Skip to content

JoaoDavid/MLVP

Repository files navigation

MLVP Logo

Installing dependencies

Within the repository root location, open the command line and run the following commands.

npm install

Install front-end npm dependencies

pip install -r requirements.pip

Install back-end python dependencies

Run in Development mode

npm start

Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.

The page will reload if you make edits.
You will also see any lint errors in the console.

python ./backend/serverDev.py

Runs the back-end in the development mode.
Listening for HTTP requests at localhost:8080

python create-node.py "Block Category" "Block Name" "template-folder-name"

Creates the four front-end and single back-end class files for the new block in the respective category directories

Deployment

npm run build

Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance. Then run it using serve -s build

python ./backend/server.py

Runs the back-end in the production mode.
Listening for HTTP requests at 194.117.20.237:443

journalctl -u SERVICE_NAME.service --since today

About

A Visual Programming Language (VPL) for the creation of ML pipelines. This language is enriched with semantic constraints regarding the behaviour of each component, along with a verification methodology to detect common ML bugs. I developed a frontend using React with TypeScript, where data scientists could create pipelines by dragging, dropping…

Resources

Stars

Watchers

Forks

Contributors