Getting Started

Installation

To install from PyPi:

python3 -m pip install kglab

If you work directly from this Git repo, be sure to install the dependencies:

python3 -m pip install -r requirements.txt

Alternatively, to install dependencies using conda:

conda env create -f environment.yml
conda activate kglab

See the Dependencies section for more information about troubleshooting installation issues.

Sample Usage

To use kglab in its simplest form:

import kglab

kg = kglab.KnowledgeGraph()
kg.load_rdf("https://storage.googleapis.com/kglab-tutorial/foaf.rdf", format="xml")

measure = kglab.Measure()
measure.measure_graph(kg)

print("edges: {}\n".format(measure.get_edge_count()))
print("nodes: {}\n".format(measure.get_node_count()))

ttl = kg.save_rdf_text()
print(ttl)

Using Docker

1. For a simple approach to running our tutorials, see use of docker compose.

2. Alternatively, container images for each release are available on DockerHub: https://hub.docker.com/repository/docker/derwenai/kglab

3. To build a container image and run it for the tutorials:

docker build --pull --rm -f "docker/Dockerfile" -t kglab:latest .
docker run -p 8888:8888 -it kglab

Hands-on Coding Tutorial

See the Tutorial notebooks for sample code and patterns to use when integrating kglab with other related libraries in Python.

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Last update: 2022-03-10