%global _empty_manifest_terminate_build 0 Name: python-pytextrank Version: 3.2.4 Release: 1 Summary: Python implementation of TextRank as a spaCy pipeline extension, for graph-based natural language work plus related knowledge graph practices; used for for phrase extraction and lightweight extractive summarization of text documents. License: MIT URL: https://derwen.ai/docs/ptr/ Source0: https://mirrors.nju.edu.cn/pypi/web/packages/b0/37/407ec5ea479e13d0230d333c4b645c786eb7f56e44e1203055b3a89ddd5d/pytextrank-3.2.4.tar.gz BuildArch: noarch Requires: python3-graphviz Requires: python3-icecream Requires: python3-networkx[default] Requires: python3-pygments Requires: python3-scipy Requires: python3-spacy Requires: python3-graphviz Requires: python3-icecream Requires: python3-networkx[default] Requires: python3-pygments Requires: python3-scipy Requires: python3-spacy Requires: python3-bandit Requires: python3-check-manifest Requires: python3-codespell Requires: python3-coverage Requires: python3-flask Requires: python3-grayskull Requires: python3-jupyterlab Requires: python3-mistune Requires: python3-mkdocs-git-revision-date-plugin Requires: python3-mkdocs-material Requires: python3-mknotebooks Requires: python3-mkrefs Requires: python3-mypy Requires: python3-nbconvert Requires: python3-nbmake Requires: python3-notebook Requires: python3-pipdeptree Requires: python3-pre-commit Requires: python3-pylint Requires: python3-pytest Requires: python3-pymdown-extensions Requires: python3-selenium Requires: python3-twine Requires: python3-wheel Requires: python3-altair %description # PyTextRank [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4637885.svg)](https://doi.org/10.5281/zenodo.4637885) ![Licence](https://img.shields.io/github/license/DerwenAI/pytextrank) ![Repo size](https://img.shields.io/github/repo-size/DerwenAI/pytextrank) ![GitHub commit activity](https://img.shields.io/github/commit-activity/w/DerwenAI/pytextrank?style=plastic) [![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/) [![security: bandit](https://img.shields.io/badge/security-bandit-yellow.svg)](https://github.com/PyCQA/bandit) [![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/DerwenAI/pytextrank.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/DerwenAI/pytextrank/context:python) ![CI](https://github.com/DerwenAI/pytextrank/workflows/CI/badge.svg) ![downloads](https://img.shields.io/pypi/dm/pytextrank) ![sponsor](https://img.shields.io/github/sponsors/ceteri) **PyTextRank** is a Python implementation of *TextRank* as a [spaCy pipeline extension](https://spacy.io/universe/project/spacy-pytextrank), for graph-based natural language work -- and related knowledge graph practices. This includes the family of [*textgraph*](https://derwen.ai/docs/ptr/glossary/#textgraphs) algorithms: - *TextRank* by [[mihalcea04textrank]](https://derwen.ai/docs/ptr/biblio/#mihalcea04textrank) - *PositionRank* by [[florescuc17]](https://derwen.ai/docs/ptr/biblio/#florescuc17) - *Biased TextRank* by [[kazemi-etal-2020-biased]](https://derwen.ai/docs/ptr/biblio/#kazemi-etal-2020-biased) - *TopicRank* by [[bougouin-etal-2013-topicrank]](https://derwen.ai/docs/ptr/biblio/#bougouin-etal-2013-topicrank) Popular use cases for this library include: - *phrase extraction*: get the top-ranked phrases from a text document - low-cost *extractive summarization* of a text document - help infer concepts from unstructured text into more structured representation See our full documentation at: ## Getting Started See the ["Getting Started"](https://derwen.ai/docs/ptr/start/) section of the online documentation. To install from [PyPi](https://pypi.python.org/pypi/pytextrank): ``` python3 -m pip install pytextrank python3 -m spacy download en_core_web_sm ``` If you work directly from this Git repo, be sure to install the dependencies as well: ``` python3 -m pip install -r requirements.txt ``` Alternatively, to install dependencies using `conda`: ``` conda env create -f environment.yml conda activate pytextrank ``` Then to use the library with a simple use case: ```python import spacy import pytextrank # example text text = "Compatibility of systems of linear constraints over the set of natural numbers. Criteria of compatibility of a system of linear Diophantine equations, strict inequations, and nonstrict inequations are considered. Upper bounds for components of a minimal set of solutions and algorithms of construction of minimal generating sets of solutions for all types of systems are given. These criteria and the corresponding algorithms for constructing a minimal supporting set of solutions can be used in solving all the considered types systems and systems of mixed types." # load a spaCy model, depending on language, scale, etc. nlp = spacy.load("en_core_web_sm") # add PyTextRank to the spaCy pipeline nlp.add_pipe("textrank") doc = nlp(text) # examine the top-ranked phrases in the document for phrase in doc._.phrases: print(phrase.text) print(phrase.rank, phrase.count) print(phrase.chunks) ``` See the **tutorial notebooks** in the `examples` subdirectory for sample code and patterns to use in integrating **PyTextTank** with related libraries in Python:
Contributing Code We welcome people getting involved as contributors to this open source project! For detailed instructions please see: [CONTRIBUTING.md](https://github.com/DerwenAI/pytextrank/blob/main/CONTRIBUTING.md)
Build Instructions Note: unless you are contributing code and updates, in most use cases won't need to build this package locally. Instead, simply install from [PyPi](https://pypi.python.org/pypi/pytextrank) or use [Conda](https://docs.conda.io/). To set up the build environment locally, see the ["Build Instructions"](https://derwen.ai/docs/ptr/build/) section of the online documentation.
Semantic Versioning Generally speaking the major release number of PyTextRank will track with the major release number of the associated spaCy version. See: [CHANGELOG.md](https://github.com/DerwenAI/pytextrank/blob/main/CHANGELOG.md)
thanks noam! ## License and Copyright Source code for **PyTextRank** plus its logo, documentation, and examples have an [MIT license](https://spdx.org/licenses/MIT.html) which is succinct and simplifies use in commercial applications. All materials herein are Copyright © 2016-2022 Derwen, Inc. ## Attribution Please use the following BibTeX entry for citing **PyTextRank** if you use it in your research or software: ```bibtex @software{PyTextRank, author = {Paco Nathan}, title = {{PyTextRank, a Python implementation of TextRank for phrase extraction and summarization of text documents}}, year = 2016, publisher = {Derwen}, doi = {10.5281/zenodo.4637885}, url = {https://github.com/DerwenAI/pytextrank} } ``` Citations are helpful for the continued development and maintenance of this library. For example, see our citations listed on [Google Scholar](https://scholar.google.com/scholar?q=related:5tl6J4xZlCIJ:scholar.google.com/&scioq=&hl=en&as_sdt=0,5). ## Kudos Many thanks to our open source [sponsors](https://github.com/sponsors/ceteri); and to our contributors: [@ceteri](https://github.com/ceteri), [@louisguitton](https://github.com/louisguitton), [@Ankush-Chander](https://github.com/Ankush-Chander), [@tomaarsen](https://github.com/tomaarsen), [@CaptXiong](https://github.com/CaptXiong), [@Lord-V15](https://github.com/Lord-V15), [@anna-droid-beep](https://github.com/anna-droid-beep), [@dvsrepo](https://github.com/dvsrepo), [@clabornd](https://github.com/clabornd), [@dayalstrub-cma](https://github.com/dayalstrub-cma), [@kavorite](https://github.com/kavorite), [@htmartin](https://github.com/htmartin), [@williamsmj](https://github.com/williamsmj/), [@mattkohl](https://github.com/mattkohl), [@vanita5](https://github.com/vanita5), [@HarshGrandeur](https://github.com/HarshGrandeur), [@mnowotka](https://github.com/mnowotka), [@kjam](https://github.com/kjam), [@SaiThejeshwar](https://github.com/SaiThejeshwar), [@laxatives](https://github.com/laxatives), [@dimmu](https://github.com/dimmu), [@JasonZhangzy1757](https://github.com/JasonZhangzy1757), [@jake-aft](https://github.com/jake-aft), [@junchen1992](https://github.com/junchen1992), [@shyamcody](https://github.com/shyamcody), [@chikubee](https://github.com/chikubee); also to [@mihalcea](https://github.com/mihalcea) who leads outstanding NLP research work, encouragement from the wonderful folks at Explosion who develop [spaCy](https://github.com/explosion/spaCy), plus general support from [Derwen, Inc.](https://derwen.ai/) ## Star History [![Star History Chart](https://api.star-history.com/svg?repos=derwenai/pytextrank&type=Date)](https://star-history.com/#derwenai/pytextrank&Date) %package -n python3-pytextrank Summary: Python implementation of TextRank as a spaCy pipeline extension, for graph-based natural language work plus related knowledge graph practices; used for for phrase extraction and lightweight extractive summarization of text documents. Provides: python-pytextrank BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-pytextrank # PyTextRank [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4637885.svg)](https://doi.org/10.5281/zenodo.4637885) ![Licence](https://img.shields.io/github/license/DerwenAI/pytextrank) ![Repo size](https://img.shields.io/github/repo-size/DerwenAI/pytextrank) ![GitHub commit activity](https://img.shields.io/github/commit-activity/w/DerwenAI/pytextrank?style=plastic) [![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/) [![security: bandit](https://img.shields.io/badge/security-bandit-yellow.svg)](https://github.com/PyCQA/bandit) [![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/DerwenAI/pytextrank.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/DerwenAI/pytextrank/context:python) ![CI](https://github.com/DerwenAI/pytextrank/workflows/CI/badge.svg) ![downloads](https://img.shields.io/pypi/dm/pytextrank) ![sponsor](https://img.shields.io/github/sponsors/ceteri) **PyTextRank** is a Python implementation of *TextRank* as a [spaCy pipeline extension](https://spacy.io/universe/project/spacy-pytextrank), for graph-based natural language work -- and related knowledge graph practices. This includes the family of [*textgraph*](https://derwen.ai/docs/ptr/glossary/#textgraphs) algorithms: - *TextRank* by [[mihalcea04textrank]](https://derwen.ai/docs/ptr/biblio/#mihalcea04textrank) - *PositionRank* by [[florescuc17]](https://derwen.ai/docs/ptr/biblio/#florescuc17) - *Biased TextRank* by [[kazemi-etal-2020-biased]](https://derwen.ai/docs/ptr/biblio/#kazemi-etal-2020-biased) - *TopicRank* by [[bougouin-etal-2013-topicrank]](https://derwen.ai/docs/ptr/biblio/#bougouin-etal-2013-topicrank) Popular use cases for this library include: - *phrase extraction*: get the top-ranked phrases from a text document - low-cost *extractive summarization* of a text document - help infer concepts from unstructured text into more structured representation See our full documentation at: ## Getting Started See the ["Getting Started"](https://derwen.ai/docs/ptr/start/) section of the online documentation. To install from [PyPi](https://pypi.python.org/pypi/pytextrank): ``` python3 -m pip install pytextrank python3 -m spacy download en_core_web_sm ``` If you work directly from this Git repo, be sure to install the dependencies as well: ``` python3 -m pip install -r requirements.txt ``` Alternatively, to install dependencies using `conda`: ``` conda env create -f environment.yml conda activate pytextrank ``` Then to use the library with a simple use case: ```python import spacy import pytextrank # example text text = "Compatibility of systems of linear constraints over the set of natural numbers. Criteria of compatibility of a system of linear Diophantine equations, strict inequations, and nonstrict inequations are considered. Upper bounds for components of a minimal set of solutions and algorithms of construction of minimal generating sets of solutions for all types of systems are given. These criteria and the corresponding algorithms for constructing a minimal supporting set of solutions can be used in solving all the considered types systems and systems of mixed types." # load a spaCy model, depending on language, scale, etc. nlp = spacy.load("en_core_web_sm") # add PyTextRank to the spaCy pipeline nlp.add_pipe("textrank") doc = nlp(text) # examine the top-ranked phrases in the document for phrase in doc._.phrases: print(phrase.text) print(phrase.rank, phrase.count) print(phrase.chunks) ``` See the **tutorial notebooks** in the `examples` subdirectory for sample code and patterns to use in integrating **PyTextTank** with related libraries in Python:
Contributing Code We welcome people getting involved as contributors to this open source project! For detailed instructions please see: [CONTRIBUTING.md](https://github.com/DerwenAI/pytextrank/blob/main/CONTRIBUTING.md)
Build Instructions Note: unless you are contributing code and updates, in most use cases won't need to build this package locally. Instead, simply install from [PyPi](https://pypi.python.org/pypi/pytextrank) or use [Conda](https://docs.conda.io/). To set up the build environment locally, see the ["Build Instructions"](https://derwen.ai/docs/ptr/build/) section of the online documentation.
Semantic Versioning Generally speaking the major release number of PyTextRank will track with the major release number of the associated spaCy version. See: [CHANGELOG.md](https://github.com/DerwenAI/pytextrank/blob/main/CHANGELOG.md)
thanks noam! ## License and Copyright Source code for **PyTextRank** plus its logo, documentation, and examples have an [MIT license](https://spdx.org/licenses/MIT.html) which is succinct and simplifies use in commercial applications. All materials herein are Copyright © 2016-2022 Derwen, Inc. ## Attribution Please use the following BibTeX entry for citing **PyTextRank** if you use it in your research or software: ```bibtex @software{PyTextRank, author = {Paco Nathan}, title = {{PyTextRank, a Python implementation of TextRank for phrase extraction and summarization of text documents}}, year = 2016, publisher = {Derwen}, doi = {10.5281/zenodo.4637885}, url = {https://github.com/DerwenAI/pytextrank} } ``` Citations are helpful for the continued development and maintenance of this library. For example, see our citations listed on [Google Scholar](https://scholar.google.com/scholar?q=related:5tl6J4xZlCIJ:scholar.google.com/&scioq=&hl=en&as_sdt=0,5). ## Kudos Many thanks to our open source [sponsors](https://github.com/sponsors/ceteri); and to our contributors: [@ceteri](https://github.com/ceteri), [@louisguitton](https://github.com/louisguitton), [@Ankush-Chander](https://github.com/Ankush-Chander), [@tomaarsen](https://github.com/tomaarsen), [@CaptXiong](https://github.com/CaptXiong), [@Lord-V15](https://github.com/Lord-V15), [@anna-droid-beep](https://github.com/anna-droid-beep), [@dvsrepo](https://github.com/dvsrepo), [@clabornd](https://github.com/clabornd), [@dayalstrub-cma](https://github.com/dayalstrub-cma), [@kavorite](https://github.com/kavorite), [@htmartin](https://github.com/htmartin), [@williamsmj](https://github.com/williamsmj/), [@mattkohl](https://github.com/mattkohl), [@vanita5](https://github.com/vanita5), [@HarshGrandeur](https://github.com/HarshGrandeur), [@mnowotka](https://github.com/mnowotka), [@kjam](https://github.com/kjam), [@SaiThejeshwar](https://github.com/SaiThejeshwar), [@laxatives](https://github.com/laxatives), [@dimmu](https://github.com/dimmu), [@JasonZhangzy1757](https://github.com/JasonZhangzy1757), [@jake-aft](https://github.com/jake-aft), [@junchen1992](https://github.com/junchen1992), [@shyamcody](https://github.com/shyamcody), [@chikubee](https://github.com/chikubee); also to [@mihalcea](https://github.com/mihalcea) who leads outstanding NLP research work, encouragement from the wonderful folks at Explosion who develop [spaCy](https://github.com/explosion/spaCy), plus general support from [Derwen, Inc.](https://derwen.ai/) ## Star History [![Star History Chart](https://api.star-history.com/svg?repos=derwenai/pytextrank&type=Date)](https://star-history.com/#derwenai/pytextrank&Date) %package help Summary: Development documents and examples for pytextrank Provides: python3-pytextrank-doc %description help # PyTextRank [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4637885.svg)](https://doi.org/10.5281/zenodo.4637885) ![Licence](https://img.shields.io/github/license/DerwenAI/pytextrank) ![Repo size](https://img.shields.io/github/repo-size/DerwenAI/pytextrank) ![GitHub commit activity](https://img.shields.io/github/commit-activity/w/DerwenAI/pytextrank?style=plastic) [![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/) [![security: bandit](https://img.shields.io/badge/security-bandit-yellow.svg)](https://github.com/PyCQA/bandit) [![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/DerwenAI/pytextrank.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/DerwenAI/pytextrank/context:python) ![CI](https://github.com/DerwenAI/pytextrank/workflows/CI/badge.svg) ![downloads](https://img.shields.io/pypi/dm/pytextrank) ![sponsor](https://img.shields.io/github/sponsors/ceteri) **PyTextRank** is a Python implementation of *TextRank* as a [spaCy pipeline extension](https://spacy.io/universe/project/spacy-pytextrank), for graph-based natural language work -- and related knowledge graph practices. This includes the family of [*textgraph*](https://derwen.ai/docs/ptr/glossary/#textgraphs) algorithms: - *TextRank* by [[mihalcea04textrank]](https://derwen.ai/docs/ptr/biblio/#mihalcea04textrank) - *PositionRank* by [[florescuc17]](https://derwen.ai/docs/ptr/biblio/#florescuc17) - *Biased TextRank* by [[kazemi-etal-2020-biased]](https://derwen.ai/docs/ptr/biblio/#kazemi-etal-2020-biased) - *TopicRank* by [[bougouin-etal-2013-topicrank]](https://derwen.ai/docs/ptr/biblio/#bougouin-etal-2013-topicrank) Popular use cases for this library include: - *phrase extraction*: get the top-ranked phrases from a text document - low-cost *extractive summarization* of a text document - help infer concepts from unstructured text into more structured representation See our full documentation at: ## Getting Started See the ["Getting Started"](https://derwen.ai/docs/ptr/start/) section of the online documentation. To install from [PyPi](https://pypi.python.org/pypi/pytextrank): ``` python3 -m pip install pytextrank python3 -m spacy download en_core_web_sm ``` If you work directly from this Git repo, be sure to install the dependencies as well: ``` python3 -m pip install -r requirements.txt ``` Alternatively, to install dependencies using `conda`: ``` conda env create -f environment.yml conda activate pytextrank ``` Then to use the library with a simple use case: ```python import spacy import pytextrank # example text text = "Compatibility of systems of linear constraints over the set of natural numbers. Criteria of compatibility of a system of linear Diophantine equations, strict inequations, and nonstrict inequations are considered. Upper bounds for components of a minimal set of solutions and algorithms of construction of minimal generating sets of solutions for all types of systems are given. These criteria and the corresponding algorithms for constructing a minimal supporting set of solutions can be used in solving all the considered types systems and systems of mixed types." # load a spaCy model, depending on language, scale, etc. nlp = spacy.load("en_core_web_sm") # add PyTextRank to the spaCy pipeline nlp.add_pipe("textrank") doc = nlp(text) # examine the top-ranked phrases in the document for phrase in doc._.phrases: print(phrase.text) print(phrase.rank, phrase.count) print(phrase.chunks) ``` See the **tutorial notebooks** in the `examples` subdirectory for sample code and patterns to use in integrating **PyTextTank** with related libraries in Python:
Contributing Code We welcome people getting involved as contributors to this open source project! For detailed instructions please see: [CONTRIBUTING.md](https://github.com/DerwenAI/pytextrank/blob/main/CONTRIBUTING.md)
Build Instructions Note: unless you are contributing code and updates, in most use cases won't need to build this package locally. Instead, simply install from [PyPi](https://pypi.python.org/pypi/pytextrank) or use [Conda](https://docs.conda.io/). To set up the build environment locally, see the ["Build Instructions"](https://derwen.ai/docs/ptr/build/) section of the online documentation.
Semantic Versioning Generally speaking the major release number of PyTextRank will track with the major release number of the associated spaCy version. See: [CHANGELOG.md](https://github.com/DerwenAI/pytextrank/blob/main/CHANGELOG.md)
thanks noam! ## License and Copyright Source code for **PyTextRank** plus its logo, documentation, and examples have an [MIT license](https://spdx.org/licenses/MIT.html) which is succinct and simplifies use in commercial applications. All materials herein are Copyright © 2016-2022 Derwen, Inc. ## Attribution Please use the following BibTeX entry for citing **PyTextRank** if you use it in your research or software: ```bibtex @software{PyTextRank, author = {Paco Nathan}, title = {{PyTextRank, a Python implementation of TextRank for phrase extraction and summarization of text documents}}, year = 2016, publisher = {Derwen}, doi = {10.5281/zenodo.4637885}, url = {https://github.com/DerwenAI/pytextrank} } ``` Citations are helpful for the continued development and maintenance of this library. For example, see our citations listed on [Google Scholar](https://scholar.google.com/scholar?q=related:5tl6J4xZlCIJ:scholar.google.com/&scioq=&hl=en&as_sdt=0,5). ## Kudos Many thanks to our open source [sponsors](https://github.com/sponsors/ceteri); and to our contributors: [@ceteri](https://github.com/ceteri), [@louisguitton](https://github.com/louisguitton), [@Ankush-Chander](https://github.com/Ankush-Chander), [@tomaarsen](https://github.com/tomaarsen), [@CaptXiong](https://github.com/CaptXiong), [@Lord-V15](https://github.com/Lord-V15), [@anna-droid-beep](https://github.com/anna-droid-beep), [@dvsrepo](https://github.com/dvsrepo), [@clabornd](https://github.com/clabornd), [@dayalstrub-cma](https://github.com/dayalstrub-cma), [@kavorite](https://github.com/kavorite), [@htmartin](https://github.com/htmartin), [@williamsmj](https://github.com/williamsmj/), [@mattkohl](https://github.com/mattkohl), [@vanita5](https://github.com/vanita5), [@HarshGrandeur](https://github.com/HarshGrandeur), [@mnowotka](https://github.com/mnowotka), [@kjam](https://github.com/kjam), [@SaiThejeshwar](https://github.com/SaiThejeshwar), [@laxatives](https://github.com/laxatives), [@dimmu](https://github.com/dimmu), [@JasonZhangzy1757](https://github.com/JasonZhangzy1757), [@jake-aft](https://github.com/jake-aft), [@junchen1992](https://github.com/junchen1992), [@shyamcody](https://github.com/shyamcody), [@chikubee](https://github.com/chikubee); also to [@mihalcea](https://github.com/mihalcea) who leads outstanding NLP research work, encouragement from the wonderful folks at Explosion who develop [spaCy](https://github.com/explosion/spaCy), plus general support from [Derwen, Inc.](https://derwen.ai/) ## Star History [![Star History Chart](https://api.star-history.com/svg?repos=derwenai/pytextrank&type=Date)](https://star-history.com/#derwenai/pytextrank&Date) %prep %autosetup -n pytextrank-3.2.4 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-pytextrank -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Apr 11 2023 Python_Bot - 3.2.4-1 - Package Spec generated