NumPys module structure#

NumPy has a large number of submodules. Most regular usage of NumPy requires only the main namespace and a smaller set of submodules. The rest either have special-purpose or niche namespaces.

Main namespaces#

Regular/recommended user-facing namespaces for general use:

• numpy

• numpy.exceptions

• numpy.fft

• numpy.linalg

• numpy.polynomial

• numpy.random

• numpy.strings

• numpy.testing

• numpy.typing

Special-purpose namespaces#

• numpy.ctypeslib - interacting with NumPy objects with ctypes

• numpy.dtypes - dtype classes (typically not used directly by end users)

• numpy.emath - mathematical functions with automatic domain

• numpy.lib - utilities & functionality which do not fit the main namespace

• numpy.rec - record arrays (largely superseded by dataframe libraries)

• numpy.version - small module with more detailed version info

Legacy namespaces#

Prefer not to use these namespaces for new code. There are better alternatives and/or this code is deprecated or isnt reliable.

• numpy.char - legacy string functionality, only for fixed-width strings

• numpy.f2py - Fortran binding generation (usually used from the command line only)

• numpy.ma - masked arrays (not very reliable, needs an overhaul)

• numpy.matlib (pending deprecation) - functions supporting matrix instances