8 ms·

Do you mean faster to write, or faster to run, or the combination of both?

corty 6y ago
Both I would guess. 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
- OOPMan 6y ago
  I've been writing Python for a good while now and I haven't seen too many issues between minor 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 :-)
  - jrumbut 6y ago
    Python 3 was released in 2008, Python 2.7 had some kind of release last year but my memory is that up to about 2013 there was still a serious question of 2.7 vs 3 when you started a new project ("I know we should use 3, but then we can't have x-lib!"). So it happened once but it took up about 25% of the last 20 years.
  - corty 6y ago
    A little. But there were changes from e.g. 2.5 to 2.7 and in the earlier 3.x versions that broke stuff. That never happened with Perl code here.
- fnord123 6y ago
  >Perl in serial is already faster to run than Python 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.
proverbialbunny 6y ago
Both. Perl is around 20x slower than C for common tasks, while Python is around 133x slower than C for common tasks like looping, depending on what you're doing of course. 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.
- petre 6y ago
  > Ofc the Perl is going to look like garbage and not be maintainable 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.
  - abiogenesis 6y ago
    > If you still write Perl code like it’s 1991 then maybe itcs not maintainable. 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.
    - virtue3 6y ago
      no you cant, cuz 2.x python wont work in 3.x ;)

Both I would guess. 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

OOPMan 6y ago
I've been writing Python for a good while now and I haven't seen too many issues between minor 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 :-)
- jrumbut 6y ago
  Python 3 was released in 2008, Python 2.7 had some kind of release last year but my memory is that up to about 2013 there was still a serious question of 2.7 vs 3 when you started a new project ("I know we should use 3, but then we can't have x-lib!"). So it happened once but it took up about 25% of the last 20 years.
- corty 6y ago
  A little. But there were changes from e.g. 2.5 to 2.7 and in the earlier 3.x versions that broke stuff. That never happened with Perl code here.
fnord123 6y ago
>Perl in serial is already faster to run than Python 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.

proverbialbunny 6y ago

Both. Perl is around 20x slower than C for common tasks, while Python is around 133x slower than C for common tasks like looping, depending on what you're doing of course. 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.

petre 6y ago
> Ofc the Perl is going to look like garbage and not be maintainable 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.
- abiogenesis 6y ago
  > If you still write Perl code like it’s 1991 then maybe itcs not maintainable. 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.
  - virtue3 6y ago
    no you cant, cuz 2.x python wont work in 3.x ;)