Motivation

Having always held an interest in graph databases and their unique applications in the realm of machine learning and data science, I was intrigued by TigerGraph. When I was onboarding onto the service, however, I found that there was a lot of overhead to simply get started. For example, I had to manually download a jar file to interact with a TigerGraph server, and use Docker to start my own instance of TigerGraph.

Thankfully, tgcloud offers free cloud instances, and pyTigerGraph offered a high-level client library to interface with the jar CLI and REST++ endpoints.

I wanted to make the onboarding experience even smoother. With other enterprise tools such as Kubernetes, a simple-to-use CLI is often the go-to choice for simple commands (for example, listing all the deployments and their status). I wanted to build something similar for TigerGraph.

Implementation

The CLI was built in Python, leveraging the pyTigerGraph library to interface with TigerGraph servers. I used the typer library, which makes it easy to build command line applications in Python.

TigerGraphCLI is on its first stable release, which is also available on PyPI. See installation instructions in the repo.

Next Steps

I would love to continue to make the development experience for TigerGraph better by contributing to both pyTigerGraph as well as TigerGraphCLI. I'm hoping to receive user feedback so I know what features to develop/bugs to squash!

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