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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.  
+    '';
+  };
+}