Day 16: Mastering Python Control Flow and Core Structures

Adrian Rubico

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Nov 21, 2024

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11:53 PM GMT+8

The Python control flow and core structures enable developers to write logical, efficient, and reusable code. Throughout this blog, we explore the basics of Python programming, such as operators, conditional statements, and loops.

Operators in Python

It is possible to perform logical operations, computations, and comparisons in Python using various types of operators. The different types of operators play an essential role in control flow and core structures. Here are detailed explanations, examples, and tables for each operator type.

Arithmetic Operators

Arithmetic operators perform mathematical operations like addition, subtraction, multiplication, etc.

x = 10

# Addition
a = x + 5
print(a)

# Subtraction
b = x - 5
print(b)

# Multiplication
c = x * 25

Table of Arithmetic Operators in Python

OperatorDescriptionExample
+Additionx + y
-Subtractionx - y
*Multiplicationx * y
/Divisionx / y
%Modulusx % y
**Exponentiationx ** y
//Floor divisionx // y

Comparison Operators

Comparison operators are used to compare two values and return a Boolean result.

x = 10

# Equal to
print(x == 10)

# Not equal to
print(x != 5)

# Greater than
print(10 > 5)

Table of Comparison Operators in Python

OperatorDescriptionExample
==Equalx == y
!=Not equalx != y
>Greater thanx > y
<Less thanx < y
>=Greater than or equal tox >= y
<=Less than or equal tox <= y

Logical Operators

Logical operators combine multiple conditions and return a Boolean result.

x = 10

# AND operator
print(x > 5 and x < 10)

# OR operator
print(x > 5 or x < 10)

# NOT operator
print(not(x > 5))

Table of Logical Operators in Python

OperatorDescriptionExample
andReturns True if both conditions are Truex > 5 and x < 10
orReturns True if at least one condition is Truex > 5 or x < 10
notReverses the Boolean valuenot(x > 5)

Membership Operators

Membership operators test for membership in a sequence (like a list, tuple, or string).

x = "Azure"

# IN operator
print(x in ["AWS", "GCP", "Azure", "Oracle"])

# NOT IN operator
print("Alibaba" not in ["AWS", "GCP", "Azure", "Oracle"])

Table of Membership Operators in Python

OperatorDescriptionExample
inReturns True if value is in sequence.x in [1, 2, 3]
not inReturns True if value is not in sequence.x not in [1, 2, 3]

Loops

Loops let you execute code repeatedly until a condition is met. Python supports for and while loops:

  • For Loop
    Iterates over a sequence (like a list, string, or range).
import time

x = ["Azure", "AWS", "GCP", "Oracle"]

# Iterating through a range  
for i in range(3):  
    print(f"'{x[i]}' is one of the best cloud service providers!")
    time.sleep(1)

  • While Loop
    Executes as long as a condition remains True.
import time

x = 5

# Counting down with a while loop
while x > 0:
    print(x)
    x -= 1
    time.sleep(1)

Loop Controls

Loop control statements modify the flow of a loop

ControlDescriptionExample
breakExits the loop prematurely.if x == 5: break
continueSkips the current iteration and moves to the next.if x == 5: continue
passA placeholder with no effect on the loop (used for empty blocks).if x == 5: pass
import time
x = ["Azure", "AWS", "GCP", "Oracle"]

print("Loop Control - BREAK")
for cloud_provider in x:
    if cloud_provider == "GCP":
        break  # Exit the loop when "GCP" is encountered

    print(cloud_provider)

time.sleep(1)
print("")
print("Loop Control - CONTINUE")
for cloud_provider in x:
    if cloud_provider == "GCP":
        continue # Skip the rest of the iteration for "GCP"

    print(cloud_provider)

time.sleep(1)
print("")
print("Loop Control - PASS")
for cloud_provider in x:
    if cloud_provider == "GCP":
        break
    elif cloud_provider == "AWS":
        continue
    else:
        pass  # Do nothing for other cloud providers

    print(cloud_provider)

Conclusion

With Python's operators, conditional statements, and loops, you can handle any logic your script may require. Developing robust Python programs starts with these core structures.

Stay tuned for the next blog, where we’ll explore Python's Essential Libraries for DevOps to further expand your scripting toolkit!

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