As the name suggests, that lets you write functions in a single-dispatch manner. That is different from multiple-dispatch.

Hi Jon, Thanks for the great release! Your post mentions support for JupyterLab, but getting Plotly working in JupyterLab is not working smoothly at the moment (see https://github.com/jupyterlab/jupyter-renderers/issues/132). Is this something you guys are looking into?

I haven't looked into this specifically. Using the FigureWidget approach in 3.0.0 doesn't actually require the current @jupyterlab/plotly-extension. It's all contained in the new plotlywidget extension.

Oh, that's a great improvement in and of itself then. Thanks!

BTW, I got a GitHub notification of a comment that you were having trouble installing it. But I can't find the comment in GitHub itself.

Ah ya, I realized afterwards from more Googling that this is a global problem in the jupyterlab extension ecosystem when using node 10. Since it's already been worked on in other issues, I deleted my comment.

“In IT we have a saying; stay away from the Three Os: Orientals, Old People, and Ovaries,” he allegedly replied.

Do you have an example of Julia not being fast enough?

Last I checked, some things that can be vectorized, but aren't in LAPACK/BLAS weren't particularly fast. There's even one example from a few years ago on Stack Overflow where it was at least an order of magnitude slower than Octave.

Can we get the headline changed? It is not at all accurate - the size of Wikipedia was a largely insignificant point in the judge's reason, as the article clearly states.

Maybe we should stop with the conspiracy theories about corrupt judges for a second and actually consider the legal situation. The judge's job is to rule based on the law, not to use his own judgment or fight for his idea of social justice.

For good reasons, you could only pursue a lawsuit against someone if you have real evidence of wrongdoing - not intuition or "common sense" or anything else. How would you feel if the RIAA could launch lawsuits against any teenager with a fast internet connection, based on a statistical argument and 'common sense' that most teens steal music?

You are right of course that having one's complaint not based on statistical likelihood but on actual evidence of a tort committed is an important principle. I was hoping someone with more knowledge of that area of law would jump in to start the substantive discussion of the issue as presented to the court.

My line of questioning above is based not on any actual evidence that anyone is actually being intimidated in that manner, but on speculation. It is still troubling if someone with more insight into game theory or organization theory cannot jump in with a reason why this sort of perversion of Justice wouldn't be possible. But that doesn't actually constitute any evidence whatsoever that it happened.

Have you looked at Julia (http://julialang.org/)?

Yes, I have, and Julia does look nice. It clearly has some very good libraries for scientific computing, and its syntax looks (to me) like an interesting combination of Python (which I like) and Matlab (which I don't like).

Aside from an entirely-subjective preference that caused me to fall in love with Nim at first sight, there are practical reasons for choosing Nim over Julia.

The overarching reason is that there is much more Python code in the world than Nim or Julia put together, and I think it will remain this way for a long time. (My startup previously worked almost completely in Python, for example, aside from some C or C++ extension modules and the usual Bash scripts for sysadmin.) Python also has some solid webserver frameworks, and is great for a variety of general-purpose tasks.

So, I wanted a solution that would enable us to incrementally rewrite code as necessary, without needing to rewrite everything from Python all at once. Also, I have no desire to rewrite our webserver code from Python. Flask & Django are just fine.

As I understand it (and please correct me if I'm wrong), Julia doesn't compile to C. So I can't compile snippets of Julia code and call them from my Python main-loop.

In contrast, not only is this possible in Nim, but Nim's macro system & well-developed AST spec make it very easy to traverse my Nim procs during compilation, to auto-generate per-proc wrapper code in C.

You're right that you can't compile Julia to static libraries (yet). Calling Julia from Python is not very mature at the moment, but calling Python from Julia is actually pretty robust via PyCall.jl (https://github.com/stevengj/PyCall.jl).

Hey -- working on similar things here. Would love to follow up but don't see your email in your profile. Mind adding it or sending me a note? (mine is in my profile)

Cheers!

Great! Email sent to the address in your profile.