Anonymized data from the Diffix-protected datasets is inherently restricted. The analyst needs to be familiar with the imposed limitations, and knowledgeable of possible workarounds. The aim of this project is to build tools to automatically extract a high-level picture of the shape of a given data set whilst intelligently navigating the restrictions imposed by Diffix.
You will need an authorization key for the Aircloak API. This should be assigned to the AIRCLOAK_API_KEY
variable in your environment.
Building and running can be simply done using Docker:
docker build -t explorer .
docker run -it --rm -e AIRCLOAK_API_KEY -p 5000:80 explorer
If you are running in a unix-like environment, you use or adapt the build.sh and run.sh scripts.
The simplest way to get started is with VS Code's remote containers feature.
Detailed information on setting this up can be found here.
The short version:
- Install Docker
- Install Visual Studio Code
- Add the remote development pack in VS Code
- Clone the Repo:
git clone https://github.com/diffix/explorer.git - Start VS Code and from the command palette (
F1) run Remote-Containers: Open Folder in Container and select the project root folder.
If you want to use an editor other than VS Code, you will need .NET Core 3.1 to compile the source files on your local machine.