Skip to main content

DOI License CI/CD codecov Code Climate Scrutinizer Code Quality codebeat badge CodeQL Quality Gate Status docs Code style: 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 discovery interface as a training corpus.

This repo contains a rewritten production version of Annif based on the prototype. It is a work in progress, but already functional for many common tasks.

Finto AI is a service based on Annif; see the source code for Finto AI.

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 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 in the wiki for more details.

Docker install

You can use Annif as a pre-built Docker container. Please see the wiki documentation for details.

Development install

A development version of Annif can be installed by cloning the GitHub repository. Poetry is used for managing dependencies and virtual environment for the development version.

See CONTRIBUTING.md for information on unit tests, code style, 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 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.

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.

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:

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.

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 library is licended under GPLv3, 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.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

annif-0.61.0.tar.gz (461.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

annif-0.61.0-py3-none-any.whl (488.6 kB view details)

Uploaded Python 3

File details

Details for the file annif-0.61.0.tar.gz.

File metadata

  • Download URL: annif-0.61.0.tar.gz
  • Upload date:
  • Size: 461.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.4.1 CPython/3.10.6 Linux/5.15.0-1035-azure

File hashes

Hashes for annif-0.61.0.tar.gz
Algorithm Hash digest
SHA256 142ff674dcaf103eb05ff744c771c9ea4534600290746c6a5331ab6692bf8893
MD5 b98305929c4c13bff94d8451801ae6a4
BLAKE2b-256 9c8dab23892c2c8ea3f61a1ec011012042d1b2f371bfba74bb03e2b4f556bd2b

See more details on using hashes here.

File details

Details for the file annif-0.61.0-py3-none-any.whl.

File metadata

  • Download URL: annif-0.61.0-py3-none-any.whl
  • Upload date:
  • Size: 488.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.4.1 CPython/3.10.6 Linux/5.15.0-1035-azure

File hashes

Hashes for annif-0.61.0-py3-none-any.whl
Algorithm Hash digest
SHA256 88ac4cc97da0f72627c896afa5287316dd1391170937dd879ee418cb9f6a08b1
MD5 33a335c94afb25885304d3c20e6bcc0c
BLAKE2b-256 48ffa7498a97bb07329c8dd5c51f0852b83ba8f017579e2d136e518868fc670f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page