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    "info": {
        "author": "Berry Schoenmakers",
        "author_email": "berry@win.tue.nl",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Environment :: Console",
            "Framework :: AsyncIO",
            "Framework :: Jupyter",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Information Technology",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: Apache Software License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Security :: Cryptography",
            "Topic :: Software Development :: Libraries :: Application Frameworks",
            "Topic :: Software Development :: Libraries :: Python Modules",
            "Topic :: System :: Distributed Computing"
        ],
        "description": "# MPyC <img align=\"center\" width=40 src=\"images/MPyC_Logo.png\"> Secure Multiparty Computation in Python\n\nMPyC supports secure *m*-party computation tolerating a dishonest minority of up to *t* passively corrupt parties,\nwhere *m &ge; 1* and *0 &le; t &le; (m-1)/2*. The underlying protocols are based on threshold secret sharing over finite\nfields (using Shamir's threshold scheme as well as pseudorandom secret sharing).\n\nThe details of the secure computation protocols are mostly transparent due to the use of sophisticated operator overloading\ncombined with asynchronous evaluation of the associated protocols.\n\nSee [MPyC homepage](https://www.win.tue.nl/~berry/mpyc/) for more info and background, and quick links to try MPyC without any install.\n\n## Example installs:\n\n`python setup.py install`\n\n`python setup.py install --user`\n\nSee `demos` for usage examples.\n\n## Notes:\n\n1. Python 3.6+ (Python 3.5 or lower is not sufficient).\n\n2. Installing package `gmpy2` is optional, but will considerably enhance the performance of `mpyc`.\nOn Linux, `pip install gmpy2` should do the job, but on Windows, this may fail with compiler errors.\nFortunately, ready-to-go Python wheels for `gmpy2` can be downloaded from Christoph Gohlke's excellent\n[Unofficial Windows Binaries for Python Extension Packages](https://www.lfd.uci.edu/~gohlke/pythonlibs/) webpage.\nUse, for example, `pip install gmpy2-2.0.8-cp36-cp36m-win_amd64.whl` to finish installation.\n\n3. Use `run-all.sh` or `run-all.bat` in the `demos` directory to have a quick look at some demos. \nAlso note the example Windows batch files in the `docs` and `tests` directories.\n\n4. Directory `demos\\.config` contains configuration info used to run MPyC with multiple parties. Also, \nWindows batch file 'gen.bat' shows how to generate fresh key material for SSL. OpenSSL is required to generate \nSSL key material of your own, use `pip install pyOpenSSL`.\n\n5. To use the [Jupyter](https://jupyter.org/) notebooks `demos\\*.ipynb`, you need to have Jupyter installed,\ne.g., using `pip install jupyter`. The latest version of Jupyter will come with IPython 7.0+, which supports\ntop-level `await`. Instead of `mpc.run(mpc.start())` one can now simply write `await mpc.start()` anywhere in\na notebook cell, even outside a coroutine.\n\nCopyright &copy; 2018-2019 Berry Schoenmakers\n\n\n",
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        "home_page": "https://github.com/lschoe/mpyc",
        "keywords": "crypto,cryptography,multiparty computation,MPC,secret sharing,Shamir threshold scheme,pseudorandom secret sharing,PRSS",
        "license": "Apache License 2.0",
        "maintainer": "",
        "maintainer_email": "",
        "name": "mpyc",
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        "summary": "MPyC -- Secure Multiparty Computation in Python",
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