Ahh, you've been running some grad students first python project as if it was a serious project like curl with 20 years of history, and expecting it to have the same quality. But you've somehow avoided the tons of grad-student CPP programs with similar quality issues, or the broken code pushed by companies like crowdstrike or IBM.
Fair enough, your experience may vary. I'd suggest not judging the language by the standards of some hobbyist code that just so happened to end up on github. I've had tons of bugs in c/cpp programs over the years, some more critical than others.
I've seen a lot of shitty and unreliable python code, and a lot of good and mature C/CPP projects. I've also seen really bad security issues and crashes with bad C code, heartbleed, crowdstrike, etc.
For what it's worth I've never had youtube-dl hard crash on me, and I could argue that it's a more complicated problem to solve than what curl is solving. In an apples-to-apples comparison I think it does pretty well.
No matter what language you use for this you're going to be relying on an AI vision model with no hard guarantees.
Actually Python was insufficient for the sort of grad student bugs I wanted to write, I was able to just wrap everything up in giant try blocks and then,
except:
print(“Something happened”, i)
(Where I might be an index. Or an element).
Fortran is able to generate better bugs, because it has allocate/free.
You have much more control over a pure C/C++ application because it does not involve the Python runtime. Crowdstrike etc. are exploits that don't really matter here: If you are on the CAN bus it's game over already.
That said, I'm pretty sure CPython has exploits, too. They'll be harder to find and trigger though.
Sure, runtimes exist and have engineering trade-offs. You avoid a whole class of memory related bugs but you lose a lot of control over memory allocation. You can do soft real-time as long as you manually manage the garbage collection and accept that there will be some (bounded) jitter on memory allocations.
The first rule of the tautology club is the first rule of the tautology club. Things have trade-offs. Python removes (or at least significantly reduces) a whole class of bugs that appear when using lower-level languages, that's part of why it's a good glue language.
Fair enough, your experience may vary. I'd suggest not judging the language by the standards of some hobbyist code that just so happened to end up on github. I've had tons of bugs in c/cpp programs over the years, some more critical than others.
I've seen a lot of shitty and unreliable python code, and a lot of good and mature C/CPP projects. I've also seen really bad security issues and crashes with bad C code, heartbleed, crowdstrike, etc.
For what it's worth I've never had youtube-dl hard crash on me, and I could argue that it's a more complicated problem to solve than what curl is solving. In an apples-to-apples comparison I think it does pretty well.
No matter what language you use for this you're going to be relying on an AI vision model with no hard guarantees.