DEV Community: Embrence

The Python Operator Most Developers Ignore: :=

Embrence — Wed, 05 Aug 2026 17:28:32 +0000

When I first discovered the walrus operator (:=), I thought:

“It’s just syntactic sugar.”

After all, you can write the same code without it.

So why does it exist?

What does the walrus operator do?

The walrus operator lets you assign a value while evaluating an expression.

Instead of this:

match = pattern.match(line)
if match:
print(match.group())

You can write:

if (match := pattern.match(line)):
print(match.group())

You both assign and check the value in one place.

Where it actually shines

One of my favorite use cases is list comprehensions.

import re
pattern = re.compile(r"ERROR (\d+): (.*)")
errors = [
(int(m.group(1)), m.group(2))
for line in log_lines
if (m := pattern.match(line))
]

Without :=, you’d either need an extra loop or call pattern.match() twice.

Another practical example is guard clauses.

if (result := a * b) > 10:
raise ValueError(
f"Result ({result}) is too large."
)

Here, the value is calculated only once and can be reused in the error message.

Should you use it everywhere?

Probably not.

The walrus operator improves code only when it makes the logic easier to follow.

If it makes a line harder to read, a separate assignment is usually the better choice.

Like many Python features, it’s a tool—not a rule.

Final thoughts

At first glance, the walrus operator looks unnecessary.

But in the right situations, it reduces repetition, avoids duplicate calculations, and keeps related logic together.

The key is using it intentionally, not everywhere.

What’s your opinion?

Do you use the walrus operator in your projects, or do you prefer traditional assignments?

Should You Use assert in Python?

Embrence — Wed, 05 Aug 2026 17:04:57 +0000

One of the more controversial Python discussions isn’t about frameworks or performance.

It’s about a single keyword:

assert

Some developers argue that assert should never be used.

Their reasoning is straightforward: assertions are removed when Python is run with optimization (python -O). If a check can disappear in production, they argue, it shouldn’t be responsible for enforcing important conditions.

Instead, they recommend explicit exceptions:

if age < 18:
raise ValueError("Age must be at least 18")

On the other hand, many experienced Python developers make a distinction between validating external input and checking internal assumptions.

For example:

assert user is not None

This isn’t validating user input.

It’s documenting an assumption that should already be true if the rest of the program is correct.

If the assertion fails, it usually indicates a bug in the program rather than invalid input from a user.

That’s why many developers use assert for debugging and internal invariants while relying on exceptions for runtime validation.

The important question isn’t:

“Should I always use assert?”

It’s:

“What am I trying to protect?”

If you’re validating user input, API responses, files, or anything that can legitimately fail during normal execution, exceptions are usually the appropriate choice.

If you’re checking assumptions that should never be false unless your own code contains a bug, an assertion can make that intent explicit.

In other words, assert and exceptions solve different problems.

What do you think?

Do you use assert in your projects, or do you prefer explicit exceptions everywhere?

Why I’m Writing This on a Programming Blog

Embrence — Sat, 01 Aug 2026 17:47:13 +0000

If you’ve followed my posts, you probably expected another article about Python, development, or learning to code.

This isn’t one of those posts.

I don’t usually talk about my personal life online, but I think this is more important than another tutorial.

For a long time, I struggled with my mental health. I’m not going to discuss diagnoses because they aren’t the point. What matters is that I eventually reached out for professional help, and treatment changed my life.

One thing I’ve learned is that many people—especially developers and students—convince themselves that they’re “just tired,” “just stressed,” or that things will get better if they ignore the problem.

Sometimes they do.

Sometimes they don’t.

If you’re constantly exhausted, overwhelmed, anxious, or feel like you’re carrying more than you can handle, please don’t ignore it. Asking for help isn’t weakness, and it isn’t failure.

If professional help isn’t immediately available, talk to someone you trust. A friend, a family member, a teacher—anyone who will listen. Many countries also have free mental health organizations and crisis support services.

I’m not a psychologist, and this isn’t medical advice. I just know what it’s like to feel alone, and I don’t want someone else to stay silent because they think nobody will understand.

Programming teaches us to debug problems instead of pretending they don’t exist.

Our own minds deserve the same attention.

Take care of yourselves

5 Python Resources I Wish I Knew When I Started Learning

Embrence — Sat, 01 Aug 2026 14:57:39 +0000

Learning Python can feel overwhelming.

There are thousands of tutorials, courses, books, and tools. The hardest part is not finding resources — it’s finding the right ones.

Here are some Python resources that are actually worth your time:

Automate the Boring Stuff with Python

Perfect for beginners who want to build useful things quickly.

You will learn:

File automation
Web scraping
Working with spreadsheets
Creating practical scripts

Python Crash Course

A project-based book that helps you learn by building.

Great for:

Beginners
Personal projects
Understanding how developers think

Python Official Documentation

The most underrated resource.

Learning how to read documentation is a skill every developer needs.

freeCodeCamp

Free, detailed courses covering Python basics and real projects.

Real Python

A great platform for improving your Python skills with practical tutorials.

⸻

My advice:

Don’t collect resources forever.

Pick one.
Build projects.
Make mistakes.
Improve.

Programming is learned by writing code, not only watching tutorials.

I’m building @embrence to share Python tips, resources, tools, and projects for developers.

More practical content coming soon. 🐍