A tool for performing declarative transformations of property graphs.
The DTGraph library is a generic framework for transforming property graphs. Transformations are written in our own declarative rule-based DSL (Domain Specific Language) and are compiled into efficient and scalable openCypher scripts. This library supports a wide range of openCypher's compatible backends.
You can install the DTGraph library from the source by cloning the repository using SSH:
git@github.com:yannramusat/DTGraph.git
or using HTTPS:
https://github.com/yannramusat/DTGraph.git
Then, install the library using Python's setup tools:
pip install .
or install it in development mode (the recommended way if you plan to contribute to the project):
pip install -r requirements.txt
There are several supported ways to connect to a database instance:
The following command retrieves and runs a Docker container serving a Neo4j database locally:
sudo docker run --name neo4j5.16 --env=NEO4J_AUTH=none -p 7687:7687 -p 7474:7474 neo4j:5.16.0-community
To connect to this instance, you can refer to the example notebook at examples/Tutorial_Connecting_Neo4j_Docker.ipynb.
The following command retrieves and runs a Docker container serving a Memgraph database locally:
sudo docker run --name memgraph2.14.0 -p 7687:7687 -p 7444:7444 -p 3000:3000 memgraph/memgraph-platform:2.14.0-memgraph2.14.0-lab2.11.1
To connect to this instance, you can refer to the example notebook at examples/Tutorial_Connecting_Memgraph_Docker.ipynb.
We provide some tutorials in the form of Jupyter notebooks (.ipynb files). To open these files, you will need to install Jupyter labs:
pip install jupyterlab
The tutorials are located in the examples folder, at the root of this repository.
You can start serving the Jupyter notebooks with the following query:
jupyter lab --notebook-dir=examples