hyperopt

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import re
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import setuptools
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with open("hyperopt/__init__.py", encoding="utf8") as f:
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    version = re.search(r"__version__ = \"(.*?)\"", f.read()).group(1)
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    if version is None:
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        raise ImportError("Could not find __version__ in hyperopt/__init__.py")
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setuptools.setup(
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    name="hyperopt",
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    version=version,
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    packages=setuptools.find_packages(include=["hyperopt*"]),
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    entry_points={"console_scripts": ["hyperopt-mongo-worker=hyperopt.mongoexp:main"]},
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    url="https://hyperopt.github.io/hyperopt",
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    project_urls={
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        "Source": "https://github.com/hyperopt/hyperopt",
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    },
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    author="James Bergstra",
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    author_email="james.bergstra@gmail.com",
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    description="Distributed Asynchronous Hyperparameter Optimization",
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    long_description="",
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    classifiers=[
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        "Development Status :: 3 - Alpha",
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        "Intended Audience :: Education",
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        "Intended Audience :: Science/Research",
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        "Intended Audience :: Developers",
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        "Environment :: Console",
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        "License :: OSI Approved :: BSD License",
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        "Operating System :: MacOS :: MacOS X",
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        "Operating System :: Microsoft :: Windows",
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        "Operating System :: POSIX",
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        "Operating System :: Unix",
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        "Programming Language :: Python",
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        "Programming Language :: Python :: 3",
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        "Programming Language :: Python :: 3 :: Only",
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        "Programming Language :: Python :: 3.7",
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        "Topic :: Scientific/Engineering",
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        "Topic :: Software Development",
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    ],
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    platforms=["Linux", "OS-X", "Windows"],
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    license="BSD",
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    keywords="Bayesian optimization hyperparameter model selection",
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    include_package_data=True,
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    requires_python=">=3.7",
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    install_requires=[
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        "numpy>=1.17",
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        "scipy",
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        "networkx>=2.2",
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        "tqdm",
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        "cloudpickle",
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    ],
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    extras_require={
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        "SparkTrials": ["pyspark", "py4j"],
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        "MongoTrials": "pymongo>=4.0.0",
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        "ATPE": ["lightgbm", "scikit-learn"],
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        "dev": ["black", "pre-commit", "nose", "pytest"],
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    },
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    tests_require=["nose", "pytest"],
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    zip_safe=False,
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)
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