I really do write Python all functional likehttp://exercism.io/submissions/48505fcb829440ddad99bfb77dc96664 …
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There are some legitimate benefits to this approach. It makes it easier to debug. We've decomposed all of the logical operations into distinct parts, not one big mashup of imperative top-down code.
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It makes the exception handling clear: if an exception happens, it's because the input has an unexpected value, and not because, idk, we've iterated out of bounds or something. There's no code that leaks into the if statements. We don't need breaks.
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This is all to say I really wish Data Science as a field used a language that was more naturally connected to functional analysis.
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