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- # Copyright 2021 The KubeEdge Authors.
- #
- # Licensed 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.
-
- """Setuptools of sedna"""
- from setuptools import setup, find_packages
- import sys
- import os
-
- assert sys.version_info >= (3, 6), "Sorry, Python < 3.6 is not supported."
-
-
- class InstallPrepare:
- """
- Parsing dependencies
- """
-
- def __init__(self):
- self.project = os.path.join(os.path.dirname(__file__), "sedna")
- self._long_desc = os.path.join(self.project, "README.md")
- self._version = os.path.join(self.project, "VERSION")
- self._owner = os.path.join(self.project, "..", "OWNERS")
- self._requirements = os.path.join(self.project, "..",
- "requirements.txt")
- self._dev_requirements = os.path.join(self.project, "..",
- "requirements.dev.txt")
-
- @property
- def long_desc(self):
- if not os.path.isfile(self._long_desc):
- return ""
- with open(self._long_desc, "r", encoding="utf-8") as fh:
- long_desc = fh.read()
- return long_desc
-
- @property
- def version(self):
- default_version = "999.dev"
- if not os.path.isfile(self._version):
- return default_version
- with open(self._version, "r", encoding="utf-8") as fh:
- __version__ = fh.read().strip()
- return __version__ or default_version
-
- @property
- def owners(self):
- default_owner = "sedna"
- if not os.path.isfile(self._owner):
- return default_owner
- with open(self._owner, "r", encoding="utf-8") as fh:
- check, approvers = False, set()
- for line in fh:
- if not line.strip():
- continue
- if check:
- approvers.add(line.strip().split()[-1])
- check = (line.startswith("approvers:") or
- (line.startswith(" -") and check))
- return ",".join(approvers) or default_owner
-
- @property
- def basic_dependencies(self):
- return self._read_requirements(self._requirements)
-
- def feature_dependencies(self, feature):
- _c = os.path.join(self.project, 'core', feature, "requirements.txt")
- if os.path.isfile(_c):
- return self._read_requirements(_c)
- return self._read_requirements(self._dev_requirements, feature)
-
- @staticmethod
- def _read_requirements(file_path, section="all"):
- print(f"Start to install requirements of {section} "
- f"in sedna from {file_path}")
- if not os.path.isfile(file_path):
- return []
- with open(file_path, "r", encoding="utf-8") as f:
- install_requires = [p.strip() for p in f.readlines() if p.strip()]
- if section == "all":
- return list(filter(lambda x: not x.startswith("#"),
- install_requires))
- section_start = False
- section_requires = []
- for p in install_requires:
- if section_start:
- if p.startswith("#"):
- return section_requires
- section_requires.append(p)
- elif p.startswith(f"# {section}"):
- section_start = True
- return section_requires
-
-
- _infos = InstallPrepare()
-
- setup(
- name='sedna',
- version=_infos.version,
- description="The sedna package is designed to help developers \
- better use open source frameworks such as tensorflow \
- on Sedna project",
- packages=find_packages(exclude=["tests", "*.tests",
- "*.tests.*", "tests.*"]),
- author=_infos.owners,
- author_email="pujie2@huawei.com",
- maintainer=_infos.owners,
- maintainer_email="",
- include_package_data=True,
- python_requires=">=3.6",
- long_description=_infos.long_desc,
- long_description_content_type="text/markdown",
- license="Apache License 2.0",
- url="https://github.com/kubeedge/sedna",
- classifiers=[
- "Programming Language :: Python :: 3",
- "License :: OSI Approved :: Apache Software License",
- "Operating System :: POSIX :: Linux",
- ],
- install_requires=_infos.basic_dependencies,
- extras_require={
- "fl": _infos.feature_dependencies("federated_learning"),
- "il": _infos.feature_dependencies("incremental_learning"),
- "ji": _infos.feature_dependencies("joint_inference"),
- "ll": _infos.feature_dependencies("lifelong_learning"),
- "me": _infos.feature_dependencies("multi_edge_tracking")
- },
- )
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