Honestly, I would have expected C++ to end with the SIGSEGV and nothing else, then for python to reply.

I think you're using this meme template backwards - the car should say most people and the text for the directions should be flipped. The car is supposed to be going somewhere it shouldn't, not somewhere it should.

Eh, Python has a very small slice where I'd consider it the right tool for the job for me. It's for when I want a less awful bash script, but going much bigger than that makes me miss type systems.

If you had let me write the C++ code, I could have literally destroyed your dataset in a couple of seconds.

Exactly what this comic is saying. C++ can handle in 20 minutes what takes python 12 hours, but something gets destroyed.

But make sure to bill for the full 12 hours.

I had a similar experience processing PDFs of building plans. 4-8k PDFs, took 5-10minutes in Python.

I ended up switching to node.js and it processed the same PDFs in 120 seconds.

Over the years I only really find Python useful for interviewing and occasionally in ci pipelines.

I ran into a similar situation many years ago, when I was trying to write a software synthesizer using Visual Basic (version 4 at the time). The big problem is that if you're doing sample-by-sample processing of audio data in a loop (like doing pixel-by-pixel processing of images) and your chosen language's compiler can't compile to a native EXE or inline calls, then you end up suffering the performance hit of function calls that have to be made for each sample (or pixel). In many applications you're not making a lot of function calls and the overall performance hit is negligible, but when you're doing something where you're making hundreds of thousands or even millions of calls per second, you're screwed by the overhead of the function calls themselves - without there being any other sort of inefficiency going on.

In my case, I eventually offloaded the heavy sample processing to a compiled DLL I wrote in C, and I was able to keep using Visual Basic for what it did really well, which was quickly building a reliable Windows GUI.

Might be latency? Python is probably slower to respond to things like when one job is done and the next job can start, since it needs time to interpret the code and call the relevant C libraries.

please explain I want to laugh

It's now cannon in my head that Python talks like Parappa the rapper

Not having true vectorization and having to regularly code that into Python helps even the odds.

__main__

You could say this about a lot of things...

I code in JS, so I'm something of a C dev myself!

Python is actually pretty baller with string operations too since so much of the C has been heavily optimized.

so?

Pypy is often considered the "best" alternative Python implementation. In some cases it can be much faster. But it's often one or two versions behind, and not 100% compatible, and of course it doesn't work with native Cpython extensions.

I thought that too! :D

Javqwcript's still arriving to the meeting

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