Building Snowflake Applications Using Streamlit
I’ll admit I’m the person who wants the maximum gain for minimum investment. Some might say that’s the definition of laziness, but I’d like to think I’m simply focused on efficiency.
Streamlit is exactly that kind of software — it allows me to write minimal code to build powerful Snowflake applications. And that’s why I love it.
And I’m not just saying it because Snowflake recently announced that they’re to acquire Streamlit. Streamlit rekindles my passion to build apps. That passion started in the early 2000s when I was building desktop apps on .NET (dotnet247 anyone?).
I wrote my first pure JQuery web app in the late 2000s. Then, I worked with Ruby on Rails for a couple of years. Later on, I worked with Angular, Vue.JS, Aurelia and Spring Boot. I’ll admit it — I’m a Java and a JavaScript person.
While these frameworks are all fun to work with, they still require us to build the full MVT/MVC stack. For the developer in me, that’s fun. But, for the sales engineer in me, that’s not very efficient.
That’s why I love Streamlit. Its components use DataFrame as the data model, which makes them very intuitive and easy to use. You literally have to write one Python file which is then run/interpreted by the Streamlit runtime.
