Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code.

Numba documentation ¶ This is the Numba documentation. Unless you are already acquainted with Numba, we suggest you start with the User manual.

Numba makes Python code fast Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code. Learn More Try Numba »

A ~5 minute guide to Numba ¶ Numba is a just-in-time compiler for Python that works best on code that uses NumPy arrays and functions, and loops. The most common way to use Numba is through its …

1.1. A ~5 minute guide to Numba ¶ Numba is a just-in-time compiler for Python that works best on code that uses NumPy arrays and functions, and loops. The most common way to use Numba is through …

Starting with numba version 0.12, it is possible to use numba.jit without providing a type-signature for the function. This functionality was provided by numba.autojit in previous versions of numba. The old …

Constructs ¶ Numba strives to support as much of the Python language as possible, but some language features are not available inside Numba-compiled functions. Below is a quick reference for the …

Compatibility ¶ Numba is compatible with Python 3.6 or later, and Numpy versions 1.15 or later. Our supported platforms are: Linux x86 (32-bit and 64-bit) Linux ppcle64 (POWER8) Windows 7 and later …

Parallel Range ¶ Numba implements the ability to run loops in parallel, similar to OpenMP parallel for loops and Cython’s prange. The loops body is scheduled in seperate threads, and they execute in a …

Supported NumPy features ¶ One objective of Numba is having a seamless integration with NumPy. NumPy arrays provide an efficient storage method for homogeneous sets of data. NumPy dtypes …