Download List

專案描述

Quotient is multi-protocol (SMTP, POP, IMAP, SIP,
HTTP, Q2Q) server that helps with all your online
conversations, be they over email, IRC, IM,
mailing lists, or voice over IP. It is written in
Python on the Twisted framework, and uses Xapian
for search and SpamBayes for spam classification.

System Requirements

System requirement is not defined
Information regarding Project Releases and Project Resources. Note that the information here is a quote from Freecode.com page, and the downloads themselves may not be hosted on OSDN.

2005-07-20 07:27
0.9.2

The license was switched to an MIT-style license.
q2q, a peer-to-peer transport protocol, was added.
Lots of bugs were fixed. Many minor feature
enhancements were added. The full-text indexer was
replaced with Xapian. Nevow and Twisted were
upgraded to recent releases. An RSS generator was
added, and the "Remember Me" button at login was
added.
標籤: Major feature enhancements

2004-06-14 14:45
0.9.1

標籤: Major feature enhancements

2003-12-16 21:04
0.8.8

This release is focused on incremental improvements to existing functionality. In particular, the database has been simplified and streamlined, and the extraction framework has been made more robust. To aid with system management, there are tools for monitoring system throughput and ways of throttling it. The UI has seen improvements above and below the hood. It is easier to configure the primary navigation elements and the visibility of items to the user. There is also a command line interface to enable quick and easy data entry and navigation for keyboard-centric users.
標籤: Major feature enhancements

2003-12-06 23:22
0.8.6

A bug in setup.py was fixed.
標籤: Minor bugfixes

2003-12-02 20:30
0.8.5

This release introduces a number of new features while improving the integration of existing features. A significant part of this release is the integration of IMAP folders with Quotient Pools. This allows for nifty ways of working with Quotient from an IMAP client. For instance, if you use Quotient as your IMAP server, and drag a message into the 'Spam' folder, it will detect that and use the filed message for training SpamBayes. Or you can drag a message into the 'Blog' folder and it will show up on your Quotient blog.
標籤: Major feature enhancements

Project Resources