mirror of
https://github.com/NixOS/nixpkgs.git
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4f0dadbf38
After final improvements to the official formatter implementation,
this commit now performs the first treewide reformat of Nix files using it.
This is part of the implementation of RFC 166.
Only "inactive" files are reformatted, meaning only files that
aren't being touched by any PR with activity in the past 2 months.
This is to avoid conflicts for PRs that might soon be merged.
Later we can do a full treewide reformat to get the rest,
which should not cause as many conflicts.
A CI check has already been running for some time to ensure that new and
already-formatted files are formatted, so the files being reformatted here
should also stay formatted.
This commit was automatically created and can be verified using
nix-build a08b3a4d19.tar.gz \
--argstr baseRev b32a094368
result/bin/apply-formatting $NIXPKGS_PATH
83 lines
2.2 KiB
Nix
83 lines
2.2 KiB
Nix
{
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python,
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fetchurl,
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anki,
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}:
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python.pkgs.buildPythonApplication rec {
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pname = "mnemosyne";
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version = "2.10.1";
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src = fetchurl {
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url = "mirror://sourceforge/project/mnemosyne-proj/mnemosyne/mnemosyne-${version}/Mnemosyne-${version}.tar.gz";
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sha256 = "sha256-zI79iuRXb5S0Y87KfdG+HKc0XVNQOAcBR7Zt/OdaBP4=";
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};
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nativeBuildInputs = with python.pkgs; [ pyqtwebengine.wrapQtAppsHook ];
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buildInputs = [ anki ];
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propagatedBuildInputs = with python.pkgs; [
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cheroot
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cherrypy
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googletrans
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gtts
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matplotlib
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pyopengl
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pyqt6
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pyqt6-webengine
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argon2-cffi
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webob
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];
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prePatch = ''
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substituteInPlace setup.py \
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--replace '("", ["/usr/local/bin/mplayer"])' ""
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'';
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# No tests/ directory in tarball
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doCheck = false;
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postInstall = ''
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mkdir -p $out/share/applications
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mv mnemosyne.desktop $out/share/applications
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'';
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dontWrapQtApps = true;
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makeWrapperArgs = [
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"\${qtWrapperArgs[@]}"
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];
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meta = {
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homepage = "https://mnemosyne-proj.org/";
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description = "Spaced-repetition software";
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mainProgram = "mnemosyne";
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longDescription = ''
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The Mnemosyne Project has two aspects:
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* It's a free flash-card tool which optimizes your learning process.
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* It's a research project into the nature of long-term memory.
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We strive to provide a clear, uncluttered piece of software, easy to use
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and to understand for newbies, but still infinitely customisable through
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plugins and scripts for power users.
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## Efficient learning
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Mnemosyne uses a sophisticated algorithm to schedule the best time for
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a card to come up for review. Difficult cards that you tend to forget
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quickly will be scheduled more often, while Mnemosyne won't waste your
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time on things you remember well.
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## Memory research
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If you want, anonymous statistics on your learning process can be
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uploaded to a central server for analysis. This data will be valuable to
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study the behaviour of our memory over a very long time period. The
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results will be used to improve the scheduling algorithms behind the
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software even further.
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'';
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};
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}
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