[majoe]

I really like "Julia, the programming language" and had a great experience using it on the few occasions, where it made sense. But whenever a colleague asks me, if I can recommend it, I have to say "no". The crux is, that its "just-ahead-of-time" compiler disqualifies it for a lot of use cases: I actually would prefer it over Python for small scripts, but the compilation overhead is too long. On the other hand I would use it over C++ for some applications, when it could easily produce portable binaries.

With the steady progress in improving precompilation, I'm optimistic to use it more often in the future, though.

[jakobnissen]

Yeah I agree. It's good for specific use cases where the JIT latency doesn't matter too much - which means either interactive work, or long-running computations. So, mostly science/engineering work, and perhaps stuff like generative art, building wbsites and stuff.

When latency is much better and/or it can compile static binaries, the use case of Julia will hopefully broaden

[stellalo]

> I actually would prefer it over Python for small scripts, but the compilation overhead is too long

Looks like this release reduces that by a lot, see the first section in the OP on caching native code, modulo adoption of good precompilation habits by the various packages.

[ziotom78]

I have the same feelings as you: I stick to Python for tasks that aren't worthy of a long compilation because the execution time would be small, but I always use Julia for computation-intensive tasks.

However, because of this, when somebody asks me if I would recommend Julia to them, instead of answering “no” I just say “it depends”