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+NumPy is the fundamental package needed for scientific computing with Python.  It contains among other things:
+
+- a powerful N-dimensional array object
+- sophisticated (broadcasting) functions
+- tools for integrating C/C++ and Fortran code
+- useful linear algebra, Fourier transform, and random number capabilities. 
+
+Besides its 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.
+
+Getting Started
+---------------
+
+- `Getting Numpy <http://www.scipy.org/Download>`_
+- `Installing NumPy and SciPy <http://www.scipy.org/Installing_SciPy>`_
+- `NumPy and SciPy documentation page <http://docs.scipy.org/doc/>`_
+- `NumPy Tutorial <http://www.scipy.org/Tentative_NumPy_Tutorial>`_
+- `NumPy for MATLAB© Users <http://www.scipy.org/NumPy_for_Matlab_Users>`_
+- `NumPy functions by category <http://www.scipy.org/Numpy_Functions_by_Category>`_
+- `NumPy Mailing List <http://www.scipy.org/Mailing_Lists>`_
+
+More Information
+----------------
+
+- `NumPy Sourceforge Home Page <http://sourceforge.net/projects/numpy/>`_
+- `SciPy Home Page <http://www.scipy.org/>`_
+- `Interfacing with compiled code <http://www.scipy.org/Topical_Software#head-7153b42ac4ea517c7d99ec4f4453555b2302a1f8>`_
+- :doc:`Older python array packages </old_array_packages>`
+
+.. toctree::
+   :hidden:
+
+   old_array_packages