Hi. As previously mentioned, I'd like someone to try out using Nucular inside Django.
In our last episode someone wanted Nucular to support Windoze. Now it does. Here is the announcement: ====== cut ===== ANNOUNCE: NUCULAR Fielded Full Text Indexing, BETA 3 Nucular is a system for creating full text indices for fielded data. It can be accessed via a Python API or via a suite of command line interfaces. NEWS Nucular now supports WIN32. Current releases of Nucular abstract the file system in order to emulate file system feature missing on NT file systems which prevented older versions from running correctly on Windows NT based systems. Proximity search added: Current versions of Nucular allow queries to search for a sequence of words near each other separated by no more than a specified number of other words. Faceted suggestions: Nucular queries now support faceted suggestions for values for fields which are related to a query. Faster index builds: Current releases of Nucular have completely revamped internal data structures which build indices much faster (and query a bit faster also). For example some builds run more than 8 times faster than previously. Read more and download at: http://nucular.sourceforge.net ONLINE DEMOS: Python source search: http://www.xfeedme.com/nucular/pydistro.py/go?FREETEXT=malodorous+parrot Mondial geographic text search: http://www.xfeedme.com/nucular/mondial.py/go?attr_name=ono Gutenberg book search: http://www.xfeedme.com/nucular/gut.py/go?attr_Comments=immoral+english BACKGROUND: Nucular is intended to help store and retrieve searchable information in a manner somewhat similar to the way that "www.hotjobs.com" stores and retrieves job descriptions, for example. Nucular archives fielded documents and retrieves them based on field value, field prefix, field word prefix, or full text word prefix, word proximity or combinations of these. Nucular also includes features for determining values related to a query often called query facets. FEATURES Nucular is very light weight. Updates and accesses do not require any server process or other system support such as shared memory locking. Nucular supports concurrency. Arbitrary concurrent updates and accesses by multiple processes or threads are supported, with no possible locking issues. Nucular supports document threading in the manner of USENET replies. Built in semantics allows "follow ups" to messages to match patterns that match the "original" messages. Nucular indexes and retrieves data quickly. I hope you like. -- Aaron Watters === It's humbling to think that when Mozart was my age he'd been dead for 5 years. -- Tom Lehrer --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Django users" group. To post to this group, send email to django-users@googlegroups.com To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/django-users?hl=en -~----------~----~----~----~------~----~------~--~---
