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As a fairly extensive user of both Python and R, I net out similarly. If I want to wrangle, explore, or visualise data I’ll always reach for R. If I want to b

by keeeba 10mo ago

As a fairly extensive user of both Python and R, I net out similarly. If I want to wrangle, explore, or visualise data I’ll always reach for R. If I want to build ML/DL models or work with LLM’s I will usually reach for Python. Often in the same document - nowadays this is very easy with Quarto.

Joel_Mckay 10mo ago
Python has a list of issues fundamentally broken in the language, and relies heavily on integrated library bindings to operate at reasonable speeds/accuracy. Julia allows embedding both R and Python code, and has some very nice tools for drilling down into datasets: https://www.queryverse.org/ https://www.queryverse.org/ It is the first language I've seen in decades that reduces entire paradigms into single character syntax, often outperforming both C and Numpy in many cases. =3
- pphysch 10mo ago
  Deeply ironic for a Julia proponent to smear a popular language as "fundamentally broken" without evidence. https://yuri.is/not-julia/ https://yuri.is/not-julia/
  - Joel_Mckay 10mo ago
    Python threading and computational errata issues go back a long time. It is a popular integration "glue" language, but is built on SWiG wrappers to work around its many unresolved/unsolvable problems. Not a "smear", but rather a well known limitation of the language. Perhaps your environment context works differently than mine. It is bizarre people get emotionally invested in something so trivial and mundane. Julia is at v1.12.2 so YMMV, but Queryverse is a lot of fun =3
  - kelipso 10mo ago
    This is like one of those people posting Dijkstra’s letter advocating for 0-based indexing without ever having read or understood what they posted.
    - pphysch 10mo ago
      What does indexing syntax have to do with Julia having a rough history of correctness bugs and footguns?
      - Joel_Mckay 10mo ago
        Sure, all software is terrible if looking at bug frequency history... https://github.com/python/cpython/issues https://github.com/python/cpython/issues Griefers ranting about years old _closed_ tickets on v1.0.5 versions on a blog as some sort of proof of lameness... is a poorly structured argument. Julia includes regression testing features built into even its plotting library output, and thus issues usually stay resolved due to pedantic reproducibility. Also, running sanity-checks in any llvm language code is usually wise. Best of luck =3
        pphysch 10mo ago
        Just saying, "other languages have bug reports" is a exceptionally poor way to promote Julia =3
        Joel_Mckay 10mo ago
        To be blunt: Moores law is now effectively dead, and chasing the monolithic philosophy with lazy monads will eventually limit your options. Languages like Julia trivially handle conditional parallelism much more cleanly with the broadcast operator, and transparent remote host process instancing over ssh (still needs a lot of work to reach OTP like cluster functionality.) Much like Go, library resources ported into the native language quietly moves devs away from the same polyglot issues that hit Python. Best of luck. =3

by keeeba 10mo ago

Joel_Mckay 10mo ago

Python has a list of issues fundamentally broken in the language, and relies heavily on integrated library bindings to operate at reasonable speeds/accuracy. Julia allows embedding both R and Python code, and has some very nice tools for drilling down into datasets: https://www.queryverse.org/ https://www.queryverse.org/ It is the first language I've seen in decades that reduces entire paradigms into single character syntax, often outperforming both C and Numpy in many cases. =3

pphysch 10mo ago
Deeply ironic for a Julia proponent to smear a popular language as "fundamentally broken" without evidence. https://yuri.is/not-julia/ https://yuri.is/not-julia/
- Joel_Mckay 10mo ago
  Python threading and computational errata issues go back a long time. It is a popular integration "glue" language, but is built on SWiG wrappers to work around its many unresolved/unsolvable problems. Not a "smear", but rather a well known limitation of the language. Perhaps your environment context works differently than mine. It is bizarre people get emotionally invested in something so trivial and mundane. Julia is at v1.12.2 so YMMV, but Queryverse is a lot of fun =3
- kelipso 10mo ago
  This is like one of those people posting Dijkstra’s letter advocating for 0-based indexing without ever having read or understood what they posted.
  - pphysch 10mo ago
    What does indexing syntax have to do with Julia having a rough history of correctness bugs and footguns?
    - Joel_Mckay 10mo ago
      Sure, all software is terrible if looking at bug frequency history... https://github.com/python/cpython/issues https://github.com/python/cpython/issues Griefers ranting about years old _closed_ tickets on v1.0.5 versions on a blog as some sort of proof of lameness... is a poorly structured argument. Julia includes regression testing features built into even its plotting library output, and thus issues usually stay resolved due to pedantic reproducibility. Also, running sanity-checks in any llvm language code is usually wise. Best of luck =3
      - pphysch 10mo ago
        Just saying, "other languages have bug reports" is a exceptionally poor way to promote Julia =3
        Joel_Mckay 10mo ago
        To be blunt: Moores law is now effectively dead, and chasing the monolithic philosophy with lazy monads will eventually limit your options. Languages like Julia trivially handle conditional parallelism much more cleanly with the broadcast operator, and transparent remote host process instancing over ssh (still needs a lot of work to reach OTP like cluster functionality.) Much like Go, library resources ported into the native language quietly moves devs away from the same polyglot issues that hit Python. Best of luck. =3