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setup.py
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setup.py
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import pathlib
from setuptools import setup,find_packages
package_name='UniFunc'
def get_package_version():
import os
from sys import platform
if platform.startswith('win'):
SPLITTER = '\\'
else:
SPLITTER = '/'
dir_name=os.path.dirname(os.path.abspath(__file__))
init_path=f'{dir_name}{SPLITTER}{package_name.lower()}{SPLITTER}__init__.py'
package_version=None
with open(init_path) as file:
for line in file:
if '__version__' in line:
package_version=line.replace('__version__','')
package_version=package_version.strip('\n')
package_version=package_version.strip()
package_version=package_version.strip('=')
package_version=package_version.strip()
package_version=package_version.strip('"')
package_version=package_version.strip('"')
return package_version
# The directory containing this file
HERE = pathlib.Path(__file__).parent
# The text of the README file
README = (HERE / "README.md").read_text(encoding='utf-8')
long_description='UniFunc is a text mining tool that processes and analysis text similarity between a pair of protein function annotations. It is mainly used as a cross-linking mechanism or redundancy elimination tool when processing annotations without any sort of database identifiers.'
setup(
name=package_name,
version=get_package_version(),
author="Pedro Queirós",
author_email="[email protected]",
description="Tool for similarity analysis of protein function annotations.",
long_description=long_description,
long_description_content_type='text/markdown',
url="https://github.com/PedroMTQ/UniFunc",
project_urls={
"Bug Tracker": "https://github.com/PedroMTQ/UniFunc/issues",
},
packages=find_packages(),
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
license="MIT",
include_package_data=True,
package_data={
'myapp': ['data/*.txt'],
},
install_requires=['nltk','numpy','requests'],
entry_points={
"console_scripts": [
"unifunc=unifunc.__main__:main",
],
},
)