""" Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/master/setup.py To create the package for pypi. 1. Run `make pre-release` (or `make pre-patch` for a patch release) then run `make fix-copies` to fix the index of the documentation. 2. Run Tests for Amazon Sagemaker. The documentation is located in `./tests/sagemaker/README.md`, otherwise @philschmid. 3. Unpin specific versions from setup.py that use a git install. 4. Commit these changes with the message: "Release: VERSION" 5. Add a tag in git to mark the release: "git tag VERSION -m 'Adds tag VERSION for pypi' " Push the tag to git: git push --tags origin master 6. Build both the sources and the wheel. Do not change anything in setup.py between creating the wheel and the source distribution (obviously). For the wheel, run: "python setup.py bdist_wheel" in the top level directory. (this will build a wheel for the python version you use to build it). For the sources, run: "python setup.py sdist" You should now have a /dist directory with both .whl and .tar.gz source versions. 7. Check that everything looks correct by uploading the package to the pypi test server: twine upload dist/* -r pypitest (pypi suggest using twine as other methods upload files via plaintext.) You may have to specify the repository url, use the following command then: twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/ Check that you can install it in a virtualenv by running: pip install -i https://testpypi.python.org/pypi transformers 8. Upload the final version to actual pypi: twine upload dist/* -r pypi 9. Copy the release notes from RELEASE.md to the tag in github once everything is looking hunky-dory. 10. Run `make post-release` (or `make post-patch` for a patch release). """ from collections import defaultdict import setuptools def parse_requirements_file( path, allowed_extras: set = None, include_all_extra: bool = True ): requirements = [] extras = defaultdict(list) find_links = [] with open(path) as requirements_file: import re def fix_url_dependencies(req: str) -> str: """Pip and setuptools disagree about how URL dependencies should be handled.""" m = re.match( r"^(git\+)?(https|ssh)://(git@)?github\.com/([\w-]+)/(?P[\w-]+)\.git", req, ) if m is None: return req else: return f"{m.group('name')} @ {req}" for line in requirements_file: line = line.strip() if line.startswith("#") or len(line) <= 0: continue if ( line.startswith("-f") or line.startswith("--find-links") or line.startswith("--index-url") ): find_links.append(line.split(" ", maxsplit=1)[-1].strip()) continue req, *needed_by = line.split("# needed by:") req = fix_url_dependencies(req.strip()) if needed_by: for extra in needed_by[0].strip().split(","): extra = extra.strip() if allowed_extras is not None and extra not in allowed_extras: raise ValueError(f"invalid extra '{extra}' in {path}") extras[extra].append(req) if include_all_extra and req not in extras["all"]: extras["all"].append(req) else: requirements.append(req) return requirements, extras, find_links allowed_extras = { "onnx", "onnx-gpu", "serve", "retriever", "reader", "all", "faiss", "dev", } # Load requirements. install_requirements, extras, find_links = parse_requirements_file( "requirements.txt", allowed_extras=allowed_extras ) # version.py defines the VERSION and VERSION_SHORT variables. # We use exec here, so we don't import allennlp whilst setting up. VERSION = {} # type: ignore with open("relik/version.py", "r") as version_file: exec(version_file.read(), VERSION) with open("README.md", "r") as fh: long_description = fh.read() setuptools.setup( name="relik", version=VERSION["VERSION"], author="Edoardo Barba, Riccardo Orlando, Pere-LluĂ­s Huguet Cabot", author_email="orlandorcc@gmail.com", description="Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget", long_description=long_description, long_description_content_type="text/markdown", url="https://github.com/SapienzaNLP/relik", keywords="NLP Sapienza sapienzanlp deep learning transformer pytorch retriever entity linking relation extraction reader budget", packages=setuptools.find_packages(), include_package_data=True, license="Apache", classifiers=[ "Intended Audience :: Science/Research", "License :: OSI Approved :: Apache Software License", "Programming Language :: Python :: 3", "Topic :: Scientific/Engineering :: Artificial Intelligence", ], install_requires=install_requirements, extras_require=extras, python_requires=">=3.10", )