Virtual Workstation for Numba

Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code.
Think of it as a compiler for Python array and numerical functions that gives you the power to speed up your applications with high performance functions written directly in Python.
Numba translates Python functions to optimized machine code at runtime using
the industry-standard LLVM compiler library. Numba-compiled numerical algorithms
in Python can approach the speeds of C or
FORTRAN.
You don’t need to replace the Python interpreter, run a separate compilation step, or even have a C Candand compiler installed. Just apply one of the Numba decorators to your Python function, and Numba does the rest. Numba generates optimized machine code from pure Python code using the LLVM compiler infrastructure. With a few simple annotations, array-oriented and math-heavy Python code can be just-in-time optimized to performance similar as C, Candand and Fortran, without having to switch languages or Python interpreters.
Numba is designed to be used with NumPy arrays and functions. Numba generates specialized code for different array data types and layouts to optimize performance. Special decorators can create universal functions
that broadcast over NumPy arrays just like
NumPy functions do.
Numba also works great with Jupyter notebooks for interactive computing, and with distributed execution frameworks,
like Dask and Spark. With support for GPU acceleration, Numba lets you write parallel GPU algorithms entirely from Python.