Julia and Python
When Python became popular, I still stuck with MATLAB because of its extensive libraries and also because I was lazy. Recently I switched to Julia because of performance. Julia is often much faster than Python or MATLAB. Julia goes a long way towards solving the “two language problem” of prototyping in one language and then rewriting the code in another language for performance.
Python is more mature and stable than Julia. Its larger ecosystem of software packages enables one to move faster by building on the work of a large community. But Julia may be superior if you mainly want to write your own code, as in most of the homework exercises of this class. And a lot of really talented people are developing Julia packages. Julia may eventually become the language of choice for numerical computation.
MATLAB may still have the best developed plotting capabilities. But its licensing model has become cumbersome. To Dockerize and run a thousand cloud instances, you’ll want to use open source software like Python or Julia, not MATLAB. And the MATLAB language itself is good for writing short scripts, but less suited to large software projects.
My lab uses Julia, Python, JavaScript, and C++. Julia has gained a lot of popularity over the past year.
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