reverend 0.4-0ubuntu1 source package in Ubuntu


reverend (0.4-0ubuntu1) raring; urgency=low

  [ Logan Rosen ]
  * New upstream release.
  * debian/watch: Create.
  * debian/control:
    - Add Homepage field.
    - Remove homepage from Description.
    - Replace python-all-dev with python in Build-Depends.
    - Add ${misc:Depends} to Depends for python-reverend binary.
    - Bump Standards-Version to 3.9.3.
  * debian/source/format: Specify 3.0 (quilt) format.

  [ Charlie Smotherman ]
  * Update to use dh_python2.
  * Remove debian/pycompat not needed.
  * Removed debian/pyversions not needed.
  * Increased debian/compat to 7.
  * Use dh7 tiny rules.
  * Update debian/rules get-orig-source for version 0.4.
  * debian/control
    - remove cdbs and python-support from B-D.
    - increased python to >= 2.6.6-3~.
    - increased debhelper to 7.0.50.
    - added X-P-V.
    - removed Provides.
 -- Logan Rosen <email address hidden>   Fri, 23 Nov 2012 22:37:55 -0500

Upload details

Uploaded by:
Logan Rosen on 2012-11-25
Sponsored by:
Uploaded to:
Original maintainer:
Ubuntu MOTU Developers
Low Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Disco release on 2018-10-30 universe python
Cosmic release on 2018-05-01 universe python
Bionic release on 2017-10-24 universe python
Artful release on 2017-04-20 universe python
Xenial release on 2015-10-22 universe python
Trusty release on 2013-10-18 universe python


Raring: [FULLYBUILT] i386


File Size SHA-256 Checksum
reverend_0.4.orig.tar.gz 11.9 KiB 33f801891bc84cd1adcbd8e1c4d53841bb27451f89b32c0418512c655a4c2054
reverend_0.4-0ubuntu1.debian.tar.gz 2.3 KiB 362670be141e4d7129ab3f006c7c75eeb140ac7aa08829dc2767234fcfefc666
reverend_0.4-0ubuntu1.dsc 1.2 KiB aeec346edf20e01ffcc1e2ad6f823ff90b4cf1ae601865e297fcb368761f43c2

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Binary packages built by this source

python-reverend: general purpose Bayesian classifier for Python

 Reverend is a general purpose Bayesian classifier, named after Rev. Thomas
 Bayes. Use the Reverend to quickly add Bayesian smarts to your app. To use it
 in your own application, you either subclass Bayes or pass it a tokenizing
 function. Bayesian fun has never been so quick and easy.
 Stuff you can do with the Reverend:
    * classify RSS stories
    * classify recipes by cuisine
    * who do you write like? Shakespeare, Dickens or Austen
    * detect the language of a document
    * is your code more like Guido's or Peter's