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        "author": "Remi Rampin",
        "author_email": "remi.rampin@nyu.edu",
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            "Development Status :: 3 - Alpha",
            "Environment :: Console",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Programming Language :: Python",
            "Programming Language :: SQL",
            "Programming Language :: Unix Shell",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development :: Build Tools",
            "Topic :: Software Development :: Interpreters",
            "Topic :: Text Processing :: Markup",
            "Topic :: Utilities"
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        "description": "CacheFlow\n=========\n\nCacheFlow is a caching workflow engine, capable of executing dataflows while\nreusing previous results where appropriate, for efficiency. It is very\nextensible and can be used in many projects.\n\nGoals\n-----\n\n* \u2611  Python 3 workflow system\n* \u2611 Executes dataflows from JSON files\n* \u2610 Can also load from SQL database\n* \u2610 Parallel execution\n* \u2610 Streaming\n* \u2611 Extensible: can add new modules, new storage formats, new caching mechanism, new executors\n* \u2610 Pluggable: extensions can be installed from PyPI without forking\n* \u2611 Re-usable: can execute workflows by itself, but can also be embedded into applications. Some I plan on developing myself:\n\n  * Literate programming app: snippets or modules embedded into a markdown file, which are executed on render (similar to Rmarkdown). Results would be cached, making later rendering fast\n  * Integrate in some of my NYU research projects (VisTrails Vizier, D3M)\n\nOther ideas:\n\n* \u2610 Use Jupyter kernels as backends to execute code (giving me quick access to all the languages they support)\n* \u2610 Isolate script execution (to run untrusted Python/... code, for example with Docker)\n\nNon-goals\n---------\n\n* Make a super-scalable and fast workflow execution engine: I'd rather make executors based on Spark, Dask, Ray than re-implement those\n\nStatus\n------\n\nBasic structures are here, extracted from D3M. Execution works.\n\n\n",
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        "license": "BSD-3-Clause",
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