A Python library and set of command line utilities for exchanging Knowledge Graphs (KGs) that conform to or are aligned to the Biolink Model.
Project description
Knowledge Graph Exchange
KGX (Knowledge Graph Exchange) is a Python library and set of command line utilities for exchanging Knowledge Graphs (KGs) that conform to or are aligned to the Biolink Model.
The core datamodel is a Property Graph (PG), represented internally in Python using a networkx MultiDiGraph model.
KGX allows conversion to and from:
- RDF serializations (read/write) and SPARQL endpoints (read)
- Neo4j endpoints (read) or Neo4j dumps (write)
- CSV/TSV and JSON (see associated data formats and example script to load CSV/TSV to Neo4j)
- Reasoner Standard API format
- OBOGraph JSON format
KGX will also provide validation, to ensure the KGs are conformant to the Biolink Model: making sure nodes are categorized using Biolink classes, edges are labeled using valid Biolink relationship types, and valid properties are used.
Internal representation is a property graph, specifically a networkx MultiDiGraph.
The structure of this graph is expected to conform to the Biolink Model standard, briefly summarized here:
- Nodes
id: CURIE; requiredname: string; recommendedcategory: string; broad high level type. Corresponds to node label in Neo4j- other properties
- Edges
subject: CURIE; requirededge_label: CURIE; required; Corresponds to edge label in Neo4jobject: CURIE, requiredrelation: CURIE; required- other properties
In addition to the main code-base, KGX also provides a series of command line operations.
Installation for Users
KGX is available on PyPI and you can install KGX via python pip.
Note: the installation of KGX requires Python 3.7+
pip install kgx
Installation for Developers
Python 3.7+ and Core Tool Dependencies
Note: the installation of KGX requires Python 3.7+
You should first confirm what version of Python you have running and upgrade to v3.7 as necessary, following best practices of your operating system. It is also assumed that the common development tools are installed including git, pip, and all necessary development libraries for your operating system.
Getting the repository
Go to where you wish to host your local project repository and clone the repository:
cd /path/to/your/local/git/project/folder
git clone https://github.com/NCATS-Tangerine/kgx.git
# then enter into the cloned project repository
cd kgx
Configuring a virtual environment for KGX
For convenience, make use of the Python venv module to create a lightweight virtual environment.
Note that you may also have to install the appropriate
venvpackage for Python 3.7.For example, under Ubuntu Linux, you might
sudo apt-get install python3.7-venv
Once venv is available, type:
python3 -m venv venv
source venv/bin/activate
Installing Python Dependencies
The Python dependencies of the application need to be installed into the local environment using a version
of pip matched to your Python 3.7+ installation (assumed here to be called pip3).
Again, follow the specific directives of your operating system for the installation.
For example, under Ubuntu Linux, to install the Python 3.7 matched version of pip, type the following:
sudo apt-get install python3-pipwhich will install the
pip3command.
At this point, it is advisable to separately install the wheel package dependency before proceeding further
(Note: it is assumed here that your venv is activated)
pip3 install wheel
After installation of the wheel package, install KGX:
pip3 install -r requirements.txt
To install KGX,
python3 setup.py install
To test installation was successful, run the following:
kgx --help
which invokes the KGX CLI tool.
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