Guppi 0.40.0 Released: Adds Graphing Capability to Gnumeric



Your Guppi development team is pleased to announce the release of
Guppi 0.40.0, code name "Wild Yipes of Joy Were Heard in Stockholm".

Guppi is a GNOME-based framework for graphing and interactive data
analysis.

A lot has happened since our last release five months ago:

	- This is the first version of Guppi to support graphs
	  "out of the box" in production builds of Gnumeric.

	- We've also cleaned house.  Lots of experimental or
          not-fully-realized features have been stripped out, and
          substantial chunks of the code have been refactored.

There are our flimsy justifications for jumping to a new, rounder,
happier version number.

Thanks to Jody Goldberg, Rob Browning, Adrian Custer, Chris Lyttle,
and all of the other Friends Of Guppi who have helped with this
release.


* Availability

        You can get the Guppi 0.40.0 tarball here:

           http://download.gnome.org/GNOME/stable/sources/Guppi

        RPMs and debs will hopefully be available soon.


* Information

	Visit http://www.gnome.org/projects/guppi to learn more about
	Guppi.


* Prerequisites

        Guppi basically requires a complete and fairly up-to-date
        GNOME installation, such as Ximian GNOME. You will need to
	have (among other things)

		- bonobo 1.0.8
		- gnome-print 0.28
		- some version of guile (1.3 through 1.6)

	installed. 

	To use Guppi to insert graphs into your Gnumeric
        spreadsheets, you need to have Gnumeric 0.72 (or better) with
        Bonobo support installed before compiling Guppi.


* Caveats

	The simple stand-alone application that was distributed
	with previous versions of Guppi has been deprecated.  It was
	never very good or very featureful.  It will be totally
        re-written and will return after we port to GNOME 2.0.

	It is worth noting that Guppi is still EXPERIMENTAL
	software, and support for graphs in Gnumeric is still VERY
	INCOMPLETE.  Feedback and bug reports are always welcome, but
        you don't need to tell us that lots of features are missing:
	We already know that.

	









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