Directory Structure

Each White Label Data instance has a set of directories and files, stored in your GitHub repository, that provide the content and configuration for the application. These files contain a mix of HTML, JSON, and SQL. Because White Label Data is a development platform, you will be editing the files in this directory structure to make changes to your application. The configuration files are used to set up navigation menu and branding, pages, as well as the data visualizations themselves.

Here is a diagram of the overall directory structure:


Folder or File Description
appconfig.json This is the main configuration file for your White Label Data application. It is located at the top of your repository. This file allows you to configure branding, connections, and navigation for the application.
pages This folder contains all of your HTML pages. There is typically one HTML file per page in your application. However, it also possible to create shared HTML templates with the Django templating language using additional files.
static Your static content such as images and CSS go in this folder. This includes your custom logo and styles.
layers These configuration files contain queries, data pipeline steps, figure layout, and data mapping rules that are used to render visualizations. Layers are flattened into a single configuration and named after the top-most layer. This layer name then becomes an HTML tag you can use in your HTML pages.
visualizations Custom HTML visualizations go here. A custom visualization is any visualization that is not using a built-in type. Custom visualizations use simple HTML markup to display your data. It is also possible for advanced users to extend these visualizations with Javascript. Note: the built-in types (Plotly, Mapbox, Single Value indicators, Dropdown Filters, and Date pickers, etc) can still be customized through configuration but are not considered custom visualizations.
extensions For Advanced Users. This folder allows you to create or consume your own API endpoints and write custom queries and transformations in Python.