NumPy’s 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 either special-purpose or niche namespaces.
Main namespaces#
Regular/recommended user-facing namespaces for general use:
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numpy.rec - record arrays (largely superseded by dataframe libraries)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 isn’t reliable.
numpy.char - legacy string functionality, only for fixed-width strings
numpy.distutils (deprecated) - build system support
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