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That's how idiomatic one-way-to-do-it generic languages slowly win. They raise the bar for the specialty languages so that, for example, after R the next statistical language really, really needs to shine in what it does in order to justify the trouble of learning another language over using a Python with a statistics library.


There's a catch though - once you start using numpy/scipy, there's no longer one-way-to-do-it and code becomes pretty messy.




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