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        "description": "============\nRunningCalcs\n============\n--------------------------------------------\nA library for executing running calculations\n--------------------------------------------\n\nIntroduction\n============\n\nInstances of the ``RunnincCalc`` classes in this library can be fed one input value at a time. This allows running several calculations in a single pass over an iterator. This isn't possible with the built-in variants of most calculations, such as ``max()`` and ``heapq.nlargest()``.\n\n``RunningCalc`` instances can be fed values directly, for example::\n\n    mean_rc, stddev_rc = RunningMean(), RunningStdDev()\n    for x in values:\n        mean_rc.feed(x)\n        stddev_rc.feed(x)\n    mean, stddev = mean_rc.value, stddev_rc.value\n\nAdditionally, the ``apply_in_parallel()`` function is supplied, which makes performing several calculations in parallel easy (and fast!). For example::\n\n    mean, stddev = apply_in_parallel([RunningMean(), RunningStdDev()], values)\n    five_smallest, five_largest = apply_in_parallel([RunningNSmallest(5), RunningNLargest(5)], values)\n\nOptimizations\n=============\nIn addition to the basic ``feed()`` method, some ``RunningCalc`` classes also implement an optimized ``feedMultiple()`` method, which accepts a sequence of values to be processed. This allows values to be processed in chunks, allowing for faster processing in many cases.\n\nThe ``apply_in_parallel()`` function automatically splits the given iterable of input values into chunks (chunk size can be controlled via the ``chunk_size`` keyword argument). Therefore using ``apply_in_parallel()`` is both fast and easy.\n\nWriting Your Own RunningCalc Class\n==================================\n1. sub-class ``RunningCalc``\n2. implement the ``__init__()`` and ``feed()`` methods\n3. make the calculation output value accessible via the ``value`` attribute\n4. optionally implement an optimized ``feedMultiple()`` method\n   Note: the ``RunningCalc`` base class includes a default naive implementation of ``feedMultiple()``",
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