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.

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/

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

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pphysch 9 hours ago | parent [-]

Deeply ironic for a Julia proponent to smear a popular language as "fundamentally broken" without evidence.

https://yuri.is/not-julia/

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kelipso 6 hours ago | parent | next [-]

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 5 hours ago \| parent [-]
		What does indexing syntax have to do with Julia having a rough history of correctness bugs and footguns?

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Joel_Mckay 8 hours ago | parent | prev [-]

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