Technical Roadmap

Python Introduction

Python is an object-oriented, high level, dynamically typed programming language. A programming language is a language used to communicate with a computer or machine. Python is known for its simple, easy to read syntax that makes it a great choice for beginners. It uses an interpreter to execute the code.

The Logicoria Tip

Python is a tool that helps you talk to computer hardware without needing to learn binary code!

Object Oriented

Python is an Object-Oriented Programming (OOP) language, meaning it uses objects and classes to organize code efficiently. It follows the four core principles of OOP: Inheritance, Encapsulation, Abstraction, and Polymorphism.

In Python, everything is treated as an object; even simple simple data like numbers and strings behave like objects. This means they come come with built-in functions you can use.

High Level

Python has a very simple syntax. It uses English like commands to write code. In languages like Java, you have to write a long, complex command just to print a simple "Hello," but in Python, you simply type print("Hello"). If you can read English, you can understand and remember most of Python's syntax.

Additionally, garbage collection in Python is automatic. This means you don't have to write manual commands to clean up memory every time, unlike in languages like C. Python is smart enough to manage memory for you.

PYTHON
print("Hello World!")

Output

Hello World!

Dynamically Typed

In Python, you don't have to worry about type declaration. It is a dynamically typed language, which means Python automatically determines the data type of a variable at runtime.

We don't have to explicitly tell Python the data type for every variable we use; it is smart enough to identify the type based on the value we assign to it.

Interpreted

Python is an interpreted language. It doesn't use a compiler like C, which translates the whole code into machine language at once.

Instead, the Python interpreter executes code line-by-line. This means the program stops exactly where an error occurs, making debugging much easier for developers. However, this process also makes Python slower, because the interpreter has to execute each line every time you run the script.

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