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Problem

When surveys are sent out to people to collect feedback in the form of text, it is difficult to parse through this text to obtain fast and actionable insights.

Solution

Provide a Juptyer Notebook and corresponding documentation that will walk someone through the process of uploading their survey to a Juptyer Notebook and Python code to provide a high-level summary of the textual data so it can be easily understood. But Juptyer Notebooks, while convenient for developers, do not help non-developers as it is not user friendly.

To make this even simpler for non-technologists, this project should also consider an extremely simple front-end to allow for CSV upload and the display of summary information using basic front-end technologies while using the same Python code for the backend.

Running the app

Without Docker

sudo xcodebuild -license # Needed for Mac since you need GCC due to Cython
pip install -r requirements.txt
python -m spacy download en
python run_app.py

Docker

docker build -t succinct-python .
docker run -d -p 4040:4040 -v /var/uploads/:/tmp/succint_upload/ succinct-python

Running the Huey Consumer

To process tasks that are long running, we use Huey

python ~/opt/miniconda3/bin/huey_consumer.py --verbose app.tasks.get_similar.huey

References

These sources were helpful to get everything up and running

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An easy way for people to get insights from their textual data

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