Conditional Statements

Conditional statements are a fundamental part of programming, allowing your code to make decisions based on certain conditions. In Python, these decisions can be made using if, elif (which stands for ‘else if’), and else statements.

Understanding if Statements

An if statement is used to test a condition and execute a block of code only if that condition is true. Here’s the basic syntax:

if condition:
    # Block of code executed if the condition is True

For example:

age = 20
if age >= 18:
    print("You are an adult.")

In this case, because age is greater than or equal to 18, the message “You are an adult.” will be printed.

Handling Multiple Conditions with elif

Sometimes you need to check multiple conditions in sequence; this is where elif comes into play. If the initial if statement evaluates to False, Python moves on to evaluate any subsequent elif blocks.

Here’s how it works:

temperature = 30

if temperature < 0:
    print("It's freezing!")
elif temperature < 20:
    print("It's cold")
elif temperature < 30:
    print("It's warm")
    print("Wow! It's hot!")

Since our temperature variable equals 30, “Wow! It’s hot!” will be printed out.

Using else for Alternative Actions

If none of the conditions specified by your if and/or elif statements are met, you can use an optional final clause called else:

number = -2

if number > 0:
    print(f"{number} is positive.")
elif number == 0:
    print(f"The number is zero.")
  	print(f"{number} is negative.")

The output here would be “-2 is negative.”

Remember that after Python finds one true condition in your series of if/elif/else clauses, it executes that block alone and skips all others—so order matters!

The while loop

The while loop in Python enables you to execute a block of code repeatedly as long as a condition is true. It’s an essential tool for when you want to continue performing an action until a particular state changes.

Creating a while loop

Here’s the basic structure of a while loop:

while condition:
    # Block of code executed repeatedly 
    # as long as the condition is True

For example, if we wanted to count from 1 to 5, we could write:

count = 1
while count <= 5:
    count += 1   # This is shorthand for count = count + 1

This will output numbers from 1 through 5. The loop continues running until count becomes greater than five.

Infinite Loops and How to Avoid Them

An infinite loop occurs when the terminating condition never becomes false. To avoid this, ensure that the variable used in the condition statement changes within each iteration so it can eventually become false.

For instance, forgetting to include count += 1 in our previous example would result in an infinite loop because count would always remain at its initial value (which is less than or equal to five).

Always double-check your loops’ logic and conditions before running them!

Combining while Loops with Conditional Statements

You can make more complex decisions by combining conditional statements inside your while loops:

user_input = ""
while user_input.lower() != "quit":
    user_input = input("Enter 'quit' to exit: ")
print("Thank you! Exiting program.")

In this script, users are prompted continuously until they type “quit” (case insensitive due to .lower()), at which point the program prints out a farewell message and stops executing.

Through careful use of conditions within your loops, you can control not only how many times those loops run but also under what circumstances they terminate or continue—giving you precise control over your programs’ behavior.

Mastering for loops

The for loop in Python is a versatile control structure that allows you to iterate over the elements of a sequence (such as a list, tuple, string, or range) and execute a block of code for each element.

Iterating Over Sequences with for loops

A basic for loop looks like this:

for item in sequence:
    # Block of code to execute for each item

For example, if we want to print out each character in a string one by one:

for character in "Python":

This will output:


You can also iterate through lists and other iterable objects using the same syntax.

Nested for loops

Sometimes you need to use one loop inside another; these are called nested loops. For instance, if you’re going to process every cell in a grid represented by rows and columns:

rows = 3 
columns = 4 

for row_num in range(rows):
    for col_num in range(columns):
        print(f"Row {row_num}, Column {col_num}")

This script would produce an output that shows the row and column index of each cell position within our grid.

Be cautious when nesting loops since it’s easy to create scripts that take much longer than expected due to their multiplying effect on execution time—this is known as quadratic runtime complexity (O(n²)).

By mastering both simple and nested for loops, you’ll be able to handle many common tasks involving repeated actions across data structures—a fundamental skill for any Python programmer.

Exploring the range() function

The range() function is a built-in Python function that generates a sequence of numbers. It is often used for looping a specific number of times in for loops.

Generating Number Sequences with range()

Here’s how you can use the range() function:

# Using range to generate numbers from 0 up to (but not including) 5
for i in range(5):

This will output:


The range() function by default starts at zero and increments by one each time, but you can customize it further.

Using range() in Loops

You can specify both start and end points for your sequences as well as a step value:

# Starting at 1, ending before 10, stepping by two each time.
for i in range(1, 10, 2):

This loop will print out odd numbers between one and ten:


It’s important to note that the starting index is inclusive while the ending index is exclusive; meaning that Python includes the first value but stops before reaching the last value specified.

Managing Loop Execution with break, continue, and pass

In Python loops, you have control statements such as break, continue, and pass that change the flow of your iterations in different ways. These can be used within both for and while loops.

Stopping a Loop Prematurely with break

The break statement is used to exit a loop before it has gone through all its iterations:

# Print numbers until we reach a number divisible by 7
for number in range(1, 100):
    if number % 7 == 0:
        print(f"{number} is divisible by 7.")
        break   # Exit the loop

When this code runs, it will stop at the first number divisible by seven (which is seven) and then terminate the loop.

Skipping Iterations with continue

Unlike break, which exits the loop entirely, the continue statement skips over the current iteration and moves on to the next one:

# Skip even numbers and only print odd ones between 1-10.
for number in range(1,11):
    if number % 2 == 0:
        continue   # Skip this iteration

This script prints out only odd numbers because whenever an even number is encountered (number % 2 == 0), it triggers a continue statement that skips to the next iteration without executing any further code below it for that cycle.

Placeholder Behavior of pass

The final control statement is pass. It does nothing—it’s simply a placeholder you can use when syntax requires some sort of action or content but you don’t want any operation or behavior implemented yet:

# A for-loop where we're not sure what we're doing yet.
for x in range(10):
    pass   # We'll figure out what goes here later.

Using ‘pass’ allows your code to run without interruption while signaling areas where future code may be added. This can be particularly useful during development stages or when implementing stubs.

Introducing Pattern Matching With match (Python 3.10+)

Starting with Python version 3.10, a new feature called structural pattern matching was introduced, resembling the switch-case statements found in other programming languages but with more powerful capabilities. This is done using the match statement followed by one or more case clauses.

Basic Syntax of match…case Statement

The basic structure of a match statement looks like this:

match subject:
    case pattern1:
        # Block of code executed if subject matches pattern1
    case pattern2:
        # Block of code executed if subject matches pattern2

Here’s an example that demonstrates how to use it:

def http_status_code(status):
    match status:
        case 200 | 201 | 202:   # You can match multiple patterns.
            return "Success"
        case 404:
            return "Not Found"
        case _:
            return "Other"

print(http_status_code(200))   # Output: Success
print(http_status_code(404))   # Output: Not Found
print(http_status_code(500))   # Output: Other

In this function, we’re matching the HTTP status codes and returning appropriate messages for each group of statuses.

Note: The last line uses _, which acts as a wildcard and will match anything not previously matched by earlier cases.

Pattern matching is especially useful when you have complex data structures such as nested lists or dictionaries because you can destructure them directly within your patterns:

point = (0, -1)
match point:
    case (0, y) if y > 0:
        print("Point lies on positive Y axis")
    case (0, y) if y < 0:
        print("Point lies on negative Y axis")
    case _ :
        print("Point does not lie on Y axis")

# Since our point variable has coordinates (0,-1), 
# it would output "Point lies on negative Y axis".

This advanced form of control flow allows for concise and readable conditions that are particularly handy when dealing with various possibilities that could arise from your program’s data.

Please note that while match statements offer powerful functionality for handling complex conditionals gracefully, they should be used judiciously—especially for beginners—as they introduce another layer of complexity to understanding program flow.

Chapter 2 | TOC | Chapter 4