#!/usr/bin/env python

"""
A setuptools based setup module.
See:
- https://packaging.python.org/en/latest/distributing.html
- https://github.com/pypa/sampleproject
To install:
1. Setup pypi by creating ~/.pypirc
        [distutils]
        index-servers =
          pypi
          pypitest
        [pypi]
        username=
        password=
        [pypitest]
        username=
        password=
2. Create the dist
   python3 setup.py sdist bdist_wheel
3. Push
   twine upload dist/*
"""

import os
import re

# Always prefer setuptools over distutils
from setuptools import setup, find_packages


ROOT = os.path.dirname(__file__)


def get_version():
    """
    Reads the version from ersatz's __init__.py file.
    We can't import the module because required modules may not
    yet be installed.
    """
    VERSION_RE = re.compile(r'''__version__ = ['"]([0-9.]+)['"]''')
    init = open(os.path.join(ROOT, 'ersatz', '__init__.py')).read()
    return VERSION_RE.search(init).group(1)


def get_description():
    DESCRIPTION_RE = re.compile(r'''__description__ = ['"](.*)['"]''')
    init = open(os.path.join(ROOT, 'ersatz', '__init__.py')).read()
    return DESCRIPTION_RE.search(init).group(1)


setup(
    name = 'ersatz',

    # 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 = get_version(),

    description = get_description(),

    long_description = "Ersatz is a simple, language-agnostic toolkit for both training sentence segmentation models as well as providing pretrained, "
                       "high-performing models for sentence segmentation in a multilingual setting.",

    # The project's main homepage.
    url = 'https://github.com/rewicks/ersatz',

    author = 'Rachel Wicks',
    author_email='rewicks@jhu.edu',
    maintainer_email='rewicks@jhu.edu',

    license = 'Apache License 2.0',

    python_requires = '>=3',

    # 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 :: 5 - Production/Stable',

        # Indicate who your project is intended for
        'Intended Audience :: Developers',
        'Intended Audience :: Science/Research',
        'Topic :: Scientific/Engineering',
        'Topic :: Scientific/Engineering :: Artificial Intelligence',
        'Topic :: Text Processing',

        # Pick your license as you wish (should match "license" above)
        'License :: OSI Approved :: Apache Software License',

        # 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 :: Only',
    ],

    # What does your project relate to?
    keywords = ['sentence segmenation, data processing, preprocessing, evaluation, NLP, natural language processing, computational linguistics'],

    # Which packages to deploy (currently sacrebleu, sacrebleu.matrics and sacrebleu.tokenizers)?
    packages = find_packages(),

    # Mark ersatz (and recursively all its sub-packages) as supporting mypy type hints (see PEP 561).
    package_data={"ersatz": ["py.typed"]},

    # 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 = [
        'typing;python_version<"3.5"',
        'torch==1.7.1',
        'sentencepiece==0.1.95',
        'tensorboard==2.4.1',
        'progressbar2'
    ],

    # 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 = {},

    # 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={
        'console_scripts': [
            'ersatz = ersatz.split:main',
            'ersatz_train = ersatz.trainer:main',
            'ersatz_score = ersatz.score:main',
            'ersatz_preprocess = ersatz.dataset:main'
        ],
    },
)
