TLDR: Let's model the entire python package dependency graph and do some TBD analysis.
Setting up the environment may require installing some or all of the following dependencies:
We use docker-compose to manage our development containers. To get started run:
sudo systemctl start docker
docker-compose up
The dgraph UI is available at http://localhost:8000/
The jupyter notebook is available at http://127.0.0.1:8888/
Poetry is used to manage the python virtual environment.
The first time you set this up, use poetry to install the needed dependencies:
poetry install
To activate the virtual environment run:
poetry shell
Running Dgraph on server
docker run -d -it -p 5080:5080 -p 6080:6080 -p 8080:8080 \
-p 9080:9080 -p 8000:8000 -v ~/dgraph:/dgraph --name dgraph \
dgraph/dgraph:v20.03.0 dgraph zero
# In another terminal, now run Dgraph alpha
docker exec -d -it dgraph dgraph alpha --lru_mb 2048 --zero localhost:5080
# And in another, run ratel (Dgraph UI)
docker exec -d -it dgraph dgraph-ratel