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My (more or less extensive) experience with Julia has been rather good. Step 1. Prototyping. Small data, don't care about performance. Julia is as easy as pyth
by warinukraine 4y ago
My (more or less extensive) experience with Julia has been rather good.
Step 1. Prototyping. Small data, don't care about performance. Julia is as easy as python, but faster. GC doesn't matter.
Step 2. Production. Very large datasets. Performance is very important so I make sure that hot loops don't allocate, and so GC doesn't matter.
Really, I struggle to see how someone can not like this.
Regarding hiring. My experience has been that you can roughly divide people into two categories. Those who like using tools, and those who like solving problems. For the former, a different language might be an issue because they might not know and might not be in the mood for learning it. For the latter, they're happy to learn any tool that can help solve their problem. We want the latter, and for the latter learning Julia hasn't been an issue.
- vHMtsdf 4y agoI am not exactly sure what they were working on, but I am not convinced that any code can be made non-allocating easily. For example, when you are building large trees with complex structures in the nodes and you need to both add/remove the nodes, the effort to make it non-allocating might be too much compared to just using C++ and writing things more naturally?