.. image:: img/header.png :height: 6em :target: http://demos.gsi.dit.upm.es/senpy .. image:: https://travis-ci.org/gsi-upm/senpy.svg?branch=master :target: https://travis-ci.org/gsi-upm/senpy Senpy lets you create sentiment analysis web services easily, fast and using a well known API. As a bonus, senpy services use semantic vocabularies (e.g. `NIF `_, `Marl `_, `Onyx `_) and formats (turtle, JSON-LD, xml-rdf). Have you ever wanted to turn your sentiment analysis algorithms into a service? With senpy, now you can. It provides all the tools so you just have to worry about improving your algorithms: `See it in action. `_ Installation ------------ The stable version can be installed in three ways. Through PIP *********** .. code:: bash pip install --user senpy Alternatively, you can use the development version: .. code:: bash git clone http://github.com/gsi-upm/senpy cd senpy pip install --user . If you want to install senpy globally, use sudo instead of the ``--user`` flag. Docker Image ************ Build the image or use the pre-built one: ``docker run -ti -p 5000:5000 gsiupm/senpy --host 0.0.0.0 --default-plugins``. To add custom plugins, add a volume and tell senpy where to find the plugins: ``docker run -ti -p 5000:5000 -v :/plugins gsiupm/senpy --host 0.0.0.0 --default-plugins -f /plugins`` Usage ----- However, the easiest and recommended way is to just use the command-line tool to load your plugins and launch the server. .. code:: bash senpy or, alternatively: .. code:: bash python -m senpy This will create a server with any modules found in the current path. For more options, see the `--help` page. Alternatively, you can use the modules included in senpy to build your own application. Deploying on Heroku ------------------- Use a free heroku instance to share your service with the world. Just use the example Procfile in this repository, or build your own. `DEMO on heroku `_ For more information, check out the `documentation `_. ------------------------------------------------------------------------------------ Acknowledgement --------------- This development has been partially funded by the European Union through the MixedEmotions Project (project number H2020 655632), as part of the `RIA ICT 15 Big data and Open Data Innovation and take-up` programme. .. image:: img/me.png :target: http://mixedemotions-project.eu :height: 100px :alt: MixedEmotions Logo .. image:: img/eu-flag.jpg :height: 100px :target: http://ec.europa.eu/research/participants/portal/desktop/en/opportunities/index.html