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# Always prefer setuptools over distutils
import re
from setuptools import setup, find_packages
# To use a consistent encoding
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
# read the version from stanza/_version.py
version_file_contents = open(path.join(here, 'stanza/_version.py'), encoding='utf-8').read()
VERSION = re.compile('__version__ = \"(.*)\"').search(version_file_contents).group(1)
# Get the long description from the README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='stanza',
# Versions should comply with PEP440. For a discussion on single-sourcing
# the version across setup.py and the project code, see
# https://packaging.python.org/en/latest/single_source_version.html
version=VERSION,
description='A Python NLP Library for Many Human Languages, by the Stanford NLP Group',
long_description=long_description,
long_description_content_type="text/markdown",
# The project's main homepage.
url='https://github.com/stanfordnlp/stanza',
# Author details
author='Stanford Natural Language Processing Group',
author_email='jebolton@stanford.edu',
# Choose your license
license='Apache License 2.0',
# See https://pypi.python.org/pypi?%3Aaction=list_classifiers
classifiers=[
# How mature is this project? Common values are
# 3 - Alpha
# 4 - Beta
# 5 - Production/Stable
'Development Status :: 4 - Beta',
# Indicate who your project is intended for
'Intended Audience :: Developers',
'Intended Audience :: Education',
'Intended Audience :: Science/Research',
'Intended Audience :: Information Technology',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Scientific/Engineering :: Information Analysis',
'Topic :: Text Processing',
'Topic :: Text Processing :: Linguistic',
'Topic :: Software Development',
'Topic :: Software Development :: Libraries',
# Specify the Python versions you support here. In particular, ensure
# that you indicate whether you support Python 2, Python 3 or both.
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
],
# What does your project relate to?
keywords='natural-language-processing nlp natural-language-understanding stanford-nlp deep-learning',
# You can just specify the packages manually here if your project is
# simple. Or you can use find_packages().
packages=find_packages(exclude=['data', 'docs', 'extern_data', 'figures', 'saved_models']),
# List run-time dependencies here. These will be installed by pip when
# your project is installed. For an analysis of "install_requires" vs pip's
# requirements files see:
# https://packaging.python.org/en/latest/requirements.html
install_requires=['emoji', 'numpy', 'protobuf', 'requests', 'six', 'torch>=1.3.0', 'tqdm'],
# List required Python versions
python_requires='>=3.6',
# List additional groups of dependencies here (e.g. development
# dependencies). You can install these using the following syntax,
# for example:
# $ pip install -e .[dev,test]
extras_require={
'dev': ['check-manifest'],
'test': ['coverage', 'pytest'],
},
# If there are data files included in your packages that need to be
# installed, specify them here. If using Python 2.6 or less, then these
# have to be included in MANIFEST.in as well.
package_data={
"": ["*.pl"],
},
include_package_data=True,
# Although 'package_data' is the preferred approach, in some case you may
# need to place data files outside of your packages. See:
# http://docs.python.org/3.4/distutils/setupscript.html#installing-additional-files # noqa
# In this case, 'data_file' will be installed into '<sys.prefix>/my_data'
data_files=[],
# To provide executable scripts, use entry points in preference to the
# "scripts" keyword. Entry points provide cross-platform support and allow
# pip to create the appropriate form of executable for the target platform.
entry_points={
},
)
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