NumPy

The fundamental package needed for scientific computing with Python is called NumPy.  This package contains:
- a powerful N-dimensional array object
- sophisticated (broadcasting) functions
- basic linear algebra functions

- basic Fourier transforms
- sophisticated random number capabilities
- tools for integrating Fortran code.
Besides it's obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide-variety of databases. NumPy derives from the old Numeric code base and can be used as a replacement for Numeric.   It also adds the features introduced by Numarray and can also be used to replace Numarray. 

Numeric users should find the transition relatively easy (although not without some effort).  There is a module (numpy.oldnumeric.alter_code1) that can make most of the necessary changes to your Python code that used Numeric to work with NumPy's Numeric compatibility module.

Users of numarray can also transition their code using a similar module (numpy.numarray.alter_code1) and the numpy.numarray compatibility layer.

C-code written to either package can be easily ported to NumPy using "numpy/oldnumeric.h" and "numpy/libnumarray.h" for the Numeric C-API and the Numarray C-API respectively.