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        "author": "Phillip Schanely",
        "author_email": "pschanely+vE7F@gmail.com",
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            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.2",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Libraries"
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        "description": "===============\nScenic Overlook\n===============\n\nThe Scenic Overlook library contains datastructures for incremental\nmap-reduces.\n\nThese datastructures are implemented as trees, and store at each node,\nintermediate values of the reduce. This means that when you slice or combine\nstructures, the new output of the maps/reduces can be efficiently computed.\n(by reusing old outputs from unchanged parts of the tree)\n\nTypical usage looks like this::\n\n    #!/usr/bin/env python\n\n    from scenicoverlook import viewablelist\n\n    space_concat = lambda x, y: x + ' ' + y\n    l = viewablelist(['the', 'quick', 'brown', 'fox'])\n    print l.reduce(space_concat)\n\n    # This yields 'the quick stealthy brown fox', reusing cached intermediate\n    # substrings from the earlier call like 'the quick' and 'brown fox':\n\n    print (l[:2] + ['stealthy'] + l[2:]).reduce(space_concat)\n\n\nSee the pydocs for more examples:\n\nhttps://github.com/pschanely/ScenicOverlook/blob/master/scenicoverlook/__init__.py\n\n\n",
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        "keywords": "algorithms datastructures",
        "license": "BSD (3 clause)",
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        "name": "ScenicOverlook",
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        "summary": "A library for incremental, in-memory map-reduces",
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