We've run into issues with Arrow – it or its dependencies would frequently break on updates, and we stopped using it. But none of the other issues mentioned in

We've run into issues with Arrow – it or its dependencies would frequently break on updates, and we stopped using it. But none of the other issues mentioned in the article have ever come up for us. In particular, a lot of the problems come from using OffsetArrays.jl, which is a library designed to let you use different starting indices for an array, which we just don't use. It's worth noting that we initially migrated ~15kloc of numpy data/numeric pipelines to Julia, and mostly found the same values, with the exception of something that turned out to be a bug in a Python library. I would say that the biggest Julia annoyance we've run into has to do with the way the Expr type is implemented, particularly the fact that it's mutable, which makes some of the metaprogramming we want to do substantially harder. But that's not a bug per se, just a design choice I don't like.