Especially in Pycharm for me, it is incredibly easy. Even when running over ssh in remote computers I can use my debugger.
Might be worth it to set up a better environment, then. Somehow I don't feel like print debugging is all that inferior though; in a sense it might actually make your debugging more efficient by forcing you to formulate concrete 'questions' about your code before even diving into the execution.
I only speak for myself, but I find that time spent inside a debugger is "lost", and bound to be re-spent again and again if you ever find new problems with the same code. I pretty much prefer to add assertions, logging and comments to my program, that will stay there and make further re-reads easier and more useful. As a matter of principle, I never use a debugger (except for assembly code, but that's rare nowadays).
You are certainly right, as I barely ever use a debugger and it is always an annoying experience. Can you suggest such good debuggers for C, Julia and Python?
Sounds like these "sessions and configurations" are important, and thus they should be formally part of the program, committed to its public repository for all to see and use. I call these things "tests" and write them using the same language as the rest of the program, and run them frequently to be sure that they don't get out of sync with the program itself.
I would say I get more use out of printing these days.
I don’t write enough Python to justify the time to learn the debugger. I write just enough to help my staff/teammate fix their problem or debug some tool I’m using and move on.
I’ve been doing this long enough to lose interest in digging deeply into each language. I learned gdb for C. After that I learned jdb and Eclipse for Java. There was probably something I used for the few years I wrote PERl later PHP. After a while I stopped getting excited about deeply learning new languages and their tools.
Debuggers and IDEs are yet another dependency. Frequently I use systems I don’t control, like client systems. They have really stringent rules about what can be installed. The lowest common denominator is vim and print.
Certainly there are lots of reasons to learn debuggers. But there are also lots of valid reasons to learn a tool like this which is easy to learn, useful in across many languages, and gets the job done in many situations.
It's easier to go back in time with print debugging: just scroll up.
It also works in situations where debugging is infeasible or would slow down execution too much.
The worst part is, I think a lot of devs resort to print-debugging which in turn leads to writing sloppy code - e.g. avoiding function calls to be able to access state, etc.
I work on an automated voice agent for restaurant drive-throughs, specifically the code that connects the voice agent to the existing point of sale system. When something goes wrong in a store, having a log of the API interactions between the voice agent and the POS is essential for troubleshooting.
Recently I updated the logging with a code generator option. I can place an order by voice on my local test setup, and it writes out a Python script that replays the same API calls, ready to run in a standalone API tester. This is super handy for testing.
But none of this is a substitute for a good debugger. For me it is a powerful thing to be able to stop the code at a breakpoint and see the actual values of all the variables at that point in time.
And it's not just for debugging. I jumped into this project after it had already been developed for a couple of years, and needless to say there is a lot that I did not understand about the code.
Of course I can read the code and use Ctrl+Click in PyCharm to see the definition of a function. But to really understand it, there is nothing like setting a breakpoint and looking at live data.
In general, debuggers give you much more contextual information, but using a debugger is extremely slow. To see what's going on, you have to step through your program, one line at a time, until the interesting thing happens. That can take ages.
If you want to see how a specific function is behaving and it's called 100 times, it's a lot easier to look at a printed log of the 100 calls and scan or search it for interesting behaviour than to pause the program in a debugger and step through it over and over, hoping to catch the interesting moment.
You can set more than one breakpoint at a time. Hitting 'c' will get you to the next breakpoint, no matter where it is.
> and step through it over and over
No, you don't (shouldn't) do that. You write a conditional breakpoint which activates when something interesting happens.
In pdb not only can you set breakpoints with conditions[1], you can also assign commands to be executed when the breakpoint is reached[2]. You can also use `display` command to - effectively - insert temporary `print`s in any stack frame[3]. Coupled with `up`, `down`, and `jump` commands, and the ability to evaluate any code in the scope of a break, it really gives you a lot of options on how to find the problem.
Though, logging is still a good thing. When I see a commented out `print` in code review, I usually suggest to replace it with a DEBUG level logger call. Extensive logging does help to trace the execution, it can be disabled when not needed, and can improve the readability of the code. Although raw print is an antipattern (can't easily enable some and disable other, need to clean up after debugging, doesn't display the stack trace, etc.), logging is a valid technique which complements the usage of a debugger nicely.
[1] https://docs.python.org/3/library/pdb.html#pdbcommand-break
[2] https://docs.python.org/3/library/pdb.html#pdbcommand-comman...
[3] https://docs.python.org/3/library/pdb.html#pdbcommand-displa...
Debuggers give you a lot of information at a particular point (stack frame) in execution time, whereby print-ing can give you a filtered view of what happen(ed) during a full run.
When I can mark breakpoints and store the stack at that time (for each pass through that bp) in a inspectable gui tree (a list for linear execution path, a tree for threads etc) then I won't need print statements any more.
It automatically syncs your local project with the remote machine and runs seamlessly. They have a similar offering for docker, but I have yet to try it when running over ssh.
print("here") till the day i die!!!