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Yeah but I think for non-trivial programs, say 10k+ lines of code, it's really difficult to show proper examples, not to speak of exhaustive coverage. Go in par
by blablabla123 7y ago
Yeah but I think for non-trivial programs, say 10k+ lines of code, it's really difficult to show proper examples, not to speak of exhaustive coverage. Go in particular doesn't have many fancy language constructs and a lot of well written code in Go 1 might look a bit repetitive, especially the error handling. But once you wrote a larger program and followed best practices with error handling, you might be delighted how much more compact error messages are and still offer a lot of greppable things to debug after.
Probably there are languages that have a really expressive syntax that solve problems also in a scalable manner. For instance Python with its list comprehension that are a real code and time saver for software that does a lot with lists. (No coincidence it's so popular with ML.)
- mratsim 7y agoIn ML you really want to use Numpy ndarrays, Pandas dataframes or Tensors. A list is much too slow because: - Not contiguous - No SIMD vectorization - No parallel processing Lists are mostly used for list of containers (for example storing the arrays inputs of a function)