%global _empty_manifest_terminate_build 0 Name: python-PyNLPl Version: 1.2.9 Release: 1 Summary: PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl contains modules for basic tasks, clients for interfacting with server, and modules for parsing several file formats common in NLP, most notably FoLiA. License: GPL URL: https://github.com/proycon/pynlpl Source0: https://mirrors.nju.edu.cn/pypi/web/packages/ba/af/ee46390c14f270c891ecc5bd4cd3f02c7be408bb2d36bd96b1ae92ccb544/PyNLPl-1.2.9.tar.gz BuildArch: noarch %description PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotatation). The library is a divided into several packages and modules. It works on Python 2.7, as well as Python 3. The following modules are available: - ``pynlpl.datatypes`` - Extra datatypes (priority queues, patterns, tries) - ``pynlpl.evaluation`` - Evaluation & experiment classes (parameter search, wrapped progressive sampling, class evaluation (precision/recall/f-score/auc), sampler, confusion matrix, multithreaded experiment pool) - ``pynlpl.formats.cgn`` - Module for parsing CGN (Corpus Gesproken Nederlands) part-of-speech tags - ``pynlpl.formats.folia`` - Extensive library for reading and manipulating the documents in `FoLiA `_ format (Format for Linguistic Annotation). - ``pynlpl.formats.fql`` - Extensive library for the FoLiA Query Language (FQL), built on top of ``pynlpl.formats.folia``. FQL is currently documented `here `__. - ``pynlpl.formats.cql`` - Parser for the Corpus Query Language (CQL), as also used by Corpus Workbench and Sketch Engine. Contains a convertor to FQL. - ``pynlpl.formats.giza`` - Module for reading GIZA++ word alignment data - ``pynlpl.formats.moses`` - Module for reading Moses phrase-translation tables. - ``pynlpl.formats.sonar`` - Largely obsolete module for pre-releases of the SoNaR corpus, use ``pynlpl.formats.folia`` instead. - ``pynlpl.formats.timbl`` - Module for reading Timbl output (consider using `python-timbl `_ instead though) - ``pynlpl.lm.lm`` - Module for simple language model and reader for ARPA language model data as well (used by SRILM). - ``pynlpl.search`` - Various search algorithms (Breadth-first, depth-first, beam-search, hill climbing, A star, various variants of each) - ``pynlpl.statistics`` - Frequency lists, Levenshtein, common statistics and information theory functions - ``pynlpl.textprocessors`` - Simple tokeniser, n-gram extraction %package -n python3-PyNLPl Summary: PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl contains modules for basic tasks, clients for interfacting with server, and modules for parsing several file formats common in NLP, most notably FoLiA. Provides: python-PyNLPl BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-PyNLPl PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotatation). The library is a divided into several packages and modules. It works on Python 2.7, as well as Python 3. The following modules are available: - ``pynlpl.datatypes`` - Extra datatypes (priority queues, patterns, tries) - ``pynlpl.evaluation`` - Evaluation & experiment classes (parameter search, wrapped progressive sampling, class evaluation (precision/recall/f-score/auc), sampler, confusion matrix, multithreaded experiment pool) - ``pynlpl.formats.cgn`` - Module for parsing CGN (Corpus Gesproken Nederlands) part-of-speech tags - ``pynlpl.formats.folia`` - Extensive library for reading and manipulating the documents in `FoLiA `_ format (Format for Linguistic Annotation). - ``pynlpl.formats.fql`` - Extensive library for the FoLiA Query Language (FQL), built on top of ``pynlpl.formats.folia``. FQL is currently documented `here `__. - ``pynlpl.formats.cql`` - Parser for the Corpus Query Language (CQL), as also used by Corpus Workbench and Sketch Engine. Contains a convertor to FQL. - ``pynlpl.formats.giza`` - Module for reading GIZA++ word alignment data - ``pynlpl.formats.moses`` - Module for reading Moses phrase-translation tables. - ``pynlpl.formats.sonar`` - Largely obsolete module for pre-releases of the SoNaR corpus, use ``pynlpl.formats.folia`` instead. - ``pynlpl.formats.timbl`` - Module for reading Timbl output (consider using `python-timbl `_ instead though) - ``pynlpl.lm.lm`` - Module for simple language model and reader for ARPA language model data as well (used by SRILM). - ``pynlpl.search`` - Various search algorithms (Breadth-first, depth-first, beam-search, hill climbing, A star, various variants of each) - ``pynlpl.statistics`` - Frequency lists, Levenshtein, common statistics and information theory functions - ``pynlpl.textprocessors`` - Simple tokeniser, n-gram extraction %package help Summary: Development documents and examples for PyNLPl Provides: python3-PyNLPl-doc %description help PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotatation). The library is a divided into several packages and modules. It works on Python 2.7, as well as Python 3. The following modules are available: - ``pynlpl.datatypes`` - Extra datatypes (priority queues, patterns, tries) - ``pynlpl.evaluation`` - Evaluation & experiment classes (parameter search, wrapped progressive sampling, class evaluation (precision/recall/f-score/auc), sampler, confusion matrix, multithreaded experiment pool) - ``pynlpl.formats.cgn`` - Module for parsing CGN (Corpus Gesproken Nederlands) part-of-speech tags - ``pynlpl.formats.folia`` - Extensive library for reading and manipulating the documents in `FoLiA `_ format (Format for Linguistic Annotation). - ``pynlpl.formats.fql`` - Extensive library for the FoLiA Query Language (FQL), built on top of ``pynlpl.formats.folia``. FQL is currently documented `here `__. - ``pynlpl.formats.cql`` - Parser for the Corpus Query Language (CQL), as also used by Corpus Workbench and Sketch Engine. Contains a convertor to FQL. - ``pynlpl.formats.giza`` - Module for reading GIZA++ word alignment data - ``pynlpl.formats.moses`` - Module for reading Moses phrase-translation tables. - ``pynlpl.formats.sonar`` - Largely obsolete module for pre-releases of the SoNaR corpus, use ``pynlpl.formats.folia`` instead. - ``pynlpl.formats.timbl`` - Module for reading Timbl output (consider using `python-timbl `_ instead though) - ``pynlpl.lm.lm`` - Module for simple language model and reader for ARPA language model data as well (used by SRILM). - ``pynlpl.search`` - Various search algorithms (Breadth-first, depth-first, beam-search, hill climbing, A star, various variants of each) - ``pynlpl.statistics`` - Frequency lists, Levenshtein, common statistics and information theory functions - ``pynlpl.textprocessors`` - Simple tokeniser, n-gram extraction %prep %autosetup -n PyNLPl-1.2.9 %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-PyNLPl -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri Apr 07 2023 Python_Bot - 1.2.9-1 - Package Spec generated