pyTigerGraphBeta 0.0.9.9.2

Library to connect to TigerGraph databases

pyTigerGraph

pyTigerGraph is a Python package for connecting to TigerGraph databases. Check out the extended docs here

Getting Started

To download pyTigerGraph, simply run: pip3 install pyTigerGraph Once the package installs, you can import it and instantiate a connection to your database:

import pyTigerGraph as tg

conn = tg.TigerGraphConnection(host="<hostname>", graphname="<graph_name>", username="<username>", password="<password>", apiToken="<api_token>")

If your database is not using the standard ports (or they are mapped), you can use the following arguments to specify those:

• restppPort (default 9000): REST++ API port
• gsPort (default: 14240): GraphStudio port

For example, in case of using a local virtual machine with the ports mapped:

conn = tg.TigerGraphConnection(host="localhost", restppPort=25900, gsPort=25240, graphname="MyGraph", username="tigergraph", password="tigergraph", apiToken="2aa016d747ede9gg6da3drslm98srfoj")

For more details on establishing a connection, read the Getting Started page.

Development

Fork or clone this repo. Check out a new branch.

Set up the dev environment:

• For core functions
• For the GDS subpackage, install the gds_dev_env.yml environment in the "conda" folder. If you don't have conda, install miniforge first. (Don't use miniconda as Anaconda repo has a restrictive license now.)

Work on your branch. Once your work is done, send a pull request. Unit tests are required for the review.

Example Projects

• Connecting to TigerGraph Database with pyTigerGraph

• Predicting IPOs using Graph Convolutional Neural Networks

• Using pyTigergraph With Plotly

• TigerGraph to Tensorflow

• Movie Prediction with Graph Convolutional Neural Networks

Credits

pyTigerGraph was originally created by Parker Erickson, a Computer Science student at the University of Minnesota. Special thanks to contributors Jon Herke and Szilard Barany of TigerGraph. Read this to learn more about how you can contribute.