Ubuntu
scour package

scour 0.26-3 source package in Ubuntu

Changelog

scour (0.26-3) unstable; urgency=low


  * Add patch from upstream's trunk to fix:
    - Incorrect handling of comments when the file starts with a comment.
    - Failure when parsing a polygon starting with a negative coordinate.

 -- Alessio Treglia <email address hidden>  Sat, 31 Dec 2011 10:31:02 +0100

Upload details

Uploaded by:
Alessio Treglia
Uploaded to:
Sid
Original maintainer:
Alessio Treglia
Architectures:
all
Section:
python
Urgency:
Low Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Precise release main python

Builds

Precise: [FULLYBUILT] i386

Downloads

File Size SHA-256 Checksum
scour_0.26-3.dsc 1.8 KiB 24269c03333f0724cf42d02a992351304853ebf8c36b4634b5ffc7bc2e3035e2
scour_0.26.orig.tar.gz 43.3 KiB a5887d986bd694958807a23fb902b396aebe725b2a96edac80c71fa1e1f724e2
scour_0.26-3.debian.tar.gz 6.5 KiB fd4b2581937314669a123765b5ce0ce4e133fbe711c64a5c85bffa937ad00ab3

No changes file available.

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%.