%global _empty_manifest_terminate_build 0 Name: python-truecase Version: 0.0.14 Release: 1 Summary: A library to restore capitalization for text License: MIT URL: https://github.com/daltonfury42/truecase Source0: https://mirrors.nju.edu.cn/pypi/web/packages/85/06/89d0adae754d32626dcd0dcd958a1b0be295a9e084a6ecda25af6ebbcdb2/truecase-0.0.14.tar.gz BuildArch: noarch Requires: python3-nltk %description # TrueCase ![Main](https://github.com/daltonfury42/truecase/workflows/Main/badge.svg) ![Publish PyPI](https://github.com/daltonfury42/truecase/workflows/Publish%20Python%20distributions%20to%20PyPI/badge.svg) A language independent, statistical, language modeling based tool in Python that restores case information for text. The model was inspired by the paper of [Lucian Vlad Lita et al., tRuEcasIng](https://www.cs.cmu.edu/~llita/papers/lita.truecasing-acl2003.pdf) but with some simplifications. A model trained on NLTK English corpus comes with the package by default, and for other languages, a script is provided to create the model. This model is not perfect, train the system on a large and recent dataset to achieve the best results (e.g. on a recent dump of Wikipedia). ### Prerequisites - Python 3 The project uses NLTK. Find install instructions [here](https://www.nltk.org/install.html). ### Installing ```bash pip3 install truecase ``` ## Usage Simple usecase: ```python >>> import truecase >>> truecase.get_true_case('hey, what is the weather in new york?') 'Hey, what is the weather in New York?'' ``` ## Training your own model TODO. For now refer to Trainer.py ## Contributing I see a lot of space for improvement. Feel free to fork and improve. Do sent a pull request. ## Authors * **Dalton Fury** - *Initial work* - [daltonfury42](https://github.com/daltonfury42) ## License This project is licensed under the MIT License - see the [LICENSE.md](LICENSE) file for details ## Acknowledgments * [Lucian Vlad Lita et al., tRuEcasIng](https://www.cs.cmu.edu/~llita/papers/lita.truecasing-acl2003.pdf) * Borrowed a lot of code, and the idea from [truecaser](https://github.com/nreimers/truecaser/blob/master/README.md) by [nreimers](https://github.com/nreimers) %package -n python3-truecase Summary: A library to restore capitalization for text Provides: python-truecase BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-truecase # TrueCase ![Main](https://github.com/daltonfury42/truecase/workflows/Main/badge.svg) ![Publish PyPI](https://github.com/daltonfury42/truecase/workflows/Publish%20Python%20distributions%20to%20PyPI/badge.svg) A language independent, statistical, language modeling based tool in Python that restores case information for text. The model was inspired by the paper of [Lucian Vlad Lita et al., tRuEcasIng](https://www.cs.cmu.edu/~llita/papers/lita.truecasing-acl2003.pdf) but with some simplifications. A model trained on NLTK English corpus comes with the package by default, and for other languages, a script is provided to create the model. This model is not perfect, train the system on a large and recent dataset to achieve the best results (e.g. on a recent dump of Wikipedia). ### Prerequisites - Python 3 The project uses NLTK. Find install instructions [here](https://www.nltk.org/install.html). ### Installing ```bash pip3 install truecase ``` ## Usage Simple usecase: ```python >>> import truecase >>> truecase.get_true_case('hey, what is the weather in new york?') 'Hey, what is the weather in New York?'' ``` ## Training your own model TODO. For now refer to Trainer.py ## Contributing I see a lot of space for improvement. Feel free to fork and improve. Do sent a pull request. ## Authors * **Dalton Fury** - *Initial work* - [daltonfury42](https://github.com/daltonfury42) ## License This project is licensed under the MIT License - see the [LICENSE.md](LICENSE) file for details ## Acknowledgments * [Lucian Vlad Lita et al., tRuEcasIng](https://www.cs.cmu.edu/~llita/papers/lita.truecasing-acl2003.pdf) * Borrowed a lot of code, and the idea from [truecaser](https://github.com/nreimers/truecaser/blob/master/README.md) by [nreimers](https://github.com/nreimers) %package help Summary: Development documents and examples for truecase Provides: python3-truecase-doc %description help # TrueCase ![Main](https://github.com/daltonfury42/truecase/workflows/Main/badge.svg) ![Publish PyPI](https://github.com/daltonfury42/truecase/workflows/Publish%20Python%20distributions%20to%20PyPI/badge.svg) A language independent, statistical, language modeling based tool in Python that restores case information for text. The model was inspired by the paper of [Lucian Vlad Lita et al., tRuEcasIng](https://www.cs.cmu.edu/~llita/papers/lita.truecasing-acl2003.pdf) but with some simplifications. A model trained on NLTK English corpus comes with the package by default, and for other languages, a script is provided to create the model. This model is not perfect, train the system on a large and recent dataset to achieve the best results (e.g. on a recent dump of Wikipedia). ### Prerequisites - Python 3 The project uses NLTK. Find install instructions [here](https://www.nltk.org/install.html). ### Installing ```bash pip3 install truecase ``` ## Usage Simple usecase: ```python >>> import truecase >>> truecase.get_true_case('hey, what is the weather in new york?') 'Hey, what is the weather in New York?'' ``` ## Training your own model TODO. For now refer to Trainer.py ## Contributing I see a lot of space for improvement. Feel free to fork and improve. Do sent a pull request. ## Authors * **Dalton Fury** - *Initial work* - [daltonfury42](https://github.com/daltonfury42) ## License This project is licensed under the MIT License - see the [LICENSE.md](LICENSE) file for details ## Acknowledgments * [Lucian Vlad Lita et al., tRuEcasIng](https://www.cs.cmu.edu/~llita/papers/lita.truecasing-acl2003.pdf) * Borrowed a lot of code, and the idea from [truecaser](https://github.com/nreimers/truecaser/blob/master/README.md) by [nreimers](https://github.com/nreimers) %prep %autosetup -n truecase-0.0.14 %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-truecase -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Apr 11 2023 Python_Bot - 0.0.14-1 - Package Spec generated