A Declarative framework for Building, Maintaining, and Analyzing Graph Data π
Nodestream allows you to work with graphs declaratively. With nodestream, you unlock a bounty of features purpose built for working with graphs. Semantically model your graph and map labels and properties directly to your data. Better yet, you are not locked into your choices. Nodestream works with you as you evolve your application by providing migration utilities to change your data schema. Nodestream even decouples you from the underyling database technology so you can even change databases.
- Connect to data sources like Kafka, files, apis, and more!
- Evolve your application over time with database migrations (Docs)
- Use your favorite Graph Database to fit any tech stack (Docs)
- Clean up your own data with TTLs (Docs)
- Infinite Customizability Since Nearly Everything is Pluggable!
Website β’ Blog β’ Discussions β’ Contributing β’ Contributing Developer Guides β’ Talks from Maintainers
Nodestream has a pleasant CLI interface to get new projects up and running fast.
Not a fan of the defaults? You can change out databases very easily
Then you can start to model your data and nodestream will evolve your database for you. No more messing with constraints or writing database queries.
Conviced? Install nodestream with pip
to get started.
pip install nodestream
nodestream new --database neo4j my_project && cd my_project
nodestream run sample -v
We highly recommend following our tutorials here
Nodestream is built on a Highly Pluggable and Modular Architecture. Thus... we have a lot of packages to keep track of.
Nodestream is a community project. We welcome all contributions. Be sure to checkout or Contributing Docs and our Code of Conduct before contributing.
Need a quick reference guide on how to contribute? Here you go!
To get started you'll need to install poery.
curl -sSL https://install.python-poetry.org | python3 -
You then can install the project dependencies with the following command:
poetry install
No need to active a virtual environment. Poetry handles that for you with poetry run
and poetry shell
.
To run tests for the entire project, run the following command:
poetry run pytest