This is a Python implementation of the Data Access Protocol, a
scientific protocol for data access developed by the OPeNDAP team
(http://opendap.org). This implementation is developed from scratch,
following the latest specification of the protocol (DAP 2.0 Draft
Community Standard 2005/04/27) and based on my experience with OPeNDAP
servers on the wild.

Using this module one can access hundreds of scientific datasets
from Python programs, accessing data in an efficient, transparent and
pythonic way. Arrays are manipulated like normal multi-dimensional arrays
(like numpy.array, e.g.), with the fundamental difference that data is
downloaded on-the-fly when a variable is sliced. Sequential data can
be filtered on the server side before being downloaded, saving bandwith
and time.

The module also implements a DAP server, allowing datasets from a
multitude of formats (netCDF, Matlab, CSV files, SQL RDBMS) to be served
on the internet. The server specifies a plugin API for supporting new
data formats in an easy way. The DAP server is implemented as a WSGI
application (see PEP 333), running on a variery of servers, and can be
combined with WSGI middleware to support authentication, gzip compression
and much more.

For more information, please check the official website (http://pydap.org)
or the included documentation.

This module was supported in 2005 by the Google Summer of Code,
mentored by Paul Dubois of Numeric Python fame, and a few donations
through PayPal. I'm currently receiving a grant from CNPq to implement
the server at CPTEC/INPE, giving me some generous time to work on the
module while being paid at the same time (to think that it all started
from fun!). Thanks for everyone that helped me with this project.

(c) 2003-2006 Roberto De Almeida <rob@pydap.org>
http://pydap.org/
