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        "description": "-------------------------------------\nppft: distributed and parallel python\n-------------------------------------\n\nAbout Ppft\n==========\n\n``ppft`` is a fork of Parallel Python, and is developed as part of ``pathos``: https://github.com/uqfoundation/pathos\n\nParallel Python module (``pp``) provides an easy and efficient way to create parallel-enabled applications for SMP computers and clusters. ``pp`` module features cross-platform portability and dynamic load balancing. Thus application written with ``pp`` will parallelize efficiently even on heterogeneous and multi-platform clusters (including clusters running other application with variable CPU loads). Visit http://www.parallelpython.com for further information.\n\n``ppft`` is part of ``pathos``, a python framework for heterogeneous computing.\n``ppft`` is in active development, so any user feedback, bug reports, comments,\nor suggestions are highly appreciated.  A list of known issues is maintained\nat http://trac.mystic.cacr.caltech.edu/project/pathos/query.html, with a public\nticket list at https://github.com/uqfoundation/ppft/issues.\n\nNOTE: ``ppft`` installs as ``pp``. If ``pp`` is installed, it should be uninstalled before ``ppft`` is installed -- otherwise, ``import pp`` will likely not find the ``ppft`` fork.\n\n\nMajor Changes:\n==============\n\n    - ``pip`` and ``setuptools`` support\n    - support for python 3\n    - enhanced serialization, using ``dill.source``\n\n\nCurrent Release\n===============\n\nThis documentation is for version ``ppft-1.6.6.1`` (a fork of ``pp-1.6.6``).\n\nThe latest released version of ``ppft`` is available from::\n\n    https://pypi.org/project/ppft\n\n``pp`` and ``ppft`` are distributed under a BSD-like license.\n\n\nDevelopment Version\n===================\n\nYou can get the latest development version with all the shiny new features at::\n\n    https://github.com/uqfoundation\n\nIf you have a new contribution, please submit a pull request.\n\n\nInstallation\n============\n\n``ppft`` is packaged to install from source, so you must\ndownload the tarball, unzip, and run the installer::\n\n    [download]\n    $ tar -xvzf ppft-1.6.6.1.tgz\n    $ cd ppft-1.6.6.1\n    $ python setup.py build\n    $ python setup.py install\n\nYou will be warned of any missing dependencies and/or settings\nafter you run the \"build\" step above.\n\nAlternately, ``ppft`` can be installed with ``pip`` or ``easy_install``::\n\n    $ pip install ppft\n\nNOTE: ``ppft`` installs as ``pp``. If ``pp`` is installed, it should be uninstalled before ``ppft`` is installed -- otherwise, ``import pp`` will likely not find the ``ppft`` fork.\n\n\nRequirements\n============\n\n``ppft`` requires::\n\n    - ``python``, **version >= 2.6** or **version >= 3.1**, or ``pypy``\n    - ``six``, **version >= 1.7.3**\n\nOptional requirements::\n\n    - ``setuptools``, **version >= 0.6**\n    - ``dill``, **version >= 0.3.0**\n\n\nMore Information\n================\n\nProbably the best way to get started is to look at the set of example scripts\nin ``ppft.examples``. You can run the test suite with ``python -m ppft.tests``.\n``ppft`` will create and execute jobs on local workers (automatically created\nusing ``python -u -m ppft``). Additionally, remote servers can be created with \n``ppserver`` (or ``python -m ppft.server``), and then jobs can be distributed\nto remote workers. See ``--help`` for more details on how to configure a server.\nPlease feel free to submit a ticket on github, or ask a question on\nstackoverflow (**@Mike McKerns**).  If you would like to share how you use\n``ppft`` in your work, please send an email (to **mmckerns at uqfoundation dot org**).\n\n\nCitation\n========\n\nIf you use ``ppft`` to do research that leads to publication, we ask that you\nacknowledge use of ``ppft`` by citing the following in your publication::\n\n    M.M. McKerns, L. Strand, T. Sullivan, A. Fang, M.A.G. Aivazis,\n    \"Building a framework for predictive science\", Proceedings of\n    the 10th Python in Science Conference, 2011;\n    http://arxiv.org/pdf/1202.1056\n\n    Michael McKerns and Michael Aivazis,\n    \"pathos: a framework for heterogeneous computing\", 2010- ;\n    http://trac.mystic.cacr.caltech.edu/project/pathos\n\nPlease see http://trac.mystic.cacr.caltech.edu/project/pathos or\nhttp://arxiv.org/pdf/1202.1056 for further information.",
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