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setup.py
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setup.py
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import re
import io
import os
from setuptools import setup, find_packages
with open('requirements.txt') as f:
requirements = f.read()
with open('README.md') as f:
readme = f.read()
# Read the version from the __init__.py file without importing it
def read(*names, **kwargs):
with io.open(
os.path.join(os.path.dirname(__file__), *names),
encoding=kwargs.get("encoding", "utf8")
) as fp:
return fp.read()
def find_version(*file_paths):
version_file = read(*file_paths)
version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]",
version_file, re.M)
if version_match:
return version_match.group(1)
raise RuntimeError("Unable to find version string.")
setup(
name='buildings_bench',
version=find_version('buildings_bench', '__init__.py'),
description='Large-scale pretraining and benchmarking for short-term load forecasting.',
author='Patrick Emami',
author_email='Patrick.Emami@nrel.gov',
url="https://nrel.github.io/BuildingsBench/",
long_description=readme,
long_description_content_type='text/markdown',
install_requires=requirements,
packages=find_packages(include=['buildings_bench',
'buildings_bench.data',
'buildings_bench.evaluation',
'buildings_bench.models'],
exclude=['test']),
package_data={'buildings_bench': ['configs/*.toml']},
license='BSD 3-Clause',
python_requires='>=3.8',
extras_require={
'benchmark': ['wandb', 'properscoring', 'matplotlib', 'seaborn', 'jupyterlab']
},
keywords=['forecasting', 'energy', 'buildings', 'benchmark'],
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: BSD License",
"Natural Language :: English",
"Programming Language :: Python :: 3",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
]
)