# feast-denormalized-tutorial
Feast + Denormalized

This repository contains an example application of using [Denormalized](https://www.denormalized.io/) to process features in real-time and sink them to an online feast store.


## Getting started

[Install UV](https://docs.astral.sh/uv/getting-started/installation/)

- `uv venv --python 3.12 &&  source .venv/bin/activate`
- `uv sync --dev`
- `uv pip install -e .`


- Start kafka in docker `docker run -p 9092:9092 --name kafka apache/kafka`
- create the feature store: `python src/feature_repo/` 
- Start emitting events: `python src/session_generator/`
- Start the pipelines: `python src/pipelines/`

### Docker

It is also possible to run the example using the provider docker-compose file:

- `docker compose up --build`

The features can be viewed in realtime using the `print_features.ipynb` notebook
`jupyter-lab`