how to use assignment operator in python

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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

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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.

01 Career Opportunities

02 beginner, 03 intermediate, 04 training programs, assignment operators in python, what is an assignment operator in python.

Types of Assignment Operators in Python

1. simple python assignment operator (=), example of simple python assignment operator, 2. augmented assignment operators in python, 1. augmented arithmetic assignment operators in python.


+=	Addition Assignment Operator
-=	Subtraction Assignment Operator
*=	Multiplication Assignment Operator
/=	Division Assignment Operator
%=	Modulus Assignment Operator
//=	Floor Division Assignment Operator
**=	Exponentiation Assignment Operator

2. Augmented Bitwise Assignment Operators in Python


&=	Bitwise AND Assignment Operator
\|=	Bitwise OR Assignment Operator
^=	Bitwise XOR Assignment Operator
>>=	Bitwise Right Shift Assignment Operator
<<=	Bitwise Left Shift Assignment Operator

Augmented Arithmetic Assignment Operators in Python

1. augmented addition operator (+=), example of augmented addition operator in python, 2. augmented subtraction operator (-=), example of augmented subtraction operator in python, 3. augmented multiplication operator (*=), example of augmented multiplication operator in python, 4. augmented division operator (/=), example of augmented division operator in python, 5. augmented modulus operator (%=), example of augmented modulus operator in python, 6. augmented floor division operator (//=), example of augmented floor division operator in python, 7. augmented exponent operator (**=), example of augmented exponent operator in python, augmented bitwise assignment operators in python, 1. augmented bitwise and (&=), example of augmented bitwise and operator in python, 2. augmented bitwise or (|=), example of augmented bitwise or operator in python, 3. augmented bitwise xor (^=), example of augmented bitwise xor operator in python, 4. augmented bitwise right shift (>>=), example of augmented bitwise right shift operator in python, 5. augmented bitwise left shift (<<=), example of augmented bitwise left shift operator in python, walrus operator in python, syntax of an assignment expression, example of walrus operator in python.

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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.

Python Assignment Operators

Python Assignment Operators	Example	Explanation
=	x= 25	Value 25 is assigned to x
+=	x += 25	This is same as x = x + 25
-=	x -= 25	Same as x = x – 25
*=	x *= 25	This is same as x = x * 25
/=	x /= 25	Same as x = x / 25
%=	x %= 25	This is identical to x = x % 25
//=	x //= 25	Same as x = x // 25
**=	x **= 25	This is same as x = x ** 25
&=	x &= 25	This is same as x = x & 25
\|=	x \|= 25	This is same as x = x \| 25
^=	x ^= 25	Same as x = x ^ 25
<<=	x <<= 25	This is same as x = x << 25
>>=	x >>= 25	Same as x = x >> 25

Python Assignment Operators Example

Python Assignment Operators

Lesson Contents

Python assignment operators are one of the operator types and assign values to variables . We use arithmetic operators here in combination with a variable.

Let’s take a look at some examples.

Operator Assignment (=)

This is the most basic assignment operator and we used it before in the lessons about lists , tuples , and dictionaries . For example, we can assign a value (integer) to a variable:

Operator Addition (+=)

We can add a number to our variable like this:

Using the above operator is the same as doing this:

The += operator is shorter to write but the end result is the same.

Operator Subtraction (-=)

We can also subtract a value. For example:

Using this operator is the same as doing this:

Operator Multiplication (*=)

We can also use multiplication. We’ll multiply our variable by 4:

Which is similar to:

Operator Division (/=)

Let’s try the divide operator:

This is the same as:

Operator Modulus (%=)

We can also calculate the modulus. How about this:

This is the same as doing it like this:

Operator Exponentiation (**=)

How about exponentiation? Let’s give it a try:

Which is the same as doing it like this:

Operator Floor Division (//=)

The last one, floor division:

You have now learned how to use the Python assignment operators to assign values to variables and how you can use them with arithmetic operators . I hope you enjoyed this lesson. If you have any questions, please leave a comment.

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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

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Assignment operator in python.

Last Updated on June 8, 2023 by Prepbytes

how to use assignment operator in python

To fully comprehend the assignment operators in Python, it is important to have a basic understanding of what operators are. Operators are utilized to carry out a variety of operations, including mathematical, bitwise, and logical operations, among others, by connecting operands. Operands are the values that are acted upon by operators. In Python, the assignment operator is used to assign a value to a variable. The assignment operator is represented by the equals sign (=), and it is the most commonly used operator in Python. In this article, we will explore the assignment operator in Python, how it works, and its different types.

What is an Assignment Operator in Python?

The assignment operator in Python is used to assign a value to a variable. The assignment operator is represented by the equals sign (=), and it is used to assign a value to a variable. When an assignment operator is used, the value on the right-hand side is assigned to the variable on the left-hand side. This is a fundamental operation in programming, as it allows developers to store data in variables that can be used throughout their code.

For example, consider the following line of code:

Explanation: In this case, the value 10 is assigned to the variable a using the assignment operator. The variable a now holds the value 10, and this value can be used in other parts of the code. This simple example illustrates the basic usage and importance of assignment operators in Python programming.

Types of Assignment Operator in Python

There are several types of assignment operator in Python that are used to perform different operations. Let’s explore each type of assignment operator in Python in detail with the help of some code examples.

1. Simple Assignment Operator (=)

The simple assignment operator is the most commonly used operator in Python. It is used to assign a value to a variable. The syntax for the simple assignment operator is:

Here, the value on the right-hand side of the equals sign is assigned to the variable on the left-hand side. For example

Explanation: In this case, the value 25 is assigned to the variable a using the simple assignment operator. The variable a now holds the value 25.

2. Addition Assignment Operator (+=)

The addition assignment operator is used to add a value to a variable and store the result in the same variable. The syntax for the addition assignment operator is:

Here, the value on the right-hand side is added to the variable on the left-hand side, and the result is stored back in the variable on the left-hand side. For example

Explanation: In this case, the value of a is incremented by 5 using the addition assignment operator. The result, 15, is then printed to the console.

3. Subtraction Assignment Operator (-=)

The subtraction assignment operator is used to subtract a value from a variable and store the result in the same variable. The syntax for the subtraction assignment operator is

Here, the value on the right-hand side is subtracted from the variable on the left-hand side, and the result is stored back in the variable on the left-hand side. For example

Explanation: In this case, the value of a is decremented by 5 using the subtraction assignment operator. The result, 5, is then printed to the console.

4. Multiplication Assignment Operator (*=)

The multiplication assignment operator is used to multiply a variable by a value and store the result in the same variable. The syntax for the multiplication assignment operator is:

Here, the value on the right-hand side is multiplied by the variable on the left-hand side, and the result is stored back in the variable on the left-hand side. For example

Explanation: In this case, the value of a is multiplied by 5 using the multiplication assignment operator. The result, 50, is then printed to the console.

5. Division Assignment Operator (/=)

The division assignment operator is used to divide a variable by a value and store the result in the same variable. The syntax for the division assignment operator is:

Here, the variable on the left-hand side is divided by the value on the right-hand side, and the result is stored back in the variable on the left-hand side. For example

Explanation: In this case, the value of a is divided by 5 using the division assignment operator. The result, 2.0, is then printed to the console.

6. Modulus Assignment Operator (%=)

The modulus assignment operator is used to find the remainder of the division of a variable by a value and store the result in the same variable. The syntax for the modulus assignment operator is

Here, the variable on the left-hand side is divided by the value on the right-hand side, and the remainder is stored back in the variable on the left-hand side. For example

Explanation: In this case, the value of a is divided by 3 using the modulus assignment operator. The remainder, 1, is then printed to the console.

7. Floor Division Assignment Operator (//=)

The floor division assignment operator is used to divide a variable by a value and round the result down to the nearest integer, and store the result in the same variable. The syntax for the floor division assignment operator is:

Here, the variable on the left-hand side is divided by the value on the right-hand side, and the result is rounded down to the nearest integer. The rounded result is then stored back in the variable on the left-hand side. For example

Explanation: In this case, the value of a is divided by 3 using the floor division assignment operator. The result, 3, is then printed to the console.

8. Exponentiation Assignment Operator (**=)

The exponentiation assignment operator is used to raise a variable to the power of a value and store the result in the same variable. The syntax for the exponentiation assignment operator is:

Here, the variable on the left-hand side is raised to the power of the value on the right-hand side, and the result is stored back in the variable on the left-hand side. For example

Explanation: In this case, the value of a is raised to the power of 3 using the exponentiation assignment operator. The result, 8, is then printed to the console.

9. Bitwise AND Assignment Operator (&=)

The bitwise AND assignment operator is used to perform a bitwise AND operation on the binary representation of a variable and a value, and store the result in the same variable. The syntax for the bitwise AND assignment operator is:

Here, the variable on the left-hand side is ANDed with the value on the right-hand side using the bitwise AND operator, and the result is stored back in the variable on the left-hand side. For example,

Explanation: In this case, the value of a is ANDed with 3 using the bitwise AND assignment operator. The result, 2, is then printed to the console.

10. Bitwise OR Assignment Operator (|=)

The bitwise OR assignment operator is used to perform a bitwise OR operation on the binary representation of a variable and a value, and store the result in the same variable. The syntax for the bitwise OR assignment operator is:

Here, the variable on the left-hand side is ORed with the value on the right-hand side using the bitwise OR operator, and the result is stored back in the variable on the left-hand side. For example,

Explanation: In this case, the value of a is ORed with 3 using the bitwise OR assignment operator. The result, 7, is then printed to the console.

11. Bitwise XOR Assignment Operator (^=)

The bitwise XOR assignment operator is used to perform a bitwise XOR operation on the binary representation of a variable and a value, and store the result in the same variable. The syntax for the bitwise XOR assignment operator is:

Here, the variable on the left-hand side is XORed with the value on the right-hand side using the bitwise XOR operator, and the result are stored back in the variable on the left-hand side. For example,

Explanation: In this case, the value of a is XORed with 3 using the bitwise XOR assignment operator. The result, 5, is then printed to the console.

12. Bitwise Right Shift Assignment Operator (>>=)

The bitwise right shift assignment operator is used to shift the bits of a variable to the right by a specified number of positions, and store the result in the same variable. The syntax for the bitwise right shift assignment operator is:

Here, the variable on the left-hand side has its bits shifted to the right by the number of positions specified by the value on the right-hand side, and the result is stored back in the variable on the left-hand side. For example,

Explanation: In this case, the value of a is shifted 2 positions to the right using the bitwise right shift assignment operator. The result, 2, is then printed to the console.

13. Bitwise Left Shift Assignment Operator (<<=)

The bitwise left shift assignment operator is used to shift the bits of a variable to the left by a specified number of positions, and store the result in the same variable. The syntax for the bitwise left shift assignment operator is:

Here, the variable on the left-hand side has its bits shifted to the left by the number of positions specified by the value on the right-hand side, and the result is stored back in the variable on the left-hand side. For example,

Conclusion Assignment operator in Python is used to assign values to variables, and it comes in different types. The simple assignment operator (=) assigns a value to a variable. The augmented assignment operators (+=, -=, *=, /=, %=, &=, |=, ^=, >>=, <<=) perform a specified operation and assign the result to the same variable in one step. The modulus assignment operator (%) calculates the remainder of a division operation and assigns the result to the same variable. The bitwise assignment operators (&=, |=, ^=, >>=, <<=) perform bitwise operations and assign the result to the same variable. The bitwise right shift assignment operator (>>=) shifts the bits of a variable to the right by a specified number of positions and stores the result in the same variable. The bitwise left shift assignment operator (<<=) shifts the bits of a variable to the left by a specified number of positions and stores the result in the same variable. These operators are useful in simplifying and shortening code that involves assigning and manipulating values in a single step.

Here are some Frequently Asked Questions on Assignment Operator in Python:

Q1 – Can I use the assignment operator to assign multiple values to multiple variables at once? Ans – Yes, you can use the assignment operator to assign multiple values to multiple variables at once, separated by commas. For example, "x, y, z = 1, 2, 3" would assign the value 1 to x, 2 to y, and 3 to z.

Q2 – Is it possible to chain assignment operators in Python? Ans – Yes, you can chain assignment operators in Python to perform multiple operations in one line of code. For example, "x = y = z = 1" would assign the value 1 to all three variables.

Q3 – How do I perform a conditional assignment in Python? Ans – To perform a conditional assignment in Python, you can use the ternary operator. For example, "x = a (if a > b) else b" would assign the value of a to x if a is greater than b, otherwise it would assign the value of b to x.

Q4 – What happens if I use an undefined variable in an assignment operation in Python? Ans – If you use an undefined variable in an assignment operation in Python, you will get a NameError. Make sure you have defined the variable before trying to assign a value to it.

Q5 – Can I use assignment operators with non-numeric data types in Python? Ans – Yes, you can use assignment operators with non-numeric data types in Python, such as strings or lists. For example, "my_list += [4, 5, 6]" would append the values 4, 5, and 6 to the end of the list named my_list.

Assignment Operators in Python

Table of Contents

Assignment Operators will work on values and variables. They are the special symbols that hold arithmetic, logical, and bitwise computations. The value which the operator operates is referred to as the Operand.

Read this article about Assignment Operators in Python

What are Assignment Operators?

The assignment operator will function to provide value to variables. The table below is about the different types of Assignment operator


+=	will add right side operand with left side operand, assign to left operand	a+=b
=	It will assign the value of the right side of the expression to the left side operand	x=y+z
-=	can subtract the right operand from the left operand and then assign it to the left operand: True if both operands are equal	a -= b
*=	can subtract the right operand from the left operand and then assign it to the left operand: True if both operands are equal	a *= b
/=	will divide the left operand with right operand and then assign to the left operand	a /= b
%=	will divide the left operand with the right operand and then assign to the left operand	a %= b
<<=	It functions bitwise left on operands and will assign value to the left operand	a <<= b
>>=	This operator will perform right shift on operands and can assign value to the left operand	a >>= b
^=	This will function the bitwise xOR operands and can assign value to the left operand	a ^= b
\|=	This will function Bitwise OR operands and will provide value to the left operand.	a \|= b
&=	This operator will perform Bitwise AND on operand and can provide value to the left operand	a&=b
**=	operator will evaluate the exponent value with the help of operands an assign value to the left operand	a**=b

Here we have listed each of the Assignment operators

1. What is Assign Operator?

This assign operator will provide the value of the right side of the expression to the left operand.

2. What is Add and Assign

This Add and Assign operator will function to add the right side operand with the left side operator, and provide the result to the left operand.

3. What is Subtract and assign ?

This subtract and assign operator works to subtract the right operand from the left operand and give the result to the left operand.

4. What is Multiply and assign ?

This Multiply and assign will function to multiply the right operand with the left operand and will provide the result in the left operand.

5. What is Divide and assign Operator?

This functions to divide the left operand and provides results at the left operand.

6. What is Modulus and Assign Operator?

This operator functions using the modulus with the left and the right operand and provides results at the left operand.

7. What is Divide ( floor)and Assign Operator?

This operator will divide the left operand with the right operand, and provide the result at the left operand.

8. What is Exponent and Assign Operator?

This operator will function to evaluate the exponent and value with the operands and, provide output in the left operand.

9.What is Bitwise and Assign Operator?

This operator will function Bitwise AND on both the operand and provide the result on the left operand.

10. What is Bitwise OR and Assign Operator?

This operand will function Bitwise OR on the operand, and can provide result at the left operand.

11. What is Bitwise XOR and Assign Operator?

This operator will function for Bitwise XOR on the operands, and provide result at the left operand.

12. What is Bitwise Right Shift and Assign Operator?

This operator will function by providing the Bitwise shift on the operands and giving the result at the left operand.

13. What is Bitwise Left shift and Assign Operator?

This operator will function Bitwise left shift by providing the Bitwise left shift on the operands and giving the result on the left operand.

To conclude, different types of assignment operators are discussed in this. Beginners can improve their knowledge and understand how to apply the assignment operators through reading this.

Assignment Operators in Python- FAQs

Q1. what is an assignment statement in python.

Ans. It will calculate the expression list and can provide a single resulting object to each target list from left to right

Q2. What is the compound operator in Python?

Ans. The compound operator will do the operation of a binary operator and will save the result of the operation at the left operand.

Q3. What are the two types of assignment statements

Ans. Simple Assignment Statements and Reference Assignment Statements are the two types of assignment statements.

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If that is about as clear as mud don't worry we're going to walk through a number of examples. And one very nice thing about the syntax for assignment operators is that it is nearly identical to a standard type of operator. So if you memorize the list of all the python operators then you're going to be able to use each one of these assignment operators quite easily.

The very first thing I'm going to do is let's first make sure that we can print out the total. So right here we have a total and it's an integer that equals 100. Now if we wanted to add say 10 to 100 how would we go about doing that? We could reassign the value total and we could say total and then just add 10. So let's see if this works right here. I'm going to run it and you can see we have a hundred and ten. So that works.

However, whenever you find yourself performing this type of calculation what you can do is use an assignment operator. And so the syntax for that is going to get rid of everything here in the middle and say plus equals and then whatever value. In this case I want to add onto it.

So you can see we have our operator and then right afterward you have an equal sign. And this is going to do is exactly like what we had before. So if I run this again you can see total is a hundred and ten

I'm going to just so you have a reference in the show notes I'm going to say that total equals total plus 10. This is exactly the same as what we're doing right here we're simply using assignment in order to do it.

I'm going to quickly go through each one of the other elements that you can use assignment for. And if you go back and you reference the show notes or your own notes for whenever you kept track of all of the different operators you're going to notice a trend. And that is because they're all exactly the same. So here if I want to subtract 10 from the total I can simply use the subtraction operator here run it again. And now you can see we have 90. Now don't be confused because we only temporarily change the value to 1 10. So when I commented this out and I ran it from scratch it took the total and it subtracted 10 from that total and that's what got printed out.

I'm going to copy this and the next one down the line is going to be multiplication. So in this case I'm going to say multiply with the asterisk the total and I'm just going to say times two just so we can see exactly what the value is going to be. And now we can see that's 200 which makes sense.

So we've taken total we have multiplied it by two and we have piped the entire thing into the total variable. So far so good. As you may have guessed next when we're going to do is division. So now I'm going to say total and then we're going to perform this division assignment and we're going to say divide this by 10 run it and you can see it gives us the value and it converts it to a float of ten point zero.

Now if this is starting to get a little bit much. Let's take a quick pause and see exactly what this is doing. Remember that all we're doing here is it's a shortcut. You could still perform it the same way we have in number 3 I could say total is equal to the total divided by 10. And if I run this you'll see we get ten point zero. And let's see what this warning is it says redefinition of total type from int to float. So we don't have to worry about this and this for if you're building Python programs you're very rarely ever going to see the syntax and it's because we have this assignment operator right here. So that is for division. And we also have the ability to use floor division as well. So if I run this you're going to see it's 10. But one thing you may notice is it's 10 it's not ten point zero. So remember that our floor division returns an integer it doesn't return a floating-point number. So if that is what you want then you can perform that task just like we did there.

Next one on the list is our exponents. I'm going to say the total and we're going to say we're going to assign that to the total squared. So going to run this and we get ten thousand. Just like you'd expect. And we have one more which is the modulus operator. So here remember it is the percent equals 2. And this is going to return zero because 100 is even if we changed 100 to be 101. This is going to return one because remember the typical purpose of the modulus operator is to let you know if you're working with an event or an odd value.

Now with all this being said, I wanted to show you every different option that you could use the assignment operator on. But I want to say that the most common way that you're going to use this or the most common one is going to be this one right here where we're adding or subtracting. So those are going to be the two most common. And what usually you're going to use that for is when you're incrementing or decrementing values so a very common way to do this would actually be like we have our total right here. So we have a total of 100 and you could imagine it being a shopping cart and it's 100 dollars and you could say product 2 and set this equal to 120. And then if I say product 3 and set this equal to 10. And so what I could do here is I could say total plus equals product to and then we could take the value and say product 3 and now if I run this you can see the value is 230.

So that's a very common way whenever you want to generate a sum you can use this type of syntax which is much faster and it's also going to be a more pythonic way it's going to be the way you're going to see in standard Python programs whenever you're wanting to generate a sum and then reset and reassign the value.

So in review, that is how you can use assignment operators in Python.

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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.

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😶 Operators

Python operators are the symbols that allow us to perform different types of operations on variables and values. They are the building blocks of any programming language, and Python is no exception. Python provides a wide range of operators that can be used to perform arithmetic, logical, comparison, assignment, and bitwise operations.

Understanding the different types of operators is crucial to writing efficient and error-free code in Python. In this section, we will explore the different types of operators available in Python and learn how to use them effectively in our programs. So buckle up and get ready to dive into the world of Python operators!

I. Arithmetic Operators

Arithmetic operators are used in Python to perform basic arithmetic operations such as addition, subtraction, multiplication, division, and more. These operators are used on numeric data types such as integers, floats, and complex numbers.

Python provides the following arithmetic operators:

Operator	Name	Example	Result

The floor division (//) operator returns the largest integer that is less than or equal to the division result.

a. Addition

Addition is one of the most basic arithmetic operations in Python. It is denoted by the + symbol and is used to add two numbers or concatenate two strings. For example, if we want to add two numbers x and y together, we can use the + operator like this:

Similarly, if we want to concatenate two strings a and b , we can use the + operator like this:

In both cases, the + operator performs the desired operation and returns a new value that we can assign to a variable or use directly.

b. Subtraction

The subtraction operator (-) is used to subtract one value from another. It takes two operands and returns the difference between them. For example, 5 - 3 will return 2, and 10.5 - 3.2 will return 7.3.

In Python, the subtraction operator can also be used with variables. For example:

Note that the subtraction operator can also be used with negative numbers. For example, 5 - (-3) will return 8.

c. Multiplication

Multiplication is a mathematical operation that is represented by the symbol * in Python. It is used to find the product of two or more values. Here's an example:

In the above example, we have two variables a and b with values 10 and 5 respectively. We multiply these two variables using the * operator and store the result in the variable c . Finally, we print the value of c which is 50 (the product of a and b ).

d. Division

In Python, the / operator is used for division. It returns the quotient (result of division) in the form of a float, even if both the operands are integers. If you want to get the quotient as an integer, you can use the // operator, which performs floor division.

Here's an example:

In the example above, we divide a by b using both the / and // operators. The result of the floating point division is stored in c , which is a float, while the result of the integer division is stored in d , which is an integer.

Modulus operator returns the remainder of the division operation between two operands. It is represented by the percentage sign % .

For example, the expression 9 % 4 returns 1 because when 9 is divided by 4, the remainder is 1.

Here is an example code snippet:

e. Exponentiation

Exponentiation is another arithmetic operator in Python represented by the double asterisk symbol (**). It raises the first operand to the power of the second operand.

Here, the base is the first operand, and the exponent is the second operand.

In the above example, 2 is raised to the power of 3, which results in 8.

f. Floor Division

Floor Division operator in Python is represented by two forward slashes // and it returns the quotient of the division operation rounding down to the nearest integer. For example, the floor division of 7 // 3 would be 2 since 3 goes into 7 two whole times with 1 left over.

Here's an example of using floor division operator:

In the above example, we have defined two variables a and b , and then used floor division operator // to divide a by b . Since a is 10 and b is 3 , the result of a // b is 3 .

II. Comparison Operators

Comparison operators, also known as relational operators, are used to compare two values or operands. In Python, comparison operators always return a boolean value - either True or False.

There are six comparison operators in Python:

Equal to (==)

Not equal to (!=)

Greater than (>)

Less than (<)

Greater than or equal to (>=)

Less than or equal to (<=)

These operators are used in conditional statements and loops to test whether a certain condition is true or false.

a. Equal to (==)

The equal to operator ( == ) is a comparison operator used to compare the equality of two operands. It returns True if the values of the two operands are equal, otherwise, it returns False .

In this example, the first comparison returns False because x is not equal to y . The second comparison returns True because x is equal to z .

b. Not equal to (!=)

In Python, the "not equal to" operator is represented by the exclamation mark followed by an equal sign (!=). It is a binary operator and is used to compare two values. The operator returns True if the values are not equal and False if they are equal.

Here's an example of using the "not equal to" operator in Python:

c. Greater than (>)

The greater than operator ( > ) is used to check if the left operand is greater than the right operand. It returns True if the left operand is greater than the right operand, otherwise, it returns False . Here is an example:

In the example above, x is greater than y , so the expression x > y returns True .

d. Less than (<)

In Python, the less than operator < is used to compare two operands. It returns True if the left operand is less than the right operand, and False otherwise.

In this example, x is less than y , so the if statement evaluates to True , and the first print statement is executed.

e. Greater than or equal to (>=)

The greater than or equal to operator (>=) is used to compare two values. It returns True if the left operand is greater than or equal to the right operand, and False otherwise.

For example:

In this example, the first print statement returns True because x (which is 5) is greater than or equal to y (which is 3). The second print statement returns False because y is less than x .

f. Less than or equal to (<=)

The "Less than or equal to" operator is represented by the symbol "<=". It is used to check if one value is less than or equal to another value.

For example, in the expression "5 <= 10", the operator "<=" checks if 5 is less than or equal to 10. Since this is true, the expression evaluates to True. However, in the expression "10 <= 5", the operator "<=" checks if 10 is less than or equal to 5. Since this is false, the expression evaluates to False.

Here's an example code snippet demonstrating the use of the "<=" operator:

This code will output "x is less than or equal to y", since 5 is indeed less than or equal to 10.

III. Logical Operators

Python Logical Operators are used to combine two or more conditions and perform logical operations on them. The following are the three logical operators in Python:

These operators are used to perform logical operations on the operands and return a Boolean value.

The 'and' operator returns True if both operands are True, otherwise, it returns False.

The 'or' operator returns True if either of the operands is True, otherwise, it returns False.

The 'not' operator returns the opposite of the operand.

Let's look at depth with some examples to understand how these operators work.

The and operator returns True if both operands are true and returns False if either one of the operands is false.

Here's the truth table for the and operator:

Operand 1	Operand 2	Result

Here's an example code snippet:

In this example, the and operator is used to check if x is smaller than both y and z . If this condition is true, then the statement "x is the smallest number" is printed.

The OR operator in Python is represented by or . It is a logical operator that returns True if at least one of the operands is True , and False otherwise. Here are the possible truth tables for the OR operator:

Operand 1	Operand 2	Result

Here's an example of using the OR operator in Python:

In this example, x is not greater than y or z , so the output will be x is not greater than y or z .

The NOT operator is a unary operator that negates the value of its operand. In Python, the NOT operator is represented by the keyword "not".

The NOT operator returns True if its operand is False, and vice versa. Here's an example:

In this example, the value of x is True. However, the NOT operator negates the value of x and returns False.

IV. Assignment Operators

Have you ever wanted to quickly assign or modify a value in Python without writing a lot of code? That's where assignment operators come in handy! They allow you to perform an operation on a variable and assign the result back to the same variable in a single step. In this section, we will explore the different types of assignment operators in Python.

a. Simple Assignment Operator

The simple assignment operator in Python is denoted by the equal sign "=" and is used to assign a value to a variable. The syntax for simple assignment is:

where variable is the name of the variable and value is the value to be assigned to the variable.

For example, the following code assigns the value 10 to the variable x :

After executing this code, the variable x will have the value 10 .

b. Arithmetic Assignment Operators

Arithmetic assignment operators are a shorthand way of performing arithmetic operations and assignment at the same time. These operators include:

+= : adds the value of the right operand to the value of the left operand and assigns the result to the left operand.

-= : subtracts the value of the right operand from the value of the left operand and assigns the result to the left operand.

*= : multiplies the value of the left operand by the value of the right operand and assigns the result to the left operand.

/= : divides the value of the left operand by the value of the right operand and assigns the result to the left operand.

%= : computes the modulus of the value of the left operand and the value of the right operand, and assigns the result to the left operand.

//= : performs floor division on the value of the left operand and the value of the right operand, and assigns the result to the left operand.

**= : raises the value of the left operand to the power of the value of the right operand, and assigns the result to the left operand.

These operators can be used with numeric values and variables of numeric types, such as integers and floating-point numbers.

In each of the above examples, the arithmetic operation and the assignment operation are performed at the same time using the shorthand arithmetic assignment operator.

c. Bitwise Assignment Operators

Bitwise assignment operators are used to perform a bitwise operation on a variable and then assign the result to the same variable. The bitwise assignment operators include:

&= : Performs a bitwise AND operation on the variable and the value on the right, then assigns the result to the variable.

|= : Performs a bitwise OR operation on the variable and the value on the right, then assigns the result to the variable.

^= : Performs a bitwise XOR operation on the variable and the value on the right, then assigns the result to the variable.

<<= : Performs a left shift operation on the variable by the number of bits specified on the right, then assigns the result to the variable.

>>= : Performs a right shift operation on the variable by the number of bits specified on the right, then assigns the result to the variable.

d. Logical Assignment Operators

There are no specific "Logical Assignment Operators" in Python, as the logical operators and , or , and not are already used for combining and negating boolean expressions. However, it is possible to use logical operators in combination with assignment operators to create compound expressions, such as x += y or z , which assigns the value of y to x if y is truthy, or the value of z otherwise.

e. Comparison Assignment Operators

There is no such thing as "Comparison Assignment Operators". The term "comparison operator" refers to operators that compare two values and return a boolean value (True or False), while "assignment operator" refers to operators that assign a value to a variable.

However, there are shorthand ways to perform a comparison and assign the result to a variable in a single line of code. For example:

x = 10 if a > b else 20 : This assigns the value 10 to x if a > b is True, otherwise it assigns the value 20.

x += 1 if a == b else 2 : This adds 1 to x if a == b is True, otherwise it adds 2.

x *= 2 if a < b else 3 : This multiplies x by 2 if a < b is True, otherwise it multiplies it by 3.

V. Bitwise Operators

Bitwise operators are used to manipulate the individual bits of binary numbers. In Python, bitwise operators can be applied to integers. The bitwise operators take two operands and operate on them bit by bit to produce a result. There are six bitwise operators in Python: AND, OR, XOR, NOT, left shift, and right shift. These operators are commonly used in low-level programming, such as device driver development and network packet processing.

a. Bitwise AND

The bitwise AND operator is represented by the & symbol in Python. It performs a logical AND operation on each corresponding bit of its operands. If both bits are 1, the resulting bit is 1. Otherwise, the resulting bit is 0.

In this example, a and b are two integers represented in binary. The & operator is used to perform a bitwise AND operation on the two numbers, resulting in the binary number 0010 , which is equivalent to the decimal number 2. The resulting value is assigned to the variable c .

b. Bitwise OR

Bitwise OR is another binary operator that operates on two integers and performs a bitwise OR operation on their binary representations. The resulting binary representation is converted back to an integer.

The syntax for the bitwise OR operator is the pipe symbol | . For example, a | b performs a bitwise OR operation on a and b .

In the above example, the binary OR operation on a and b results in 0011 1101 , which is equal to 61 in decimal representation.

c. Bitwise XOR

Bitwise XOR (exclusive OR) operator is represented by the symbol ^ in Python. The operator returns a binary number that has a 1 in each bit position where the corresponding bits of either but not both operands are 1.

For example, let's say we have two variables a = 13 and b = 17 . The binary representation of 13 is 1101 and the binary representation of 17 is 10001 . Now, let's perform the bitwise XOR operation on these two variables:

In the above example, the resulting binary number is 11000 , which is equivalent to the decimal number 24 . Therefore, the value of the variable c will be 24 .

Here is another example that demonstrates the use of bitwise XOR:

In this example, we first define a and b as binary numbers using the 0b prefix. We then perform the bitwise XOR operation on these two numbers and store the result in c . The resulting binary number is 0b110 , which is equivalent to the decimal number 6 . Therefore, the value of the variable c will be 6 .

d. Bitwise NOT

Bitwise NOT is a unary operator in Python that flips the bits of a number. It is represented by the tilde (~) symbol. When applied to a binary number, the Bitwise NOT operator returns the complement of the number.

In the above code, the value of x is 7, which is represented in binary as 0000 0111. When we apply the Bitwise NOT operator (~) to x , it flips all the bits of the number, resulting in 1111 1000. The output is in two's complement form, which is the way negative numbers are represented in binary.

VI. Membership Operators

Membership operators are used to test if a sequence is present in an object. In Python, we have two membership operators:

in : Evaluates to True if the sequence is present in the object.

not in : Evaluates to True if the sequence is not present in the object.

These operators are typically used with strings, lists, tuples, and sets to check if a certain element or a sequence of elements is present in them.

VII. Identity Operators

Identity Operators are used to compare the memory locations of two objects. There are two identity operators in Python:

is - Returns True if both variables are the same object.

is not - Returns True if both variables are not the same object.

In this example, x and y have the same values, but they are not the same object. z is assigned the same memory location as x , so x and z are the same object. The is operator returns True when comparing x and z , but False when comparing x and y . The is not operator returns False when comparing x and z , but True when comparing x and y .

Last updated 1 year ago

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.

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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.

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Augmented Assignment Operators in Python

An assignment operator is an operator that is used to assign some value to a variable. Like normally in Python, we write “ a = 5 “ to assign value 5 to variable ‘a’. Augmented assignment operators have a special role to play in Python programming. It basically combines the functioning of the arithmetic or bitwise operator with the assignment operator. So assume if we need to add 7 to a variable “a” and assign the result back to “a”, then instead of writing normally as “ a = a + 7 “, we can use the augmented assignment operator and write the expression as “ a += 7 “. Here += has combined the functionality of arithmetic addition and assignment.

So, augmented assignment operators provide a short way to perform a binary operation and assigning results back to one of the operands. The way to write an augmented operator is just to write that binary operator and assignment operator together. In Python, we have several different augmented assignment operators like +=, -=, *=, /=, //=, **=, |=, &=, >>=, <<=, %= and ^=. Let’s see their functioning with the help of some exemplar codes:

1. Addition and Assignment (+=): This operator combines the impact of arithmetic addition and assignment. Here,

a = a + b can be written as a += b

2. Subtraction and Assignment (-=): This operator combines the impact of subtraction and assignment.

a = a – b can be written as a -= b

Example:

3. Multiplication and Assignment (*=): This operator combines the functionality of multiplication and assignment.

a = a * b can be written as a *= b

4. Division and Assignment (/=): This operator has the combined functionality of division and assignment.

a = a / b can be written as a /= b

5. Floor Division and Assignment (//=): It performs the functioning of floor division and assignment.

a = a // b can be written as a //= b

6. Modulo and Assignment (%=): This operator combines the impact of the modulo operator and assignment.

a = a % b can be written as a %= b

7. Power and Assignment (**=): This operator is equivalent to the power and assignment operator together.

a = a**b can be written as a **= b

8. Bitwise AND & Assignment (&=): This operator combines the impact of the bitwise AND operator and assignment operator.

a = a & b can be written as a &= b

9. Bitwise OR and Assignment (|=): This operator combines the impact of Bitwise OR and assignment operator.

a = a | b can be written as a |= b

10. Bitwise XOR and Assignment (^=): This augmented assignment operator combines the functionality of the bitwise XOR operator and assignment operator.

a = a ^ b can be written as a ^= b

11. Bitwise Left Shift and Assignment (<<=): It puts together the functioning of the bitwise left shift operator and assignment operator.

a = a << b can be written as a <<= b

12. Bitwise Right Shift and Assignment (>>=): It puts together the functioning of the bitwise right shift operator and assignment operator.

a = a >> b can be written as a >>= b

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How can I do assignments in a list comprehension?

I want to use the assignment operator in a list comprehension. How can I do that?

The following code is invalid syntax. I mean to set lst[0] to an empty string '' if it matches pattern :

list-comprehension

8 Answers 8

Python 3.8 will introduce Assignment Expressions .

It is a new symbol: := that allows assignment in (among other things) comprehensions. This new operator is also known as the walrus operator .

It will introduce a lot of potential savings w.r.t. computation/memory, as can be seen from the following snippet of the above linked PEP (formatting adapted for SO):

Syntax and semantics In most contexts where arbitrary Python expressions can be used, a named expression can appear. This is of the form NAME := expr where expr is any valid Python expression other than an unparenthesized tuple, and NAME is an identifier. The value of such a named expression is the same as the incorporated expression, with the additional side-effect that the target is assigned that value: Handle a matched regex if (match := pattern.search(data)) is not None: # Do something with match A loop that can't be trivially rewritten using 2-arg iter() while chunk := file.read(8192): process(chunk) Reuse a value that's expensive to compute [y := f(x), y**2, y**3] Share a subexpression between a comprehension filter clause and its output filtered_data = [y for x in data if (y := f(x)) is not None]

This is already available in the recently releases alpha version (not recommended for production systems!). You can find the release schedule for Python 3.8 here .

8 Unfortunately, you cannot assign to an expression using a subscript. a[i] := 'foo' will throw an exception: SyntaxError: cannot use assignment expressions with subscript – Mike Rapadas Commented Oct 26, 2020 at 18:29
2 isn't None falsey in python? ie: is the is not None necessary, and if so, when? – CervEd Commented May 5, 2021 at 16:38
@CervEd when asserting that a value is not None, or more expressively, when trying to determine that an object has a value different than None. – Iuri Guilherme Commented Jul 24, 2022 at 21:31

It looks like you are confusing list comprehension with looping constructs in Python.

A list comprehension produces -- a list! It does not lend itself to a single assignment in an existing list. (Although you can torture the syntax to do that...)

While it isn't exactly clear what you are trying to do from your code, I think it is more similar to looping over the list (flow control) vs producing a list (list comprehension)

Loop over the list like this:

That is a reasonable way to do this, and is what you would do in C, Pascal, etc. But you can also just test the list for the one value and change it:

Or, if you don't know the index:

or, if you have a list of lists and want to change each first element of each sublist:

etc, etc, etc.

If you want to apply something to each element of a list, then you can look at using a list comprehension, or map, or one of the many other tools in the Python kit.

Personally, I usually tend to use list comprehensions more for list creation:

Which is more natural than:

But to modify that same list of lists, which is more understandable?

Here is a great tutorial on this.

3 And this should be written as if lst[0] in patterns: lst[0] = '' . – Tim Pietzcker Commented Apr 24, 2012 at 5:17
1 @Tim: Submit that as an answer! I can't believe I came up with three other ways of doing that without the obvious one... ;-) – Cameron Commented Apr 24, 2012 at 5:19
@Tim Pietzcker: that the way I would write it, but I did want to show (my interpretation) that he had this inside out... – dawg Commented Apr 24, 2012 at 5:19
@TimPietzcker: Well if the OP has a wager on this, it could be written like this: lst[0]='' if lst[0]==[x for x in patterns][0] else lst[0] :D – dawg Commented Apr 24, 2012 at 11:07

The Python language has distinct concepts for expressions and statements.

Assignment is a statement even if the syntax sometimes tricks you into thinking it's an expression (e.g. a=b=99 works but is a special syntax case and doesn't mean that the b=99 is an expression like it is for example in C).

List comprehensions are instead expressions because they return a value, in a sense the loop they perform is an incident and the main point is the returned list.

A statement can contain expressions but an expression cannot contain statements.

That said however list item assigment to is internally converted to a method call (to allow creation of list-like objects) and method calls are expressions. Therefore you can technically use list item assignment in an expression:

This is however considered bad because it harms readability and how easy is to read source code is the main focus in the Python language. You should write instead for example...

that by the way thanks to the in operator is equivalent to the even more readable

List comprehensions are used for their return value and they make a loop internally... If what you want is the loop then just write a loop... whoever will read the code trying to understand what it does would appreciate that a lot (and whoever includes yourself in a few weeks).

In short: you don't. List comprehensions are for generating lists, not modifying existing lists. If you want to modify a list, use a for loop, as that's what they're for.

The Pythonic way to write that code would be something like:

However, if you really, really want to do assignment inside one, and don't mind every Python programmer who ever deals with your code hating it for all eternity, there are a few functions you can use:

If the variable you want to assign to is a global, then you can do

If the variable you want to assign to is a mutable sequence or a map (such as a list or a dict)

The break is always valid. Even if there's a '' in the data, it's only going to cause lst[0] to be reassigned the same value... – Cameron Commented Apr 24, 2012 at 5:20
Unless lst is a mutable sequence type where element assignment has been overloaded to keep track of how many times a given value was assigned, or any other sort of non-standard behavior. – Colin Valliant Commented Apr 24, 2012 at 5:25
Hmm, good point. I would hope that's a very rare occurrence, though :-) – Cameron Commented Apr 24, 2012 at 5:31
It's probably more common than you think, but less common than my comment assumes. The last several times I created a __setitem__ method, they didn't do anything you wouldn't expect them to. However, relying on others' code to behave sensibly is not a very safe way to code. – Colin Valliant Commented Apr 24, 2012 at 5:39

As mentioned in the above answers there is no direct assignment possible in the list comprehension feature, but there is a hackable way to do it using the exec method to achieve the assignment.

Not just assignments we can pas any python expression in exec method to evaluate it.

In your case, it could be achieved by

If we have a list of objects and we want to assign a value to a specific attribute of the object on a specific condition then it could be like:

Note: This will change the state of existing objects of a list and will not return the list of objects as it returns in normal use of list comprehention.

If what you ment in the question is:

or for a list of patterns

This can actually be done easily

or for a list of patterns again

Maybe it isn't exactly what you're looking for, but I believe that it is worth to present this scenario.

Suppose that you have a list of dictionaries, like this:

With a normal list comprehension, you might find the object that you're looking for:

As a result, you have a list with a single element, thanks to the if condition above.

Therefore, you can index the only element, accessing one of the dictionary keys and assigning a value:

Here the result:

I can suggest you, use a class instead of using variables to assign values. When you use a class you can simply change the class value and then return the result.

I added one example that I did:

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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 ...
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What is an Assignment Operator in Python?

Types of Assignment Operator in Python

1. Simple Assignment Operator (=)

2. Addition Assignment Operator (+=)

3. Subtraction Assignment Operator (-=)

4. Multiplication Assignment Operator (*=)

5. Division Assignment Operator (/=)

6. Modulus Assignment Operator (%=)

7. Floor Division Assignment Operator (//=)

8. Exponentiation Assignment Operator (**=)

9. Bitwise AND Assignment Operator (&=)

10. Bitwise OR Assignment Operator (|=)

11. Bitwise XOR Assignment Operator (^=)

12. Bitwise Right Shift Assignment Operator (>>=)

13. Bitwise Left Shift Assignment Operator (<<=)

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