mirror of
https://github.com/elastic/eland.git
synced 2025-07-11 00:02:14 +08:00
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.
97 lines
3.2 KiB
Python
97 lines
3.2 KiB
Python
# Licensed to Elasticsearch B.V. under one or more contributor
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# license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright
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# ownership. Elasticsearch B.V. licenses this file to you under
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# the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# flake8: noqa
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from codecs import open
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from os import path
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from setuptools import find_packages, setup
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here = path.abspath(path.dirname(__file__))
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about = {}
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with open(path.join(here, "eland", "_version.py"), "r", "utf-8") as f:
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exec(f.read(), about)
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CLASSIFIERS = [
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"Development Status :: 5 - Production/Stable",
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"License :: OSI Approved :: Apache Software License",
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"Environment :: Console",
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"Operating System :: OS Independent",
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"Intended Audience :: Developers",
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"Intended Audience :: Science/Research",
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"Operating System :: OS Independent",
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"Programming Language :: Python",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3 :: Only",
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"Programming Language :: Python :: 3.7",
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"Programming Language :: Python :: 3.8",
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10",
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"Topic :: Scientific/Engineering",
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]
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# Remove all raw HTML from README for long description
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with open(path.join(here, "README.md"), "r", "utf-8") as f:
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lines = f.read().split("\n")
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last_html_index = 0
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for i, line in enumerate(lines):
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if line == "</p>":
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last_html_index = i + 1
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long_description = "\n".join(lines[last_html_index:])
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extras = {
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"xgboost": ["xgboost>=0.90,<2"],
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"scikit-learn": ["scikit-learn>=0.22.1,<2"],
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"lightgbm": ["lightgbm>=2,<4"],
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"pytorch": [
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"torch>=1.11.0,<1.12.0",
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"sentence-transformers>=2.1.0,<=2.2.2",
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"transformers[torch]>=4.12.0,<=4.20.1",
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],
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}
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extras["all"] = list({dep for deps in extras.values() for dep in deps})
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setup(
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name=about["__title__"],
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version=about["__version__"],
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description=about["__description__"],
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long_description=long_description,
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long_description_content_type="text/markdown",
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url=about["__url__"],
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author=about["__author__"],
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author_email=about["__author_email__"],
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maintainer=about["__maintainer__"],
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maintainer_email=about["__maintainer_email__"],
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license="Apache-2.0",
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classifiers=CLASSIFIERS,
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keywords="elastic eland pandas python",
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packages=find_packages(include=["eland", "eland.*"]),
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install_requires=[
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"elasticsearch>=8.3,<9",
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"pandas>=1.5,<2",
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"matplotlib>=3.6",
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"numpy<1.24",
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],
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scripts=["bin/eland_import_hub_model"],
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python_requires=">=3.8",
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package_data={"eland": ["py.typed"]},
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include_package_data=True,
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zip_safe=False,
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extras_require=extras,
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)
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