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The reasons for all this stuff having been developed in Python also make Python interesting right now, all by themselves. It did not happen by accident; this st

by yosefk 2y ago

The reasons for all this stuff having been developed in Python also make Python interesting right now, all by themselves. It did not happen by accident; this stuff was developed fairly recently and there was no shortage of mature languages to choose from.

pjmlp 2y ago
Using Python as C and C++ REPL of sorts has been common in academia since it took the scripting crown away from Perl and Tcl, which were used during the late 90's. Example see the Bioinformatics papers from that period, and the Perl tooling used alongside the research. Already in 2003 CERN was using Python on some of their build infrastructure (see CMT), Grid Computing scripting efforts, and we had Python trainings available to us. Now there is a difference between a REPL of sorts, scripting OS tasks, and going full blown applications with a pure interpreter.
BiteCode_dev 2y ago
The people disliking the language are very vocal about it, but there is a huge amount of silent people that loves it and an even bigger amount that just like it as much as alternatives. It's mainstream now, not trending like 10 years ago, so there is no hype about it anymore. We just use it to do stuff. Add to that the existing excellent ecosystem, the strong culture of scientific stacks and a very good story for providing c-extentions (actually the best one in all scripting languages because of things like cibuildwheel). It's only in small tech bubbles like HN that devs find it surprising.
- lordgroff 2y ago
  I mean, even on HN, I'd say if there's derision, it's mostly one uttered with a yawn rather than genuine hate. And that's almost justified; while I spend a lot of my time with lots of different languages (I can't think of a single one I outright hate btw), Python is the one that pays for my things and... Well, there's not much drama there is there (now that we're lost 2->3 anyway)? It's a glue language that's easy to learn, but offers tons of depth should you want it. My primary annoyance at Python used to be the typing, but type annotations have made this less of an issue. It's a nice language and you can do almost everything with it. It's a bit boring, but I guess that's a good thing.
- devjab 2y ago
  I’ve always found Python to be sort of loved on HN. Not by everyone or course but I guess it depends on each of our experiences on here. I’m usually rather surprised when I meet people who genuinely dislike Python, because that seems like such an odd occurrence. Even if people don’t “love” the language most people seem to have had rather fond experiences or memories of it. Usually criticism comes down to its inefficiencies, but those aren’t exactly unreasonable critiques. As I said it’s anecdotal, but in my experience Python gets a lot of love compared to something like Java or C#. Both of which are often met with real harshness. Hell I’ve ranted unseemly about C# myself.
- pm90 2y ago
  Python has many issues that are quite clear when you operate at some kind of scale and need proper multiprocessing/multithreading support. And its not just the GIL, you get very unexpected behaviors when dealing with exit handlers and signal handlers in edge cases. Having seen what other languages look like it just doesn’t feel like a language that was designed well for running at scale. The tooling has markedly improved though. Things like typing and compile time checks, great. But its also funny to me that some of the fastest tools for python are being built in rust (eg uv).
- pjmlp 2y ago
  My only big critism is the CPython folks resistance to any kind of performance improvements, and the way PyPy efforts have been largely ignored, making Python the last major dynamic language to finally start caring about performance and having a JIT in the box. Finally thanks to data science, and people getting fed up with always writing bindings, this is changing, and Python can join Common Lisp, Scheme, Smalltalk, SELF, JavaScript, Ruby, Lua, Dylan, Julia, BASIC club.
  - gpderetta 2y ago
    and elisp. Let's not forget that elisp got a JIT (well, actually a static compiler) before CPython did!
    - pjmlp 2y ago
      Indeed, I only listed the languages I know more about, it has been a long time since XEmacs was my poor man's IDE on UNIX systems.
  - neonsunset 2y ago
    To be fair, Ruby YJIT can still somehow be slower than Python 3.11+ at times. Lua JIT is a bit of a separate effort and the ones that truly try the hardest here are Julia (which is not necessarily interpreted, it's really difficult to call it a pure scripting language at this point) and JavaScript engine implementations. I can see pretty good numbers for SBCL on BenchmarksGame too.
    - pjmlp 2y ago
      Yes, but it isn't the only one, the oldest Ruby JIT goes back to Ruby Motion, still being sold. I would not put Julia and Common Lisp on the scripting basket yep.
- gpderetta 2y ago
  The people disliking the language might also be the people that love it. I know I am in that camp. It is a great language in many ways, that's why its shortcomings are so painful.
Eridrus 2y ago
It didn't happen by total accident, but it didn't happen by design for where we are today either. The original choice to start building data science tooling in Python happened intentionally, but since then path dependence has been a huge thing.
wenc 2y ago
As a former Perl hacker who started using Python in 2005, I saw Python ride several waves. (Numerical computation, data science, deep learning) Perl was the leading tool for scripting and text parsing. Python didn’t really supplant it for a long time — until people started writing more complicated scripts that had to be maintained. Perl reads like line noise after 6 months whereas I can look at Python code from 20 years ago, prettify it with black, and understand it. Python got picked up by the scientific computing community, which gave it some its earliest libraries like numpy, f2py, scipy. Some of us who were on MATLAB moved over. Then data science happened. Pandas built off the scientific computation foundations and eventually libraries like scikit and matplotlib (mimicking matlab’s plotting) came along. Then tensorflow came along and built on the foundation of numerical libraries. PyTorch followed. Other systems like Django came and made python popular for building database backed websites. Suddenly there was momentum and today almost all numerical software have a python API — this includes proprietary stuff like CPLEX and what have you. Python was the glue language that had the lowest barrier of entry. For instance, Spark was written in Scala and has a performant Scala API but everyone uses PySpark because it’s much more accessible, despite the interop cost. The counterfactual to all this was Ruby. It had much nicer syntax than Python but when I tried to use it in grad school I was quickly stymied by the lack of numerical libraries. Ruby never found a niche outside of Rails and config management. Essentially Python — like Nvidia today — bet on linear algebra (and more broadly on data processing) and won. I get why there’s hate for Python — it’s not a perfect language. Yet those of us pragmatists who use it understand the trade offs. You trade off on the metal performance for programmer performance. You trade off packaging difficulties for something that works. You trade off an imperfect syntax for getting things done. I could have used Ruby — a much more beautiful lanaguage — in grad school and worked around its lacks, but I would have not graduated on time. Python was pragmatic choice for me and continues to be one for me today (outside of situations requiring raw performance)
- o11c 2y ago
  There was also the major anti-wave of Python 3. But it has managed to pull through despite ending up with broken strings (RIP all old code that needs to deal with legacy-encoded data), probably because there was no viable replacement.

by yosefk 2y ago

pjmlp 2y ago

Using Python as C and C++ REPL of sorts has been common in academia since it took the scripting crown away from Perl and Tcl, which were used during the late 90's. Example see the Bioinformatics papers from that period, and the Perl tooling used alongside the research. Already in 2003 CERN was using Python on some of their build infrastructure (see CMT), Grid Computing scripting efforts, and we had Python trainings available to us. Now there is a difference between a REPL of sorts, scripting OS tasks, and going full blown applications with a pure interpreter.

BiteCode_dev 2y ago

The people disliking the language are very vocal about it, but there is a huge amount of silent people that loves it and an even bigger amount that just like it as much as alternatives. It's mainstream now, not trending like 10 years ago, so there is no hype about it anymore. We just use it to do stuff. Add to that the existing excellent ecosystem, the strong culture of scientific stacks and a very good story for providing c-extentions (actually the best one in all scripting languages because of things like cibuildwheel). It's only in small tech bubbles like HN that devs find it surprising.

lordgroff 2y ago
I mean, even on HN, I'd say if there's derision, it's mostly one uttered with a yawn rather than genuine hate. And that's almost justified; while I spend a lot of my time with lots of different languages (I can't think of a single one I outright hate btw), Python is the one that pays for my things and... Well, there's not much drama there is there (now that we're lost 2->3 anyway)? It's a glue language that's easy to learn, but offers tons of depth should you want it. My primary annoyance at Python used to be the typing, but type annotations have made this less of an issue. It's a nice language and you can do almost everything with it. It's a bit boring, but I guess that's a good thing.
devjab 2y ago
I’ve always found Python to be sort of loved on HN. Not by everyone or course but I guess it depends on each of our experiences on here. I’m usually rather surprised when I meet people who genuinely dislike Python, because that seems like such an odd occurrence. Even if people don’t “love” the language most people seem to have had rather fond experiences or memories of it. Usually criticism comes down to its inefficiencies, but those aren’t exactly unreasonable critiques. As I said it’s anecdotal, but in my experience Python gets a lot of love compared to something like Java or C#. Both of which are often met with real harshness. Hell I’ve ranted unseemly about C# myself.
pm90 2y ago
Python has many issues that are quite clear when you operate at some kind of scale and need proper multiprocessing/multithreading support. And its not just the GIL, you get very unexpected behaviors when dealing with exit handlers and signal handlers in edge cases. Having seen what other languages look like it just doesn’t feel like a language that was designed well for running at scale. The tooling has markedly improved though. Things like typing and compile time checks, great. But its also funny to me that some of the fastest tools for python are being built in rust (eg uv).
pjmlp 2y ago
My only big critism is the CPython folks resistance to any kind of performance improvements, and the way PyPy efforts have been largely ignored, making Python the last major dynamic language to finally start caring about performance and having a JIT in the box. Finally thanks to data science, and people getting fed up with always writing bindings, this is changing, and Python can join Common Lisp, Scheme, Smalltalk, SELF, JavaScript, Ruby, Lua, Dylan, Julia, BASIC club.
- gpderetta 2y ago
  and elisp. Let's not forget that elisp got a JIT (well, actually a static compiler) before CPython did!
  - pjmlp 2y ago
    Indeed, I only listed the languages I know more about, it has been a long time since XEmacs was my poor man's IDE on UNIX systems.
- neonsunset 2y ago
  To be fair, Ruby YJIT can still somehow be slower than Python 3.11+ at times. Lua JIT is a bit of a separate effort and the ones that truly try the hardest here are Julia (which is not necessarily interpreted, it's really difficult to call it a pure scripting language at this point) and JavaScript engine implementations. I can see pretty good numbers for SBCL on BenchmarksGame too.
  - pjmlp 2y ago
    Yes, but it isn't the only one, the oldest Ruby JIT goes back to Ruby Motion, still being sold. I would not put Julia and Common Lisp on the scripting basket yep.
gpderetta 2y ago
The people disliking the language might also be the people that love it. I know I am in that camp. It is a great language in many ways, that's why its shortcomings are so painful.

Eridrus 2y ago

It didn't happen by total accident, but it didn't happen by design for where we are today either. The original choice to start building data science tooling in Python happened intentionally, but since then path dependence has been a huge thing.

wenc 2y ago

As a former Perl hacker who started using Python in 2005, I saw Python ride several waves. (Numerical computation, data science, deep learning) Perl was the leading tool for scripting and text parsing. Python didn’t really supplant it for a long time — until people started writing more complicated scripts that had to be maintained. Perl reads like line noise after 6 months whereas I can look at Python code from 20 years ago, prettify it with black, and understand it. Python got picked up by the scientific computing community, which gave it some its earliest libraries like numpy, f2py, scipy. Some of us who were on MATLAB moved over. Then data science happened. Pandas built off the scientific computation foundations and eventually libraries like scikit and matplotlib (mimicking matlab’s plotting) came along. Then tensorflow came along and built on the foundation of numerical libraries. PyTorch followed. Other systems like Django came and made python popular for building database backed websites. Suddenly there was momentum and today almost all numerical software have a python API — this includes proprietary stuff like CPLEX and what have you. Python was the glue language that had the lowest barrier of entry. For instance, Spark was written in Scala and has a performant Scala API but everyone uses PySpark because it’s much more accessible, despite the interop cost. The counterfactual to all this was Ruby. It had much nicer syntax than Python but when I tried to use it in grad school I was quickly stymied by the lack of numerical libraries. Ruby never found a niche outside of Rails and config management. Essentially Python — like Nvidia today — bet on linear algebra (and more broadly on data processing) and won. I get why there’s hate for Python — it’s not a perfect language. Yet those of us pragmatists who use it understand the trade offs. You trade off on the metal performance for programmer performance. You trade off packaging difficulties for something that works. You trade off an imperfect syntax for getting things done. I could have used Ruby — a much more beautiful lanaguage — in grad school and worked around its lacks, but I would have not graduated on time. Python was pragmatic choice for me and continues to be one for me today (outside of situations requiring raw performance)

o11c 2y ago
There was also the major anti-wave of Python 3. But it has managed to pull through despite ending up with broken strings (RIP all old code that needs to deal with legacy-encoded data), probably because there was no viable replacement.