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{ stdenv
, fetchurl
, buildPythonPackage
, pyqt4
, matplotlib
, cherrypy
, sqlite3
}:
let
version = "2.2.1";
in buildPythonPackage rec {
name = "mnemosyne-${version}";
src = fetchurl {
url = "http://sourceforge.net/projects/mnemosyne-proj/files/mnemosyne/${name}/Mnemosyne-${version}.tar.gz";
sha256 = "7f5dd06a879b9ab059592355412182ee286e78e124aa25d588cacf9e4ab7c423";
};
pythonPath = [
pyqt4
matplotlib
cherrypy
sqlite3
];
preConfigure = ''
substituteInPlace setup.py --replace /usr $out
find . -type f -exec grep -H sys.exec_prefix {} ';' | cut -d: -f1 | xargs sed -i s,sys.exec_prefix,\"$out\",
'';
installCommand = "python setup.py install --prefix=$out";
meta = {
homepage = http://mnemosyne-proj.org/;
description = "Spaced-repetition software";
longDescription = ''
The Mnemosyne Project has two aspects:
* It's a free flash-card tool which optimizes your learning process.
* It's a research project into the nature of long-term memory.
We strive to provide a clear, uncluttered piece of software, easy to use
and to understand for newbies, but still infinitely customisable through
plugins and scripts for power users.
## Efficient learning
Mnemosyne uses a sophisticated algorithm to schedule the best time for
a card to come up for review. Difficult cards that you tend to forget
quickly will be scheduled more often, while Mnemosyne won't waste your
time on things you remember well.
## Memory research
If you want, anonymous statistics on your learning process can be
uploaded to a central server for analysis. This data will be valuable to
study the behaviour of our memory over a very long time period. The
results will be used to improve the scheduling algorithms behind the
software even further.
'';
};
}
|