pyTigerGraph is a Python package for connecting to TigerGraph databases. We offer two versions of the package: pyTigerGraph and pyTigerGraph[gds].

pyTigerGraph is the default version and contains the core functionality of pyTigerGraph, including the following:

  • Data manipulation functions:inserting, updating, upserting, deleting, and retrieving vertices and edges.

  • Query functions: running and managing queries inside the TigerGraph database

  • Metadata functions: fetching details of graphs/schemas, vertex and edge types, and other schema objects and object types

  • Authentication and authorization functions

  • Miscellaneous utility functions

The pyTigerGraph[gds] version of pyTigerGraph is a drop-in replacement for pyTigerGraph, but adds support for Graph Data Science and Graph machine learning capabilities. This includes:

  • Graph feature engineering using algorithms from the GSQL Graph Data Science Library.

  • Data loaders for training and inference of Graph Neural Network (GNN) models using PyTorch Geometric and DGL.

  • Machine learning utilities for splitting vertices into training, validation, and testing sets.

Getting Started

Checkout the Getting Started section for a quick introduction to pyTigerGraph. It walks you through how to perform the following:

In addition, we also provide a video tutorial and a Google Colab notebook that walks you through all core functions of pyTigergraph:

pyTigerGraph Community

There are many community resources that you can use for help and support using pyTigerGraph:


Checkout the Contributing section for instructions on how to contribute. pyTigerGraph was started as an open-source community project, and we welcome contributions from the community.