Python Variables, Data Types, Control Structures, Functions, and Modules Overview

Variables and Data Types In Python, variables store data without explicit type declaration. Example assignments:

x = 10
y = "Hello, world!"
z = True

Variable naming rules: letters, digits, underscores; cannot start with a digit; case‑sensitive.

Data Types Python includes numeric types (int, float, complex), strings, booleans, sequence types (list, tuple), and mapping type (dict). Examples:

# numeric types
int: 10
float: 3.14
complex: 1+2j

# string
name = "Alice"
greeting = "Hello, " + name
print(greeting)  # Hello, Alice

# boolean
is_student = True
is_teacher = False

# list
numbers = [1, 2, 3, 4]
names = ["Alice", "Bob", "Charlie"]

# tuple
coordinates = (10, 20, 30)

# dict
person = {"name": "Alice", "age": 25, "city": "New York"}

Control Structures Conditional statements and loops control program flow. Example if‑else:

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

Nested conditions and logical operators (and, or, not) are also demonstrated. For loops:

# iterate list
for name in names:
    print(name)

# range
for i in range(5):
    print(i)

While loop example:

count = 0
while count < 5:
    print(count)
    count += 1

Function Definition and Calls Functions encapsulate reusable code. Basic definition:

def greet(name):
    print(f"Hello, {name}!")
greet("Alice")  # Hello, Alice

Examples of functions with parameters, default values, *args, and **kwargs are provided.

Module Import Importing modules or specific functions extends functionality. Examples:

import math
print(math.sqrt(16))  # 4.0

from math import sqrt
print(sqrt(16))  # 4.0

import math as m
print(m.sqrt(16))  # 4.0

These foundational concepts are essential for further learning, such as writing automated test scripts.