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setup.py
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setup.py
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from setuptools import setup
setup(
name="text-fabric",
packages=[
"tf",
"tf.about",
"tf.advanced",
"tf.client",
"tf.client.make",
"tf.convert",
"tf.core",
"tf.dataset",
"tf.search",
"tf.server",
"tf.volumes",
"tf.writing",
],
install_requires=[
"wheel",
"rpyc",
"flask",
"psutil",
"markdown",
"ipython",
"requests",
"pygithub>=1.47",
"pyyaml>=5.3",
],
python_requires=">=3.6.3",
include_package_data=True,
exclude_package_data={
"": ["text_fabric.egg-info", "__pycache__", ".DS_Store", "docs"]
},
zip_safe=False,
entry_points={
"console_scripts": [
"text-fabric = tf.server.start:main",
"text-fabric-zip = tf.advanced.zipdata:main",
"text-fabric-make = tf.client.make.build:main",
]
},
version='9.1.3',
description="""Processor and browser for Text Fabric Data""",
author="Dirk Roorda",
author_email="dirk.roorda@dans.knaw.nl",
url="https://github.com/annotation/text-fabric",
keywords=[
"text",
"linguistics",
"database",
"graph",
"hebrew",
"bible",
"peshitta",
"quran",
"cuneiform",
"uruk",
"greek",
"syriac",
"akkadian",
"babylonian",
],
classifiers=[
"Development Status :: 4 - Beta",
"Environment :: Other Environment",
"Framework :: Jupyter",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Religion",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Natural Language :: English",
"Natural Language :: Hebrew",
"Natural Language :: Greek",
"Operating System :: MacOS :: MacOS X",
"Operating System :: Microsoft :: Windows :: Windows 10",
"Operating System :: POSIX :: Linux",
"Programming Language :: Python :: 3 :: Only",
"Programming Language :: Python :: Implementation :: CPython",
"Programming Language :: JavaScript",
"Topic :: Religion",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Sociology :: History",
"Topic :: Text Processing :: Filters",
"Topic :: Text Processing :: Linguistic",
"Topic :: Text Processing :: Markup",
],
long_description="""\
Tools to read text corpora with (linguistic) annotations
and process them efficiently.
With a built in web-interface for querying a corpus.
More info on https://annotation.github.io/text-fabric/tf
""",
)