Hello everyone,

I'm pleased to announce the first release of hpodder.  hpodder is a
podcast downloader (podcatcher) written in pure Haskell.  I wrote it
because I was unsatisfied with the other podcatchers for Linux.

I am using hpodder for my own purposes already.

hpodder homepage: http://quux.org/devel/hpodder
documentation: http://darcs.complete.org/hpodder/doc/hpodder.pdf
darcs repo: http://darcs.complete.org/hpoder

feature list:

       · Convenient, easy to learn, and fast command-line interface (it's sim-
         ple to do simple things, and advanced things are possible)

       · Automatic discovery of feed metadata such as title

       · Full history database for accurate prevention of duplicate  downloads
         and tracking of new episodes

       · Conversion  tools to convert your existing feed list and history from
         other applications to hpodder.  Supported  applications  and  formats
         include: castpodder and ipodder.

       · Most  operations can work fully automatically across your entire pod-
         cast database, or they can work manually as well.

       · Automatic updating of ID3 (v1 and v2) tags based on metadata  in  the
         podcast  itself.   This important feature is available through iTunes
         but is often missed by other podcatchers.

       · hpodder operations can be easily scripted or scheduled using  regular
         operating system tools.

       · Fully customizable naming scheme for downloaded episodes, including a
         name collision detection and workaround algorithm.

       · Automatic support for appending .mp3 extensions  to  MP3  files  that
         lack it.

       · Numerous database and history inquiry tools

       · Small, minimalist footprint

       · Power  users  and  developers can interact directly with the embedded
         Sqlite3 database used by hpodder.  The database has a  simple  schema
         that is developer-friendly.

       · Support for resuming interrupted downloads of podcasts

       · hpodder  is SAFE and is designed with data integrity in mind from the
         beginning.  It should be exceedingly  difficult  to  lose  a  podcast
         episode, even in the event of a power failure.