scour 0.26-1 source package in Ubuntu

Changelog

scour (0.26-1) unstable; urgency=low

  [ Alessio Treglia ]
  * New upstream version.
  * debian/control: Bump Standards-Version to 3.9.2 (no changes necessary).

  [ Martin Pitt ]
  * debian/dh_scour: Support *.svgz icons as well. Thanks to Felix Geyer for
    the patch. (LP: #781810)
 -- Ubuntu Archive Auto-Sync <email address hidden>   Sat,  21 May 2011 09:04:10 +0000

Upload details

Uploaded by:
Ubuntu Archive Auto-Sync
Uploaded to:
Oneiric
Original maintainer:
Alessio Treglia
Architectures:
all
Section:
python
Urgency:
Low Urgency

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Series Pocket Published Component Section

Builds

Oneiric: [FULLYBUILT] i386

Downloads

File Size SHA-256 Checksum
scour_0.26.orig.tar.gz 43.3 KiB a5887d986bd694958807a23fb902b396aebe725b2a96edac80c71fa1e1f724e2
scour_0.26-1.debian.tar.gz 5.6 KiB 7092ff8a9080834f9cf3a3e1610dff13ef33a44088ef91e9d20d4765442b3141
scour_0.26-1.dsc 1.8 KiB 14558e3dd3ad3991d0d36d5079d70de68997f418fb5f45c76a16b9ad481c6a6f

Available diffs

View changes file

Binary packages built by this source

python-scour: SVG scrubber and optimizer

 Scour is a Python module that aggressively cleans SVG files, removing a lot of
 unnecessary information that certain tools or authors embed into their
 documents. The goal of scour is to provide an identically rendered image
 (i.e. a scoured document should have no discernable visible differences from
 the original file) while minimizing the file size.
 .
 WARNING: Scour is intended to be run on files that have been edited in Vector
 Graphics editors such as Inkscape or Adobe Illustrator. Scour attempts to
 optimize the file, and as result, it will change the file's structure and
 (possibly) its semantics. If you have hand-edited your SVG files, you will
 probably not be happy with the output of Scour.
 .
 Never use scour to overwrite your original file!
 .
 This package also provides a dh_scour debhelper extension which optimizes all
 shipped SVGs during package build. If python-rsvg and python-cairo are
 available, it will also do a before/after comparison and discard the optimized
 image if they differ by more than 0.05%.