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Tool for collecting, processing and analyzing place-based feedback

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FVH Feedback Map

App for collecting and processing feedback related to geospatial points.

Installation

Using docker-compose (preferred way)

  • Requires that docker is installed on the host system

In project root:

  • sh configure_dev.sh or sh configure_prod.sh to ensure the correct configurations are in use for the intended environment
  • Create empty file kafka2api.env if you are not planning to use Kafka functionality or copy kafka2api.env.sample --> kafka2api.env and correct the values
  • For prod setup, cp .env.prod.sample .env.prod and fill in the correct settings for your prod env
  • docker-compose up -d should then launch the needed docker containers for the env
  • To get started with development, docker exec -it fvhfeedbackmap-web-1 python manage.py createsuperuser should allow creation of a super user for the Django backend
  • Navigating to http://localhost:8000/admin/feedback_map/tag/ should then allow logging in as the super user and creating tags (i.e. feedback categories)
  • Once some tags have been created & published, they should show up in the react UI at http://127.0.0.1:3000/

Installing natively

Prerequisites:

  • Python 3.10+ with pip
  • Node.js 13.3 with ./node_modules/.bin in the PATH
  • Postgres with a db available as configured in django_server/feedback_map_config/settings.py

In project root:

sudo pip install pipenv
cd django_server
pipenv install
pipenv shell
python manage.py migrate
python manage.py createsuperuser
<Configure user to your satisfaction>
python manage.py runserver
<Verify that you can login at 127.0.0.1:8000/admin/ >

If you are sending to and receiving messages from Kafka, you will need ca.pem in both of these directories:

kafka2api/ca.pem
django_server/ca.pem

In react_ui:

npm install yarn
yarn install
yarn start
<Verify that you can login to React UI at 127.0.0.1:3000 using your superuser or courier user credentials>

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  • TypeScript 45.7%
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