@enhance_dev Backend agnostic server-side rendering (SSR) for Web Components
> https://enhance.dev is an HTML-first full-stack web framework that gives you everything you need to build standards-based multi-page web apps that perform and scale. #Enhance apps and their elements are server-side rendered for incredible performance and seamless progressive enhancement.
When you sit down to give Enhance a look over, it's handy to review this doc from MDN. We take advantage of the order in which browsers populate the page to reach our performance targets.
Today, the Enhance team is excited to introduce our latest demo app: Enhance Music — a music library and audio player app built with HTML and CSS, and progressively enhanced with a couple pinches of JavaScript. Despite being built as a traditional multipage website, Enhance Music features an audio player that persists across page loads, and some gorgeous interactive UI built entirely with web standards.
The load time for the timelines bothers me; it's still occasionally timing out just loading 20 toots from two servers. I feel like introducing a #webSocket is my only choice, but I don't like the idea of adding client-side rendering.
Right now, when you visit schizo.social/timelines/home the server fetches from the API before rendering the page using @enhance_dev
I like that the page comes down populated with content so there's no further delay, but there's still a significant delay from waiting on mastodon, so it kinda defeats the purpose.
I could use enhance-element to render the toots on the client instead; either by making an #async#API request, or with a #WebSocket.
I gotta mention it again because I'm so proud of our new sample application, Enhance Movies. It's like IMDB.
The app runs blazingly fast, and since it is written with progressive enhancement in mind, it even works without JavaScript enabled. Mind you there is under 10 kb of client-side JavaScript. The web platform got really, really good folks.
My latest blog post is up on begin.com/blog. I'm happy with the Enhance plugin I wrote to syndicate an RSS feed to multiple targets. Mastodon, Twitter and Dev.to for now with more planned.
It works seamlessly with our Enhance Blog template, but you can also deploy it as a stand-alone app. Feel free to reach out to me with questions and feature requests.
I've been trying to implement the #shareTarget API in my #PWA for years now and I'm so close to being able to accept files from a share (at least from #Chrome#Android) that I can taste it!!!
In manifest.json I set my method to "POST" and enctype to "multipart/form-data", but when I share to my app it just GETs the page with no POST or even querystring params.
I could try disabling the GET response and see what happens...
I have a Tado smart thermostat - part of my smarthome project. As well as letting me set the temperature from my phone, it records environmental data, and provides a handy API for me to retrieve it.
This blog post will show you why I've gathered the data, let you download the full dataset, and explain what I learned from it.
A low temperature heat main would connect directly to the chillers at the superstore via a heat recovery unit and circulate ~25° hot water around the neighbourhood. The homes will symbiotically draw on the waste heat produced by the supermarket.
A heat pump would be installed in each household, as a replacement to their existing gas boiler.
The properties will use the existing radiators to run their heating longer but at a lower temperature in order to deliver the same level of thermal comfort. Bioregional's Rose Hill renewable energy feasibility study
In order to assess whether this is feasible, we need to understand heating demand.
This graph shows February 14th 2017 - 2019. The green graph line is the temperature inside my house. The blue graph line is the external temperature as measured by a local weather sensor in Oxford. The vertical lines represent when the heating was on - with yellow, orange, and red representing low-demand, medium-demand, and high-demand.
Here you can see the heating demand. The theory is that Tado can use the weather forecast to see how much heat it needs to generate. I can't easily assess whether it works in practice, but there are a few instances where the heating cuts off before the house reaches the target temperature. Presumably because it know the environment will provide the rest of the thermal energy.