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        "description": "=======\ntart.py\n=======\n\nPython implementation of the `Actor Model`_ inspired from `tart.js`_.\n\nOverview\n========\n\nThe initial ideas for ``tartpy`` are copied from `@dalnefre`_ and\n`@tristanls`_.  At the beginning, the goal was to replicate `tart.js`_\nin Python.  Lately, it has diverged slightly, to experiment with the\nnew Python asynchrony model introduced in version 3.4.\n\n``tartpy`` aims to be an actor library with the following features:\n\n- it implements the pure actor model (rather than the Erlang model),\n\n- it can be used in practical situations to express lock-free and\n  concurrent algorithms,\n\n- it abstracts the network transport to allow arbitrary protocols,\n\n- it implements a `capability based approach`_ to isolate actors,\n  using membranes (again, the ideas are due to `@dalnefre`_ and\n  `@tristanls`_).  The semantics of membranes may differ between\n  ``tartpy`` and ``tartjs``.\n\nInstalling\n==========\n\nInstall with::\n\n    $ pip install git+https://github.com/waltermoreira/tartpy\n\nor clone this repository and install with ``python3 setup.py install``::\n\n    $ git clone https://github.com/waltermoreira/tartpy\n    $ cd tartpy\n    $ python3 setup.py install\n\nTest\n====\n\nRun tests with::\n\n    $ python3 setup.py test\n\n\nExamples\n========\n\nRun example with:\n\n.. code-block:: bash\n\n   python3 tartpy/example.py\n\nThere is also an `IPython notebook`_ showing the basic properties of actors.\n\nThe project `actor_model`_ contains slides and IPython notebooks from\na talk presented at TACC_ in April 17, 2014.\n\n\nErlang Challenge\n================\n\nCreate a ring of ``M`` actors, sending ``N`` messages around the ring:\n\n.. code-block:: bash\n\n   python3 tartpy/erlang_challenge.py M N\n\nBenchmarks\n----------\n\nFor ``M = 100000`` and ``N = 10``::\n\n    Starting 100000 actor ring\n    Construction time: 1.5192079544067383 seconds\n    Loop times:\n      0.7743091583251953 seconds\n      0.7793149948120117 seconds\n      0.7702958583831787 seconds\n      0.7602570056915283 seconds\n      0.7704610824584961 seconds\n      0.779731035232544 seconds\n      0.7654228210449219 seconds\n      0.7625432014465332 seconds\n      0.7740719318389893 seconds\n      0.7699680328369141 seconds\n    Average: 0.7706375122070312 seconds\n\n.. _Actor Model: http://en.wikipedia.org/wiki/Actor_model\n.. _tart.js: https://github.com/organix/tartjs\n.. _@dalnefre: https://github.com/dalnefre\n.. _@tristanls: https://github.com/tristanls\n.. _capability based approach: http://en.wikipedia.org/wiki/Capability-based_security\n.. _IPython notebook: http://nbviewer.ipython.org/github/waltermoreira/tartpy/blob/master/demo/tartpy_demo.ipynb\n.. _actor_model: https://github.com/waltermoreira/actor_model\n.. _TACC: https://www.tacc.utexas.edu/",
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