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0 pointsnmfisher5y ago0 comments

Not a mathematician/physicist/etc, but having literally dived into Julia today, I think you’d be surprised. It definitely seems like “Python 2.0” for numerical computing.

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4 comments · 1 top-level

gypsyharlot5y ago· 3 in thread

Julia is probably excellent. How large are the benefits to using Julia compared to Python? Are the benefits great enough to compensate for the time spent:

- Training your entire team to use Julia instead of learning about other relevant things

- Re-writing your Python-infrastructure (or dealing with Julia to Python-interoperability, which means new employees now have to learn or know both Python and Julia)

- Replacing Jupyter and learning new, similar tools

- All employees making their favorite IDEs function well with Julia

- Figuring out how to make Julia talk to software that already has an existing Python API (Wireshark, AutoCAD, GNU Radio, ... just about everything you can think of)

nmfisherOP5y ago

Those are definitely problems for the corporate world (except for Jupyter, a Julia kernel already exists for that).

Again, I’m not an academic so take what I say with a grain of salt - but I can see Julia paying dividends very very quickly in that sphere (once you’re over the admittedly steep learning curve).

kirill5pol5y ago

A few of these are non-problems IMO.

- Julia is relatively easy to learn for Python people (especially the numerical people who have experience with stuff like Cython)

- The interop (both ways) is pretty great with Python

N1H1L5y ago

The Ju of Jupyter is for Julia.

j / k navigate · click thread line to collapse