Getting started with Numba

Numba was started in 2012 by Travis Oliphant, the original author of NumPy, as a library for compiling individual Python functions at runtime using the Low-Level Virtual Machine (LLVM) toolchain.

LLVM is a set of tools designed to write compilers. LLVM is language-agnostic and is used to write compilers for a wide range of languages (an important example is the Clang compiler). One of the core aspects of LLVM is the intermediate representation (the LLVM IR), a very low-level, platform-agnostic language-like assembly, that can be compiled to machine code for the specific target platform.

Numba works by inspecting Python functions and compiling them, using LLVM, to the IR. As we saw in the last chapter, speed gains can be obtained when we introduce types for variables and functions. Numba implements clever algorithms to guess the types (this is called type inference) and compiles type-aware versions of the functions for fast execution.

Note that Numba...