Metadata-Version: 2.1
Name: deepaas
Version: 1.1.0
Summary: DEEPaaS is a REST API to expose a machine learning model.
Home-page: https://github.com/indigo-dc/deepaas
Author: Alvaro Lopez Garcia
Author-email: aloga@ifca.unican.es
License: Apache-2
Project-URL: Bug Tracker, https://github.com/indigo-dc/deepaas/issues
Project-URL: Documentation, https://deepaas.readthedocs.io/
Description: # DEEPaaS
        
        [![GitHub license](https://img.shields.io/github/license/indigo-dc/DEEPaaS.svg)](https://github.com/indigo-dc/DEEPaaS/blob/master/LICENSE)
        [![GitHub release](https://img.shields.io/github/release/indigo-dc/DEEPaaS.svg)](https://github.com/indigo-dc/DEEPaaS/releases)
        [![PyPI](https://img.shields.io/pypi/v/deepaas.svg)](https://pypi.python.org/pypi/deepaas)
        [![Python versions](https://img.shields.io/pypi/pyversions/deepaas.svg)](https://pypi.python.org/pypi/deepaas)
        [![Build Status](https://jenkins.indigo-datacloud.eu/buildStatus/icon?job=Pipeline-as-code%2FDEEPaaS%2Fmaster)](https://jenkins.indigo-datacloud.eu/job/Pipeline-as-code/job/DEEPaaS/job/master/)
        [![DOI](https://joss.theoj.org/papers/10.21105/joss.01517/status.svg)](https://doi.org/10.21105/joss.01517)
        
        <img src="https://marketplace.deep-hybrid-datacloud.eu/images/logo-deep.png" width=200 alt="DEEP-Hybrid-DataCloud logo"/>
        
        DEEP as a Service API (DEEPaaS API) is a REST API built on
        [aiohttp](https://docs.aiohttp.org/) 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](https://github.com/OAI/OpenAPI-Specification).
        
        # Documentation
        
        The DEEPaaS documentation is hosted on [Read the Docs](https://deepaas.readthedocs.io/).
        
        
        ## 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](https://joss.theoj.org/papers/10.21105/joss.01517/status.svg)](https://doi.org/10.21105/joss.01517)
        
        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](https://doi.org/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.
        
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Environment :: Web Environment
Classifier: Framework :: AsyncIO
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: System Administrators
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Interface Engine/Protocol Translator
Requires-Python: >=3.6
Description-Content-Type: text/markdown; charset=UTF-8
