Experimenting with Android malware requires to manipulate a large amount of samples and to chain multiple analyses. Scripting such a sequence of analyses on a large malware dataset becomes a challenge: the analysis has to handle fails on the computer and crashes on the used smartphone, in caseof dynamic analyses. We present a new tool, PyMaO, for handling such experiments on a regular desktop PC with the highest performance throughput. PyMaO helps to write sequences of analyses and handle partial experiments that should be restarted after a crash or continued with new unknown analyses. The tool also offers a post processing capability for generating number tables or bar graphs from the analyzed datasets.