- Machine Learning for Plant Properties — startup building database of plant genomics, properties, research, etc. for mining. The more familiar you are with your data and its meaning, the better your machine learning will be at suggesting fruitful lines of query … and the more valuable your startup will be.
- Dissecting Message Queues — throughput, latency, and qualitative comparison of different message queues. MQs are to modern distributed architectures what function calls were to historic unibox architectures.
- 1915 Data Visualization Rules — a reminder that data visualization is not new, but research into effectiveness of alternative presentation styles is.
- The Broken Promise of the Mobile Web — it’s not just about the UI – it’s also about integration with the mobile device.
ENTRIES TAGGED "mobile"
Adding consistency to Kivy's Python UI tools
Kivy has a wonderful set of built-in widgets that can be extended in numerous ways. They have very useful behaviors, but their look and feel may not integrate well with your App or the platforms you are targeting. Kivy doesn’t support theming out of the box right now, but if you poke around enough, there are a range of options you can use to customize the default look of widgets without having to define your own inherited versions of them.
I’ll first introduce you to Kivy’s image atlases, which are less mysterious than they sound, and are important groundwork for understanding theming in Kivy. Then you’ll learn two different ways to do manual theming in Kivy, with an eye to future automation.
To understand theming, you must first understand atlases. An atlas is essentially a collection of distinct images combined into a single image file for loading efficiency. A JSON file describes the location of the separate images inside that master image file so that Kivy can access them directly. If you’ve ever worked with CSS sprites, you know exactly what I’m talking about. If you haven’t, the following example should explain everything.