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|
{ python
, fetchurl
, anki
}:
python.pkgs.buildPythonApplication rec {
pname = "mnemosyne";
version = "2.10.1";
src = fetchurl {
url = "mirror://sourceforge/project/mnemosyne-proj/mnemosyne/mnemosyne-${version}/Mnemosyne-${version}.tar.gz";
sha256 = "sha256-zI79iuRXb5S0Y87KfdG+HKc0XVNQOAcBR7Zt/OdaBP4=";
};
nativeBuildInputs = with python.pkgs; [ pyqtwebengine.wrapQtAppsHook ];
buildInputs = [ anki ];
propagatedBuildInputs = with python.pkgs; [
cheroot
cherrypy
googletrans
gtts
matplotlib
pyopengl
pyqt6
pyqt6-webengine
argon2-cffi
webob
];
prePatch = ''
substituteInPlace setup.py \
--replace '("", ["/usr/local/bin/mplayer"])' ""
'';
# No tests/ directory in tarball
doCheck = false;
postInstall = ''
mkdir -p $out/share/applications
mv mnemosyne.desktop $out/share/applications
'';
dontWrapQtApps = true;
makeWrapperArgs = [
"\${qtWrapperArgs[@]}"
];
meta = {
homepage = "https://mnemosyne-proj.org/";
description = "Spaced-repetition software";
mainProgram = "mnemosyne";
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.
'';
};
}
|
