Stop Breaking Your Own Code: 15 Common Python Mistakes Beginners Must Avoid in 2026

Namaste, DEV Community! 👋

If you're staring at a screen full of red error messages and wondering if you're cut out for this, take a breath. Every senior engineer you admire has spent hours debugging a missing colon or a weird indentation error. It's not a lack of talent—it's a rite of passage.

As a mentor who has watched hundreds of students navigate the path from "Hello World" to getting hired, I’ve noticed that most beginners trip over the same 15 stones. In 2026, Python is more powerful than ever, but the Common Python Mistakes remain surprisingly consistent.

Let’s clean up your habits and move you toward writing professional, "Pythonic" code.

1. The Whitespace Trap: Python IndentationError Fix

Python doesn't use curly braces {} to define blocks; it uses spaces. The most frequent Python Beginner Error is mixing tabs and spaces. To your eyes, they look the same. To Python, they are an illegal mess.

The Fix: Configure your editor (VS Code or PyCharm) to "Insert Spaces" instead of Tabs. If you get an IndentationError, clear the line and re-indent properly.

2. The Identity Crisis: is vs ==

I see this daily: a beginner uses is when they should use ==.

• == checks if the values are equal.
• is checks if they are the exact same object in memory.

Unless you are checking if something is None, stick to ==. This is a vital Learning Python for Beginners Tip.

3. The "Silent" Bug: Mutable Default Arguments

Never use a list or dictionary as a default argument in a function.
Example: def add_user(name, users=[])
Python creates that list once when the function is defined, not every time it's called. Your data will "leak" from one call to the next.

The Fix: Use None and initialize the list inside the function.

4. Shadowing Built-in Functions

Don't name your variables list, str, dict, or int. You "shadow" Python’s built-in functions. Later, when you try to use list(), your code will crash because it thinks you are calling your variable. Always follow Python PEP 8 naming conventions.

5. Modifying a List While Iterating

If you loop through a list and remove items at the same time, Python’s internal counter gets confused. You’ll skip items or crash.
The Fix: Use a list comprehension to create a new, filtered version of the list instead of deleting from the original.

6. Confusion Between NameError and TypeError

Learn to read your traceback:

• NameError: "I don't know what this variable is." (Usually a typo).
• TypeError: "I know what it is, but I can't do that to it." (Like adding a string to an integer).

7. Swallowing Errors with Bare Excepts

Avoid except: pass. This catches every error, including your own typos, and hides them. Always catch specific exceptions like ValueError or KeyError.

8. Not Writing "Pythonic" Code

Beginners often write Python like it’s C++ or Java.

• Non-Pythonic: for i in range(len(my_list)): print(my_list[i])
• Pythonic: for item in my_list: print(item) The Pythonic way to write code is cleaner, faster, and more readable.

9. Forgetting the with Statement for Files

Opening a file with f = open('file.txt') is risky. If your code crashes before f.close(), the file stays locked.
The Fix: Always use with open(...) as f:. It handles the closing for you automatically.

10. Overcomplicating Simple Logic

Python has "batteries included." Don't write a 20-line function for something that a built-in library like math or itertools already does. This is a key part of Python Best Practices 2026.

11. Avoiding Infinite Loops

A while True loop without a clear break condition is a recipe for a frozen system. Always ensure your loop's condition will eventually become False.

12. Misunderstanding Scope

A variable created inside a function is "local." If you try to print it outside that function, you’ll get a Python NameError. Learn to pass variables as arguments instead of relying on global state.

13. Neglecting PEP 8 Style

Readability counts. If you use camelCase for variables instead of snake_case, your code looks amateur. Following PEP 8 makes your code professional.

14. Hardcoding Sensitive Data

Never put your passwords or API keys directly in your script. Use environment variables or .env files. This is one of the most critical Python Programming Mistakes to Avoid.

15. The "Manual" Search Syndrome

Before you spend hours coding a complex algorithm, check if there is a library for it. From data science to web scraping, Python likely already has a tool for your problem.

Pro-Tip for 2026

With the rise of AI-assisted coding, it’s easy to copy-paste code. However, if you don't know these Python Syntax Errors 2026, you won't be able to debug what the AI gives you.

For a deeper dive into code examples and fixes, check out this depth guide on how to fix common Python beginner mistakes and coding pitfalls.

Which of these mistakes is currently haunted your code? Let’s debug it together in the comments!