eland/setup.py
David Kyle b507bb6d6c
Restrict NumPy and Pandas versions (#539)
Shap is incompatible with NumPy 1.24 due to a deprecated usage becoming
an error. There is no fix in Shap yet so an earlier version of NumPy must
be used.
Pandas 2.0 was recently released we will continue to use the latest 1.5 release 
to avoid any incompatibilities.
2023-05-19 16:04:33 +01:00

97 lines
3.2 KiB
Python

# Licensed to Elasticsearch B.V. under one or more contributor
# license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright
# ownership. Elasticsearch B.V. licenses this file to you under
# the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
# flake8: noqa
from codecs import open
from os import path
from setuptools import find_packages, setup
here = path.abspath(path.dirname(__file__))
about = {}
with open(path.join(here, "eland", "_version.py"), "r", "utf-8") as f:
exec(f.read(), about)
CLASSIFIERS = [
"Development Status :: 5 - Production/Stable",
"License :: OSI Approved :: Apache Software License",
"Environment :: Console",
"Operating System :: OS Independent",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"Operating System :: OS Independent",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3 :: Only",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Topic :: Scientific/Engineering",
]
# Remove all raw HTML from README for long description
with open(path.join(here, "README.md"), "r", "utf-8") as f:
lines = f.read().split("\n")
last_html_index = 0
for i, line in enumerate(lines):
if line == "</p>":
last_html_index = i + 1
long_description = "\n".join(lines[last_html_index:])
extras = {
"xgboost": ["xgboost>=0.90,<2"],
"scikit-learn": ["scikit-learn>=0.22.1,<2"],
"lightgbm": ["lightgbm>=2,<4"],
"pytorch": [
"torch>=1.11.0,<1.12.0",
"sentence-transformers>=2.1.0,<=2.2.2",
"transformers[torch]>=4.12.0,<=4.20.1",
],
}
extras["all"] = list({dep for deps in extras.values() for dep in deps})
setup(
name=about["__title__"],
version=about["__version__"],
description=about["__description__"],
long_description=long_description,
long_description_content_type="text/markdown",
url=about["__url__"],
author=about["__author__"],
author_email=about["__author_email__"],
maintainer=about["__maintainer__"],
maintainer_email=about["__maintainer_email__"],
license="Apache-2.0",
classifiers=CLASSIFIERS,
keywords="elastic eland pandas python",
packages=find_packages(include=["eland", "eland.*"]),
install_requires=[
"elasticsearch>=8.3,<9",
"pandas>=1.5,<2",
"matplotlib>=3.6",
"numpy<1.24",
],
scripts=["bin/eland_import_hub_model"],
python_requires=">=3.8",
package_data={"eland": ["py.typed"]},
include_package_data=True,
zip_safe=False,
extras_require=extras,
)