For maybe some regex tasks sure, but there are also plenty of Python operations that are significantly faster than Perl, not to even mention all the data science stuff. I might have misunderstood the comment as evaluating the language on one thing doesn't capture a broad/general spectrum of usefulness.
Every language in this category will have bindings to domain specific high performance modules. This is part of why performance doesn't matter all that much - we can always push hot operations into another language.
Perl generally outperforms python in core language features.
The benchmarks shown elsewhere here tend to disagree with that. I think at one point that was more true than it is now. Overall though they seem to be comparable enough to where it probably doesn't matter.
Also, the bindings have to exist which they don't with Perl for a lot of scientific uses (PDL is not a substitute for Numpy/SciPy/Pandas).
Don't get me wrong. I own at least 12 Perl books and have reviewed some of the latest Perl 6 (Raku) books and really really like Raku. There's not much wrong with Perl in my book (certainly not what most people claim). I've reached for it a few times at work and found it to be fairly pleasant to use. My biggest complaints about building complex data structures in Perl (yes it's much easier than C, but still complicated if you're coming from Python) and having to remember when something is "$" that in my mind should be "@" have all been fixed by Raku.
I just wanted to point out that your views about it being much faster across the board don't seem to be correct.
Any data to back up this claim? My experience in dealing with large numbers of files, huge data sets, is that Perl generally roars, while python lags. I converted a python code to Perl associated with some recent work, and got a good ~2.5x overall improvement. It varied a bit as a function of the input, but generally Perl is superior in performance. Some areas Python is better, but not many.
