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Interesting, I think this is the first time I have seen anyone bash Python this hard. Why would a decent C-API fuel its growth? Also can you give me some examp

Interesting, I think this is the first time I have seen anyone bash Python this hard. Why would a decent C-API fuel its growth? Also can you give me some examples of better languages? Am no senior developer but I find python very elegant and easy to get started with.

linguae 2y ago
I’m not the parent poster, but I’ve seen two major spurts of Python’s popularity: (1) the mid-2000s when Python became a popular scripting language, displacing Perl, and (2) beginning in the first half of the 2010s when an entire ecosystem of Python APIs backed by code written in C, C++, and even Fortran made up the infrastructure for machine learning code (e.g., NumPy, SciPy, scikit-learn, Pandas, etc.). If Python didn’t have a good way of interfacing with code written in languages like C, then it might not have been as popular among machine learning researchers and practitioners, who needed the performance of C/C++/Fortran for numerical computing but wanted to work with higher levels of abstraction than what is provided in those languages. What drew me to Python back in 2006 as a CS student who knew C and Java was its feeling like executable pseudocode compared to languages that required more “boilerplate.” Python’s more expressive syntax, combined with its extensive “batteries included” standard library, meant I could get more done in less time. Thus, for a time in my career Python was my go-to language for short- and medium-sized programs. To this day I often write pseudocode in a Python-like syntax. Since then I have discovered functional programming languages. I’m more likely to grab something like Common Lisp or Haskell these days; I find Lisps to be more expressive and more flexible than Python, and I also find static typing to be very helpful in larger programs. But I think Python is still a good choice for small- and medium-sized programs.
- hackboyfly 2y ago
  Ah thanks, that makes sense!
- taeric 2y ago
  I'm convinced python's main asset for its growth was how ubiquitous it was. It was basically pre installed everywhere. With the batteries included idea, you were mostly good with basics, too. This changed with heavy use, of course. Such that now packaging is a main reason to hate python. Comically so.
  - pjmlp 2y ago
    In the 2000's you had to install it in most UNIXes still.
    - taeric 2y ago
      That may be. I recall perl being bigger back then. I mainly consider python to have grown around the 2010s. And it was basically already on most machines. It is only in the later versions where they have pushed compatibility boundaries that this has gotten obnoxious.
- pjmlp 2y ago
  Forgetting about Zope.
fiddlerwoaroof 2y ago
I try to avoid python in production code bases as much as possible: dependency management issues alone are a good reason to do so for anything that will last longer than a year or two.
bitwize 2y ago
It was relatively easy to lash Python as a higher-level orchestration layer to popular number crunching libraries, yielding NumPy and similar, which made Python popular for machine learning applications. If you're used to Scheme, Common Lisp, or Haskell, Python's arbitrary decisions about e.g. lambda or how scopes work may be grating. But Python is the BASIC of the modern day, and people laughed at BASIC in the 80s too... except businesses ran on BASIC code and fortunes had been made from it.

linguae 2y ago

I’m not the parent poster, but I’ve seen two major spurts of Python’s popularity: (1) the mid-2000s when Python became a popular scripting language, displacing Perl, and (2) beginning in the first half of the 2010s when an entire ecosystem of Python APIs backed by code written in C, C++, and even Fortran made up the infrastructure for machine learning code (e.g., NumPy, SciPy, scikit-learn, Pandas, etc.). If Python didn’t have a good way of interfacing with code written in languages like C, then it might not have been as popular among machine learning researchers and practitioners, who needed the performance of C/C++/Fortran for numerical computing but wanted to work with higher levels of abstraction than what is provided in those languages. What drew me to Python back in 2006 as a CS student who knew C and Java was its feeling like executable pseudocode compared to languages that required more “boilerplate.” Python’s more expressive syntax, combined with its extensive “batteries included” standard library, meant I could get more done in less time. Thus, for a time in my career Python was my go-to language for short- and medium-sized programs. To this day I often write pseudocode in a Python-like syntax. Since then I have discovered functional programming languages. I’m more likely to grab something like Common Lisp or Haskell these days; I find Lisps to be more expressive and more flexible than Python, and I also find static typing to be very helpful in larger programs. But I think Python is still a good choice for small- and medium-sized programs.

hackboyfly 2y ago
Ah thanks, that makes sense!
taeric 2y ago
I'm convinced python's main asset for its growth was how ubiquitous it was. It was basically pre installed everywhere. With the batteries included idea, you were mostly good with basics, too. This changed with heavy use, of course. Such that now packaging is a main reason to hate python. Comically so.
- pjmlp 2y ago
  In the 2000's you had to install it in most UNIXes still.
  - taeric 2y ago
    That may be. I recall perl being bigger back then. I mainly consider python to have grown around the 2010s. And it was basically already on most machines. It is only in the later versions where they have pushed compatibility boundaries that this has gotten obnoxious.
pjmlp 2y ago
Forgetting about Zope.

fiddlerwoaroof 2y ago

I try to avoid python in production code bases as much as possible: dependency management issues alone are a good reason to do so for anything that will last longer than a year or two.

bitwize 2y ago

It was relatively easy to lash Python as a higher-level orchestration layer to popular number crunching libraries, yielding NumPy and similar, which made Python popular for machine learning applications. If you're used to Scheme, Common Lisp, or Haskell, Python's arbitrary decisions about e.g. lambda or how scopes work may be grating. But Python is the BASIC of the modern day, and people laughed at BASIC in the 80s too... except businesses ran on BASIC code and fortunes had been made from it.