automatic import of python-textacy

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diff --git a/.gitignore b/.gitignore
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+/textacy-0.13.0.tar.gz
diff --git a/python-textacy.spec b/python-textacy.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-textacy
+Version:	0.13.0
+Release:	1
+Summary:	NLP, before and after spaCy
+License:	Copyright 2016 Chartbeat, Inc.  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. 
+URL:		https://pypi.org/project/textacy/
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/04/fe/4a578d9f68e7aaf6b7be7d8df974ab3b1b21f2e64d492919adda3cd80b71/textacy-0.13.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-cachetools
+Requires:	python3-catalogue
+Requires:	python3-cytoolz
+Requires:	python3-floret
+Requires:	python3-jellyfish
+Requires:	python3-joblib
+Requires:	python3-networkx
+Requires:	python3-numpy
+Requires:	python3-pyphen
+Requires:	python3-requests
+Requires:	python3-scipy
+Requires:	python3-scikit-learn
+Requires:	python3-spacy
+Requires:	python3-tqdm
+Requires:	python3-black
+Requires:	python3-isort
+Requires:	python3-mypy
+Requires:	python3-pytest
+Requires:	python3-pytest-cov
+Requires:	python3-ruff
+Requires:	python3-black
+Requires:	python3-build
+Requires:	python3-isort
+Requires:	python3-mypy
+Requires:	python3-recommonmark
+Requires:	python3-sphinx
+Requires:	python3-pytest
+Requires:	python3-pytest-cov
+Requires:	python3-ruff
+Requires:	python3-twine
+Requires:	python3-wheel
+Requires:	python3-Jinja2
+Requires:	python3-recommonmark
+Requires:	python3-sphinx
+Requires:	python3-matplotlib
+
+%description
+## textacy: NLP, before and after spaCy
+
+`textacy` is a Python library for performing a variety of natural language processing (NLP) tasks, built on the high-performance spaCy library. With the fundamentals --- tokenization, part-of-speech tagging, dependency parsing, etc. --- delegated to another library, `textacy` focuses primarily on the tasks that come before and follow after.
+
+[![build status](https://img.shields.io/travis/chartbeat-labs/textacy/master.svg?style=flat-square)](https://travis-ci.org/chartbeat-labs/textacy)
+[![current release version](https://img.shields.io/github/release/chartbeat-labs/textacy.svg?style=flat-square)](https://github.com/chartbeat-labs/textacy/releases)
+[![pypi version](https://img.shields.io/pypi/v/textacy.svg?style=flat-square)](https://pypi.python.org/pypi/textacy)
+[![conda version](https://anaconda.org/conda-forge/textacy/badges/version.svg)](https://anaconda.org/conda-forge/textacy)
+
+### features
+
+- Access and extend spaCy's core functionality for working with one or many documents through convenient methods and custom extensions
+- Load prepared datasets with both text content and metadata, from Congressional speeches to historical literature to Reddit comments
+- Clean, normalize, and explore raw text before processing it with spaCy
+- Extract structured information from processed documents, including n-grams, entities, acronyms, keyterms, and SVO triples
+- Compare strings and sequences using a variety of similarity metrics
+- Tokenize and vectorize documents then train, interpret, and visualize topic models
+- Compute text readability and lexical diversity statistics, including Flesch-Kincaid grade level, multilingual Flesch Reading Ease, and Type-Token Ratio
+
+... *and much more!*
+
+### links
+
+- Download: https://pypi.org/project/textacy
+- Documentation: https://textacy.readthedocs.io
+- Source code: https://github.com/chartbeat-labs/textacy
+- Bug Tracker: https://github.com/chartbeat-labs/textacy/issues
+
+### maintainer
+
+Howdy, y'all. 👋
+
+- Burton DeWilde (<burtdewilde@gmail.com>)
+
+
+%package -n python3-textacy
+Summary:	NLP, before and after spaCy
+Provides:	python-textacy
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-textacy
+## textacy: NLP, before and after spaCy
+
+`textacy` is a Python library for performing a variety of natural language processing (NLP) tasks, built on the high-performance spaCy library. With the fundamentals --- tokenization, part-of-speech tagging, dependency parsing, etc. --- delegated to another library, `textacy` focuses primarily on the tasks that come before and follow after.
+
+[![build status](https://img.shields.io/travis/chartbeat-labs/textacy/master.svg?style=flat-square)](https://travis-ci.org/chartbeat-labs/textacy)
+[![current release version](https://img.shields.io/github/release/chartbeat-labs/textacy.svg?style=flat-square)](https://github.com/chartbeat-labs/textacy/releases)
+[![pypi version](https://img.shields.io/pypi/v/textacy.svg?style=flat-square)](https://pypi.python.org/pypi/textacy)
+[![conda version](https://anaconda.org/conda-forge/textacy/badges/version.svg)](https://anaconda.org/conda-forge/textacy)
+
+### features
+
+- Access and extend spaCy's core functionality for working with one or many documents through convenient methods and custom extensions
+- Load prepared datasets with both text content and metadata, from Congressional speeches to historical literature to Reddit comments
+- Clean, normalize, and explore raw text before processing it with spaCy
+- Extract structured information from processed documents, including n-grams, entities, acronyms, keyterms, and SVO triples
+- Compare strings and sequences using a variety of similarity metrics
+- Tokenize and vectorize documents then train, interpret, and visualize topic models
+- Compute text readability and lexical diversity statistics, including Flesch-Kincaid grade level, multilingual Flesch Reading Ease, and Type-Token Ratio
+
+... *and much more!*
+
+### links
+
+- Download: https://pypi.org/project/textacy
+- Documentation: https://textacy.readthedocs.io
+- Source code: https://github.com/chartbeat-labs/textacy
+- Bug Tracker: https://github.com/chartbeat-labs/textacy/issues
+
+### maintainer
+
+Howdy, y'all. 👋
+
+- Burton DeWilde (<burtdewilde@gmail.com>)
+
+
+%package help
+Summary:	Development documents and examples for textacy
+Provides:	python3-textacy-doc
+%description help
+## textacy: NLP, before and after spaCy
+
+`textacy` is a Python library for performing a variety of natural language processing (NLP) tasks, built on the high-performance spaCy library. With the fundamentals --- tokenization, part-of-speech tagging, dependency parsing, etc. --- delegated to another library, `textacy` focuses primarily on the tasks that come before and follow after.
+
+[![build status](https://img.shields.io/travis/chartbeat-labs/textacy/master.svg?style=flat-square)](https://travis-ci.org/chartbeat-labs/textacy)
+[![current release version](https://img.shields.io/github/release/chartbeat-labs/textacy.svg?style=flat-square)](https://github.com/chartbeat-labs/textacy/releases)
+[![pypi version](https://img.shields.io/pypi/v/textacy.svg?style=flat-square)](https://pypi.python.org/pypi/textacy)
+[![conda version](https://anaconda.org/conda-forge/textacy/badges/version.svg)](https://anaconda.org/conda-forge/textacy)
+
+### features
+
+- Access and extend spaCy's core functionality for working with one or many documents through convenient methods and custom extensions
+- Load prepared datasets with both text content and metadata, from Congressional speeches to historical literature to Reddit comments
+- Clean, normalize, and explore raw text before processing it with spaCy
+- Extract structured information from processed documents, including n-grams, entities, acronyms, keyterms, and SVO triples
+- Compare strings and sequences using a variety of similarity metrics
+- Tokenize and vectorize documents then train, interpret, and visualize topic models
+- Compute text readability and lexical diversity statistics, including Flesch-Kincaid grade level, multilingual Flesch Reading Ease, and Type-Token Ratio
+
+... *and much more!*
+
+### links
+
+- Download: https://pypi.org/project/textacy
+- Documentation: https://textacy.readthedocs.io
+- Source code: https://github.com/chartbeat-labs/textacy
+- Bug Tracker: https://github.com/chartbeat-labs/textacy/issues
+
+### maintainer
+
+Howdy, y'all. 👋
+
+- Burton DeWilde (<burtdewilde@gmail.com>)
+
+
+%prep
+%autosetup -n textacy-0.13.0
+
+%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-textacy -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.13.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..27ed4d9
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+54f049988924accaba14c18c268b0c34  textacy-0.13.0.tar.gz