Hi all, We had a great Sprint at Berkeley over last weekend. Jarrod deserves a huge hand for organizing it and Fernando should be also congradulated for making the Sprint a productive communication session with a lot of different people. Going forward, there will be a relatively informal SciPy board whose purpose is to keep SciPy (and NumPy) moving forward. Currently, this board consists of (alphabetically) Eric Jones Robert Kern Jarrod Millman Travis Oliphant Our goal is to clean up SciPy and get it ready for 1.0 release over the next year or so (which will need lots of help from the community). If anybody else is interested in serving on this board, just send me email. As part of this goal, we will be having regular "sprints" as well virtual "bug-days" and "doc-days" where people who want to participate using IRC can join in and coordinate efforts. There will be at least one bug-day or doc-day every month over the next year (on the last Friday of the month). The first one is a "doc-day" which will be held Friday on December 28, 2007 (getting started on New Year's resolutions early). This doc-day will be virtual where anyone with an internet connection can join in on the scipy channel on irc.freenode.net. At least one board member will be available at each "doc-day" or "bug-day" (even if we have to recruit board members to make it happen :-) ) The recent Sprint was very helpful. Jarrod is putting together some material from the Sprint. But, I wanted to provide over-view information for those who may be interested in what happend. Summary: A lot of great discussion took place (and some fine actual coding by a few) which resulted in the following plans: Schedule ------------ * NumPy 1.0.5 in mid January * SciPy 0.7.0 in mid March to April * NumPy 1.1 by August 2008 (may slip a bit depending on what is wanted to be included) The plans below are for NumPy 1.0.5 and SciPy 0.7.0 unless otherwise noted. IO ---- * scipy.io will be gutted and what functionality remains will be placed in numpy.io. * scipy.io will be a place for file readers and writers for various data formats (data, audio, video, images, matlab, excel, etc.) * NumPy will get a standard binary file format (.npy/.npz) for arrays/groups_of_arrays. * NumPy will be trying to incorporate some of matplotlib's csv2rec and rec2csv functionality. * Pickling arrays will be discouraged (you will still be able to do it, we will just try to not make it seem that it is the "default" way to save arrays). Testing --------- * scipy unit-testing will be "nose-compliant" and therefore nose will be required to run the SciPy tests. * NumPy will still use the current testing framework but will support SciPy's desire to be nose-compliant. NumPy 1.1 tests may move to just being "nose-compliant" * The goal is to make tests easier for contributors to write. Weave --------- * weave will not move into NumPy yet, but possibly at NumPy 1.1, there could be a separate package containing all the "wrapping" support code for NumPy in a more unified fashion (if somebody is interested in this, it is a great time to jump in). Sandbox ----------- * the scipy sandbox is disappearing (except for user playgrounds) and useful code in it will be placed in other areas. Python versions -------------------- * SciPy 0.7.0 will require Python 2.4 (we can now use decorators for SciPy). * NumPy will still be useful with Python 2.3 until at least 1.1 Other discussions ---------------------- * numpy-scons will be a separate package for now for building extensions with scons (we need experience to figure out what to do with it). * fixes to repr for numpy float scalars were put in place * Thanks to Rob Falck scipy.optimize grew slsqp (sequential least-squares programming) method (allows for equality and inequality constraints). The code by Dieter Kraft was wrapped. * We will be working to coordinate efforts with William Stein (of SAGE fame) in the future. Sage developers will be coming to Austin at the end of February to do some cooperative sprinting. * Brian Granger is working on a parallel version of NumPy that is very interesting. Deprecation approaches ------------------------------- Functions in SciPy that are disappearing will be "deprecated" with appendages to the docstring to explain how to do it differently. The deprecation will issue a warning when the function is run. In the next version, the function will disappear. Once SciPy hits 1.0, the deprecation paradigm will be a bit more conservative. A lot of fabulous things are happening with SciPy. It is an exciting time to be a part of it. There are a lot of ways to jump in and participate so feel free. If there is something you think needs addressing, then please share it. We may have a simple PEP process in the future, but for now the rule is basically "working code." Best regards, -Travis O.