Will Julia ever fix its "using ..." latency problems?

[Volker_Weissmann]

@Sukera

May I ask how long you’ve been around with julia? I certainly remember the days of 0.6, where e.g. using Plots took tens of minutes on the very machine I’m typing on now.

Only since about a month. In my bachelor thesis of physics, I wrote rust and python and for my master thesis of physics, I’m hoping to replace both of them with Julia (at least for scientific computing).

@Sukera

Also, there have been multiple links in this thread (and in the linked issues and other things) pointing towards improving that state even more. As a short recap what has happened in the past few months:
…

I’m happy to see that Julia is very actively developed.

@Sukera

@Volker_Weissmann

Would this problem still exist if there would be no eval and @eval command?

(I’m not proposing to remove these commands, I just want to understand how Julia works.)

I’m only 95% sure that nothing similar would crop up, but yes, these specific problems are gone insofar you can’t express that idea at all anymore.

Without eval and @eval , there is no REPL and there is no interactive mode. There’s also no recompilation at runtime and there’s no shadowing of existing things in the same namespace since there’s no way to “redefine” anything like a struct or a function at runtime. There’s also no convenient creating of similar function expressions and writing boilerplate (where you define functions with different names but that can take the same arguments) would be a dread. Julia would just be another statically compiled language like C, C++ or Rust (or any number of other compiled languages).

Thank you for your explanation.

@Sukera

Always remember, the really fast parts in Python are not written in Python

Of course.