- python >= 3.6
- virtualenv
- rabbitmq (https://www.rabbitmq.com/download.html)
- Figma App (https://www.figma.com/developers/apps)
- copy the .env.example file into .env, and fill the values according to your needs:
- LOCAL_FOLDER_LOTTIE_FILES is the absolute path of the folder the lottie files and metadata will be saved in
- CONSERVATION_TIME is the number of seconds after which lottie files and their metadata will be deleted
- DEBUG activates Django's debug
- HOST is the url of the API
- FRONT is the url of the front-end
- SECRET_KEY is secret!
- FIGMA_API_URL is the url of the Figma API you use (if you don't want to host it, use https://api.figma.com/v1)
- FIGMA_APP_CLIENT_ID and FIGMA_APP_CLIENT_SECRET are the credentials of your Figma app
- create a virtualenv in the project root (tacos folder) with virtualenv -p python3 env, activate it with source env/bin/activate and set up the environment with pip install -r requirements.txt
- run Rabbitmq with rabbitmq-server
- run your app with python manage.py runserver :, and you're ready to go (Celery will automatically start by running the manage.py with celery -A tacos worker -l info)
In Figma, create a frame named @lottie. That’s where your animation will be rendered. It gets its size and position from that rectangle.
{
“arguments”: {
“loop”: false,
”speed”: 5,
}
}
On Figma Lottie, you’ll be able to connect to your Figma account and paste your Frame link. Then, upload your Lottie files and enjoy your animated mockup 🎉 Edit your animations files or Figma canvas and update the render until you’re happy with the result.