> People are increasingly running out of reasons to not use Julia

I'm sorry, but I can't really let you say that.

I like Julia, it has many nice features, but it still IMHO exhibits a lot of reasons not to use it, all of which I stumbled upon while using it to develop non-trivial pieces of software in bioinformatics.

  - parallelism is very confusing, very easy to break, and not very efficient when it works;
  

  - cold-boot time is prohibitive;


  - the ecosystem is brittle, and very much underdocumented;


  - the dispatch mechanism is both a blessing and a curse;


  - the stdlib should include some way of encoding errors, otherwise everyone cook their own stuff in their corner (should I raise an exception? Return -1, or maybe null? Or a Union?);

 
  - not being able to redefine types in REPL is a PITA for REPL-driven development;


  - debugging cross-packages bugs with multi-dispatch in time-consuming;


  - the stdlib doc website is *excruciatingly* slow;


  - memory consumption is hard to control;

 
  - iterators are weird (i.e. eager and hardly composable), and either pipe should be a part of the language or they should be chainable, map(f, filter(g, sort(h, [...]map(t, xs)))) leads to unreadable & uneditable mess;


  - performances do not follow what was promised (*C-like order of magnitude*), unless maybe you're (a) a Julia god or (b) only using numeric computations.

Now none of these flaws are intrinsic, and I very much hope that all these edges will be polished in the coming times. But as a ‶grunt on the field″, it is exasperating to see the core Julia community just telling you that you're holding it wrong and that all is best in the best of worlds.