The context for this thread, was the mega-thread about “how do we increase popularity of Julia?” I’m not sure that I’d say I’m currently under the impression that Julia is a wholesale package, but certainly tools like Python and Matlab achieve a significant portion of their popularity from the ease and clarity that their ecosystems provide.
I will say that in the early-mid 2010s I, as non-Julian, I was definitely under the impression that Julia was the “Matlab, Python, Fortran, C++ successor” so I was definitely expecting performance of the latter and ease-of-use of the former. Standard libraries and ecosystem are definitely part of that ease-of-use. The first words of the introduction in Julia’s manual are:
Scientific computing
And later goes on to say:
Julia provides ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general programming. To achieve this, Julia builds upon the lineage of mathematical programming languages, but also borrows much from popular dynamic languages, including Lisp, Perl, Python, Lua, and Ruby.
and
The core language imposes very little;
I would argue that the core language imposes very little, but also provides very little. I just remember being very disenchanted with Julia when I spun it up and found there was almost no built-in functionality to do what I wanted and then a piece-meal, maze-like ecosystem that seemed constantly in flux.
So maybe the answer here is addressed by my other post on ease of adding entire organizations’ production packages, or maybe its having a link on the Julia downloads page to “Pre-packaged ecosystem installation providers” like JuliaHub.