simiscore-biblio

An ML API to compute similarity scores between meta information about sentence examples. The API is programmed with the fastapi Python package, uses the packages datasketch and kshingle to compute similarity scores. The deployment is configured for Docker Compose.

Docker Deployment

Call Docker Compose

export API_PORT=8081
docker-compose -f docker-compose.yml up --build
# or as oneliner:

API_PORT=8081 docker-compose up --build

(Start docker daemon before, e.g. open /Applications/Docker.app on MacOS).

Check

curl http://localhost:8081

Notes: Only main.py is used in Dockerfile.

Local Development

Install a virtual environment

python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt --no-cache-dir
pip install -r requirements-dev.txt --no-cache-dir

(If your git repo is stored in a folder with whitespaces, then don't use the subfolder .venv. Use an absolute path without whitespaces.)

Start Server

source .venv/bin/activate
# uvicorn app.main:app --reload
gunicorn app.main:app --reload --bind=0.0.0.0:8081 \
    --worker-class=uvicorn.workers.UvicornH11Worker \
    --workers=1 --timeout=600

Run some requests

curl -X POST "http://localhost:8081/similarities/" \
    -H "accept: application/json" \
    -H "Content-Type: application/json" \
    -d '[
        "Christ, Lena: Die Rumplhanni. In: Deutsche Literatur von Frauen, Berlin: Directmedia Publ. 2001 [1917], S. 13229", 
        "Christ, Lena: Erinnerungen einer Überflüssigen. In: Deutsche Literatur von Frauen, Berlin: Directmedia Publ. 2001 [1912], S. 12498"
    ]'

Other commands and help

• Check syntax: flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')
• Run Unit Tests: PYTHONPATH=. pytest

• Show the docs: http://localhost:8081/docs
• Show Redoc: http://localhost:8081/redoc

Clean up

find . -type f -name "*.pyc" | xargs rm
find . -type d -name "__pycache__" | xargs rm -r
rm -r .pytest_cache
rm -r .venv

Appendix

Citation

@software{ulf_hamster_2022_7096467,
  author       = {Ulf Hamster and
                  Luise Köhler},
  title        = {simiscore-biblio: ML API for bibliographic similarities},
  month        = sep,
  year         = 2022,
  publisher    = {Zenodo},
  version      = {0.1.0},
  doi          = {10.5281/zenodo.7096467},
  url          = {https://doi.org/10.5281/zenodo.7096467}
}

References

• Sebastián Ramírez, 2018, FastAPI, https://github.com/tiangolo/fastapi
• Eric Zhu, Vadim Markovtsev, aastafiev, Wojciech Łukasiewicz, ae-foster, Sinusoidal36, Ekevoo, Kevin Mann, Keyur Joshi, Peter Kubov, Qin TianHuan, Spandan Thakur, Stefano Ortolani, Titusz, Vojtech Letal, Zac Bentley, fpug, & oisincar. (2021). ekzhu/datasketch: v1.5.4 (v1.5.4). Zenodo. https://doi.org/10.5281/zenodo.5758425
• Ulf Hamster. (2022). kshingle: Shingling text data (0.10.0). Zenodo. https://doi.org/10.5281/zenodo.7096407
• Leonard Richardson, 2007, Beautiful soup, https://www.crummy.com/software/BeautifulSoup/

Support

Please open an issue for support.

Contributing

Please contribute using Github Flow. Create a branch, add commits, and open a pull request.

Acknowledgements

The "Evidence" project was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 433249742 (GU 798/27-1; GE 1119/11-1).

Maintenance

• till 31.Aug.2023 (v0.1.0) the code repository was maintained within the DFG project 433249742
• since 01.Sep.2023 (v0.2.0) the code repository is maintained by Ulf Hamster.