diversolab_app

A web application built with SPLENT, derived from the cms_spl product line.

This repository is a thin shell. It declares which features the product installs (see pyproject.toml) and SPLENT composes, validates and runs them.

Run it locally

Your machine only needs Docker, Git and GNU Make. Python, Node and the database all live inside containers, so nothing else has to be installed.

1. Create a workspace

A SPLENT product is not standalone. It lives in a workspace folder next to the SPLENT tooling repositories.

mkdir splent_workspace && cd splent_workspace
git clone https://github.com/diverso-lab/splent_framework.git
git clone https://github.com/diverso-lab/splent_cli.git
git clone https://github.com/splent-io/diversolab_app.git

Those three are all you need to run the product. The SPL catalog (splent_catalog) is only required to create new products or to validate the variability model, and the features themselves are installed from PyPI.

2. Check your Git config file

The CLI container mounts your ~/.gitconfig. If that file does not exist, Docker creates it as an empty directory and installing features fails later. Create it once as a real file.

rm -rf ~/.gitconfig && touch ~/.gitconfig
git config --global user.name "Your Name"
git config --global user.email "you@example.com"

3. Start the SPLENT CLI

cd splent_cli
make setup

That prepares the workspace .env, starts the CLI container and drops you inside it. Every splent command below runs in there. From the host you can also use docker exec splent_cli_container splent <command>.

4. Bring the product up

splent product:select diversolab_app
splent product:resolve        # install the features declared in pyproject.toml
splent product:derive --dev   # build images, run migrations, start the stack
splent db:seed -y             # load demo data, optional

The first derive downloads images and compiles assets, so give it a few minutes. When it finishes the app is served at http://localhost:5125, and splent product:port prints that URL again whenever you need it.

Everyday commands

Command	What it does
splent product:up --dev	Start the stack
splent product:down --dev	Stop the stack
splent product:restart	Restart the Flask app
splent product:logs	Tail the container logs
splent product:console	Python shell with the app loaded
splent feature:status	Features installed in this product
splent db:migrate	Generate and apply a migration
splent product:port	Print the local URL

When something looks wrong

splent product:logs       # what the app actually says
splent doctor             # full workspace diagnosis

splent product:validate goes further and checks that the feature selection satisfies the variability model, so it needs the splent_catalog clone.

Documentation

Everything else, from the feature catalog and the UVL variability model to the full command reference and deployment, lives at docs.splent.io.