{ "info": { "author": "Simon Dobson", "author_email": "simon.dobson@computer.org", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering" ], "description": "epyc: Python computational experiment management\n================================================\n\nOverview\n--------\n\n``epyc`` is a Python module for controlling a long-running series of\ncomputational experiments, as is often found when writing simulations\nof complex networks and other such domains. There is often a need to\nperform a computation across a multi-dimensional parameter space,\nvarying the parameters, performing and aggregating multiple\nrepetitions, and wrangling results for analysis and\npresentation. Often the experiments being performed are on such a\nscale as to require the use of a computing cluster to perform multiple\nexperiments simultaneously.\n\nManaging all these tasks is complicated, so ``epyc`` tries to automate\nit. It provides a way to define a \"laboratory\" performing a collection\nof \"experiments\" whose parameters and results are recorded in a \"lab\nnotebook\" for later retrieval. Laboratories can be sequential (for a\nsingle machine) or parallel (to use a multicore or cluster of\nmachines); lab notebooks can be persistent to allow experiments to be\nfired-off and their results retrieved later -- handy if you use a\nlaptop. Notebooks store all the data and metadata in a portable format\nto improve the reproducibility of computational experiments. \n\n``epyc`` also includes a small number of \"experiment combinators\" that\nseparate the logic of a single experiment from the logic of performing\nmultiple repetitions and other structuring tasks. This means that\nany experiment can be repeated and statistically summarised, for\nexample.\n\n\nInstallation\n------------\n\n``epyc`` works with both Python 2.7 and Python 3. You can install it directly from PyPi using ``pip``:\n\n::\n\n pip install epyc\n\nThe master distribution of ``epyc`` is hosted on GitHub. 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