Why Python Build Tools Feel Like Overkill for Most Projects

Why Python's Build Tools Feel Like Overkill for Most Projects

I’ve spent the last few years working with Python, and I’ve noticed something strange. Every new project seems to start with the same ritual: someone asks "which build tool should we use?" and then the team spends the next hour debating poetry vs. pipenv vs. setuptools vs. flit. Meanwhile, the actual code doesn’t get written until the afternoon.

This isn’t just my experience. At PythonSkillset, we’ve seen countless developers get bogged down by these decisions. And honestly? Most Python projects don’t need the complexity we’re throwing at them.

The Reality Check

Think about what most Python projects actually do. They’re either:

• A small script that processes some data
• A web app using Django or Flask
• A library that needs to be shared with others
• An automation tool for internal use

For the first two categories, the build tool doesn’t matter much. You’re going to use pip anyway. The framework handles the heavy lifting. So why are we adding extra layers?

Where the Pain Starts

Let me give you a real example. At PythonSkillset, we once had a junior developer spend three days trying to set up a project with Poetry. The issue? A version conflict between two dependencies that no one actually needed. The developer didn’t know how to resolve it because they were new to Python. The fix was simple: remove one unnecessary dependency. But the build tool made it feel like a disaster.

This happens all the time. Build tools like Poetry, Pipenv, and even the newer PDM are powerful. But they also introduce complexity that most projects don’t need. They add:

• Lock files that can be a pain to merge
• Virtual environment management that conflicts with other tools
• Dependency resolution that takes minutes for simple projects
• Syntax and configuration that’s different from normal pip

What Most Projects Actually Need

Here’s the truth: for 80% of Python projects, a requirements.txt file and simple virtual environment are enough. That’s it. No poetry.lock. No Pipfile.lock. No pyproject.toml with complicated build system section.

Just:

flask==3.0.0
requests==2.31.0
pandas==2.1.0

And then you run:

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

This works. It’s simple. Anyone who knows Python can maintain it. And when something breaks, you can fix it in minutes, not hours.

When Build Tools Actually Help

Now, I’m not saying build tools are useless. They shine in specific situations:

• Libraries you publish to PyPI: Tools like Flit or Setuptools make this simpler
• Projects with complex dependency trees: Poetry’s resolver helps avoid conflicts
• Teams that need exact reproducibility: Lock files are essential here
• Projects using modern packaging features: pyproject.toml becomes necessary

But for the average Python project—the one-liner script, the small web app, the data analysis notebook—these tools add overhead without benefit.

The Hidden Cost

Every tool you introduce has a learning curve. Every configuration file is another thing to maintain. When you use Poetry, you need everyone on your team to understand Poetry. When you use Conda, everyone needs Conda. This might seem small, but it adds up.

I’ve seen senior developers struggle to set up a project because they hadn’t used the specific build tool before. The tool became a barrier to entry. And for what? To have a slightly nicer way of managing dependencies?

A Simpler Approach

If you’re starting a new Python project today, here’s my advice:

1. Start with pip and requirements.txt – It’s battle-tested, simple, and works everywhere
2. Add a virtual environment – This is non-negotiable, but Python’s built-in venv is fine
3. Only add build tools when you have a specific need – Publishing a library? Add setuptools. Need exact reproducibility? Add Poetry. Otherwise, wait

Most importantly, remember that your build tool should serve your project, not the other way around.

Final Thoughts

Python’s build tools ecosystem is a testament to the language’s maturity. But maturity doesn’t mean complexity. Sometimes the simplest tool is the right one. If your build tool is making development harder instead of easier, maybe it’s time to step back and ask: do we really need this?

At PythonSkillset, we’ve seen that the best projects are the ones where developers spend more time writing code and less time configuring tools. Keep it simple. Your future self will thank you.