Intial commit with first 3 tutorials

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1_variables.py Normal file
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"""
In this example, we'll cover the fundamental variable types in Python and introduce the basics of functions.
Key Concepts:
**Variables**: Variables store data that can be changed while the program is running.
**Dynamic Typing**: Python is a dynamically-typed language, which means you don't need to specify
the data type of a variable explicitly (unlike statically-typed languages like C or Java, where you do).
- Example in Java: `int number = 1;`
- In Python: `number = 1` (Python automatically understands that `number` is an integer).
"""
# The following are common variable types in Python. This list is not exhaustive, but it covers the basics.
# Integer: An integer (int) represents a whole number, with no decimal point.
number = 1
# Float: A floating point number (float) represents a number with a decimal point.
number_float = 1.1
# String: A string (str) represents a sequence of characters, typically used for text.
text = "Hello, World!"
# Boolean: A boolean (bool) represents a logical value, either True or False.
boolean = True
# List: A list stores a collection of values in a specific order, and the values can be of any type.
# Lists are mutable, meaning they can be changed after theyre created (e.g., adding or removing items).
a_list = ["Apple", 64, 1.1, True]
# Tuple: A tuple is similar to a list in that it can store multiple values, but it is immutable,
# meaning once its created, it cannot be changed.
a_tuple = ("Apple", 54, 11, 1.2, False)
#dict: stores a value with a key
# Dictionaries (dict) are extremely useful, they allow you to map a name (key) to a value.
# they are mutable, meaning they can be changed after theyre created (e.g., adding or removing items).
dictionary = {
"Jan" : "January",
"Feb" : "February",
"Mar" : "March",
"Apr" : "April",
"May" : "May",
"Jun" : "June",
"Jul" : "July",
"Aug" : "August",
"Sep" : "September",
"Oct" : "October",
"Nov" : "November",
"Dec" : "December"
}
"""
A function allows you to define a reusable block of code that performs a specific task.
Functions can:
- Take input (called parameters or arguments)
- Perform operations with that input
- Return a result, or simply perform an action (like printing something)
Below is a function called `show_type` that takes in one parameter, `var`, and prints its data type.
"""
def show_type(var):
"""Prints the data type of the variable passed to it."""
print(f"The type of {var} is {type(var)}")
# Let's test our function with the variables defined above.
show_type(number) # Expected output: <class 'int'>
show_type(number_float) # Expected output: <class 'float'>
show_type(text) # Expected output: <class 'str'>
show_type(boolean) # Expected output: <class 'bool'>
show_type(a_list) # Expected output: <class 'list'>
show_type(a_tuple) # Expected output: <class 'tuple'>

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"""
Their is going to be a relatively big jump in difficulty here, but dont be scared!
All you need to know to understand classes are variables and functions, as covered in the previous file.
Key Concepts:
**class** is a blueprint for creating objects (specific instances of that class),
a class represents a collection of attributes and methods to represent something (e.g a Person)
**object** is an instance of a class with its own unique data.
**attributes** are values tied to a object
**methods** are the exact same as functions, but are tried to a class.
**Magic/dunder methods** are methods predefined by python that can be used for various things.
**__init__** is a type of magic method, it is known as a constructor and initializes the objects attributes when its created
"""
class Person:
"""A class Representing a Human/Person"""
# This is the constructor, whenever a new person is created it runs and can be used to assign the new person their attributes!
def __init__(self, name, age, eye_color):
self.name = name # An attribute
self.age = age
self.eye_color = eye_color
# This is a method, note "self" must be passed as a paramater/arguement for it to access the attributes of... itself.
def canApplyForLicence(self):
if self.age >= 17:
return f"{self.name} can apply for their driving permit!"
else:
return f"{self.name} is too young ({self.age}) and can not apply for a driving permit."
pedro = Person("Pedro", 19, "Brown") # Creates a new person with the following values
print(pedro.canApplyForLicence()) # Runs the canApplyForLicence method, and prints the return value
Iain = Person("Iain", 16, "Blue") # Creates a Another new person with the following values (iain armitage if you wanted to know.)
print(Iain.canApplyForLicence()) # Runs the canApplyForLicence method, and prints the return value

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"""
Now that we know the basics of classes, variables, and functions, we will move on to more
abstract ideas.
I'm also going to introduce type hinting; this reduces ambiguity and improves readability.
Key Concepts:
**Encapsulation** is the concept of grouping related data and methods within a
class and restricting access to them to control how they are used.
**Access Modifiers** are used to determine who/what can access a certain attribute or method.
- **Public**: Accessible from any part of the code. Used for attributes and methods intended to be part
of the class's interface for external use.
- **Protected**: Intended for internal use within the class and its subclasses. "_value" represents it.
Useful for attributes/methods that should be accessible in subclasses but not publicly.
- **Private**: Only accessible within the class, represented by "__value". Useful for securing sensitive
data or internal methods that should not be altered externally.
IMPORTANT: Python does not strictly enforce access control, so these conventions mainly serve as guidelines.
"""
from abc import ABC, abstractmethod # This is the abstraction library in Python
from typing import Optional # Type hinting, not needed but reduces ambiguity. Note: not enforced at runtime.
class Shape(ABC): # An abstract class, provides a blueprint for other classes to inherit.
@abstractmethod
def area(self) -> float:
"""Implemented to ensure each subclass contains this method."""
# This method is required in all subclasses, ensuring they provide their own area calculation.
class Rectangle(Shape):
def __init__(self, width: float, height: float):
self.__width = width # A private attribute to store width.
self.__height = height # A private attribute to store height.
@property # This allows access to the private 'width' attribute in a controlled way.
def width(self) -> float:
return self.__width
@width.setter # This allows you to set the value of 'width' after initialization.
def width(self, value: float):
if value <= 0:
raise ValueError("Width must be positive.")
self.__width = value
@property # This allows access to the private 'height' attribute in a controlled way.
def height(self) -> float:
return self.__height
@height.setter # This allows you to set the value of 'height' after initialization.
def height(self, value: float):
if value <= 0:
raise ValueError("Height must be positive.")
self.__height = value
def area(self) -> float:
return self.__width * self.__height # Calculates the area of the rectangle.
def set_dimensions(self, width: Optional[float] = None, height: Optional[float] = None):
if width is not None:
self.width = width # Sets 'width' using the setter.
if height is not None:
self.height = height # Sets 'height' using the setter.
rect = Rectangle(5, 10)
print(rect.area()) # Prints the area of the rectangle (5 * 10 = 50).
rect.set_dimensions(width=8) # Updates 'width' using the setter, height remains the same.
print(rect.area()) # Prints the new area of the rectangle (8 * 10 = 80).