provide additional libraries of scientific programming tools and use numpy as core component the pypy implementation of python (discussed in has also gained traction in the numeric domainin part because heavily algorithmic code of the sort that' common in this domain can run dramatically faster in pypy--often to quicker and moregamingimagesdata miningrobotsexcel python is commonly applied in more domains than can be covered here for exampleyou'll find tools that allow you to use python to dogame programming and multimedia with pygamecgkitpygletpysoypanda dand others serial port communication on windowslinuxand more with the pyserial extension image processing with pil and its newer pillow forkpyopenglblendermayaand more robot control programming with the pyro toolkit natural language analysis with the nltk package instrumentation on the raspberry pi and arduino boards mobile computing with ports of python to the google android and apple ios platforms excel spreadsheet function and macro programming with the pyxll or datanitro add-ins media file content and metadata tag processing with pymediaid pil/pillowand more artificial intelligence with the pybrain neural net library and the milk machine learning toolkit expert system programming with pyclipspykepyrologand pydatalog network monitoring with zenosswritten in and customized with python python-scripted design and modeling with pythoncadpythonoccfreecadand others document processing and generation with reportlabsphinxcheetahpypdfand so on data visualization with mayavimatplotlibvtkvpythonand more xml parsing with the xml library packagethe xmlrpclib moduleand third-party extensions json and csv file processing with the json and csv modules python & session