[jhbadger]

It's a matter of ecosystem of packages. R has a huge number of packages for many fields. Python has fewer, but might work for particular use cases. I was excited for Julia, and played around with it since 0.2, but it really hasn't generated very many packages of note in my particular field (bioinformatics).

[Der_Einzige]

Pretty sure that Python has a larger total ecosystem of packages than R.

[jhbadger]

I mean fewer (and less developed) in the context of data analysis and statistics where it is a competitor to R. Every time I consider using Python after getting frustrated with the more ugly features of R as a language, I take a look at what's available in Python, as from a language point of view it is a bit nicer (as is Julia). But then I see what I would have to reimplement myself if I switched, so I don't.

[adamnemecek]

julia has really good interop with both of python and R as well as cpp, matlab, mathematica and others.

Also it's not just about the numbers.

[randomvectors]

So you're telling us not to waste our time with R or Python... but to constantly interop with R and Python?

[adamnemecek]

I mean if there are packages that you need then be my guest. But like if you are starting a new project, julia is a more productive language.

[s_Hogg]

> julia is a more productive language

Source for this, please?

[ddragon]

It would really still depend on the support libraries around the task you want to write, if you really need more performance for the parts that those support libraries don't cover (and beyond what you get with PyPy or Numba) and which language you have more experience with.

If you're really going down to the FFI, it's hard to think it wouldn't be more productive, but that's not what a true beginner like the target of this book would do. Though it's quite nice to quickly extend some tool for your purpose without compromising anything or to understand how something works thanks to being written in high level code.

Syntax-wise, Julia's Common Lisp-like feature set gives the language a lot of power, but normal use will probably be just on par with Python in terms of productivity.

[adamnemecek]

https://news.ycombinator.com/item?id=20240155

[ivirshup]

I love Julia, but feel the interop story could use some work. If I want to have my python package depend on some Julia code, how easy is that? Last time I checked (a few months ago), it was pretty difficult.

[ChrisRackauckas]

You can get it done with a little bit of user interaction: https://github.com/JuliaDiffEq/diffeqpy