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Expressions in Python

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  • Difficulty Level : Easy
  • Last Updated : 03 Sep, 2021
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An expression is a combination of operators and operands that is interpreted to produce some other value. In any programming language, an expression is evaluated as per the precedence of its operators. So that if there is more than one operator in an expression, their precedence decides which operation will be performed first. We have many different types of expressions in Python. Let’s discuss all types along with some exemplar codes :

1. Constant Expressions: These are the expressions that have constant values only.

Example:

Python3




# Constant Expressions
x = 15 + 1.3
  
print(x)

Output

16.3

2. Arithmetic Expressions: An arithmetic expression is a combination of numeric values, operators, and sometimes parenthesis. The result of this type of expression is also a numeric value. The operators used in these expressions are arithmetic operators like addition, subtraction, etc. Here are some arithmetic operators in Python:

OperatorsSyntaxFunctioning
+x + yAddition
x – ySubtraction
*x * yMultiplication
/x / yDivision
//x // yQuotient
%x % yRemainder
**x ** yExponentiation

Example:

Let’s see an exemplar code of arithmetic expressions in Python :

Python3




# Arithmetic Expressions
x = 40
y = 12
  
add = x + y
sub = x - y
pro = x * y
div = x / y
  
print(add)
print(sub)
print(pro)
print(div)

Output

52
28
480
3.3333333333333335

3. Integral Expressions: These are the kind of expressions that produce only integer results after all computations and type conversions.

Example:

Python3




# Integral Expressions
a = 13
b = 12.0
  
c = a + int(b)
print(c)

Output

25

4. Floating Expressions: These are the kind of expressions which produce floating point numbers as result after all computations and type conversions.

Example:

Python3




# Floating Expressions
a = 13
b = 5
  
c = a / b
print(c)

Output

2.6

5. Relational Expressions: In these types of expressions, arithmetic expressions are written on both sides of relational operator (> , < , >= , <=). Those arithmetic expressions are evaluated first, and then compared as per relational operator and produce a boolean output in the end. These expressions are also called Boolean expressions.

Example:

Python3




# Relational Expressions
a = 21
b = 13
c = 40
d = 37
  
p = (a + b) >= (c - d)
print(p)

Output

True

6. Logical Expressions: These are kinds of expressions that result in either True or False. It basically specifies one or more conditions. For example, (10 == 9) is a condition if 10 is equal to 9. As we know it is not correct, so it will return False. Studying logical expressions, we also come across some logical operators which can be seen in logical expressions most often. Here are some logical operators in Python:

OperatorSyntaxFunctioning
andP and QIt returns true if both P and Q are true otherwise returns false
orP or QIt returns true if at least one of P and Q is true
notnot PIt returns true if condition P is false

Example:

Let’s have a look at an exemplar code :

Python3




P = (10 == 9)
Q = (7 > 5)
  
# Logical Expressions
R = P and Q
S = P or Q
T = not P
  
print(R)
print(S)
print(T)

Output

False
True
True

7. Bitwise Expressions: These are the kind of expressions in which computations are performed at bit level.

Example:

Python3




# Bitwise Expressions
a = 12
  
x = a >> 2
y = a << 1
  
print(x, y)

Output

3 24

8. Combinational Expressions: We can also use different types of expressions in a single expression, and that will be termed as combinational expressions.

Example:

Python3




# Combinational Expressions
a = 16
b = 12
  
c = a + (b >> 1)
print(c)

Output

22

But when we combine different types of expressions or use multiple operators in a single expression, operator precedence comes into play.

Multiple operators in expression (Operator Precedence)

It’s a quite simple process to get the result of an expression if there is only one operator in an expression. But if there is more than one operator in an expression, it may give different results on basis of the order of operators executed. To sort out these confusions, the operator precedence is defined. Operator Precedence simply defines the priority of operators that which operator is to be executed first. Here we see the operator precedence in Python, where the operator higher in the list has more precedence or priority:

PrecedenceNameOperator
1Parenthesis   ( ) [ ] { }
2Exponentiation **
3Unary plus or minus, complement -a , +a , ~a
4Multiply, Divide, Modulo  /  *  //  %
5Addition & Subtraction +  –
6Shift Operators>>  <<
7Bitwise AND&
8Bitwise XOR^
9Bitwise OR|
10Comparison Operators>=  <=  >  <
11Equality Operators==  !=
12Assignment Operators =  +=  -=  /=  *=
13Identity and membership operatorsis, is not, in, not in
14Logical Operators   and, or, not

So, if we have more than one operator in an expression, it is evaluated as per operator precedence. For example, if we have the expression “10 + 3 * 4”. Going without precedence it could have given two different outputs 22 or 52. But now looking at operator precedence, it must yield 22. Let’s discuss this with the help of a Python program:

Python3




# Multi-operator expression
  
a = 10 + 3 * 4
print(a)
  
b = (10 + 3) * 4
print(b)
  
c = 10 + (3 * 4)
print(c)

Output

22
52
22

Hence, operator precedence plays an important role in the evaluation of a Python expression.


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