In addition to the most recent 0.21 release, we also published a VSCode extension that aims to ease the Wave app development even more. This extension adds plenty of code snippets and autocomplete functionality for wave-specific code.
In addition to the most recent 0.20 release, we also published a PyCharm plugin that aims to ease the Wave app development even more. This plugin adds plenty of code snippets and autocomplete functionality for wave-specific code.
This blog is intended to help new users learn and become comfortable with the H2O Wave framework. Use the Overview section for an ordered-list of how to get started, learn more, and get hands on with the capabilities of H2O Wave. Move onto the Examples and Existing Apps to see what’s possible and being built by other developers. In the Friends of Wave section you can learn about companion libraries which help take your Wave projects to the next level.
H2O Wave allows for easily building front ends to your projects. I was recently inspired by this tutorial notebook which explains how to use open source H2O-3 for finding anomalies in a dataset. Part of this process is using the H2O-3 aggregator function to visualize relationships in large datasets. A data scientist is at home in a Jupyter Notebook, but we could make it easier for ourselves and analysts or other business users to run this code and benefit from the H2O-3 aggregator function by building a front-end using H2O Wave.