%global _empty_manifest_terminate_build 0
Name: python-annif
Version: 0.61.0
Release: 1
Summary: Automated subject indexing and classification tool
License: Apache-2.0
URL: https://annif.org
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/9c/8d/ab23892c2c8ea3f61a1ec011012042d1b2f371bfba74bb03e2b4f556bd2b/annif-0.61.0.tar.gz
BuildArch: noarch
Requires: python3-connexion[swagger-ui]
Requires: python3-flask
Requires: python3-flask-cors
Requires: python3-click
Requires: python3-click-log
Requires: python3-joblib
Requires: python3-nltk
Requires: python3-gensim
Requires: python3-scikit-learn
Requires: python3-scipy
Requires: python3-rdflib
Requires: python3-gunicorn
Requires: python3-numpy
Requires: python3-optuna
Requires: python3-stwfsapy
Requires: python3-dateutil
Requires: python3-tomli
Requires: python3-simplemma
Requires: python3-jsonschema
Requires: python3-fasttext-wheel
Requires: python3-voikko
Requires: python3-tensorflow-cpu
Requires: python3-lmdb
Requires: python3-omikuji
Requires: python3-yake
Requires: python3-spacy
%description
[](https://zenodo.org/badge/latestdoi/100936800)
[](https://opensource.org/licenses/Apache-2.0)
[](https://github.com/NatLibFi/Annif/actions/workflows/cicd.yml)
[](https://codecov.io/gh/NatLibFi/Annif)
[](https://codeclimate.com/github/NatLibFi/Annif)
[](https://scrutinizer-ci.com/g/NatLibFi/Annif/?branch=main)
[](https://codebeat.co/projects/github-com-natlibfi-annif-main)
[](https://github.com/NatLibFi/Annif/actions/workflows/codeql.yml)
[](https://sonarcloud.io/dashboard?id=NatLibFi_Annif)
[](https://annif.readthedocs.io/en/latest/index.html)
[](https://github.com/psf/black)
Annif is an automated subject indexing toolkit. It was originally created as
a statistical automated indexing tool that used metadata from the
[Finna.fi](https://finna.fi) discovery interface as a training corpus.
This repo contains a rewritten production version of Annif based on the
[prototype](https://github.com/osma/annif). It is a work in progress, but
already functional for many common tasks.
[Finto AI](https://ai.finto.fi/) is a service based on Annif; see the [source code for Finto AI](https://github.com/NatLibFi/FintoAI).
# Basic install
Annif is developed and tested on Linux. If you want to run Annif on Windows or Mac OS, the recommended way is to use Docker (see below) or a Linux virtual machine.
You will need Python 3.8+ to install Annif.
The recommended way is to install Annif from
[PyPI](https://pypi.org/project/annif/) into a virtual environment.
python3 -m venv annif-venv
source annif-venv/bin/activate
pip install annif
You will also need NLTK data files:
python -m nltk.downloader punkt
Start up the application:
annif
See [Getting Started](https://github.com/NatLibFi/Annif/wiki/Getting-started)
in the wiki for more details.
# Docker install
You can use Annif as a pre-built Docker container. Please see the
[wiki documentation](https://github.com/NatLibFi/Annif/wiki/Usage-with-Docker)
for details.
# Development install
A development version of Annif can be installed by cloning the [GitHub
repository](https://github.com/NatLibFi/Annif).
[Poetry](https://python-poetry.org/) is used for managing dependencies and virtual environment for the development version.
See [CONTRIBUTING.md](CONTRIBUTING.md) for information on [unit tests](CONTRIBUTING.md#unit-tests), [code style](CONTRIBUTING.md#code-style), [development flow](CONTRIBUTING.md#development-flow) etc. details that are useful when participating in Annif development.
## Installation and setup
Clone the repository.
Switch into the repository directory.
Install [pipx](https://pypa.github.io/pipx/) and Poetry if you don't have them. First pipx:
python3 -m pip install --user pipx
python3 -m pipx ensurepath
Open a new shell, and then install Poetry:
pipx install poetry
Poetry can be installed also without pipx: check the [Poetry documentation](https://python-poetry.org/docs/master/#installation).
Create a virtual environment and install dependencies:
poetry install
By default development dependencies are included. Use option `-E` to install dependencies for selected optional features (`-E "extra1 extra2"` for multiple extras), or install all of them with `--all-extras`. By default the virtual environment directory is not under the project directory, but there is a [setting for selecting this](https://python-poetry.org/docs/configuration/#virtualenvsin-project).
Enter the virtual environment:
poetry shell
You will also need NLTK data files:
python -m nltk.downloader punkt
Start up the application:
annif
# Getting help
Many resources are available:
* [Usage documentation in the wiki](https://github.com/NatLibFi/Annif/wiki)
* [Annif tutorial](https://github.com/NatLibFi/Annif-tutorial) for learning to use Annif
* [annif-users](https://groups.google.com/forum/#!forum/annif-users) discussion forum
* [Internal API documentation](https://annif.readthedocs.io) on ReadTheDocs
* [annif.org](https://annif.org) project web site
# Publications / How to cite
Two articles about Annif have been published in peer-reviewed Open Access
journals. The software itself is also archived on Zenodo and
has a [citable DOI](https://doi.org/10.5281/zenodo.5654173).
## Citing the software itself
See "Cite this repository" in the details of the repository.
## Annif articles
-
Suominen, O.; Inkinen, J.; Lehtinen, M., 2022.
Annif and Finto AI: Developing and Implementing Automated Subject Indexing.
JLIS.It, 13(1), pp. 265–282. URL:
https://www.jlis.it/index.php/jlis/article/view/437
See BibTex
@article{suominen2022annif,
title={Annif and Finto AI: Developing and Implementing Automated Subject Indexing},
author={Suominen, Osma and Inkinen, Juho and Lehtinen, Mona},
journal={JLIS.it},
volume={13},
number={1},
pages={265--282},
year={2022},
doi = {10.4403/jlis.it-12740},
url={https://www.jlis.it/index.php/jlis/article/view/437},
}
-
Suominen, O.; Koskenniemi, I, 2022.
Annif Analyzer Shootout: Comparing text lemmatization methods for automated subject indexing.
Code4Lib Journal, (54). URL:
https://journal.code4lib.org/articles/16719
See BibTex
@article{suominen2022analyzer,
title={Annif Analyzer Shootout: Comparing text lemmatization methods for automated subject indexing},
author={Suominen, Osma and Koskenniemi, Ilkka},
journal={Code4Lib J.},
number={54},
year={2022},
url={https://journal.code4lib.org/articles/16719},
}
-
Suominen, O., 2019. Annif: DIY automated subject indexing using multiple
algorithms. LIBER Quarterly, 29(1), pp.1–25. DOI:
https://doi.org/10.18352/lq.10285
See BibTex
@article{suominen2019annif,
title={Annif: DIY automated subject indexing using multiple algorithms},
author={Suominen, Osma},
journal={{LIBER} Quarterly},
volume={29},
number={1},
pages={1--25},
year={2019},
doi = {10.18352/lq.10285},
url = {https://doi.org/10.18352/lq.10285}
}
# License
The code in this repository is licensed under Apache License 2.0, except for the
dependencies included under `annif/static/css` and `annif/static/js`,
which have their own licenses, see the file headers for details.
Please note that the [YAKE](https://github.com/LIAAD/yake) library is licended
under [GPLv3](https://www.gnu.org/licenses/gpl-3.0.txt), while Annif is
licensed under the Apache License 2.0. The licenses are compatible, but
depending on legal interpretation, the terms of the GPLv3 (for example the
requirement to publish corresponding source code when publishing an executable
application) may be considered to apply to the whole of Annif+Yake if you
decide to install the optional Yake dependency.
%package -n python3-annif
Summary: Automated subject indexing and classification tool
Provides: python-annif
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-annif
[](https://zenodo.org/badge/latestdoi/100936800)
[](https://opensource.org/licenses/Apache-2.0)
[](https://github.com/NatLibFi/Annif/actions/workflows/cicd.yml)
[](https://codecov.io/gh/NatLibFi/Annif)
[](https://codeclimate.com/github/NatLibFi/Annif)
[](https://scrutinizer-ci.com/g/NatLibFi/Annif/?branch=main)
[](https://codebeat.co/projects/github-com-natlibfi-annif-main)
[](https://github.com/NatLibFi/Annif/actions/workflows/codeql.yml)
[](https://sonarcloud.io/dashboard?id=NatLibFi_Annif)
[](https://annif.readthedocs.io/en/latest/index.html)
[](https://github.com/psf/black)
Annif is an automated subject indexing toolkit. It was originally created as
a statistical automated indexing tool that used metadata from the
[Finna.fi](https://finna.fi) discovery interface as a training corpus.
This repo contains a rewritten production version of Annif based on the
[prototype](https://github.com/osma/annif). It is a work in progress, but
already functional for many common tasks.
[Finto AI](https://ai.finto.fi/) is a service based on Annif; see the [source code for Finto AI](https://github.com/NatLibFi/FintoAI).
# Basic install
Annif is developed and tested on Linux. If you want to run Annif on Windows or Mac OS, the recommended way is to use Docker (see below) or a Linux virtual machine.
You will need Python 3.8+ to install Annif.
The recommended way is to install Annif from
[PyPI](https://pypi.org/project/annif/) into a virtual environment.
python3 -m venv annif-venv
source annif-venv/bin/activate
pip install annif
You will also need NLTK data files:
python -m nltk.downloader punkt
Start up the application:
annif
See [Getting Started](https://github.com/NatLibFi/Annif/wiki/Getting-started)
in the wiki for more details.
# Docker install
You can use Annif as a pre-built Docker container. Please see the
[wiki documentation](https://github.com/NatLibFi/Annif/wiki/Usage-with-Docker)
for details.
# Development install
A development version of Annif can be installed by cloning the [GitHub
repository](https://github.com/NatLibFi/Annif).
[Poetry](https://python-poetry.org/) is used for managing dependencies and virtual environment for the development version.
See [CONTRIBUTING.md](CONTRIBUTING.md) for information on [unit tests](CONTRIBUTING.md#unit-tests), [code style](CONTRIBUTING.md#code-style), [development flow](CONTRIBUTING.md#development-flow) etc. details that are useful when participating in Annif development.
## Installation and setup
Clone the repository.
Switch into the repository directory.
Install [pipx](https://pypa.github.io/pipx/) and Poetry if you don't have them. First pipx:
python3 -m pip install --user pipx
python3 -m pipx ensurepath
Open a new shell, and then install Poetry:
pipx install poetry
Poetry can be installed also without pipx: check the [Poetry documentation](https://python-poetry.org/docs/master/#installation).
Create a virtual environment and install dependencies:
poetry install
By default development dependencies are included. Use option `-E` to install dependencies for selected optional features (`-E "extra1 extra2"` for multiple extras), or install all of them with `--all-extras`. By default the virtual environment directory is not under the project directory, but there is a [setting for selecting this](https://python-poetry.org/docs/configuration/#virtualenvsin-project).
Enter the virtual environment:
poetry shell
You will also need NLTK data files:
python -m nltk.downloader punkt
Start up the application:
annif
# Getting help
Many resources are available:
* [Usage documentation in the wiki](https://github.com/NatLibFi/Annif/wiki)
* [Annif tutorial](https://github.com/NatLibFi/Annif-tutorial) for learning to use Annif
* [annif-users](https://groups.google.com/forum/#!forum/annif-users) discussion forum
* [Internal API documentation](https://annif.readthedocs.io) on ReadTheDocs
* [annif.org](https://annif.org) project web site
# Publications / How to cite
Two articles about Annif have been published in peer-reviewed Open Access
journals. The software itself is also archived on Zenodo and
has a [citable DOI](https://doi.org/10.5281/zenodo.5654173).
## Citing the software itself
See "Cite this repository" in the details of the repository.
## Annif articles
-
Suominen, O.; Inkinen, J.; Lehtinen, M., 2022.
Annif and Finto AI: Developing and Implementing Automated Subject Indexing.
JLIS.It, 13(1), pp. 265–282. URL:
https://www.jlis.it/index.php/jlis/article/view/437
See BibTex
@article{suominen2022annif,
title={Annif and Finto AI: Developing and Implementing Automated Subject Indexing},
author={Suominen, Osma and Inkinen, Juho and Lehtinen, Mona},
journal={JLIS.it},
volume={13},
number={1},
pages={265--282},
year={2022},
doi = {10.4403/jlis.it-12740},
url={https://www.jlis.it/index.php/jlis/article/view/437},
}
-
Suominen, O.; Koskenniemi, I, 2022.
Annif Analyzer Shootout: Comparing text lemmatization methods for automated subject indexing.
Code4Lib Journal, (54). URL:
https://journal.code4lib.org/articles/16719
See BibTex
@article{suominen2022analyzer,
title={Annif Analyzer Shootout: Comparing text lemmatization methods for automated subject indexing},
author={Suominen, Osma and Koskenniemi, Ilkka},
journal={Code4Lib J.},
number={54},
year={2022},
url={https://journal.code4lib.org/articles/16719},
}
-
Suominen, O., 2019. Annif: DIY automated subject indexing using multiple
algorithms. LIBER Quarterly, 29(1), pp.1–25. DOI:
https://doi.org/10.18352/lq.10285
See BibTex
@article{suominen2019annif,
title={Annif: DIY automated subject indexing using multiple algorithms},
author={Suominen, Osma},
journal={{LIBER} Quarterly},
volume={29},
number={1},
pages={1--25},
year={2019},
doi = {10.18352/lq.10285},
url = {https://doi.org/10.18352/lq.10285}
}
# License
The code in this repository is licensed under Apache License 2.0, except for the
dependencies included under `annif/static/css` and `annif/static/js`,
which have their own licenses, see the file headers for details.
Please note that the [YAKE](https://github.com/LIAAD/yake) library is licended
under [GPLv3](https://www.gnu.org/licenses/gpl-3.0.txt), while Annif is
licensed under the Apache License 2.0. The licenses are compatible, but
depending on legal interpretation, the terms of the GPLv3 (for example the
requirement to publish corresponding source code when publishing an executable
application) may be considered to apply to the whole of Annif+Yake if you
decide to install the optional Yake dependency.
%package help
Summary: Development documents and examples for annif
Provides: python3-annif-doc
%description help
[](https://zenodo.org/badge/latestdoi/100936800)
[](https://opensource.org/licenses/Apache-2.0)
[](https://github.com/NatLibFi/Annif/actions/workflows/cicd.yml)
[](https://codecov.io/gh/NatLibFi/Annif)
[](https://codeclimate.com/github/NatLibFi/Annif)
[](https://scrutinizer-ci.com/g/NatLibFi/Annif/?branch=main)
[](https://codebeat.co/projects/github-com-natlibfi-annif-main)
[](https://github.com/NatLibFi/Annif/actions/workflows/codeql.yml)
[](https://sonarcloud.io/dashboard?id=NatLibFi_Annif)
[](https://annif.readthedocs.io/en/latest/index.html)
[](https://github.com/psf/black)
Annif is an automated subject indexing toolkit. It was originally created as
a statistical automated indexing tool that used metadata from the
[Finna.fi](https://finna.fi) discovery interface as a training corpus.
This repo contains a rewritten production version of Annif based on the
[prototype](https://github.com/osma/annif). It is a work in progress, but
already functional for many common tasks.
[Finto AI](https://ai.finto.fi/) is a service based on Annif; see the [source code for Finto AI](https://github.com/NatLibFi/FintoAI).
# Basic install
Annif is developed and tested on Linux. If you want to run Annif on Windows or Mac OS, the recommended way is to use Docker (see below) or a Linux virtual machine.
You will need Python 3.8+ to install Annif.
The recommended way is to install Annif from
[PyPI](https://pypi.org/project/annif/) into a virtual environment.
python3 -m venv annif-venv
source annif-venv/bin/activate
pip install annif
You will also need NLTK data files:
python -m nltk.downloader punkt
Start up the application:
annif
See [Getting Started](https://github.com/NatLibFi/Annif/wiki/Getting-started)
in the wiki for more details.
# Docker install
You can use Annif as a pre-built Docker container. Please see the
[wiki documentation](https://github.com/NatLibFi/Annif/wiki/Usage-with-Docker)
for details.
# Development install
A development version of Annif can be installed by cloning the [GitHub
repository](https://github.com/NatLibFi/Annif).
[Poetry](https://python-poetry.org/) is used for managing dependencies and virtual environment for the development version.
See [CONTRIBUTING.md](CONTRIBUTING.md) for information on [unit tests](CONTRIBUTING.md#unit-tests), [code style](CONTRIBUTING.md#code-style), [development flow](CONTRIBUTING.md#development-flow) etc. details that are useful when participating in Annif development.
## Installation and setup
Clone the repository.
Switch into the repository directory.
Install [pipx](https://pypa.github.io/pipx/) and Poetry if you don't have them. First pipx:
python3 -m pip install --user pipx
python3 -m pipx ensurepath
Open a new shell, and then install Poetry:
pipx install poetry
Poetry can be installed also without pipx: check the [Poetry documentation](https://python-poetry.org/docs/master/#installation).
Create a virtual environment and install dependencies:
poetry install
By default development dependencies are included. Use option `-E` to install dependencies for selected optional features (`-E "extra1 extra2"` for multiple extras), or install all of them with `--all-extras`. By default the virtual environment directory is not under the project directory, but there is a [setting for selecting this](https://python-poetry.org/docs/configuration/#virtualenvsin-project).
Enter the virtual environment:
poetry shell
You will also need NLTK data files:
python -m nltk.downloader punkt
Start up the application:
annif
# Getting help
Many resources are available:
* [Usage documentation in the wiki](https://github.com/NatLibFi/Annif/wiki)
* [Annif tutorial](https://github.com/NatLibFi/Annif-tutorial) for learning to use Annif
* [annif-users](https://groups.google.com/forum/#!forum/annif-users) discussion forum
* [Internal API documentation](https://annif.readthedocs.io) on ReadTheDocs
* [annif.org](https://annif.org) project web site
# Publications / How to cite
Two articles about Annif have been published in peer-reviewed Open Access
journals. The software itself is also archived on Zenodo and
has a [citable DOI](https://doi.org/10.5281/zenodo.5654173).
## Citing the software itself
See "Cite this repository" in the details of the repository.
## Annif articles
-
Suominen, O.; Inkinen, J.; Lehtinen, M., 2022.
Annif and Finto AI: Developing and Implementing Automated Subject Indexing.
JLIS.It, 13(1), pp. 265–282. URL:
https://www.jlis.it/index.php/jlis/article/view/437
See BibTex
@article{suominen2022annif,
title={Annif and Finto AI: Developing and Implementing Automated Subject Indexing},
author={Suominen, Osma and Inkinen, Juho and Lehtinen, Mona},
journal={JLIS.it},
volume={13},
number={1},
pages={265--282},
year={2022},
doi = {10.4403/jlis.it-12740},
url={https://www.jlis.it/index.php/jlis/article/view/437},
}
-
Suominen, O.; Koskenniemi, I, 2022.
Annif Analyzer Shootout: Comparing text lemmatization methods for automated subject indexing.
Code4Lib Journal, (54). URL:
https://journal.code4lib.org/articles/16719
See BibTex
@article{suominen2022analyzer,
title={Annif Analyzer Shootout: Comparing text lemmatization methods for automated subject indexing},
author={Suominen, Osma and Koskenniemi, Ilkka},
journal={Code4Lib J.},
number={54},
year={2022},
url={https://journal.code4lib.org/articles/16719},
}
-
Suominen, O., 2019. Annif: DIY automated subject indexing using multiple
algorithms. LIBER Quarterly, 29(1), pp.1–25. DOI:
https://doi.org/10.18352/lq.10285
See BibTex
@article{suominen2019annif,
title={Annif: DIY automated subject indexing using multiple algorithms},
author={Suominen, Osma},
journal={{LIBER} Quarterly},
volume={29},
number={1},
pages={1--25},
year={2019},
doi = {10.18352/lq.10285},
url = {https://doi.org/10.18352/lq.10285}
}
# License
The code in this repository is licensed under Apache License 2.0, except for the
dependencies included under `annif/static/css` and `annif/static/js`,
which have their own licenses, see the file headers for details.
Please note that the [YAKE](https://github.com/LIAAD/yake) library is licended
under [GPLv3](https://www.gnu.org/licenses/gpl-3.0.txt), while Annif is
licensed under the Apache License 2.0. The licenses are compatible, but
depending on legal interpretation, the terms of the GPLv3 (for example the
requirement to publish corresponding source code when publishing an executable
application) may be considered to apply to the whole of Annif+Yake if you
decide to install the optional Yake dependency.
%prep
%autosetup -n annif-0.61.0
%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-annif -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue May 30 2023 Python_Bot - 0.61.0-1
- Package Spec generated