Skip to main content

DEEPaaS is a REST API to expose a machine learning model.

Project description

DEEPaaS

GitHub license GitHub release PyPI Python versions Build Status DOI

DEEP-Hybrid-DataCloud logo

DEEP as a Service API (DEEPaaS API) is a REST API built on aiohttp that allows to provide easy access to machine learning, deep learning and artificial intelligence models. By using the DEEPaaS API users can easily run a REST API in front of their model, thus accessing its functionality via HTTP calls. DEEPaaS API leverages the OpenAPI specification.

Documentation

The DEEPaaS documentation is hosted on Read the Docs.

Quickstart

The best way to quickly try the DEEPaaS API is through:

make run

This command will install a virtualenv (in the virtualenv directory) with DEEPaaS and all its dependencies and will run the DEEPaaS REST API, listening on 127.0.0.1:5000. If you browse to http://127.0.0.1:5000 you will get the Swagger documentation page (i.e. the Swagger web UI).

Develop mode

If you want to run the code in develop mode (i.e. pip install -e), you can issue the following command before:

make develop

Citing

DOI

If you are using this software and want to cite it in any work, please use the following:

Lopez Garcia, A. "DEEPaaS API: a REST API for Machine Learning and Deep Learning models". In: Journal of Open Source Software 4(42) (2019), pp. 1517. ISSN: 2475-9066. DOI: 10.21105/joss.01517

You can also use the following BibTeX entry:

@article{Lopez2019DEEPaaS,
    journal = {Journal of Open Source Software},
    doi = {10.21105/joss.01517},
    issn = {2475-9066},
    number = {42},
    publisher = {The Open Journal},
    title = {DEEPaaS API: a REST API for Machine Learning and Deep Learning models},
    url = {http://dx.doi.org/10.21105/joss.01517},
    volume = {4},
    author = {L{\'o}pez Garc{\'i}a, {\'A}lvaro},
    pages = {1517},
    date = {2019-10-25},
    year = {2019},
    month = {10},
    day = {25},}

Acknowledgements

This software has been developed within the DEEP-Hybrid-DataCloud (Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud) project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 777435.

Download files

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

Source Distribution

deepaas-2.1.0.tar.gz (253.9 kB view details)

Uploaded Source

File details

Details for the file deepaas-2.1.0.tar.gz.

File metadata

  • Download URL: deepaas-2.1.0.tar.gz
  • Upload date:
  • Size: 253.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.9

File hashes

Hashes for deepaas-2.1.0.tar.gz
Algorithm Hash digest
SHA256 95cf2d0f6a2e54cef6a67d9d1d05a5ba5d61ad8f20744328891690bfb93f74b7
MD5 613b9752a3b6eb1ee5967476520d1137
BLAKE2b-256 ccca5d1681816e102798bcca06ec9d2f63f4f7428782c8c6218083eb03e1d0f3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page