cap/setup.py at main · via-cs/cap · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
#!/usr/bin/env python
# -*- coding: utf-8 -*-

from setuptools import setup, find_packages

try:
    with open('README.md', encoding='utf-8') as readme_file:
        readme = readme_file.read()
except IOError:
    readme = ''

def load_requirements(filename):
    with open(filename) as f:
        return [line.strip() for line in f if line.strip() and not line.startswith('#')]

install_requires = [
    'torch>=2.0.0',
    'numpy>=1.19.0',
    'pandas>=1.2.0',
    'scikit-learn>=0.24.0',
    'matplotlib>=3.3.0',
    'tqdm>=4.50.0',
]

tests_require = [
    'pytest>=6.0.0',
    'pytest-cov>=2.10.0',
]

development_requires = [
    # general
    'pip>=21.0.0',
    'wheel>=0.37.0',

    # style check
    'flake8>=3.9.0',
    'isort>=5.9.0',
    'autopep8>=1.5.7',

    # docs
    'Sphinx>=4.0.0',
    'sphinx-rtd-theme>=1.0.0',

    # testing
    'coverage>=6.0.0',
]

setup(
    name='catf',
    author="anonymous",
    author_email='xxx',
    classifiers=[
        'Development Status :: 3 - Alpha',
        'Intended Audience :: Science/Research',
        'License :: OSI Approved :: MIT License',
        'Natural Language :: English',
        'Programming Language :: Python :: 3',
        'Programming Language :: Python :: 3.8',
        'Programming Language :: Python :: 3.9',
        'Programming Language :: Python :: 3.10',
        'Programming Language :: Python :: 3.11',
        'Topic :: Scientific/Engineering :: Artificial Intelligence',
    ],
    description="CATF: A Manager-Worker Framework for Context-Aware Multivariate Time-Series Forecasting",
    entry_points={
        'console_scripts': [
            'cap=cap.__main__:main'
        ]
    },
    extras_require={
        'test': tests_require,
        'dev': development_requires + tests_require,
    },
    include_package_data=True,
    install_requires=install_requires,
    keywords=['Time-series Forecasting', 'Context-aware Learning', 'Multivariate Time-series', 'Training Algorithm', 'Manager-Worker Architecture', 'Deep Learning'],
    license="MIT license",
    long_description=readme,
    long_description_content_type='text/markdown',
    packages=find_packages(include=['cap', 'cap.*']),
    python_requires='>=3.8,<3.13',
    test_suite='tests',
    tests_require=tests_require,
    url='xxx',
    version='0.7.1.dev0',
    zip_safe=False,
)