boolean context or as an operand in an expression built with logical operators. Here’s what the documentation says about this topic:

By default, an object is considered true unless its class defines either a __bool__() method that returns False or a __len__() method that returns zero, when called with the object. Here are most of the built-in objects considered false: constants defined to be false: None and False . zero of any numeric type: 0 , 0.0 , 0j , Decimal(0) , Fraction(0, 1) empty sequences and collections: '' , () , [] , {} , set() , range(0) ( Source )

You can determine the truth value of an object by calling the built-in bool() function with that object as an argument. If bool() returns True , then the object is truthy . If bool() returns False , then it’s falsy .

For numeric values, you have that a zero value is falsy, while a non-zero value is truthy:

Python considers the zero value of all numeric types falsy. All the other values are truthy, regardless of how close to zero they are.

Note: Instead of a function, bool() is a class. However, because Python developers typically use this class as a function, you’ll find that most people refer to it as a function rather than as a class. Additionally, the documentation lists this class on the built-in functions page. This is one of those cases where practicality beats purity .

When it comes to evaluating strings, you have that an empty string is always falsy, while a non-empty string is truthy:

Note that strings containing white spaces are also truthy in Python’s eyes. So, don’t confuse empty strings with whitespace strings.

Finally, built-in container data types, such as lists, tuples, sets , and dictionaries , are falsy when they’re empty. Otherwise, Python considers them truthy objects:

To determine the truth value of container data types, Python relies on the .__len__() special method . This method provides support for the built-in len() function, which you can use to determine the number of items in a given container.

In general, if .__len__() returns 0 , then Python considers the container a falsy object, which is consistent with the general rules you’ve just learned before.

All the discussion about the truth value of Python objects in this section is key to understanding how the logical operators behave when they take arbitrary objects as operands.

You can also use any objects, such as numbers or strings, as operands to and , or , and not . You can even use combinations of a Boolean object and a regular one. In these situations, the result depends on the truth value of the operands.

Note: Boolean expressions that combine two Boolean operands are a special case of a more general rule that allows you to use the logical operators with all kinds of operands. In every case, you’ll get one of the operands as a result.

You’ve already learned how Python determines the truth value of objects. So, you’re ready to dive into creating expressions with logic operators and regular objects.

To start off, below is a table that summarizes what you get when you use two objects, x and y , in an and expression:

If is	returns
Truthy
Falsy

It’s important to emphasize a subtle detail in the above table. When you use and in an expression, you don’t always get True or False as a result. Instead, you get one of the operands. You only get True or False if the returned operand has either of these values.

Here are some code examples that use integer values. Remember that in Python, the zero value of numeric types is falsy. The rest of the values are truthy:

In the first expression, the left-hand operand ( 3 ) is truthy. So, you get the right-hand operand ( 4 ) as a result.

In the second example, the left-hand operand ( 0 ) is falsy, and you get it as a result. In this case, Python applies the short-circuit evaluation technique. It already knows that the whole expression is false because 0 is falsy, so Python returns 0 immediately without evaluating the right-hand operand.

In the final expression, the left-hand operand ( 3 ) is truthy. Therefore Python needs to evaluate the right-hand operand to make a conclusion. As a result, you get the right-hand operand, no matter what its truth value is.

Note: To dive deeper into the and operator, check out Using the “and” Boolean Operator in Python .

When it comes to using the or operator, you also get one of the operands as a result. This is what happens for two arbitrary objects, x and y :

Again, the expression x or y doesn’t evaluate to either True or False . Instead, it returns one of its operands, x or y .

As you can conclude from the above table, if the left-hand operand is truthy, then you get it as a result. Otherwise, you get the second operand. Here are some examples that demonstrate this behavior:

In the first example, the left-hand operand is truthy, and or immediately returns it. In this case, Python doesn’t evaluate the second operand because it already knows the final result. In the second example, the left-hand operand is falsy, and Python has to evaluate the right-hand one to determine the result.

In the last example, the left-hand operand is truthy, and that fact defines the result of the expression. There’s no need to evaluate the right-hand operand.

An expression like x or y is truthy if either x or y is truthy, and falsy if both x and y are falsy. This type of expression returns the first truthy operand that it finds. If both operands are falsy, then the expression returns the right-hand operand. To see this latter behavior in action, consider the following example:

In this specific expression, both operands are falsy. So, the or operator returns the right-hand operand, and the whole expression is falsy as a result.

Note: To learn more about the or operator, check out Using the “or” Boolean Operator in Python .

Finally, you have the not operator. You can also use this one with any object as an operand. Here’s what happens:

The not operator has a uniform behavior. It always returns a Boolean value. This behavior differs from its sibling operators, and and or .

Here are some code examples:

In the first example, the operand, 3 , is truthy from Python’s point of view. So, the operator returns False . In the second example, the operand is falsy, and not returns True .

Note: To better understand the not operator, check out Using the “not” Boolean Operator in Python .

In summary, the Python not operator negates the truth value of an object and always returns a Boolean value. This latter behavior differs from the behavior of its sibling operators and and or , which return operands rather than Boolean values.

So far, you’ve seen expressions with only a single or or and operator and two operands. However, you can also create compound logical expressions with multiple logical operators and operands.

To illustrate how to create a compound expression using or , consider the following toy example:

This expression returns the first truthy value. If all the preceding x variables are falsy, then the expression returns the last value, xn .

Note: In an expression like the one above, Python uses short-circuit evaluation . The operands are evaluated in order from left to right. As soon as one is found to be true, the entire expression is known to be true. At that point, Python stops evaluating operands. The value of the entire expression is that of the x that terminates the evaluation.

To help demonstrate short-circuit evaluation, suppose that you have an identity function , f() , that behaves as follows:

Takes a single argument
Displays the function and its argument on the screen
Returns the argument as its return value

Here’s the code to define this function and also a few examples of how it works:

The f() function displays its argument, which visually confirms whether you called the function. It also returns the argument as you passed it in the call. Because of this behavior, you can make the expression f(arg) be truthy or falsy by specifying a value for arg that’s truthy or falsy, respectively.

Now, consider the following compound logical expression:

In this example, Python first evaluates f(0) , which returns 0 . This value is falsy. The expression isn’t true yet, so the evaluation continues from left to right. The next operand, f(False) , returns False . That value is also falsy, so the evaluation continues.

Next up is f(1) . That evaluates to 1 , which is truthy. At that point, Python stops the evaluation because it already knows that the entire expression is truthy. Consequently, Python returns 1 as the value of the expression and never evaluates the remaining operands, f(2) and f(3) . You can confirm from the output that the f(2) and f(3) calls don’t occur.

A similar behavior appears in an expression with multiple and operators like the following one:

This expression is truthy if all the operands are truthy. If at least one operand is falsy, then the expression is also falsy.

In this example, short-circuit evaluation dictates that Python stops evaluating as soon as an operand happens to be falsy. At that point, the entire expression is known to be false. Once that’s the case, Python stops evaluating operands and returns the falsy operand that terminated the evaluation.

Here are two examples that confirm the short-circuiting behavior:

In both examples, the evaluation stops at the first falsy term— f(False) in the first case, f(0.0) in the second case—and neither the f(2) nor the f(3) call occurs. In the end, the expressions return False and 0.0 , respectively.

If all the operands are truthy, then Python evaluates them all and returns the last (rightmost) one as the value of the expression:

In the first example, all the operands are truthy. The expression is also truthy and returns the last operand. In the second example, all the operands are truthy except for the last one. The expression is falsy and returns the last operand.

As you dig into Python, you’ll find that there are some common idiomatic patterns that exploit short-circuit evaluation for conciseness of expression, performance, and safety. For example, you can take advantage of this type of evaluation for:

Avoiding an exception
Providing a default value
Skipping a costly operation

To illustrate the first point, suppose you have two variables, a and b , and you want to know whether the division of b by a results in a number greater than 0 . In this case, you can run the following expression or condition:

This code works. However, you need to account for the possibility that a might be 0 , in which case you’ll get an exception :

In this example, the divisor is 0 , which makes Python raise a ZeroDivisionError exception. This exception breaks your code. You can skip this error with an expression like the following:

When a is 0 , a != 0 is false. Python’s short-circuit evaluation ensures that the evaluation stops at that point, which means that (b / a) never runs, and the error never occurs.

Using this technique, you can implement a function to determine whether an integer is divisible by another integer:

In this function, if b is 0 , then a / b isn’t defined. So, the numbers aren’t divisible. If b is different from 0 , then the result will depend on the remainder of the division.

Selecting a default value when a specified value is falsy is another idiom that takes advantage of the short-circuit evaluation feature of Python’s logical operators.

For example, say that you have a variable that’s supposed to contain a country’s name. At some point, this variable can end up holding an empty string. If that’s the case, then you’d like the variable to hold a default county name. You can also do this with the or operator:

If country is non-empty, then it’s truthy. In this scenario, the expression will return the first truthy value, which is country in the first or expression. The evaluation stops, and you get "Canada" as a result.

On the other hand, if country is an empty string , then it’s falsy. The evaluation continues to the next operand, default_country , which is truthy. Finally, you get the default country as a result.

Another interesting use case for short-circuit evaluation is to avoid costly operations while creating compound logical expressions. For example, if you have a costly operation that should only run if a given condition is false, then you can use or like in the following snippet:

In this construct, your clean_data() function represents a costly operation. Because of short-circuit evaluation, this function will only run when data_is_clean is false, which means that your data isn’t clean.

Another variation of this technique is when you want to run a costly operation if a given condition is true. In this case, you can use the and operator:

In this example, the and operator evaluates data_is_updated . If this variable is true, then the evaluation continues, and the process_data() function runs. Otherwise, the evaluation stops, and process_data() never runs.

Sometimes you have a compound expression that uses the and operator to join comparison expressions. For example, say that you want to determine if a number is in a given interval. You can solve this problem with a compound expression like the following:

In this example, you use the and operator to join two comparison expressions that allow you to find out if number is in the interval from 0 to 10 , both included.

In Python, you can make this compound expression more concise by chaining the comparison operators together. For example, the following chained expression is equivalent to the previous compound one:

This expression is more concise and readable than the original expression. You can quickly realize that this code is checking if the number is between 0 and 10 . Note that in most programming languages, this chained expression doesn’t make sense. In Python, it works like a charm.

In other programming languages, this expression would probably start by evaluating 0 <= number , which is true. This true value would then be compared with 10 , which doesn’t make much sense, so the expression fails.

Python internally processes this type of expression as an equivalent and expression, such as 0 <= number and number <= 10 . That’s why you get the correct result in the example above.

Python has what it calls conditional expressions . These kinds of expressions are inspired by the ternary operator that looks like a ? b : c and is used in other programming languages. This construct evaluates to b if the value of a is true, and otherwise evaluates to c . Because of this, sometimes the equivalent Python syntax is also known as the ternary operator.

However, in Python, the expression looks more readable:

This expression returns expression_1 if the condition is true and expression_2 otherwise. Note that this expression is equivalent to a regular conditional like the following:

So, why does Python need this syntax? PEP 308 introduced conditional expressions as an effort to avoid the prevalence of error-prone attempts to achieve the same effect of a traditional ternary operator using the and and or operators in an expression like the following:

However, this expression doesn’t work as expected, returning expression_2 when expression_1 is falsy.

Some Python developers would avoid the syntax of conditional expressions in favor of a regular conditional statement. In any case, this syntax can be handy in some situations because it provides a concise tool for writing two-way conditionals.

Here’s an example of how to use the conditional expression syntax in your code:

When day is equal to "Sunday" , the condition is true and you get the first expression, "11AM" , as a result. If the condition is false, then you get the second expression, "9AM" . Note that similarly to the and and or operators, the conditional expression returns the value of one of its expressions rather than a Boolean value.

Python provides two operators, is and is not , that allow you to determine whether two operands have the same identity . In other words, they let you check if the operands refer to the same object. Note that identity isn’t the same thing as equality. The latter aims to check whether two operands contain the same data.

Note: To learn more about the difference between identity and equality, check out Python ‘!=’ Is Not ‘is not’: Comparing Objects in Python .

Here’s a summary of Python’s identity operators. Note that x and y are variables that point to objects:

Operator	Sample Expression	Result
		• if and hold a reference to the same in-memory object • otherwise
		• if points to an object different from the object that points to • otherwise

These two Python operators are keywords instead of odd symbols. This is part of Python’s goal of favoring readability in its syntax.

Here’s an example of two variables, x and y , that refer to objects that are equal but not identical:

In this example, x and y refer to objects whose value is 1001 . So, they’re equal. However, they don’t reference the same object. That’s why the is operator returns False . You can check an object’s identity using the built-in id() function:

As you can conclude from the id() output, x and y don’t have the same identity. So, they’re different objects, and because of that, the expression x is y returns False . In other words, you get False because you have two different instances of 1001 stored in your computer’s memory.

When you make an assignment like y = x , Python creates a second reference to the same object. Again, you can confirm that with the id() function or the is operator:

In this example, a and b hold references to the same object, the string "Hello, Pythonista!" . Therefore, the id() function returns the same identity when you call it with a and b . Similarly, the is operator returns True .

Note: You should note that, on your computer, you’ll get a different identity number when you call id() in the example above. The key detail is that the identity number will be the same for a and b .

Finally, the is not operator is the opposite of is . So, you can use is not to determine if two names don’t refer to the same object:

In the first example, because x and y point to different objects in your computer’s memory, the is not operator returns True . In the second example, because a and b are references to the same object, the is not operator returns False .

Note: The syntax not x is y also works the same as x is not y . However, the former syntax looks odd and is difficult to read. That’s why Python recognizes is not as an operator and encourages its use for readability.

Again, the is not operator highlights Python’s readability goals. In general, both identity operators allow you to write checks that read as plain English.

Sometimes you need to determine whether a value is present in a container data type, such as a list, tuple, or set. In other words, you may need to check if a given value is or is not a member of a collection of values. Python calls this kind of check a membership test .

Note: For a deep dive into how Python’s membership tests work, check out Python’s “in” and “not in” Operators: Check for Membership .

Membership tests are quite common and useful in programming. As with many other common operations, Python has dedicated operators for membership tests. The table below lists the membership operators in Python:

Operator	Sample Expression	Result
		• if present in • otherwise
		• if present in of values • otherwise

As usual, Python favors readability by using English words as operators instead of potentially confusing symbols or combinations of symbols.

Note: The syntax not value in collection also works in Python. However, this syntax looks odd and is difficult to read. So, to keep your code clean and readable, you should use value not in collection , which almost reads as plain English.

The Python in and not in operators are binary. This means that you can create membership expressions by connecting two operands with either operator. However, the operands in a membership expression have particular characteristics:

Left operand : The value that you want to look for in a collection of values
Right operand : The collection of values where the target value may be found

To better understand the in operator, below you have two demonstrative examples consisting of determining whether a value is in a list:

The first expression returns True because 5 is in the list of numbers. The second expression returns False because 8 isn’t in the list.

The not in membership operator runs the opposite test as the in operator. It allows you to check whether an integer value is not in a collection of values:

In the first example, you get False because 5 is in the target list. In the second example, you get True because 8 isn’t in the list of values. This may sound like a tongue twister because of the negative logic. To avoid confusion, remember that you’re trying to determine if the value is not part of a given collection of values.

There are two operators in Python that acquire a slightly different meaning when you use them with sequence data types, such as lists, tuples, and strings. With these types of operands, the + operator defines a concatenation operator , and the * operator represents the repetition operator :

Operator	Operation	Sample Expression	Result
	Concatenation		A new sequence containing all the items from both operands
	Repetition		A new sequence containing the items of repeated times

Both operators are binary. The concatenation operator takes two sequences as operands and returns a new sequence of the same type. The repetition operator takes a sequence and an integer number as operands. Like in regular multiplication, the order of the operands doesn’t alter the repetition’s result.

Note: To learn more about concatenating string objects, check out Efficient String Concatenation in Python .

Here are some examples of how the concatenation operator works in practice:

In the first example, you use the concatenation operator ( + ) to join two strings together. The operator returns a completely new string object that combines the two original strings.

In the second example, you concatenate two tuples of letters together. Again, the operator returns a new tuple object containing all the items from the original operands. In the final example, you do something similar but this time with two lists.

Note: To learn more about concatenating lists, check out the Concatenating Lists section in the tutorial Python’s list Data Type: A Deep Dive With Examples .

When it comes to the repetition operator, the idea is to repeat the content of a given sequence a certain number of times. Here are a few examples:

In the first example, you use the repetition operator ( * ) to repeat the "Hello" string three times. In the second example, you change the order of the operands by placing the integer number on the left and the target string on the right. This example shows that the order of the operands doesn’t affect the result.

The next examples use the repetition operators with a tuple and a list, respectively. In both cases, you get a new object of the same type containing the items in the original sequence repeated three times.

Regular assignment statements with the = operator don’t have a return value, as you already learned. Instead, the assignment operator creates or updates variables. Because of this, the operator can’t be part of an expression.

Since Python 3.8 , you have access to a new operator that allows for a new type of assignment. This new assignment is called assignment expression or named expression . The new operator is called the walrus operator , and it’s the combination of a colon and an equal sign ( := ).

Note: The name walrus comes from the fact that this operator resembles the eyes and tusks of a walrus lying on its side. For a deep dive into how this operator works, check out The Walrus Operator: Python’s Assignment Expressions .

Unlike regular assignments, assignment expressions do have a return value, which is why they’re expressions . So, the operator accomplishes two tasks:

Returns the expression’s result
Assigns the result to a variable

The walrus operator is also a binary operator. Its left-hand operand must be a variable name, and its right-hand operand can be any Python expression. The operator will evaluate the expression, assign its value to the target variable, and return the value.

The general syntax of an assignment expression is as follows:

This expression looks like a regular assignment. However, instead of using the assignment operator ( = ), it uses the walrus operator ( := ). For the expression to work correctly, the enclosing parentheses are required in most use cases. However, in certain situations, you won’t need them. Either way, they won’t hurt you, so it’s safe to use them.

Assignment expressions come in handy when you want to reuse the result of an expression or part of an expression without using a dedicated assignment to grab this value beforehand. It’s particularly useful in the context of a conditional statement. To illustrate, the example below shows a toy function that checks the length of a string object:

In this example, you use a conditional statement to check whether the input string has fewer than 8 characters.

The assignment expression, (n := len(string)) , computes the string length and assigns it to n . Then it returns the value that results from calling len() , which finally gets compared with 8 . This way, you guarantee that you have a reference to the string length to use in further operations.

Bitwise operators treat operands as sequences of binary digits and operate on them bit by bit. Currently, Python supports the following bitwise operators:

Operator	Operation	Sample Expression	Result
	Bitwise AND		• Each bit position in the result is the logical AND of the bits in the corresponding position of the operands. • if both bits are , otherwise .
	Bitwise OR		• Each bit position in the result is the logical of the bits in the corresponding position of the operands. • if either bit is , otherwise .
	Bitwise NOT		• Each bit position in the result is the logical negation of the bit in the corresponding position of the operand. • if the bit is and if the bit is .
	Bitwise XOR (exclusive OR)		• Each bit position in the result is the logical of the bits in the corresponding position of the operands. • if the bits in the operands are different, if they’re equal.
	Bitwise right shift		Each bit is shifted right places.
	Bitwise left shift		Each bit is shifted left places.

As you can see in this table, most bitwise operators are binary, which means that they expect two operands. The bitwise NOT operator ( ~ ) is the only unary operator because it expects a single operand, which should always appear at the right side of the expression.

You can use Python’s bitwise operators to manipulate your data at its most granular level, the bits. These operators are commonly useful when you want to write low-level algorithms, such as compression, encryption, and others.

Note: For a deep dive into the bitwise operators, check out Bitwise Operators in Python . You can also check out Build a Maze Solver in Python Using Graphs for an example of using bitwise operators to construct a binary file format.

Here are some examples that illustrate how some of the bitwise operators work in practice:

In the first example, you use the bitwise AND operator. The commented lines begin with # and provide a visual representation of what happens at the bit level. Note how each bit in the result is the logical AND of the bits in the corresponding position of the operands.

The second example shows how the bitwise OR operator works. In this case, the resulting bits are the logical OR test of the corresponding bits in the operands.

In all the examples, you’ve used the built-in bin() function to display the result as a binary object. If you don’t wrap the expression in a call to bin() , then you’ll get the integer representation of the output.

Up to this point, you’ve coded sample expressions that mostly use one or two different types of operators. However, what if you need to create compound expressions that use several different types of operators, such as comparison, arithmetic, Boolean, and others? How does Python decide which operation runs first?

Consider the following math expression:

There might be ambiguity in this expression. Should Python perform the addition 20 + 4 first and then multiply the result by 10 ? Should Python run the multiplication 4 * 10 first, and the addition second?

Because the result is 60 , you can conclude that Python has chosen the latter approach. If it had chosen the former, then the result would be 240 . This follows a standard algebraic rule that you’ll find in virtually all programming languages.

All operators that Python supports have a precedence compared to other operators. This precedence defines the order in which Python runs the operators in a compound expression.

In an expression, Python runs the operators of highest precedence first. After obtaining those results, Python runs the operators of the next highest precedence. This process continues until the expression is fully evaluated. Any operators of equal precedence are performed in left-to-right order.

Here’s the order of precedence of the Python operators that you’ve seen so far, from highest to lowest:

Operators	Description
	Exponentiation
, ,	Unary positive, unary negation, bitwise negation
, , ,	Multiplication, division, floor division,
,	Addition, subtraction
,	Bitwise shifts
	Bitwise AND
	Bitwise XOR
	Bitwise OR
, , , , , , , , ,	Comparisons, identity, and membership
	Boolean NOT
	Boolean AND
	Boolean OR
	Walrus

Operators at the top of the table have the highest precedence, and those at the bottom of the table have the lowest precedence. Any operators in the same row of the table have equal precedence.

Getting back to your initial example, Python runs the multiplication because the multiplication operator has a higher precedence than the addition one.

Here’s another illustrative example:

In the example above, Python first raises 3 to the power of 4 , which equals 81 . Then, it carries out the multiplications in order from left to right: 2 * 81 = 162 and 162 * 5 = 810 .

You can override the default operator precedence using parentheses to group terms as you do in math. The subexpressions in parentheses will run before expressions that aren’t in parentheses.

Here are some examples that show how a pair of parentheses can affect the result of an expression:

In the first example, Python computes the expression 20 + 4 first because it’s wrapped in parentheses. Then Python multiplies the result by 10 , and the expression returns 240 . This result is completely different from what you got at the beginning of this section.

In the second example, Python evaluates 4 * 5 first. Then it raises 3 to the power of the resulting value. Finally, Python multiplies the result by 2 , returning 6973568802 .

There’s nothing wrong with making liberal use of parentheses, even when they aren’t necessary to change the order of evaluation. Sometimes it’s a good practice to use parentheses because they can improve your code’s readability and relieve the reader from having to recall operator precedence from memory.

Consider the following example:

Here the parentheses are unnecessary, as the comparison operators have higher precedence than and . However, some might find the parenthesized version clearer than the version without parentheses:

On the other hand, some developers might prefer this latter version of the expression. It’s a matter of personal preference. The point is that you can always use parentheses if you feel that they make your code more readable, even if they aren’t necessary to change the order of evaluation.

So far, you’ve learned that a single equal sign ( = ) represents the assignment operator and allows you to assign a value to a variable. Having a right-hand operand that contains other variables is perfectly valid, as you’ve also learned. In particular, the expression to the right of the assignment operator can include the same variable that’s on the left of the operand.

That last sentence may sound confusing, so here’s an example that clarifies the point:

In this example, total is an accumulator variable that you use to accumulate successive values. You should read this example as total is equal to the current value of total plus 5 . This expression effectively increases the value of total , which is now 15 .

Note that this type of assignment only makes sense if the variable in question already has a value. If you try the assignment with an undefined variable, then you get an error:

In this example, the count variable isn’t defined before the assignment, so it doesn’t have a current value. In consequence, Python raises a NameError exception to let you know about the issue.

This type of assignment helps you create accumulators and counter variables, for example. Therefore, it’s quite a common task in programming. As in many similar cases, Python offers a more convenient solution. It supports a shorthand syntax called augmented assignment :

In the highlighted line, you use the augmented addition operator ( += ). With this operator, you create an assignment that’s fully equivalent to total = total + 5 .

Python supports many augmented assignment operators. In general, the syntax for this type of assignment looks something like this:

Note that the dollar sign ( $ ) isn’t a valid Python operator. In this example, it’s a placeholder for a generic operator. The above statement works as follows:

Evaluate expression to produce a value.
Run the operation defined by the operator that prefixes the assignment operator ( = ), using the current value of variable and the return value of expression as operands.
Assign the resulting value back to variable .

The table below shows a summary of the augmented operators for arithmetic operations:

Operator	Description	Sample Expression	Equivalent Expression
	Adds the right operand to the left operand and stores the result in the left operand
	Subtracts the right operand from the left operand and stores the result in the left operand
	Multiplies the right operand with the left operand and stores the result in the left operand
	Divides the left operand by the right operand and stores the result in the left operand
	Performs of the left operand by the right operand and stores the result in the left operand
	Finds the remainder of dividing the left operand by the right operand and stores the result in the left operand
	Raises the left operand to the power of the right operand and stores the result in the left operand

As you can conclude from this table, all the arithmetic operators have an augmented version in Python. You can use these augmented operators as a shortcut when creating accumulators, counters, and similar objects.

Did the augmented arithmetic operators look neat and useful to you? The good news is that there are more. You also have augmented bitwise operators in Python:

Operator	Operation	Example	Equivalent
	Augmented bitwise AND ( )
	Augmented bitwise OR ( )
	Augmented bitwise XOR ( )
	Augmented bitwise right shift
	Augmented bitwise left shift

Finally, the concatenation and repetition operators have augmented variations too. These variations behave differently with mutable and immutable data types:

Operator	Description	Example
	• Runs an augmented concatenation operation on the target sequence. • Mutable sequences are updated in place. • If the sequence is immutable, then a new sequence is created and assigned back to the target name.
	• Adds to itself times. • Mutable sequences are updated in place. • If the sequence is immutable, then a new sequence is created and assigned back to the target name.

Note that the augmented concatenation operator works on two sequences, while the augmented repetition operator works on a sequence and an integer number.

Now you know what operators Python supports and how to use them. Operators are symbols, combinations of symbols, or keywords that you can use along with Python objects to build different types of expressions and perform computations in your code.

In this tutorial, you’ve learned:

What Python’s arithmetic operators are and how to use them in arithmetic expressions
What Python’s comparison , Boolean , identity , membership operators are
How to write expressions using comparison, Boolean, identity, and membership operators
Which bitwise operators Python supports and how to use them
How to combine and repeat sequences using the concatenation and repetition operators
What the augmented assignment operators are and how they work

In other words, you’ve covered an awful lot of ground! If you’d like a handy cheat sheet that can jog your memory on all that you’ve learned, then click the link below:

With all this knowledge about operators, you’re better prepared as a Python developer. You’ll be able to write better and more robust expressions in your code.

🐍 Python Tricks 💌

Get a short & sweet Python Trick delivered to your inbox every couple of days. No spam ever. Unsubscribe any time. Curated by the Real Python team.

About Leodanis Pozo Ramos

Leodanis is an industrial engineer who loves Python and software development. He's a self-taught Python developer with 6+ years of experience. He's an avid technical writer with a growing number of articles published on Real Python and other sites.

Each tutorial at Real Python is created by a team of developers so that it meets our high quality standards. The team members who worked on this tutorial are:

Master Real-World Python Skills With Unlimited Access to Real Python

Join us and get access to thousands of tutorials, hands-on video courses, and a community of expert Pythonistas:

What Do You Think?

What’s your #1 takeaway or favorite thing you learned? How are you going to put your newfound skills to use? Leave a comment below and let us know.

Commenting Tips: The most useful comments are those written with the goal of learning from or helping out other students. Get tips for asking good questions and get answers to common questions in our support portal . Looking for a real-time conversation? Visit the Real Python Community Chat or join the next “Office Hours” Live Q&A Session . Happy Pythoning!

Keep Learning

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.

Why does Python assignment not return a value?

Why is Python assignment a statement rather than an expression? If it was an expression which returns the value of the right hand side in the assignment, it would have allowed for much less verbose code in some cases. Are there any issues I can't see?

For example:

could have been rewritten as:

Well, to be precise, the above won't work because x would be treated as a keyword argument. But another pair of parens (or another symbol for keyword arguments) would have resolved that.

language-design

What does your code example have to do with the question? – Ignacio Vazquez-Abrams Commented Feb 2, 2011 at 1:16
@Ignacio: my mistake. The version edited (@Laurence Gonsalves) is good. – max Commented Feb 2, 2011 at 2:09
2 "Are there any issues I can't see?" It appears that "much less verbose code" is somehow not a problem. Terse, cryptic code golf seems like an issue. Are you discounting that one for some reason? – S.Lott Commented Feb 2, 2011 at 2:17
@S Lott: I guess I was thinking of simple examples (like the one I gave, which I don't see as too cryptic); I agree that the ability to abuse this might be one of the reasons against this feature. – max Commented Feb 3, 2011 at 17:14
I like this question and other questions like it. I believe the answers and comments are very constructive and helpful. I'm just amazed the closure police hasn't shut it down already as NC ;-) – cfi Commented Feb 19, 2013 at 9:26

5 Answers 5

There are many who feel that having assignments be expressions, especially in languages like Python where any value is allowable in a condition (not just values of some boolean type), is error-prone. Presumably Guido is/was among those who feel that way. The classic error is:

The situation is also a bit more complicated in Python than it is in a language like C, since in Python the first assignment to a variable is also its declaration. For example:

In these two functions the " print x " lines do different things: one refers to the global variable x , and the other refers to the local variable x . The x in g is local because of the assignment. This could be even more confusing (than it already is) if it was possible to bury the assignment inside some larger expression/statement.

20 The "= vs ==" thing is a red herring. It hasn't been an actual problem in C/C++ for years, ever since compilers learned how to warn about it. I've been using both languages for over ten years and I can't remember the last time I was bitten by that. – Glenn Maynard Commented Feb 2, 2011 at 4:11
19 @Glenn: Python doesn't have a compiler to warn you, there is no concept of "almost syntax errors" like that. – Lennart Regebro Commented Feb 2, 2011 at 9:20
6 @Glenn: But since its used at runtime it can't warn about these things in the same sense. Compiler warnings in C are sort of "almost syntax errors", it says "Are you really sure you want this". That concept has no Python equivalent. It's either correct, or it's a syntax error. And Python tries to avoid supporting things that lead newbies to make errors. :-) – Lennart Regebro Commented Feb 2, 2011 at 12:04
13 @Lennart: Trying to prevent beginners from making beginner mistakes is futile and not--at least not by itself, and at the expense of something else--a good design rationale; and "we can't do that with a warning because our warning system isn't discoverable enough" points at a problem with the warning system or the documentation--you don't design a language around the warning system, you do the reverse. – Glenn Maynard Commented Feb 2, 2011 at 22:23
8 The point again being that there is no "compile time" in normal usage of the word, as compiling is done on demand during running. Which is the difference I have been pointing out all the time here. It's getting boring repeating myself, so I'm going to stop now. – Lennart Regebro Commented Feb 3, 2011 at 9:18

Assignment (sub-)expressions (x := y) are supported since Python 3.8 (released Oct. 2019), so you can indeed now rewrite your example as lst.append(x := X()) .

The proposal, PEP 572 , was formally accepted by Guido in July 2018. There had also been earlier proposals for assignment expressions, such as the withdrawn PEP 379 .

Recall that until version 3, print was also a statement rather than an expression.

The statement x = y = z to assign the same value to multiple targets (or rather, multiple target-lists , since unpacking is also permitted) was already supported (e.g. since version 1) but is implemented as a special syntax rather than by chaining successive assignment sub-expressions. Indeed, the order in which the individual assignments are performed is reversed: nested walruses (x := (y := z)) must assign to y before x , whereas x = y = z assigns to x before y (which may be pertinent if you set/assign to the subscripts or attributes of a class that has been overloaded to create some side-effect).

2 You should just edit the text to contain the current information without the update part :) – Antti Haapala -- Слава Україні Commented Jul 17, 2018 at 16:24
1 BTW, How does a = b = 3 work in the first place when it is not an expression? – huggie Commented Jul 18, 2018 at 2:17
2 @huggie The same way (a*2 for a in b if a) and other compounds work. The entirety of a = b = 3 is one assignment statement, not two expressions as in a = (b:=3) . Compare with container literals, which are also of arbitrary element size - (a, b, 3) is not the same as (a, (b, 3)) . – user5349916 Commented Jul 26, 2018 at 11:10
2 It's going in 3.8. – Ciro Santilli OurBigBook.com Commented Jul 27, 2019 at 9:49
Thanks! Now I can write something like master = [] while(str.lower(n := input('Enter number to append to master or q to quit: ')) != 'q'): master.append(int(n)) – Bala TJ Commented Feb 12, 2020 at 5:32

The real-world answer: it's not needed.

Most of the cases you see this in C are because of the fact that error handling is done manually:

Similarly for the way many loops are written:

These common cases are done differently in Python. Error handling typically uses exception handling; loops typically use iterators.

The arguments against it aren't necessarily earth-shattering, but they're weighed against the fact that it simply isn't that important in Python.

3 Sometimes you may need things like while (x[k] += 1) <= limit: ... ; you could rewrite it without the assignment as an expression, but that requires a non-trivial restructuring. – musiphil Commented Dec 31, 2014 at 0:44

I believe this was deliberate on Guido's part in order to prevent certain classic errors. E.g.

when you actually meant to say

I do agree there are times I wished it would work, but I also miss { and } around a block of code, and that sure isn't going to change.

Python's syntax is much less verbose than C's syntax.
It has much more sophisticated scope rules than C.
To use parentheses in every single expression reduces the code readability and python avoids that.

If assigments were expressions, these and many other features would have to be re-worked. For me it is like a deal you have to make in order to have such readable code and useful features. In order to have

rather than

[not talking about the classic (if a = b:) kind of error.]

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 python-3.x language-design or ask your own question .

The Overflow Blog
Where developers feel AI coding tools are working—and where they’re missing...
He sold his first company for billions. Now he’s building a better developer...
Featured on Meta
User activation: Learnings and opportunities
Preventing unauthorized automated access to the network
Should low-scoring meta questions no longer be hidden on the Meta.SO home...
Announcing the new Staging Ground Reviewer Stats Widget

Hot Network Questions

How old was Abraham when Rebecca (Isaac's wife) was born?
Story from the mid-20th century about a biochemist who finds youth algae
Do early termination fees hold up in court?
Why would an escrow/title company not accept ACH payments?
Why the proper acceleration is zero during free fall?
Will a car seat fit into a standard economy class seat on a plane?
How to do distance based sorting in Sitecore Search
Unable to re-use an old deleted Apple Account (aka Apple ID)
Is the Earth still capable of massive volcanism, like the kind that caused the formation of the Siberian Traps?
Two parallel lines in a parabola with a ratio of 1/3
Soldering a thermal fuse. 92°C
Why was Z moved to the end of the alphabet when Zeta was near the beginning?
Why would an ocean world prevent the creation of ocean bases but allow ships?
Is there any language which distinguishes between “un” as in “not” and “un” as in “inverse”?
Tikz template for organization chart
Can a floppy disk be wiped securely using the Windows format command with the passes-parameter?
How can the doctor measure out a dose (dissolved in water) of exactly 10% of a tablet?
How was the year spoken in late 1800s England?
Is "into" a verb in this sentence?
What should you list as location in job application?
What is the mechanical equivalent of an electronic AND gate?
Expected value of a matrix = matrix of expected value?
Meaning of "wordplay from definition"
A military space Saga with a woman who is a brilliant tactician and strategist

IMAGES

What are Python Assignment Expressions and Using the Walrus Operator
Python Operators and Expressions
Python Tutorials: Assignment Operators In python
Assignment Operators in Python
Python Operator
Assignment operators in python

VIDEO

Assignment
Assignment Operator in python|#python #shorts #assignmentoperators #python3 #pythonprogramming
Assignment operator #operator #operator in python #python #code #datascience #pythonfullcourse
Python Assignment Operator: Beginner's Guide by ByteAdmin
"Mastering Assignment Operators in Python: A Comprehensive Guide"
python assignment operator

COMMENTS

Python's Assignment Operator: Write Robust Assignments
Here, variable represents a generic Python variable, while expression represents any Python object that you can provide as a concrete value—also known as a literal—or an expression that evaluates to a value. To execute an assignment statement like the above, Python runs the following steps: Evaluate the right-hand expression to produce a concrete value or object.
The Walrus Operator: Python's Assignment Expressions
Each new version of Python adds new features to the language. Back when Python 3.8 was released, the biggest change was the addition of assignment expressions.Specifically, the := operator gave you a new syntax for assigning variables in the middle of expressions. This operator is colloquially known as the walrus operator.. This tutorial is an in-depth introduction to the walrus operator.
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
Since Python 3.8, code can use the so-called "walrus" operator (:=), documented in PEP 572, for assignment expressions.This seems like a really substantial new feature, since it allows this form of assignment within comprehensions and lambdas.. What exactly are the syntax, semantics, and grammar specifications of assignment expressions?
Assignment Operators in Python
The Walrus Operator in Python is a new assignment operator which is introduced in Python version 3.8 and higher. This operator is used to assign a value to a variable within an expression. Syntax: a := expression. Example: In this code, we have a Python list of integers. We have used Python Walrus assignment operator within the Python while loop.
6. Expressions
assignment_expression::= [identifier ":="] expression. ... The following table summarizes the operator precedence in Python, from highest precedence (most binding) to lowest precedence (least binding). Operators in the same box have the same precedence. Unless the syntax is explicitly given, operators are binary.
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.. Assignment expressions allow you to assign and return a value in the same expression.
How To Use Assignment Expressions in Python
The author selected the COVID-19 Relief Fund to receive a donation as part of the Write for DOnations program.. 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. ...
Python's Walrus Operator: The Assignment Expression (Tutorial)
Python 3.8 introduced a new operator to the language. Its official name is the assignment expression, and it uses the := operator.. However, it's more commonly called the walrus operator as it looks like the tasks of a walrus!. There was controversy in the normally calm Python world when this operator was added to the language, and its use is still relatively limited.
Python Assignment Operators
Reset. Assignment operators in Python. The above code is useful when we want to update the same number. We can also use two different numbers and use the assignment operators to apply them on two different values. num_one = 6. num_two = 3. print(num_one) num_one += num_two. print(num_one)
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 Assignment Operator. The = (equal to) symbol is defined as assignment operator in Python. The value of Python expression on its right is assigned to a single variable on its left. The = symbol as in programming in general (and Python in particular) should not be confused with its usage in Mathematics, where it states that the expressions on the either side of the symbol are equal.
7. Simple statements
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.
Python Assignment Operators
Multiplication and Assignment Operator. The multiplication and assignment operator multiplies the right-side operand with the left-side operand, and then the result is assigned to the left-hand side operand. Below code is equivalent to: a = a * 2. In [1]: a = 3 a *= 2 print(a) 6.
Python Operators: Arithmetic, Assignment, Comparison, Logical, Identity
Python Operators: Arithmetic, Assignment, Comparison, Logical, Identity, Membership, Bitwise. Operators are special symbols that perform some operation on operands and returns the result. For example, 5 + 6 is an expression where + is an operator that performs arithmetic add operation on numeric left operand 5 and the right side operand 6 and ...
Python Operators (With Examples)
Here's a list of different assignment operators available in Python. Operator Name Example = Assignment Operator: a = 7 += Addition Assignment: a += 1 # a = a + 1-= Subtraction Assignment: ... Logical operators are used to check whether an expression is True or False. They are used in decision-making. For example, a = 5 b = 6 print((a > 2) and ...
Python Operators
Python Assignment Operators. Assignment operators are used to assign values to variables: Operator Example Same As Try it = x = 5: x = 5: ... Parentheses has the highest precedence, meaning that expressions inside parentheses must be evaluated first: print((6 + 3) - (6 + 3))
Operators and Expressions in Python
For a deep dive into how this operator works, check out The Walrus Operator: Python's Assignment Expressions. Unlike regular assignments, assignment expressions do have a return value, which is why they're expressions. So, the operator accomplishes two tasks: ... In an expression, Python runs the operators of highest precedence first. After ...
How does Python's comma operator work during assignment?
32. Python does not have a "comma operator" as in C. Instead, the comma indicates that a tuple should be constructed. The right-hand side of. a, b = a + b, a. is a tuple with th two items a + b and a. On the left-hand side of an assignment, the comma indicates that sequence unpacking should be performed according to the rules you quoted: a will ...
10. Повна граматична специфікація
Це повна граматика Python, отримана безпосередньо з граматики, яка використовувалася для ...
python
Note that in Python, unlike C, assignment cannot occur inside expressions. C programmers may grumble about this, but it avoids a common class of problems encountered in C programs: typing = in an expression when == was intended. ... PEP 572 proposes Assignment Expressions and has already been accepted. ... The assignment operator - also known ...
Why does Python assignment not return a value?
Assignment (sub-)expressions (x := y) are supported since Python 3.8 (released Oct. 2019), so you can indeed now rewrite your example as lst.append(x := X()).. The proposal, PEP 572, was formally accepted by Guido in July 2018.There had also been earlier proposals for assignment expressions, such as the withdrawn PEP 379.. Recall that until version 3, print was also a statement rather than an ...

Assignment Operators in Python

Assignment Operator

Addition Assignment Operator

S ubtraction Assignment Operator

M ultiplication Assignment Operator

D ivision Assignment Operator

M odulus Assignment Operator

F loor Division Assignment Operator

Exponentiation Assignment Operator

Bitwise AND Assignment Operator

Bitwise OR Assignment Operator

Bitwise XOR Assignment Operator

Bitwise Right Shift Assignment Operator

Bitwise Left Shift Assignment Operator

Walrus Operator

Assignment Operators in Python – FAQs

What is the := Operator in Python?

What is the Assignment Operator in Structure?

What is the Assignment Operator in Python Dictionary?

What is += and -= in Python?

Similar Reads

Please Login to comment...

Improve your Coding Skills with Practice

What kind of Experience do you want to share?

Assignment Operators

Python - Assignment Operators

Python Assignment Operator

Example of Assignment Operator in Python

Augmented Assignment Operators in Python

Augmented Addition Operator (+=)

Augmented Subtraction Operator (-=)

Augmented Multiplication Operator (*=)

Augmented Division Operator (/=)

Augmented Modulus Operator (%=)

Augmented Exponent Operator (**=)

Augmented Floor division Operator (//=)

Python Assignment Operators

Assignment Operators

Addition and Assignment Operator

Subtraction and Assignment Operator

Multiplication and Assignment Operator

Division and Assignment Operator

Modulus and Assignment Operator

Floor Division and Assignment Operator

Exponential and Assignment Operator

Bitwise AND and Assignment Operator

Bitwise OR and Assignment Operator

Bitwise XOR and Assignment Operator

Bitwise Right Shift and Assignment Operator

Bitwise Left Shift and Assignment Operator

References:

Python Operators: Arithmetic, Assignment, Comparison, Logical, Identity, Membership, Bitwise

Arithmetic Operators

Popular Tutorials

Python Fundamentals

Python Operators

Python Data types

Python Files

Python Object & Class

Python Advanced Topics

Python Date and Time

Additional Topic

Python Tutorials

1. Python Arithmetic Operators

Example 1: Arithmetic Operators in Python

2. Python Assignment Operators

Example 2: Assignment Operators

3. Python Comparison Operators

Example 3: Comparison Operators

4. Python Logical Operators

Example 4: Logical Operators

5. Python Bitwise operators

6. Python Special operators

Example 4: Identity operators in Python

Example 5: Membership operators in Python

Table of Contents

Video: Operators in Python

Related Tutorials

Python Tutorial

Python Arithmetic Operators