A few months ago, I published You're a Real JavaScript Developer Only If...
It was supposed to be a little post for fun.
You know, just a few things JavaScript developers could laugh about before going back to fighting their bugs 😅
But the community loved it, and the comments made me realize that developers have an incredible talent for turning their daily struggles into comedy.
Then @sylwia-lask published her own take, You're a Real Software Developer Only If… and surprised me how much fun this kind of post can be.
So I kept the fun going.
I published You're a Real TypeScript Developer Only If..., and now I'm back for another round with Python.
Well, Python developers have a very special relationship with whitespace 😂
They also have virtual environments, mysterious package conflicts, notebooks full of experiments, and that script that was supposed to take five minutes, but it became an entire project.
So, Python developers, this one's for you.
You're a real Python developer only if...
🤏🏻 You forgot one tiny indentation
Your code was almost perfect.
Almost.
Then Python reminded you that indentation is not just a formatting preference.
It's the difference between a working program and a confusing afternoon.
📦 You installed a package and broke everything
Everything was working perfectly.
Then you ran:
pip install some-package
Suddenly, another package needs a different version.
Your project has trust issues.
And you're asking what brought you here.
🧪 You created a virtual environment...
...and forgot to activate it.
You installed all your dependencies.
You ran your script.
And Python told you the module doesn't exist.
You installed it again.
Same problem.
Then you realized you were using the wrong environment.
🐼 You imported pandas just to open a CSV file
At first, it was a simple CSV.
A few rows. A few columns. Nothing complicated.
Then you started cleaning the data, filtering records, grouping results, and creating charts.
Three hours later, you're building an entire data analysis pipeline.
And you're having a great time.
🤔 You wrote a list comprehension and felt unstoppable
You started with a simple loop.
Then you discovered list comprehensions.
Now everything looks like this:
squares = [x**2 for x in range(10) if x % 2 == 0]
You could have written three lines, but this fits on one.
And that makes it better.
🐞 You used print() to debug everything
You could have used a debugger.
You could have added proper logging.
You could have investigated the issue systematically.
Instead:
print("HERE")
print(user)
print("WHY IS THIS NONE?")
And somehow, you found the bug.
📓 Your Jupyter notebook became a crime scene
You have cells numbered [1], [7], [14], and [39].
Some cells have been run five times.
Others haven't been touched since the day before.
One variable contains the result of an experiment you no longer remember.
And restarting the kernel feels like playing Russian roulette with your entire afternoon.
🧠 You discovered that is and == are not the same thing
You thought they did the same job.
Then someone explained object identity versus equality.
You nodded.
You understood the explanation.
You closed the article.
And six months later, you still pause for a few moments whenever you write one of them.
Just to be safe.
🐛 You caught a bug caused by None
Everything looked reasonable. The function ran. The variable existed.
But you were trying to perform an operation on None.
And the error message was basically Python saying:
"You gave me nothing. What exactly did you expect?"
Fair enough.
🔄 You turned a simple script into a reusable module
You needed to rename a few files.
So you wrote a quick script.
Then you added arguments.
Then error handling.
Then logging.
Then a configuration file.
Then a README.
At some point, you stopped calling it a script.
It's a tool now.
And you're considering publishing it on GitHub.
📚 You read the documentation and still had questions
Python has excellent documentation.
You know this and you appreciate it.
But sometimes you just want to know why a three-line example works in the tutorial and fails in your project.
So you open another tab. Then another.
And somehow, you're reading a discussion about a completely different problem.
That's programming.
🧹 You ran a formatter and discovered how much you needed it
Your code worked.
Your variable names made sense to you.
Your spacing was... creative.
Then you ran Black.
You didn't change the logic.
But you feel more professional already.
🚀 You wrote a Python script that worked locally...
...then discovered the server had a different Python version.
Or a missing dependency.
Or a different environment variable.
Or permissions you didn't know existed.
Your little script was supposed to automate a boring task.
Now you're learning deployment.
Character development comes in many forms.
🧩 You used try/except because you didn't want to see the error
You had an exception.
You didn't understand it.
So you wrote:
try:
do_the_thing()
except Exception:
pass
Problem solved!
Well, technically, the error disappeared.
The actual problem is still in the shadows.
And future-you is going to have some questions.
💛 You started learning Python because it looked simple
The syntax was clean.
The examples were easy to follow.
You could write something useful without spending half your day configuring a project.
You thought, "This language is so friendly!"
Then you met asynchronous programming, dependency management, packaging, decorators, and type hints.
Python is still friendly.
It just has a few rooms you haven't explored yet.
☕ You said, "I'll automate this little task"
You were doing something repetitive.
Surely, writing a script would save time.
So you spent two hours automating a task that takes five minutes.
Was it worth it?
Absolutely.
Will you admit how long it took?
Absolutely not.
🐍 The Python Developer Paradox
Here's the funny part.
You can spend an entire afternoon fighting with dependencies, wondering why your notebook has forgotten every variable, or trying to understand an error that looks completely unrelated to your code.
And the next day you open Python again.
Because you know how much you can build with it.
Python always has another interesting project waiting for you.
💬 Your Turn!
Python developers, although this list ended up being longer than I expected, but I know it still is missing some classics.
What's the most "Python developer" thing you've ever done?
Tell me your stories in the comments 😄
| Thanks for reading! 🙏🏻 I hope you found this useful ✅ Please react and follow for more 😍 Made with 💙 by Hadil Ben Abdallah |
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Top comments (26)
Hahaha, thanks, Hadil, for the mention! I'm not a python developer, but it's still funny 🤣
I know you're into JavaScript 😄
I went through almost every trick of the list. I think I'm a real Python developer 😅
If you went through over 70% of these stages, so you're a real Python developer 😅
I am python developer i know,behind the scene of python code
Then you definitely know there's a whole world hiding behind those clean Python lines! 😄
The syntax makes it look so simple, but the real adventure is when you get into what's happening underneath.
yeah definitely,after knowing behind the scene,i laugh on statement like "python is easy" ,assume these are not real python developer
Now days who Writes code in hand .. this kind of things done by LLM only . But me thinking about interview hands on coding round .
That's an interesting point! 😄 LLMs can definitely speed up writing code, but understanding what's happening, catching bugs, and knowing when the generated code is wrong still matter a lot.
And hands-on coding interviews make that especially clear. You can have the best AI tools, but when you're asked to solve a problem and explain your thinking on the spot, your own understanding really counts.
If you don't understand the project not idea on that still you explain the project using LLM then also they explain only thing is that token will increase and significantly you price . still no need to write code in hand
I still write a lot of my code by hand so that I don't lose my coding skills. I lean on AI to clean up my code or help out with something that I'm stuck on. I also find it a timesaver to add some functionality to a code base that I've already created.
If you understand implicitly why a foolish consistency is the hobgoblin of little minds.
Bringing Emerson into a Python developer discussion! There's a line between keeping your code consistent and following a convention so blindly that you forget why it exists in the first place.
The hobgoblin admonishment in PEP 8 is a nice reminder that even the Python style guides themselves offer wisdom about when to use one's own best judgment! 🐍🙂
I am not a professional! 😅
It will just take a little time to work through the list, but you've got this! 😅
The part about 'turning a simple script into a tool' hits right at the core of Python's evolutionary trap.
You write a 15-line script to parse a malformed CSV on a Friday afternoon. By Monday, someone needs it to run on a schedule, so you add argparse. By Wednesday, someone feeds it an empty byte stream, so you wrap it in custom exception hierarchies. By Friday, you've added type annotations, pydantic models, logging with structured JSON output, and you find yourself writing a pyproject.toml and debating whether to switch from setuptools to flit or hatch. Python's gentle learning curve is essentially an onboarding funnel designed to turn script kiddies into systems architects without their prior consent.
And let’s not forget the canonical right of passage: mutable default arguments. Every Python developer remembers the exact day they wrote def process_batch(items, cache=[]) and spent three hours discovering that function definitions are executed once at import time, turning their innocent default list into a permanent, module-scoped shared memory leak across every subsequent invocation.
There are only 10 types of people in the world: those who understand binary, and those who spend their morning debugging why is evaluated to False on an integer larger than 256.
Mine is a sequel to the wrong-environment one.
We built a before/after comparison to prove a refactoring didn't change behavior. The top-level package came from the old checkout. But an editable-install finder in sys.meta_path quietly loaded some submodules from the new one. So for those modules we compared new code with new code. Hard to find differences that way.
Now I check where every loaded submodule comes from, not just the root package's file.
That's a sneaky one! 😂 You think you're comparing two different versions, only to discover that Python has quietly mixed them together behind your back.
Checking the root package is one thing, but tracing every loaded submodule takes the investigation to another level. Knowing where your code comes from matters just as much as knowing what it does!
Yeah ... i was surprised as well , love these experiments, always show new insights about what can go wrong :D ... and helps me to enrich / improve my skills and plugin
Haha 😂 The “onboarding funnel designed to turn script kiddies into systems architects without their prior consent” is SO accurate!
You start with a tiny script, and you're making architectural decisions by the end of the week. And mutable default arguments deserve their own horror story. The first time you encounter that bug, you really start questioning everything you thought you knew about Python 😂
The 'except Exception: pass' section needs a sequel where the script prints 'Done!' after quietly skipping every file. That's the moment the absence of a traceback becomes much scarier than the traceback itself. For a batch script, I'd rather see '0 processed, 12 failed' than a cheerful success message with nothing behind it. Your five-minute automation has now acquired an exit code policy, which feels like the next stage of turning it into a tool.
Interesting, because it really looks like Javascript issues 😄
The notebook crime scene deserves its own sequel: “Restart and Run All” as the final boss. A notebook that only works in the order 7, 14, 1, 39 has accidentally invented a puzzle game.
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