774-project

TLDR: Let's model the entire python package dependency graph and do some TBD analysis.

Getting Started

Setting up the environment may require installing some or all of the following dependencies:

• Python 3.7
• Docker
• docker-compose
• poetry

Docker Compose

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/

Python virtual environment

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