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        "author": "Jim Crist",
        "author_email": "jiminy.crist@gmail.com",
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        "description": "ptime\n=====\n\nA tool for measuring serial and parallel execution, and comparing the results.\nProvides an `IPython magic\n<http://ipython.readthedocs.io/en/stable/interactive/magics.html>`_ ``%ptime``.\nThis can be useful for measuring the benefits of parallelizing code, including\nmeasuring the effect of the `Global Interpreter Lock\n<https://wiki.python.org/moin/GlobalInterpreterLock>`_ (GIL).\n\nExample\n-------\n\n.. code::\n\n    In [1]: %load_ext ptime\n\n    In [2]: import numpy as np\n\n    In [3]: x = np.ones((5000, 10000))\n\n    In [4]: %ptime x + x\n    Total serial time:   0.42 s\n    Total parallel time: 0.25 s\n    For a 1.67X speedup across 2 threads\n\n    In [5]: %ptime -n4 x + x  # use 4 threads\n    Total serial time:   0.82 s\n    Total parallel time: 0.31 s\n    For a 2.60X speedup across 4 threads\n\n    In [6]: res = %ptime -o x + x  # Get the result\n    Total serial time:   0.41 s\n    Total parallel time: 0.25 s\n    For a 1.66X speedup across 2 threads\n\n    In [7]: res.speedup\n    Out[7]: 1.6610825669011922\n\n    In [8]: %%ptime  # Use as a cell magic\n    ...: x = np.ones((5000, 10000))\n    ...: y = x + x\n    ...:\n    Total serial time:   0.72 s\n    Total parallel time: 0.47 s\n    For a 1.54X speedup across 2 threads\n\nInstall\n-------\n\nThis package is available via pip:\n\n.. code::\n\n    pip install ptime\n",
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        "license": "BSD",
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