Master Python Basics: Variables, Control Flow, Data Structures, and OOP Explained

What Is Python?

Python is a high‑level, readable programming language designed for simplicity and versatility, widely used in data science, web development, and machine learning.

Variables

Variables store values and are created with simple assignment:

one = 1
two = 2
some_number = 10000
true_boolean = True
false_boolean = False
my_name = "Leandro Tk"
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")
if 1 > 2:
    print("1 is greater than 2")
else:
    print("1 is not greater than 2")
if 1 > 2:
    print("1 is greater than 2")
elif 2 > 1:
    print("2 is greater than 1")
else:
    print("1 is equal to 2")

Loops / Iterators

While loop repeats while a condition is true:

num = 1
while num <= 10:
    print(num)
    num += 1
loop_condition = True
while loop_condition:
    print("Loop Condition keeps: %s" % (loop_condition))
    loop_condition = False

For loop iterates over a range or collection:

for i in range(1, 11):
    print(i)
for book in bookshelf:
    print(book)
for key in dictionary:
    print("%s --> %s" % (key, dictionary[key]))
for key, value in dictionary.items():
    print("%s --> %s" % (key, value))

Lists (Array Data Structure)

Lists store ordered collections and support indexing and appending:

my_integers = [1, 2, 3, 4, 5]
print(my_integers[0])  # 1
my_integers = [5, 7, 1, 3, 4]
print(my_integers[0])  # 5
bookshelf = []
bookshelf.append("The Effective Engineer")
bookshelf.append("The 4 Hour Work Week")
print(bookshelf[0])
print(bookshelf[1])

Dictionaries (Key‑Value Data Structure)

Dictionaries map keys to values and allow any hashable type as a key:

dictionary_example = {"key1": "value1", "key2": "value2", "key3": "value3"}
print(dictionary_example["key1"])  # value1
# Adding a new key‑value pair
dictionary_example["age"] = 24
print(dictionary_example)

Classes and Objects

Classes define blueprints for objects. Example of a simple Vehicle 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
Vehicle.number_of_wheels = 2  # using property setter
print(tesla_model_s.number_of_wheels)  # 2
tesla_model_s.make_noise()  # VRUUUUUUUM

Encapsulation

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

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

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

Inheritance

Subclasses inherit attributes and methods from parent classes:

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

Source: Machine Heart (机器之心) Original article: Learning Python from Zero to Hero