Rapid data visualization engine
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A Collaborative Planning Tool. dataviva.info

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DataViva will run on all modern browsers so long as they have Javascript turned on and full support for SVG graphics. This includes the latest versions of Firefox, Chrome (Chromium), Safari (WebKit), Opera and IE.

Note: Internet Explorer versions 8 and below will not work as they do not have SVG support built in.


DataViva is a web platform built using Flask, an open source Python library for interacting with HTTP. this installation guide is written assuming a Linux or Linux-like environment. The following software is required to be installed locally in order to get DataViva running:

  • Python
  • MySQL
  • Redis (at least version 2.8.6)
  1. Clone from github (this will create dataviva folder in the current directory)

    git clone https://github.com/alexandersimoes/dataviva.git
  2. [optional] Create a virtual environment. We suggest installing virtualenv with virtualenvwrapper especially if the machine you are using is used for many other web projects. This allows python libraries to be installed easily and specifically on a per proeject basis.

    Once this is complete, run the following to initialize your dataviva environment.

    mkvirtualenv dataviva
    workon dataviva
  3. Install the required Python libraries

    pip install -r requirements.txt
  4. Install librsvg

    apt-get install librsvg2-bin (Ubuntu)
    brew install librsvg (Mac)
  5. Create a MySQL database and import the latest database dump

    # Import the schema
    gzip -dc DV2015_DB/*/schema/*.sql.gz | mysql -u USERNAME -p -h DB_NAME
    # Import the content
    gzip -dc DV2015_DB/*/content/*.sql.gz | mysql -u USERNAME -p -h DB_NAME
  6. Set the following environment variables

    (if using virtualenv) add the following to to the bottom of your virtualenv activate file (virtualenv_root/bin/activate).

    export DATAVIVA_SECRET_KEY=my-super-secret-k3y
    export DATAVIVA_DB_NAME=dataviva
    export DATAVIVA_DB_USER=root
    export DATAVIVA_DB_PW=my-pw
    * export DATAVIVA_ACCOUNTS=True
    export DATAVIVA_API_BASE_URL=http://api.staging.dataviva.info/
    * only necessary if you want to enable user accounts
  7. Handle en/pt subdomains for translations. For example, when testing locally you may add these lines to /etc/hosts en.localhost pt.localhost
  8. Run the site locally!

     python run.py runserver