Master Python Basics: Variables, Control Flow, Data Structures & OOP

Introduction to Python

Python is a high‑level, readable language used for data science, web development, and machine learning. Its design emphasizes clear syntax and supports multiple programming paradigms.

Variables

Assign values to names using the = operator:

one = 1
two = 2
some_number = 10000

Python supports booleans, strings, floats, and other types:

# booleans
true_boolean = True
false_boolean = False
# string
my_name = "Leandro Tk"
# float
book_price = 15.80

Control Flow – Conditional Statements

Use if, elif, and else to execute code based on conditions:

if True:
    print("Hello Python If")
if 2 > 1:
    print("2 is greater than 1")
else:
    print("1 is not greater than 2")
elif 1 > 2:
    print("1 is greater than 2")
else:
    print("1 is equal to 2")

Loops

While loop repeats while a condition is true:

num = 1
while num <= 10:
    print(num)
    num += 1

For loop iterates over a range or collection:

for i in range(1, 11):
    print(i)
for book in bookshelf:
    print(book)

Lists (Arrays)

Create, index, and modify lists:

my_integers = [1, 2, 3, 4, 5]
print(my_integers[0])  # 1
bookshelf = []
bookshelf.append("The Effective Engineer")
bookshelf.append("The 4 Hour Work Week")
print(bookshelf[0])  # The Effective Engineer

Iterate over a list:

for book in bookshelf:
    print(book)

Dictionaries (Key‑Value)

Define and access key‑value pairs:

dictionary_example = {"key1": "value1", "key2": "value2", "key3": "value3"}
print(dictionary_example["key1"])  # value1
# add a new entry
dictionary_example["age"] = 24
print(dictionary_example)

Iterate over keys and values:

for key, value in dictionary_example.items():
    print(f"{key} --> {value}")

Classes and Objects

Define a class with an initializer and methods:

class Vehicle:
    def __init__(self, number_of_wheels, type_of_tank, seating_capacity, maximum_velocity):
        self.number_of_wheels = number_of_wheels
        self.type_of_tank = type_of_tank
        self.seating_capacity = seating_capacity
        self.maximum_velocity = maximum_velocity
    def make_noise(self):
        print('VRUUUUUUUM')

tesla_model_s = Vehicle(4, 'electric', 5, 250)
print(tesla_model_s.number_of_wheels)  # 4
tesla_model_s.make_noise()  # VRUUUUUUUM

Use @property for getters and setters:

class Vehicle:
    def __init__(self, number_of_wheels, type_of_tank, seating_capacity, maximum_velocity):
        self._number_of_wheels = number_of_wheels
        # other attributes omitted for brevity
    @property
    def number_of_wheels(self):
        return self._number_of_wheels
    @number_of_wheels.setter
    def number_of_wheels(self, value):
        self._number_of_wheels = value

car = Vehicle(4, 'gas', 5, 180)
print(car.number_of_wheels)  # 4
car.number_of_wheels = 2
print(car.number_of_wheels)  # 2

Encapsulation

Public attributes are accessed directly, while private (conventionally prefixed with an underscore) are accessed via methods:

class Person:
    def __init__(self, first_name, email):
        self.first_name = first_name
        self._email = email
    def email(self):
        return self._email
    def update_email(self, new_email):
        self._email = new_email

p = Person('TK', '[email protected]')
print(p.first_name)  # TK
print(p.email())      # [email protected]
p.update_email('[email protected]')
print(p.email())      # [email protected]

Inheritance

Subclass a parent class to reuse its attributes and methods:

class Car:
    def __init__(self, number_of_wheels, seating_capacity, maximum_velocity):
        self.number_of_wheels = number_of_wheels
        self.seating_capacity = seating_capacity
        self.maximum_velocity = maximum_velocity

class ElectricCar(Car):
    def __init__(self, number_of_wheels, seating_capacity, maximum_velocity):
        super().__init__(number_of_wheels, seating_capacity, maximum_velocity)

my_electric = ElectricCar(4, 5, 250)
print(my_electric.number_of_wheels)      # 4
print(my_electric.seating_capacity)    # 5
print(my_electric.maximum_velocity)    # 250

These examples provide a solid foundation for writing Python code in machine‑learning, data‑science, and web‑development projects.