So, instead of printing a pretty plot in 2 lines of code, you will be... making these 20k syscalls yourself?
You have such unusual hobby, my friend!
You have such unusual hobby, my friend!
To engage with your point: loading a dynamic library in a regular language takes significantly less than 20k syscalls. Probably 20-40 for C on Linux. Python is uniquely inefficient. On most plots comparing resource use by different languages, in order to even show python together with regular languages like Java and C, either you use the log scale, or everything but Python is shown as a single point.
Of course, most people use Python to glue together stuff written in C, so it’s not that big of a deal, but it becomes a problem when people forget pure Python code is literally hundreds or thousands times slower than a “regular” program doing the same thing.
It just worries me when I sometimes see those same Jupyter notebooks running in production, crunching 100s of terabytes of data. Maybe I’m wrong, but I didn’t get the impression everyone realizes exactly how wasteful that is. I guess AWS credits are easy to come by.
One thing Google did well back in the day, was making resource costs report in SWE/hours, the idea being that you see if you should go and rewrite something. If it cost 100 SWE/h to run, and it only took you a day to cut that in half, you should do it.
Can you cite a source/example for that? I cannot imagine an optimized C program that doesn't blow python with numpy out of the water. Even a poorly written C program is likely to be 2x faster simply because it doesn't have to round trip operations from C to python and back.
I found some metrics after 30 seconds of googling.
I'm not your monkey.
A team I used to work with was forced to throw away a finished Python data pipeline that took them a year to build, because it cost more to run than the combined salaries of the team. And I really think if they’d had better intuition about Python’s performance under different scenarios, they could have saved a year of effort. This is why I feel it’s worth having frank discussions about trade offs when it comes to this language.
It’s incredibly useful, but people in the community aren’t clearly told about its limitations. (Especially wrt performance, but also maintainability.)
Sure but there's a trade off, no? Go is typically 3x the code than python. And C++ is 10x the complexity easily.
There was one point back when I stopped coding C++ where one coder might not understand what another C++ coder was doing because the standard was so large.
> A team I used to work with was forced to throw away a finished Python data pipeline that took them a year to build, because it cost more to run than the combined salaries of the team.
You know, I have horror stories about C++ and Java as well. Usually that kind of blame goes to management for not understanding the issues up front. Pretty soon, I'll have slew of stories about go misusage as well.
Python is certainly very terse and expressive. I like writing Python, it’s fun. And it hides a lot of problems from the programmer, but that’s not the same as being simple.
Go is simple, that’s why it’s verbose. It has no syntax sugar and it’s not fun to write Go, but you can read it and see what it’s doing really quickly.
Anyway, it’s about picking the right set of trade-offs, as you say. But the trade off in performance is 1:100, and that’s so punishing at scale that all other considerations kind of fall by the wayside.
You haven't lived until you've argued with a C++ language lawyer.
> Go is simple, that’s why it’s verbose. It has no syntax sugar and it’s not fun to write Go, but you can read it and see what it’s doing really quickly.
Python is great. It has a lot of syntax sugar, but it's also easy to read and understand what it's doing. They teach it to elementary school kids. But they use it in F500 companies. And it has made huge strides into the scientific computing, because it's relatively easy to call existing C/Fortran libraries.
Go's experience by comparison is awful. Their community is an anti-social gate-keeping echo chamber. Their FFI is awful. Their language design is awful as well.
Edited to add: I feel like Go got popular because Rob Pike had no problem bad mouthing other languages. "Python/C++ are so terrible...".
Consider Rust on the other hand, where python and Rust seems to be getting along quite well. Rust seems to care about the coding experience. I think that makes a difference.
Yes, because you're importing a library that does a lot more than just print a plot. A purpose-built Python program that just printed the plot, nothing else, would need a lot less than 20k syscalls too.
(Of course an import call in Python does a lot more, but the end result is roughly the same as calling `dlopen` in, e.g., Swift.)
I just don't see how a person could spend 20 years using python and still can't figure out that you shouldn't hammer nails with a microscope.