My passion is in web development, so I was immediately drawn to using Streamlit because it was the first of its kind that I've ever used. I found it very easy to get started, and I was able to get started on my project immediately. I was also drawn to the concept of graph databases, which I had never heard of before.
What it does
My project Connects to a TigerGraph database, allows the user to run an installed query or write a custom one, set arguments using interactive Streamlit widgets, and choose the format in which the data is displayed.
How I built it
Using Python and Python libraries including pyTigerGraphBeta, streamlit, pandas, and flat_table.
Challenges I ran into
- Formatting issues when trying to print query data as a chart.
- Using GSQL for the first time.
Accomplishments that I'm proud of
The application can successfully connect to a database, run queries with user-defined arguments, and display the data to the page as a JSON object or a table.
What I learned
- Lots of Streamlit and pyTigerGraph API.
- Benefits of graph databases over other types.
- New data analysis and visualization tools.
What's next for TigerGraph Visual Query Tool
- More user control over how data is displayed
- More options to output data