Category: Python

“What’s the best way to learn Python in 2025?”

I get asked this question at least once every encounter with someone who wants to start learning to program. And every single time, I want to give a straightforward answer, some magic course or perfect roadmap that unlocks Python mastery in 30 days. But here’s the truth that nobody wants to hear: there is no best way.

The question itself is flawed. It’s like asking “What’s the best way to get fit?” when you haven’t decided whether you enjoy running, lifting weights, or playing basketball. The answer completely depends on who you are.

The One-Size-Fits-All Myth

We’ve been conditioned to believe that somewhere out there exists the ultimate Python course. The one with perfect reviews, taught by a Stanford professor, with gamified lessons and AI-powered feedback. If we could just find it, learning would be effortless.

But I’ve watched countless people burn through Udemy courses, abandon Codecademy subscriptions, and give up on thick O’Reilly books, all while convinced they were following the “best” path. The problem wasn’t the resources. The problem was the mismatch between the learning method and how their brain actually works.

The Three Learning Tribes

Through years of talking with developers, I’ve noticed that most people fall into three learning tribes. Understanding which one you belong to changes everything.

The Builders (Learning by Doing)

If you’re a Builder, reading documentation feels like torture. Watching tutorial videos makes you jumpy. You need to get your hands dirty immediately, breaking things, fixing them, and figuring stuff out through experimentation.

I’m a Builder. Back in 2018, I stumbled across a 4-hour FreeCodeCamp Python course on YouTube. I didn’t just watch it. I coded along, pausing every few minutes to tinker with the examples. When the instructor built a calculator, I built a tip calculator. When they showed loops, I created a number guessing game.

Here’s what that first game looked like:

import random

secret_number = random.randint(1, 100)
guesses = 0

print("I'm thinking of a number between 1 and 100...")

while True:
    guess = int(input("Your guess: "))
    guesses += 1
    
    if guess < secret_number:
        print("Too low!")
    elif guess > secret_number:
        print("Too high!")
    else:
        print(f"You got it in {guesses} guesses!")
        break

Was it elegant? Absolutely not. But I built it, it worked, and I learned more from those 30 lines than I would have from reading three chapters about control flow.

If you’re a Builder: Skip the theory-heavy courses. Start with project-based learning. Build a password generator. Create a weather app that scrapes data from a website. Make a bot that texts you daily motivation quotes. The messier, the better.

The Readers (Learning by Understanding)

Some people need to understand the “why” before they touch the “how.” If you’re a Reader, you want to see the full picture, understand the underlying concepts, and build a mental model before writing a single line of code.

Readers thrive with books like “Python Crash Course” or “Automate the Boring Stuff.” They love documentation, written tutorials, and blog posts that explain not just what code does, but why it’s designed that way.

My friend Alex is a Reader. She spent two weeks reading about Python fundamentals before writing any code. When she finally started coding, though, everything clicked instantly because she’d built such a solid conceptual foundation.

If you’re a Reader: Invest in quality books and written resources. Don’t feel guilty about spending a week reading before coding. Take detailed notes. Draw diagrams. Create your own documentation. Once you start coding, you’ll move faster than everyone else because you’ll actually understand what’s happening under the hood.

The Watchers (Learning by Observing)

Watchers learn best when someone shows them how it’s done. They need to see the process, hear the explanations, and follow along with an instructor who can demonstrate techniques in real-time.

Video courses, live coding sessions, and bootcamps are perfect for Watchers. They benefit from seeing someone else’s thought process, including the mistakes and debugging sessions that books and documentation skip over.

If you’re a Watcher: YouTube is your goldmine. Channels like Corey Schafer, Tech With Tim, and freeCodeCamp have hundreds of hours of quality Python content. Consider joining a bootcamp or taking a comprehensive video course on Udemy or Coursera. Watch someone build a complete project from start to finish, then recreate it yourself.

Finding Your Tribe (And It’s Okay to Overlap)

Most people aren’t purely one type. I’m primarily a Builder, but I still watch videos when I’m learning a completely new concept, and I’ll read documentation when I need to understand something deeply.

Here’s a quick test: Think about the last time you learned something new, maybe cooking a recipe, assembling furniture, or figuring out a new app.

• Did you dive right in and figure it out as you went? (Builder)
• Did you read all the instructions first? (Reader)
• Did you watch a tutorial or ask someone to show you? (Watcher)

Your natural instinct tells you everything you need to know.

Making It Work in Your Actual Life

Here’s the part nobody talks about: even the perfect learning method fails if it doesn’t fit your lifestyle.

You have three uninterrupted hours on Sunday mornings? That’s perfect for diving deep into a comprehensive course or building a substantial project.

You commute an hour each way? Audio courses or podcasts about programming concepts might be your secret weapon.

The best learning method isn’t just about your learning style. It’s about the intersection of your style and your real-world constraints.

Your First Steps (Starting Today)

Enough theory. Here’s what to do right now:

1. Pick a small project (not a course): Think of something you’d actually use. A budget tracker? A script that renames your messy photo library? A program that reminds you to drink water?
2. Start building it badly: Don’t research the “right” way. Google as you go. Copy code from Stack Overflow. Make it work first, make it pretty later.
3. Notice when you’re stuck: Are you stuck because you don’t understand a concept? Read about it. Need to see how something works? Watch a video. Want to just try different approaches? Experiment in code.
4. Double down on what works: When something clicks, do more of that. If a particular YouTube channel makes sense, binge their content. If you loved building your first project, build three more.
5. Ignore the guilt: You don’t need to finish that course you bought. You don’t need to read that 800-page book. Learning isn’t about completing resources—it’s about building skills.

The Real Secret

Want to know what actually separates people who learn Python from people who buy Python courses? It’s not intelligence, prior experience, or finding the “best” resource.

It’s simply this: they start building something that matters to them, using a method that fits their brain, on a schedule that fits their life. And they don’t quit when it gets hard.

So here’s my actual answer to “What’s the best way to learn Python in 2025?”

Figure out how you learn best. Build something. Start today. Adjust as you go.

The best way isn’t out there waiting to be discovered. You create it yourself, one line of code at a time.

Recently, someone asked me: “How do I avoid running into type issues in python?”

The question came after they’d spent an entire afternoon debugging what they assumed was a logic error, only to discover the real culprit was a type mismatch. A function they thought returned a list was actually returning a string, and that single assumption fell into hours of frustration.

I couldn’t help but laugh, not at them, but with them. Because, I’d been there just weeks before.

The Problem With Dynamic Typing

Don’t get me wrong. I love Python’s dynamic typing. It’s one of the reasons Python feels so intuitive and quick to write. You don’t need to declare types everywhere, which makes prototyping fast and code readable.

But that flexibility comes with a hidden cost.

Imagine this, You’re reviewing code from a teammate. You see a variable named lst, and naturally assume it contains a list. You write a loop, maybe call .append() or iterate with an index. Everything looks fine.

Then you run the code and get an error. Turns out, lst was actually a string the whole time. Now you’re diving through multiple files, tracing function calls, and questioning your career choices.

Sounds familiar?

Enter Type Hints

The solution that transformed my workflow: type hints.

Introduced in Python 3.5, type hints are optional annotations that specify what types your variables, parameters, and return values should be. They look like this:

def get_user_names(user_ids: list[int]) -> list[str]:
    """Fetch user names from a list of user IDs."""
    return [fetch_name(uid) for uid in user_ids]

Notice the : list[int] after the parameter and -> list[str] before the colon? Those are type hints telling you exactly what goes in and what comes out.

Why Type Hints Changed Everything

1. Bugs caught before runtime – With a static type checker like mypy, type mismatches get flagged before the code even runs. No more surprise errors in production.
2. Self-documenting code – Instead of digging through function implementations or docstrings, you can see at a glance what types a function expects and returns.
3. Better IDE support – Modern editors like VS Code and PyCharm use type hints to provide accurate autocomplete suggestions and catch errors as you type.
4. Easier Refactoring – When you change a function’s return type, your type checker immediately shows you every place that needs updating.

Conclusion

Python’s dynamic typing is a feature, not a bug. But type hints give you the best of both worlds: the flexibility of dynamic typing during development and the safety of static typing when you need it.

If you’re still debugging type errors for hours, give type hints a try. Your future self will thank you.

And that person who asked me the question? They’re now a type hints user too.