Stop Using Print for Debugging: Use Python's Built-in Tools

Why Most Developers Ignore Python’s Best Debugging Tools (And Why That’s a Mistake)

I’ve seen it happen more times than I can count. A developer hits a bug, fires up a dozen print() statements, and spends the next hour digging through logs. Meanwhile, Python ships with tools that could solve the problem in minutes—but nobody uses them.

It’s not laziness. It’s habit. And it’s costing teams real time and real headaches.

The Print Statement Trap

Let me be honest. I’ve been guilty of this too. When something breaks, the instinct is to add print("here") and see what happens. It works for small scripts. But I’ve watched developers push dozens of print statements into production code, only to remove them later and introduce new bugs.

At PythonSkillset, we’ve seen teams where debugging sessions blow into multi-day rabbit holes because they never bothered to learn the built-in debugger. The pdb module has been part of Python since version 2.0. It’s stable, it’s powerful, and it’s sitting there unused.

Why Are These Tools Overlooked?

The biggest reason is that debugging tools feel like learning overhead. When you’re under deadline pressure, the path of least resistance is more print(). But here’s the thing—once you learn a tool like pdb, you solve bugs faster than you ever could with print statements.

There’s also the perception that debugging tools are for advanced users only. That’s false. Python’s pdb is surprisingly accessible. To start a debugging session, you can insert this one line anywhere in your code:

import pdb; pdb.set_trace()

That stops execution and drops you into a command-line debugger. From there, you can step through code, inspect variables, and even execute Python expressions on the fly. No special editors. No plugins. Just pure Python.

What You’re Missing

Here’s a real-world example from a project I worked on at PythonSkillset. We had a data pipeline that was occasionally corrupting CSV files. The developer spent two days adding print statements to trace the issue. When I showed them pdb, we found the bug in 15 minutes—a race condition that only occurred when two files were processed simultaneously.

Tools like pdb let you freeze time. You can see exactly what variables hold at the exact moment things go wrong. Print statements give you a snapshot, but debugging tools give you the whole movie.

Beyond pdb

Python’s debugging ecosystem doesn’t stop there. The ipdb package gives you an IPython-like debugger with syntax highlighting and tab completion. For larger projects, pdb++ adds features like sticky mode and better stack traces.

Even simpler is the breakpoint() function introduced in Python 3.7. It does the same as pdb.set_trace() but respects the PYTHONBREAKPOINT environment variable, so you can switch debuggers without changing your code.

How to Start

If you’ve never used a Python debugger, start small. Next time you hit a tricky bug, replace your first print() statement with breakpoint(). Run your script. You’ll see a (Pdb) prompt. Type help to see available commands. Try n to step to the next line, c to continue, and p variable_name to print a variable’s value.

That’s all it takes to get started. The rest you can learn as you go.

The Bottom Line

Neglecting Python’s debugging tools is like owning a workshop full of power tools and insisting on using a hand saw. Yes, you can get the job done. But you’re working harder than you need to.

At PythonSkillset, we’ve made debugging tools a standard part of our onboarding. New developers learn pdb before they write their first production code. It saves us hours every week.

Give it a real try. Not just a glance. The next time you’re stuck, skip the print() and drop a breakpoint(). You might wonder why you waited so long.