/
setup.py
139 lines (127 loc) · 3.31 KB
/
setup.py
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import os
import sys
from setuptools import find_packages, setup
from setuptools.command.develop import develop
from setuptools.command.egg_info import egg_info
from setuptools.command.install import install
# Histolab has a dependency that requires options
histolab_dep_commands = [
sys.executable, # the python interpreter (needed to install in the right pipenv)
"-m",
"pip",
"install",
"large-image-source-openslide",
"--find-links",
"https://girder.github.io/large_image_wheels",
]
class CustomInstallCommand(install):
def run(self):
install.run(self)
os.system(" ".join(histolab_dep_commands))
class CustomDevelopCommand(develop):
def run(self):
develop.run(self)
os.system(" ".join(histolab_dep_commands))
class CustomEggInfoCommand(egg_info):
def run(self):
egg_info.run(self)
os.system(" ".join(histolab_dep_commands))
# datasets has a dependency that requires options
camelyon16 = [
"google-api-python-client",
"google-auth-httplib2",
"google-auth-oauthlib",
"histolab",
"openslide-python",
"requests",
"transformers",
]
heart = ["wget"]
isic2019 = ["albumentations", "efficientnet-pytorch", "requests", "wget"]
ixi = ["monai", "nibabel"]
kits19 = ["batchgenerators", "nibabel==3.2.2", "nnunet==1.7.0"]
lidc = [
"dask",
"dicom-numpy",
"networkx",
"nibabel==3.2.2",
"pydicom",
"scipy",
"scikit-image",
]
tcga = ["lifelines"]
docs = [
"albumentations",
"batchgenerators",
"dask",
"dicom-numpy",
"efficientnet-pytorch",
"google-api-python-client",
"google-auth-httplib2",
"google-auth-oauthlib",
"histolab",
"lifelines",
"matplotlib",
"monai",
"nnunet==1.7.0",
"pydicom",
"requests",
"scipy",
"sphinx",
"sphinx-rtd-theme",
]
tests = ["albumentations", "pytest"]
all_extra = camelyon16 + heart + isic2019 + ixi + kits19 + lidc + tcga + docs + tests
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setup(
name="flamby",
version="0.0.1",
python_requires=">=3.8.0",
license="MIT",
classifiers=[
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Intended Audience :: Science/Research",
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
],
install_requires=[
"argparse",
"numpy",
"pandas",
"pre-commit",
"scikit-learn",
"scipy",
"seaborn",
"setuptools>=65.5.1",
"tensorboard",
"torch>=1.13.1",
"torchvision",
"tqdm",
"umap-learn",
"opacus",
],
extras_require={
"cam16": camelyon16,
"heart": heart,
"isic2019": isic2019,
"ixi": ixi,
"kits19": kits19,
"lidc": lidc,
"tcga": tcga,
"all_extra": all_extra,
"docs": docs,
"tests": tests,
},
description="FLamby: A cross-silo Federated Learning Benchmark.",
long_description=long_description,
author="FL-datasets team",
author_email="unknown",
packages=find_packages(),
include_package_data=True,
cmdclass={
"install": CustomInstallCommand,
"develop": CustomDevelopCommand,
"egg_info": CustomEggInfoCommand,
},
)