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A sentiment and emotion analysis server in Python


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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.


The stable version can be installed in three ways.

Through PIP

pip install -U --user senpy

Alternatively, you can use the development version:

git clone
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 --default-plugins.

To add custom plugins, add a volume and tell senpy where to find the plugins: docker run -ti -p 5000:5000 -v <PATH OF PLUGINS>:/plugins gsiupm/senpy --default-plugins -f /plugins



This command will run the senpy container using the latest image available, mounting your current folder so you get your latest code:

# Python 3.5
make dev
# Python 2.7
make dev-2.7

Building a docker image

# Python 3.5
make build-3.5
# Python 2.7
make build-2.7


make test


This command will run the senpy server listening on localhost:5000

# Python 3.5
make run-3.5
# Python 2.7
make run-2.7


However, the easiest and recommended way is to just use the command-line tool to load your plugins and launch the server.


or, alternatively:

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.


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.

MixedEmotions Logo img/eu-flag.jpg


A sentiment and emotion analysis server in Python







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