Forem: Leandro Rodrigues Alexandre

Let's Go with CSharp!

Leandro Rodrigues Alexandre — Thu, 31 Jul 2025 13:04:48 +0000

Learn C# in 2025: A Beginner-Friendly Guide (With Real-World Examples)
New to programming or switching stacks in 2025? If you’re curious about C#, this guide is for you. I’ll walk you through the first steps — from installing your development environment to writing simple programs that solve everyday problems.

My Setup (But You Can Use Yours Too)
Here’s what I personally use to code in C#:
MacBook Pro M2
IDE: JetBrains Rider — fast, cross-platform, and perfect for .NET development
Terminal: Warp — a modern terminal with AI and smart suggestions
.NET SDK: Latest stable version (like .NET 8 or higher)
You can follow this tutorial on Windows, Linux, or macOS — Rider is optional; Visual Studio Code or Visual Studio also work great!

Step 1: Installing the .NET SDK
To write and run C# code, you need the .NET SDK.
Go to: https://dotnet.microsoft.com/en-us/download
Download and install the latest LTS version (e.g., .NET 8)
Open your terminal and verify the installation:

dotnet --version

Step 2: Create Your First Project
Let’s start with the famous “Hello, World!”

dotnet new console -n HelloWorldApp
cd HelloWorldApp
dotnet run

It will output:

Hello, World!

Welcome to the world of C#!

Step 3: Understanding the Project Structure
A basic console project looks like this:
Program.cs: Where your C# code lives
HelloWorldApp.csproj: Project config
bin/ and obj/: Output folders generated during build
You can open this project in Rider, Visual Studio Code, or any C#-compatible IDE.

What Can You Build With C#?
Here are some everyday use cases:
Automate tasks like file renaming or batch operations
Build your own command-line tools
Create powerful web APIs using ASP.NET Core
Make bots for Telegram, Discord, etc.
Create games with Unity
Work with Excel files and PDFs
Build small utilities to solve personal or work problems

Real-World Example: Email Validator
Here's a simple program to check if an email is valid:

using System.Text.RegularExpressions;

Console.WriteLine("Enter your email:");
var email = Console.ReadLine();

bool isValid = Regex.IsMatch(email, @"^[^@\s]+@[^@\s]+\.[^@\s]+$");

Console.WriteLine(isValid ? "Valid email!" : "Invalid email.");

What's Next? (Stay Tuned!)
In the next articles, I’ll cover:
Variables, data types, and functions in C#
Creating your first calculator
Introduction to Object-Oriented Programming (OOP)
Building your first REST API with ASP.NET Core
Storing data with Entity Framework Core (EF Core)
Writing unit tests in a beginner-friendly way

Final Thoughts
If you enjoyed this guide, drop a comment or follow me here on Dev.to. I’ll be sharing more step-by-step tutorials very soon!

Object-Oriented Programming (OOP) in Python

Leandro Rodrigues Alexandre — Tue, 15 Apr 2025 19:31:11 +0000

📘 Educational Documentation: Object-Oriented Programming (OOP) in Python

Development Environment:
Terminal: Warp
IDE: IntelliJ IDEA with Python Plugin

What is Object-Oriented Programming (OOP)?

Object-Oriented Programming is a paradigm that organizes code around "objects" that represent real-world entities with properties (attributes) and behaviors (methods).

Key Concepts:
Class: Blueprint to create objects.
Object: Instance of a class.
Attribute: Characteristic of an object.
Method: Behavior or action of an object.
Encapsulation: Hiding internal details of an object.
Inheritance: Reusing code through class hierarchies.
Polymorphism: Ability of different classes to respond to the same method differently.
Abstraction: Modeling relevant objects while hiding unnecessary complexity.

Everyday Example:
A Person is a class. João and Maria are objects of this class. They have attributes like name and age, and methods like speak or walk.

Setting Up the Environment

Warp Terminal
Download and install Warp (https://www.warp.dev/)
Use the terminal to navigate to your project directory.
IntelliJ IDEA with Python Plugin
Download IntelliJ IDEA (https://www.jetbrains.com/idea/)
Go to Preferences → Plugins → Marketplace and install the "Python" plugin.
Create a new Python project (File → New Project → Python).
Set up the virtual environment:

Creating Your First Class and Object

Class: Person

Encapsulation

Hides internal data of the object, allowing controlled access.

Inheritance

Allows a class to inherit attributes and methods from another class.

Polymorphism

Allows methods with the same name to behave differently depending on the class.

Abstraction with abc

Create abstract classes with mandatory methods.

Practical Project: User Registration System

Structure:
Base class: User
Subclasses: Admin, Client
Methods: show_data(), validate_age()

Tips with IntelliJ + Warp

Use shortcut Shift + Shift to search any file/command.
Use integrated terminal with Warp to run and test your scripts.
Enable debug mode: Run → Debug and set breakpoints beside the line numbers.

10. Illustration: Class Structure

(Add diagram with labels: class, attributes, methods, inheritance)
I can generate an image representing this structure. Would you like it now?

✅ Conclusion

Object-Oriented Programming allows you to create more organized, reusable, and scalable applications. With Python, these concepts are applied in a simple and clear way. Practice by creating your own classes and relationships!

If you'd like, I can continue expanding this content with:

Practical exercises
Guided projects
Learning checklists
Visual explanations per concept

BONUS

Mini Game:

Story-Style Explanation

Imagine you are playing with building blocks. Each block is special:
A blue block is a Rabbit — it hops.
A green block is a Turtle — it walks slowly.
A brown block is a Horse — it runs fast.
You build your toy and say: "Block, run!" And each one runs in its own way!
This is what Object-Oriented Programming does: you tell the object what to do (like "run!"), and each object does it in its own unique way.

Data Structures and Algorithms in Python

Leandro Rodrigues Alexandre — Mon, 07 Apr 2025 13:39:09 +0000

1. Arrays e Linked Lists

Arrays
An array is a collection of elements stored in contiguous memory locations.

Characteristics:

Fast access to any element using an index.
Insertion/removal can be costly.

Linked Lists
A Linked List is a data structure where each element (node) points to the next.

Characteristics:

Efficient insertion/removal.
Sequential access.

2. Hash Tables

Hash tables store data in key-value pairs with fast lookup using hashing.

3. Heaps, Stacks, and Queues

Heaps
A heap is a special binary tree used to quickly access the smallest (min-heap) or largest (max-heap) element.

Stacks

A stack follows the LIFO (Last In, First Out) principle.

Queues

A queue follows the FIFO (First In, First Out) principle.

4. Binary Search Tree (BST)

A BST is a binary tree where the left subtree contains smaller values and the right subtree, larger ones.

5. Recursion

Recursion is when a function calls itself.

6. Sorting Algorithms

Bubble Sort

Merge Sort

Conclusion

Data structures and algorithms are essential for building efficient and scalable solutions. They are found in everyday tasks such as searching through lists, organizing files, queue systems, and much more.

Introductory Collections in Python

Leandro Rodrigues Alexandre — Sat, 05 Apr 2025 10:58:01 +0000

This document aims to explain, in a simple and straightforward way, the main types of collections in Python: Lists, Tuples, Sets, and Dictionaries. If you've never programmed before, don't worry!

1. Lists

What it is:
A list is like a box where you can store various items (numbers, words, etc.) in a specific order.

Example of a list in Python:

Main characteristics:

Maintains the order of items
Can be modified (add/remove items)
Accepts repeated items

Example usage:

2. Tuples

What it is:
A tuple is similar to a list, but the items inside it cannot be changed once they are defined.

Example of a tuple in Python:

Main characteristics:

Maintains the order of items
Cannot be modified (immutable)
Accepts repeated items

Example usage:

3. Sets

What it is:
A set is a collection of items without a defined order and without repetition.

Example of a set in Python:

Main characteristics:

Does not maintain order
Does not accept duplicate items
Can be modified

Example usage:

4. Dictionaries

What it is:
A dictionary is a collection of key-value pairs. Think of it like a notebook where each word (key) has a definition (value).

Example of a dictionary in Python:

Main characteristics:

Uses key:value pairs
Does not accept repeated keys
Can be modified

Example usage:

Conclusion

These four types of collections are widely used in Python and are essential for beginners. Think of them as different ways to store and organize information:

List: a shelf with order
Tuple: fixed shelf
Set: bag with no repeated items
Dictionary: mini notebook with word and meaning
Explore, test, and see how each one behaves in practice!

Let’s imagine a day in the life of Maria, who is planning a visit to the market.

Step 1 – The List (List):
Before leaving, Maria writes down all the things she needs to buy: apples, bread, milk, and eggs. She might remember later that she also needs bananas, so she adds that to her list. The list helps her keep everything in order, and she can add or remove items anytime. This is just like a Python list: ordered and flexible.

Step 2 – The Colors of the Bags (Tuple):
Maria has three reusable shopping bags—one red, one green, and one blue. These are always the same and never change. No matter how many times she goes shopping, these are the bags she uses. They represent a tuple: fixed and dependable.

Step 3 – The Fruits She Picks (Set):
At the market, Maria picks up various fruits. She ends up with an apple, a banana, and another banana. But at the end, she only counts the unique fruits she got: apple and banana. That’s how a set works—it automatically removes duplicates and doesn't care about order.

Step 4 – The Receipts (Dictionary):
When Maria returns home, she looks at the receipt. It shows what she bought and how much each item cost: 'apple': $1, 'milk': $2, 'bread': $1.5. This is a dictionary in action—each item (key) is linked to its price (value).

By using a list, tuple, set, and dictionary, Maria’s simple shopping trip becomes a perfect analogy for how Python collections work in everyday life.

🐍 Mastering the Basics of Python: Type Casting, Exceptions, Functions, and Built-in Functions

Leandro Rodrigues Alexandre — Fri, 04 Apr 2025 09:40:18 +0000

I’ve started diving into Python, and to make everything easier, I’m documenting what I’m learning! Today, I want to explain Type Casting, Exceptions, Functions, and Built-in Functions in a way that’s simple and direct.

🎭 Type Casting
When you work with Python, sometimes the data types aren’t what you expect. Let’s say you have a number stored as text (a string), but you need to use it in a mathematical operation. What do you do? The solution is converting the variable's type — this is what we call Type Casting.
Imagine you have a number stored as text and you want to add it to another number. To do that, you need to convert the text to an integer.
Example:

You can also convert between other types:
int(value): Converts to an integer
float(value): Converts to a decimal number
str(value): Converts to text
list(value): Converts to a list
It’s simple but super useful!

🚨 Exceptions (Error Handling)
Now, let’s talk about an important aspect: errors. Who hasn’t faced that annoying error, right? 🤦‍♂️ Well, in Python, we can handle those errors so that our program doesn’t break completely.
The way we handle errors is by using try and except. This allows you to try running a piece of code, and if it fails, you catch the error and can show a friendly message or take some action.
Example:

Output:

This way, the program doesn’t “crash.” It just handles the error and keeps running.

🔄 Functions
Now, if you're writing code that you’ll use over and over again, how about organizing it in a way that you can reuse it anytime? That’s exactly what functions do. They help organize code and avoid repetition.
Imagine you always need to greet someone. Instead of writing the same code every time, you can create a function to do that:

Output:

If you need to use it again, just call the function! Simple, right?
Functions can also return values. For example, if you want to add two numbers, you can create a function to do that:

Output:

🏗 Built-in Functions
Python also comes with lots of built-in functions. These are super helpful for common tasks, like counting the number of characters in a string or adding numbers.
Examples of built-in functions:

Output:

🚀 Conclusion
Now that you know fundamental concepts like Type Casting, Exceptions, Functions, and Built-in Functions in Python, understand that these are essential steps to writing cleaner, more efficient, and robust code. If you're just starting out, practice a lot! These concepts are the foundation for creating amazing programs. And remember: we learn by making mistakes.
I'm starting to document my Python journey, and maybe by sharing what I’m learning, I can help others with doubts to learn as well. What motivates me every day is knowing that each small achievement brings me closer to doing what I love and feeling happy about sharing this knowledge. Not everyone has the same amount of time or opportunities, but we can always help each other.
Let’s build a chain of learning and collaboration, where everyone has a space to grow and include themselves in the world they want to be in! Every dream is possible, no matter the size.
Let’s go on this journey together! 💻✨

Basic Syntax of Python 3

Leandro Rodrigues Alexandre — Thu, 03 Apr 2025 15:28:48 +0000

Basic Syntax of Python 3

Python 3 is a high-level programming language known for its simple and readable syntax. Unlike other languages, Python uses indentation to define code blocks, making the code more organized and intuitive.

1. Key Features of Python Syntax:
Mandatory Indentation
Instead of curly braces {} or keywords like begin and end, Python uses indentation (spaces or tabs) to structure the code:

2. Variable Declaration
Python does not require explicit type declaration, as it is dynamically typed:

3. Comments
To write comments in Python, use # for single-line comments and ''' ''' or """ """ for multi-line comments:

4. Conditional Statements
Python uses if, elif, and else for control flow:

5. Loops
for and while loops are used for repeating code:

6. Functions
Functions in Python are defined using def:

✔ Variables store values, just like a box where we can keep different types of information, such as numbers, words, or even lists of items. Python automatically identifies the type of each value.
✔ Indentation organizes the code. Unlike other languages that use {} to define code blocks, Python uses spaces or tabs (indentation). This makes the code more readable and organized, but it must be used correctly.
✔ Conditionals (if, elif, else) help make decisions. Just like in real life, where we make choices based on conditions, Python uses if, elif, and else to execute different actions depending on the situation.
✔ Loops (for and while) allow repeating actions. When we need to execute a piece of code multiple times without rewriting it, we use loops. The for loop iterates over elements in a list or sequence, while while runs a block of code as long as a condition is true.
✔ Functions (def) help organize and reuse code. A function is a reusable block of code that we can call whenever needed, making programs more efficient and easier to maintain.