DEV Community: Jessica milano

Getting Started with Python: Build Your First Command-Line To-Do App

Jessica milano — Fri, 03 Jul 2026 00:33:46 +0000

If you've ever wanted to learn programming but felt overwhelmed by all the buzzwords, Python is one of the friendliest languages to start with. It reads almost like plain English, and you can build something useful in your very first sitting. In this guide, we'll walk through setting up Python and building a simple command-line to-do list — a classic first project that teaches you the core building blocks of any real application.

Why Python?

Python has become one of the most popular languages in the world, and for good reason:

Readable syntax — Python code looks close to natural language, so beginners can focus on logic instead of getting lost in symbols and semicolons.

Huge community — Whatever problem you run into, chances are someone has already asked (and answered) it online.

Versatile — The same language you use to build a to-do app today can power web servers, data analysis pipelines, or automation scripts tomorrow.

Batteries included — Python ships with a rich standard library, so you can do a lot without installing anything extra.

Setting Up Your Environment

Before writing any code, let's get Python installed.

Step 1: Install Python

Head over to python.org and download the latest version for your operating system. During installation on Windows, make sure to check the box that says "Add Python to PATH" — it'll save you a headache later.

Step 2: Verify the Installation

Open your terminal (or Command Prompt) and run:

python --version

If you see a version number printed back, you're ready to go.

Step 3: Create a Project Folder

mkdir todo-app
cd todo-app

Step 4: Create Your Script File

Inside that folder, create a file called todo.py. This is where all our code will live.

Building the To-Do App

We're going to build a simple app that lets you:

Add tasks
View your task list
Mark tasks as complete
Exit the program

Step 1: Set Up the Task List

At the top of todo.py, add:

tasks = []

def show_menu():
    print("\n--- To-Do List ---")
    print("1. Add a task")
    print("2. View tasks")
    print("3. Mark a task as done")
    print("4. Exit")

Step 2: Add the Core Functions

def add_task():
    task = input("Enter a new task: ")
    tasks.append({"task": task, "done": False})
    print(f"Added: {task}")

def view_tasks():
    if not tasks:
        print("Your list is empty.")
        return
    for i, t in enumerate(tasks, start=1):
        status = "✓" if t["done"] else " "
        print(f"[{status}] {i}. {t['task']}")

def complete_task():
    view_tasks()
    if not tasks:
        return
    choice = int(input("Which task number is done? "))
    if 1 <= choice <= len(tasks):
        tasks[choice - 1]["done"] = True
        print("Nice work — task marked complete!")
    else:
        print("That task number doesn't exist.")

Step 3: Tie It All Together

def main():
    while True:
        show_menu()
        choice = input("Choose an option (1-4): ")

        if choice == "1":
            add_task()
        elif choice == "2":
            view_tasks()
        elif choice == "3":
            complete_task()
        elif choice == "4":
            print("Goodbye!")
            break
        else:
            print("Please choose a valid option.")

if __name__ == "__main__":
    main()

Step 4: Run It

Back in your terminal:

python todo.py

You now have a working to-do list you can add to, check off, and manage entirely from the command line.

What You Just Learned

In building this small app, you actually practiced several core programming concepts:

Lists and dictionaries — storing structured data
Functions — organizing code into reusable pieces
Loops and conditionals — controlling the flow of a program
User input — making a program interactive

Where to Go From Here

This to-do app is intentionally simple, but it's a great foundation. From here, you could try:

Saving tasks to a file so they persist after you close the program
Adding due dates or priority levels
Turning it into a small web app using Flask

Programming rewards curiosity more than talent — the more small projects you build, the more natural it all becomes.

Every workspace could use a little personality once you're done coding for the day — much like a well-placed neon sign adds character to a room, a clean, well-organized script adds a bit of craftsmanship to your code.

Happy coding!

Why Python Remains the Best Programming Language for Beginners in 2026

Jessica milano — Thu, 18 Jun 2026 17:11:36 +0000

Learning to code for the first time can feel a bit like standing at the entrance of a massive library with no idea which book to open first. Every direction seems to offer a different path. JavaScript promises web development. C++ is praised for performance. Java dominates enterprise software. Then there's Python—a language that somehow manages to stay at the top of nearly every "best language for beginners" list year after year.

The obvious question follows:

If so many programming languages exist, why does Python continue to be the go-to recommendation for new programmers in 2026?

The answer isn't simply because it's easy to learn. While accessibility certainly plays a role, Python's enduring popularity stems from something much bigger: it offers beginners a rare combination of simplicity, versatility, and real-world relevance.

In a technology landscape increasingly driven by artificial intelligence, automation, and data, Python remains one of the few languages that allows newcomers to start small while opening doors to some of the industry's most exciting opportunities.

What Exactly Is Python?

Python is a high-level, interpreted programming language created by Guido van Rossum and first introduced in 1991.

Unlike many older programming languages that prioritize technical complexity or strict syntax rules, Python was designed around readability. The philosophy behind the language has always been simple: code should be easy for humans to understand.

That design decision proved remarkably successful.

Today, Python is used by everyone from complete beginners writing their first program to engineers building sophisticated artificial intelligence systems. It powers web applications, automates repetitive business tasks, analyzes enormous datasets, supports cybersecurity operations, and serves as a foundation for countless machine learning projects.

Few programming languages have achieved such broad applicability.

Why Python Continues to Dominate in 2026

Python Remains at the Heart of the AI Boom

Artificial intelligence is no longer an emerging technology—it's becoming part of everyday life.

From intelligent assistants and recommendation systems to generative AI platforms and advanced analytics tools, AI is reshaping industries at an unprecedented pace. And throughout this transformation, Python continues to be the language most developers reach for first.

There are practical reasons for that.

Powerful frameworks such as TensorFlow, PyTorch, and Scikit-learn make building machine learning applications significantly more accessible than they would otherwise be.

For beginners interested in artificial intelligence, Python offers perhaps the smoothest entry point available today.

You can start by learning variables and loops and eventually find yourself creating predictive models, image-recognition systems, or AI-powered applications without abandoning the language you learned on day one.

That's a rare advantage.

The Learning Curve Is Surprisingly Gentle

One reason beginners often quit programming is frustration.

Complex syntax, cryptic error messages, and endless punctuation requirements can make learning feel overwhelming. Python avoids much of that friction.

Its syntax is intentionally clean and readable. In many cases, Python code resembles plain English more closely than traditional programming languages.

Consider the classic first program:

print("Hello, World!")

That's it.

No excessive boilerplate. No complicated declarations. No intimidating blocks of code.

Because the language itself stays out of the way, learners can focus on understanding programming logic rather than memorizing syntax rules.

That seemingly small difference often has a huge impact on confidence and long-term progress.

An Enormous Community Means You're Never Learning Alone

Every programmer gets stuck.

It's not a matter of if—it happens to everyone.

The difference is how quickly you can find help.

Python benefits from one of the largest and most active developer communities in the world. Whether you're troubleshooting an error, looking for project ideas, exploring a new framework, or trying to understand a difficult concept, chances are someone has already encountered the same challenge.

Thousands of tutorials, discussion forums, video courses, open-source projects, and documentation resources are available online.

For beginners, this support ecosystem can be invaluable.

Instead of spending hours searching for answers, you'll often find solutions within minutes.

Employers Continue to Value Python Skills

Technology trends come and go.

Programming languages rise in popularity, then gradually fade as industry needs evolve. Python, however, has demonstrated remarkable staying power.

In 2026, Python remains one of the most sought-after technical skills across multiple industries.

Organizations use it for everything from automating internal workflows to powering large-scale cloud applications and advanced analytics systems. As a result, Python knowledge can lead to opportunities in a wide variety of career paths.

Some of the most common include:

Data Science
Software Engineering
Machine Learning Engineering
Artificial Intelligence Development
Cybersecurity
Automation Engineering
Cloud Computing
Business Intelligence

The beauty of learning Python is that it doesn't lock you into a single specialization. Instead, it provides a foundation that can support numerous career directions as your interests evolve.

Few Languages Are This Versatile

Versatility is where Python truly shines.

Many programming languages excel in one particular area. Python manages to perform exceptionally well across many.

With Python, you can build:

Dynamic websites and web applications
Automation tools that eliminate repetitive tasks
Data visualization dashboards
Machine learning models
Scientific computing projects
Cybersecurity utilities
Robotics applications
Internet of Things (IoT) systems
Desktop software
AI-powered chatbots

This flexibility means the time invested in learning Python continues to pay dividends regardless of where your professional journey leads.

Creativity can take many forms, from designing custom decor to creating digital experiences. Even making art with code—whether you're visualizing complex data or creating a custom animation that looks as flashy as a neon beer signs on your website, shows how powerful visual design can be in capturing attention and creating memorable experiences
You learn one language—but gain access to countless possibilities.

Beginner Projects That Actually Build Real Skills

Reading tutorials has its place.

Building projects is where genuine learning happens.

The moment you begin solving real problems with code, abstract concepts suddenly become meaningful. Variables, functions, loops, and data structures stop being theoretical ideas and become practical tools.

If you're new to Python, consider experimenting with projects such as:

A calculator application
A task management or to-do list system
A weather dashboard using public APIs
A web scraper that collects online data
A personal budgeting tool
A basic AI chatbot
A password generator
A habit-tracking application
A data visualization dashboard

Each project introduces new challenges while reinforcing the fundamentals you'll use throughout your programming journey.

Getting Started Is Easier Than Ever

One of Python's biggest strengths is its accessibility.

You don't need expensive hardware. You don't need a computer science degree. You don't even need complicated software installations if you don't want them.

Most beginners can start with just three things:

The latest version of Python
A code editor such as Visual Studio Code or PyCharm
Access to learning resources and documentation

Prefer a browser-based approach?

Platforms like Replit and Jupyter Notebook allow you to write and execute Python code directly online, eliminating much of the setup process altogether.

In other words, there are very few barriers standing between you and your first program.

Final Thoughts

Technology changes rapidly. New frameworks emerge. Programming trends shift. Entire industries evolve.

Yet through all of that change, Python continues to hold a unique position.

In 2026, it remains one of the most beginner-friendly programming languages available while simultaneously serving as a cornerstone of modern software development, artificial intelligence, automation, and data science.

That's a powerful combination.

For newcomers, Python offers an approachable introduction to coding. For experienced developers, it provides the tools necessary to build sophisticated, real-world applications. Very few languages manage to serve both audiences so effectively.

Whether your goal is to create websites, analyze data, automate tedious tasks, explore cybersecurity, or build the next generation of AI applications, Python provides a strong and future-proof foundation.

And for many developers, that first line of Python code becomes the starting point of a lifelong journey in technology.