Exploring Python Decision Statements: If, Elif, and Else


link to this section

Python, as a high-level, interpreted programming language, is known for its readability and simplicity. Its syntax is not just user-friendly but also versatile, enabling developers to create a wide range of applications including web applications, data analysis scripts, and even game development. One of the fundamental concepts in Python (and indeed, most programming languages) is decision-making or control flow, which allows your program to respond in different ways depending on certain conditions. This article provides a deep dive into Python's decision statements - If, Elif, and Else.

Understanding Decision Making in Python

link to this section

Decision making in Python involves using conditional statements that evaluate whether certain conditions are true or false. Depending on the outcome, the program will then decide the subsequent course of action. This feature allows a program to execute different sequences of code based on different inputs or conditions, enabling more complex, dynamic behavior.

In Python, the primary decision statements are if , elif (short for 'else if'), and else .

The 'if' Statement

The if statement is the most basic type of decision statement in Python. It checks a condition and executes a block of code if the condition is true. If the condition is false, it simply skips the code block. Here's a simple syntax for the if statement:

if condition: 
    # block of code to execute if condition is true 


x = 10 
if x > 5: 
    print("x is greater than 5") 

In this example, the if statement checks whether x is greater than 5. Since x is 10, the condition is true, so it prints "x is greater than 5".

The 'elif' Statement

The elif statement is Python's way of saying "if the previous conditions were not true, then try this condition". It allows you to check multiple expressions for True and execute a block of code as soon as one of the conditions evaluates to True .

Here's the syntax:

if condition1: 
    # executes when condition1 is true 
elif condition2: 
    # executes when condition2 is true 
    # executes when both conditions are false 


x = 20 
if x > 30: 
    print("x is greater than 30") 
elif x > 10: 
    print("x is greater than 10 but not greater than 30") 
    print("x is not greater than 10 or 30") 

The 'else' Statement

The else statement catches anything which isn't caught by the preceding conditions. It's like a last resort, which will execute if all preceding conditions are false.

x = 5 
if x > 10: 
    print("x is greater than 10") 
    print("x is not greater than 10") 

In the above example, since x is not greater than 10, it executes the code under the else statement.

Nested If Statements

link to this section

Python allows you to nest if statements within if statements, which means you can create an if ... elif statement inside another if ... elif statement. This gives you more granularity in your decision-making process. Here's the syntax:

if condition1: 
    # Executes when condition1 is true 
    if condition2: 
        # Executes when condition2 is true 
    # You can add as many nested if statements as you want 
    # Executes when condition1 is false 

Using Logical Operators in Decision Statements

link to this section

Python’s decision-making process can become more complex and nuanced by combining conditions with logical operators like and , or , and not . These operators allow you to create more detailed conditions for your if , elif , and else statements.

The 'and' Operator

The and operator returns True only if both conditions being compared are true. If one (or both) of the conditions is false, then it returns False .

x = 10 
y = 20 
if x > 5 and y > 15: 
    print("Both conditions are True") 

The 'or' Operator

The or operator returns True if at least one of the conditions being compared is true. If both conditions are false, then it returns False .

x = 10 
y = 5 
if x > 5 or y > 15: 
    print("At least one condition is True") 

The 'not' Operator

The not operator reverses the truth-value of the condition. It returns False if the condition is true and True if the condition is false.

x = 10 
if not x > 15: 
    print("x is not greater than 15") 

Short-circuit Evaluation

link to this section

When Python evaluates a complex condition with multiple parts, it uses a strategy known as short-circuit evaluation. For an and operator, if the first condition is False , Python doesn't check the second condition because the entire condition can't be True . Similarly, for an or operator, if the first condition is True , Python doesn't check the second condition, as at least one condition being True is enough. This strategy can speed up your program, especially when the conditions involve complex computations.

Ternary Operator for Decision Making

link to this section

Python includes a syntax known as the ternary operator, which allows you to write if ... else statements in a single, concise line of code. It follows this syntax:

value_if_true if condition else value_if_false 

Here's an example:

x = 10 
message = "x is greater than 5" if x > 5 else "x is not greater than 5" 

The 'pass' Statement

link to this section

Python's pass statement is used when a statement is required syntactically, but you don't want any command or code to execute. It is like a placeholder and is commonly used in places where your code will eventually go but has not been written yet. Here is an example:

x = 10 
if x > 5: 
    pass # Will do something here later 

In the above example, you might not be ready to write code for the case where x > 5. By using pass , you prevent a syntax error and can run your program.

The 'assert' Statement

link to this section

Python includes an assert statement as a debugging aid. It tests a condition and immediately triggers an error if the condition is false. The syntax is as follows:

assert condition, 'Error message' 

If the condition is True , the program continues running as usual. If the condition is False , an AssertionError is raised with an optional error message. Here's an example:

x = 10 
assert x > 5, 'x is not greater than 5' 

In this case, the assertion does not do anything because the condition is True . However, if x was 4, then the AssertionError would be raised with the message 'x is not greater than 5'.

The 'break' and 'continue' Statements

link to this section

The break and continue statements are used inside loops, but they are essentially part of the decision-making process as they control the flow of the program.

The break statement ends the current loop and resumes execution at the next statement. Here's an example:

for num in range(10): 
    if num == 5: 

In this case, the loop will print numbers from 0 to 4, and when num equals 5, it will break out of the loop.

The continue statement rejects all the remaining statements in the current iteration of the loop and moves the control back to the top of the loop for the next iteration.

for num in range(10): 
    if num == 5: 

In this case, the loop will print numbers from 0 to 4, skip 5, and then print numbers from 6 to 9.

Switch-case Equivalents in Python

link to this section

Python doesn't natively support the switch-case construct available in some other languages. However, Python's dictionary and functions can serve as decent substitutes. Here's an example of how you might implement a basic switch-case construct:

def switch_case(value): 
    return { 
        'case1': "This is case 1", 
        'case2': "This is case 2", 
        'case3': "This is case 3", 
    }.get(value, "This is a default case") 

In the above example, the function switch_case acts like a switch-case construct. If the input value matches one of the predefined cases, it returns the corresponding string. If there's no match, it returns the default string.


link to this section

Python's decision-making capabilities are varied and powerful, thanks to a rich set of built-in statements. Understanding and effectively using these elements will significantly enhance the functionality of your programs, making them more dynamic and responsive. Remember, the best way to learn is by doing, so be sure to experiment with these statements in your code. Happy Pythoning!