I'm the developer of an in-production sensor analysis backend program written in Nim. Our server scripts invoke it on individual or batches of records, so it doesn't continuously run, and we get free parallelism via the shell. I make copious use of Datamancer dataframes. The program is entirely processing logic. I have maybe 3 lines of memory semantic code in 40k lines. I rely on Nim's default behavior, wherein dynamic types such as collections are stack-managed hidden unique pointers treated as value types.

The performance is impressive. I've done some exercises on the side to compare Nim's performance to C++ building large collections along with sequential and random access, and -d:release from Nim puts out results that are neck-and-neck with -O3 for C++. No special memory tricks or anything, just writing very Pythonic, clear code.

Feel free to ask me anything.