Perl is the ultimate mockup language in that you can crank out code very fast and get good bug free results. It lets you write in the way you think where other programming languages force you to write a specific way. Ofc you can get good at Python, so good at it you might get as fast as Perl. And Python is easier to read. The advantage of Perl, writing like you think, makes it difficult for anyone but you (or someone else who thinks like you) to read and maintain your code. The ugly code stereotype comes into play from this.
Perl isn't like Python. It's great if you want to write a one off script for doing quick analytics or a one off script that checks something on a server. It's fantastic for that. Python, you'd need to google around for a library, hope you find one, grab it, write a 100 lined file, and then finally be done, where Perl was a quick one-liner to do the same thing. Ofc the Perl is going to look like garbage and not be maintainable and the Python is going to look golden and be maintainable. They both fit a different need and different use case.
Unless you're doing something really simple with Perl command line switches that operate over an entire file, I'd bet Perl and Python solutions will be in the neighborhood of the same number of loc even with all the magic in Perl as Python has a lot of modern conveniences. It's easy to build a complex datastructure in Python with nested dictionaries with sets/lists/other dictionaries... whatever. In Perl it's more complex.
Perl is significantly faster than Python for many types of common string manipulation tasks. They're both fast, sure, but Perl has some key optimizations.
As for the nested complex data structures, Perl's been doing that forever (e.g. since 5.x started). And its trivial to use.
That's one of the nicer aspects of Perl. Things you think should work, often, just do. And work the way you want them to. It's not perfect. It is very, very good though.
[1] https://scalability.org/2020/05/on-optimizing-scripting-lang...
Food for thought.
https://benchmarksgame-team.pages.debian.net/benchmarksgame/...
Please stop perpetuating this myth. It really depends how you write it. Perl isn't going to do the tidying up for you, you'll have to properly structure the code yourself. If you still write Perl code like it’s 1991 then maybe itcs not maintainable. I work on a largeish Perl code base and I can assure you it's quite maintainable, moreso than most Js that people install via npm as we speak.
This is probably one of the issues with Perl. You can still write Python code like it's 1991 and it will still be readable and maintainable.
I tried googling around and couldn't find any speed comparisons between the languages, just talk between the two like eg https://news.ycombinator.com/item?id=8626131
So, I guess I'll address this directly:
The tasks Perl is designed to do are different than the kinds of tasks PyPy is designed to do, so it is a bit of apples an oranges comparison.
PyPy starts to get its speed benefit when a task takes 1) longer than 3 seconds to run and 2) Is directly written in Python, not using libraries written in C.
Perl is designed to parse large files, do string parsing, and one off scripts. It being fast is nice, but it's not designed to be running large math heavy processing scripts to begin with. If a Perl script takes longer than a second to run, not including IO limitations and network limitations, it may not be the ideal tool for the job.
So while PyPy gets comparable to Perl speeds, Perl being fast is almost moot, because it's not designed to be used that way to begin with.
Perl in serial is already faster to run than Python, and as soon as you start using threads Perl blows Python straight out of the water. The only reason that stuff like tensorflow or numpy is not as dog slow as the rest of python is that they are bindings to c(++) or fortran libs.
Writing faster is debateable, but Perl has tons of niceties like embedded regex syntax, string interpolation, one-line if/unless that make Perl both more concise and less boilerplatey, which arguably also makes it faster to write.
There is also "faster to maintain". Perls compatibility means that there is almost none of the churn e.g. Python has with regard to syntax and semantics changes. Perl code from almost 3 decades ago usually works quite fine, whereas Python code breaks in every minor version upgrade and needs a complete rewrite for major versions
As for major versions...well...there's only been one significant change in this area (2 to 3) so I feel like maybe you're hyperbolizing a little :-)
So it happened once but it took up about 25% of the last 20 years.
Not it isn't.
>The only reason that stuff like tensorflow or numpy is not as dog slow as the rest of python is that they are bindings to c(++) or fortran libs.
So if I make a foo.py file and run the code, it runs faster. "but it's really c(++) or fortran!" doesn't matter in the slightest.
