September 2016
Beginner to intermediate
346 pages
6h 35m
English
Content preview from Julia for Data ScienceBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Facilitating language interoperability
Although Julia can be used to write most kinds of code, there are mature libraries for numerical and scientific computing which we would like to exploit. These libraries can be in C, Fortran or Python. Julia allows the ease of using the existing code written in Python, C, or Fortran. This is done by making Julia perform simple and efficient-to-call C, Fortran, or Python functions.
The C/Fortran libraries should be available to Julia. An ordinary but valid call with ccall is made to this code. This is possible when the code is available as a shared library. Julia's JIT generates the same machine instructions as the native C call. Therefore, it is generally no different from calling through a C code with a minimal ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.