mirror of
https://github.com/elastic/eland.git
synced 2025-07-11 00:02:14 +08:00
102 lines
3.4 KiB
Python
102 lines
3.4 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 :: 3.8",
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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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>=1.3,<1.4"],
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"lightgbm": ["lightgbm>=2,<4"],
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"pytorch": [
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"requests<3",
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"torch==2.1.2",
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"tqdm",
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"sentence-transformers>=2.1.0,<=2.3.1",
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"transformers[torch]>=4.31.0,<4.36.0",
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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>=1.2.0,<2",
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"packaging",
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],
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entry_points={
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"console_scripts": "eland_import_hub_model=eland.cli.eland_import_hub_model:main"
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},
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python_requires=">=3.8,<3.12",
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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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