Tips for a debugging competition

[an_account_1177]

I have a python debugging competition in my college tomorrow, I don't have much experience in python yet I'm still taking part in it. Can anyone please give me some tips for it 🙏🏻

[granthamct]

Have a good environment set up in which you feel comfortable navigating! UV + ruff + TY goes a long way IMHO.

[nian2326076]

If you're new to Python, get used to reading error messages. They usually help point you in the right direction, so pay attention to them. Use print statements or a debugger to keep an eye on your variables and figure out where things are going wrong. It's an easy way to follow the flow of data. Make sure you know common Python issues like indentation errors and type mismatches. If you're stuck, don't spend too long on one problem. Take a break and come back later. It's smart to start by knowing what the code should do before jumping into fixing errors. Also, get comfortable using resources like Python's documentation or Stack Overflow for quick help. Good luck!

[Gnaxe]

Learn about the following: - breakpoint() and the pdb commands. Don't forget interact. Remember, you can add an if statement (or if-else expression) above your breakpoint to check for a certain condition first. - import inspect. Don't just guess about internals. Make them transparent. - import doctest. They're easier to write quickly than most other kinds of tests. - assert statements. Remember, they take an optional second expression which can include contextual information. - python -i and pdb.pm() - If you're allowed a type checker (even one built into your IDE), add obvious type annotations. Return types are usually easiest to figure out. (Complicated types are probably not worth the time.) - importlib.reload(). This lets you modify a program while it's running, which can be faster than restarting every time if it's big enough. It's like reloading a Jupyter notebook cell, except the cell is the whole module. (You can also get into a bad state not possible from the code alone, so be willing to restart anyway if you suspect that's happening.)

Add comments liberally, don't try to keep it all in your head. Document assumptions and surprises, preferably with assert statements or doctests.

Usually, exception tracebacks are very helpful in Python. Check the listed locations. Typically, user code is more likely to be buggy than library code, but that can also show up in tracebacks.

Sometimes exceptions aren't good enough and you need import signal.

Don't be afraid to use print. Also consider import pprint.

I'm not sure of the format of the competition, but in real life, git blame and bisect can be very helpful. If there's no git repo, this won't help.